Concepts in Complexity II - Emergence and the Difference Between Order and Organization, Jon Lawhead
Transcript of Concepts in Complexity II - Emergence and the Difference Between Order and Organization, Jon Lawhead
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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Abstract
There are a number of contemporary scientific problems that can benefit from good
metaphysical analysis and philosophical clarification This paper examines one of these
problemsmdashexplaining the nature of self-organized emergent behavior in dynamical physical
systems While discussions of emergence have long been the province of metaphysicians recent
advances in network theory and complex systems theory have begun to suggest that there is both
philosophical and metaphysical work to be done here and that a rigorous mathematically-
grounded account of emergence might serve as the foundation upon which we can construct atremendous number of other novel contributions to our understanding of the world This paper
explores the conceptual connection between this mathematically rigorous account of ldquostrongemergencerdquo (developed primarily by Yaneer Bar-Yam) and the still somewhat murky notion of
self-organized systems I argue that a clear scientific understanding of emergence leads to a
natural way of understanding the metaphysics of self-organization and (more generally) the
difference between order and organization All three of these notions are central to the nascent
field of complex systems theory and getting a strong grasp on their conceptual relationships
would represent not only a significant step toward developing a cohesive metaphysics of
complex systems but would also provide the theoretical tools necessary for continued
philosophical and scientific work in that area Given the sheer number (and diversity) of fields
that stand to benefit from complexity-theoretic insights this is work that urgently needs to bedone
0 The Problem
Therersquos a growing body of multidisciplinary research exploring complexity theory and related
ideas This field has not yet really settled down yet and so therersquos a lot of terminological
confusion out there Different people use the same terms to mean different things (witness the
constellation of definitions of lsquocomplexityrsquo itself a field that canrsquot even agree on what itrsquos about
is in serious need of philosophical help) The situation today is roughly analogous to the
situation in pre-Newtonian mechanics (when people had a rough idea of the concepts Newton
would eventually unify but still wrote confusingly about topics like ldquothe conservation of forcerdquo)
or in pre-Carnot thermodynamics That is a lot of people have something to say but almost no
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one is quite sure how best to say it The importance of getting this stuff clear is becoming more
widely-appreciated by the daymdashcomplexity theory has contributions to make in very many fields
of scientific inquirymdashbut the progress so far has been piecemeal with individual scientists
cobbling together tools as they go along This approach has been successful to a point but
tinkering can only take us so far if the field is to move forward as a coherent focused unified
body of research then it is vital that we start to do the very difficult work of conceptual
clarification A good understanding of how central concepts in complexity theory fit together
will go a long way toward facilitating continued progress in applying those concepts to real-
world social and scientific problems
The purpose of this essay is to call attention to one set of these terminological confusions and to
begin the work of clarifying it I have treated two other conceptsmdashnon-linearity and chaosmdashin
the first part of this paper1 and would now like to turn to two more emergence and self-
organization These two concepts both have a central role to play in the discussion of
complexity yet there is much confusion about how they relate to one another and what they
might suggest about the study of real-world physical systems Much progress has already been
made in giving an account of emergence in rigorous termsmdashthe work by Yaneer Bar-Yam and
his colleagues at the New England Complex Systems Institute has been particularly ground-
breakingmdashbut this progress has received precious little attention in the philosophical literature a
place where it has the potential to have a truly spectacular impact
While discussions of organization also abound (mostly in the literature surrounding dynamical
systems theory and cybernetics) there is even less agreement about what it means for a system to
be organized or how organization actually takes place While there is a cluster of conceptual
1Lawhead (2012)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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confusion surrounding the use of ldquoorganizationrdquo I would like to focus here on one problem in
particular the (almost ubiquitous) conflation of organization and order This problem is
particularly salient when it comes to self-organizationmdasha phenomenon that arises inmany
discussions of complexity as well as in contemporary work in biology cognitive neuroscience
and economics (just to name a few)mdashwhere the terms ldquoorderrdquo and ldquoorganizationrdquo are
consistently used as if they were interchangeable The central thesis of this essay is that they are
very much not interchangeable and that a careful examination of the differences between
ordered systems and organized systems will shed quite a lot of light on the nature of both
concepts
Herersquos how this paper will go In Section 1 I will give a brief survey of the concept of
emergence which has a long and storied history in philosophy Rather than focusing primarily
on the traditional metaphysical debates about emergence though we will spend most of the
section exploring the recent advances that systems-theoretic thinking has made in giving an
account of emergence with strong mathematical underpinnings Getting a handle on this view of
emergence is essential for what will follow the complexity-theoretic account of emergence treats
the phenomenon as the genesis of certain restrictions on the possible states into which a system
can evolve and I will argue that organization is very closely related to the source (and nature) of
those sorts of restrictions Our discussion here will include only as much mathematics as is
necessary appreciate the force of this new way of looking at emergence Readers interested in
pursuing the mathematical foundations in more detail will referred to a number of secondary
sources
In Section 2 we will explore the implications of the complexity-theoretic account of
emergence with respect to organization Wersquoll think about the effects of emergence on real-
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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world physical systems and see how this account of emergence suggests a natural way to
understand the metaphysics of self-organization in the natural world Wersquoll also see how a clear
understanding of the physical interpretation of the mathematics underlying this sense of
emergence highlights the difference between order and organization Finally wersquoll think about
how organization might impact a systemrsquos interactions with its environment and suggest some
directions for future work on the metaphysics of self-organized complex systems
1 Emergence A Step Toward Organization
lsquoEmergencersquo is a heavily loaded term in philosophy laden with conflicting interpretations and
figuring prominently (one way or another) into many metaphysical theories In some ways the
term has never recovered from the discrediting damage done to it by the failure of vitalism and
the ldquostrong emergencerdquo program of the 19th and 20thcenturies2 The common rallying cry of
these two camps was that the analytic approach championed by mainstream science was
inevitably doomed to fail as some aspect of the natural world (living things for example) were
sui generis in that their behavior was not governed by (or perhaps just not deducible from) the
behavior of their parts but rather anomalously emerged in certain circumstances The last major
stronghold for this viewmdashlifemdashwas dealt a critical blow by the advent of molecular biology the
discovery of genetic molecules showed that living things were not anomalous sui generis
systems but rather were just as dependent on the coordinated action of simpler constituents as
any physical system Biology might be messy and but it isnrsquot magic By the middle of the 20th
century vitalism had fallen far out of favor and most mainstream scientists and philosophers
held at least a vaguely reductionistic view of the world While quantum mechanics was busy
2 See for instance Morgan (1921)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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overthrowing other pillars of classical science it seemed to only reinforce this one the whole is
nothing more than the sum of its parts While the behavior of that sum may be difficult (or even
impossible) to predict sometimes just by looking at the parts therersquos nothing fundamentally
newto be learned by looking at systems any higher-level scientific laws are just special cases
course-grainings or simplifications of the story that fundamental physics has to tell It would
perhaps be preferable to introduce an entirely new term for the property that we will be
considering here but unnecessarily idiosyncratic multiplication of terminology has in no small
part led to the kind of confusion that Irsquom trying to start clearing away in this paper Moreover
(as wersquoll see) this old approachmdashwhile misguided and ultimately incorrectmdashwasnrsquot grasping at
nothing it would just be another century (or so) before the concerns of the strong emergentists
could be stripped of their ldquospookyrdquo trappings and given a place in the project of understanding
the world Rather than try to coin my own term then I have chosen to stick with lsquoemergencersquo
and will attempt to elucidate what aspects of the constellation of related definitions are worth
salvaging and which would be better jettisoned into the history books
I have already used the term ldquostrong emergencerdquo several times in this paper without
explanation and it is perhaps advisable to begin with a clear definition of what this means and
how it differs (historically) from weak emergence At the risk of oversimplifying things
somewhat we might cast the distinction between weak and strong emergence as being a
distinction between epistemic emergence and metaphysical emergence That is we might
understand strongly emergent features of a system as being metaphysically genuine (whatever
that might mean) features that are distinct are distinct from the features of the parts that
constitute the system Weak emergence on the other hand can be seen as merely a restriction on
our knowledge about the behavior of a system It is possible to hold a completely reductionistic
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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metaphysical view and still admit this sort of weak emergence even the most hardened
reductionist can admit that it might be impossible to predict the behavior of (say) a human being
by treating only the behavior of his most basic proper parts (the quarks composing his body
say) The utility of the special sciences as independent from fundamental physics requires only
this sort of weak emergence even if the impossibility of predicting the behavior of a whole from
knowledge of its parts is a practical rather than principled one system-level behavior (and
properties) might be said to be weakly emergent
The compatibility of this kind of weak emergence with strong ontological reductionism
means that it is rather uninteresting philosophically Virtually no one would deny weak
(epistemic) emergence and so the position is worth very little consideration It is a truism that
physics is not always the most practical way to study the physical world If wersquore to say
something interesting then we should restrict ourselves here to a discussion of strong
emergence I argue that contrary to some prejudice in the existing philosophical literature the
notion of strong emergence is not only conceptually tractable but that complexity-theoretic
considerations give us reason to think that it is straightforwardly scientifically tractable as well
I have said that we can think of strong emergence as being about the emergence of system-
level features that are not just reducible to features the individual parts of the system but what
exactly does that mean The evocative notion of ldquocausal drainagerdquo that appears in the
philosophy of mind literature can help to clarify things here if only by presenting a neat
statement of a view opposed to this kind of strong emergence so perhaps that is the best place to
start
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The ldquocausal drainagerdquo argument is perhaps most clearly and forcefully argued for in Kim
(1998) and (2003) The claim goes something like this ldquoUpward causationrdquo is uncontroversial
in the following sense everyone agrees that the actions of parts can have real tangible effects on
the behavior of wholes3 That is everyone agrees that shifting the positions of a few electrons
can have an effect on an atomrsquos chemical properties (say its propensity to form covalent bonds
with other atoms) or that changes in the structure of a single cell can have an effect on an
organismrsquos biological fitness (say by triggering the formation of a fatal malignancy) On the
other hand it would be absurd (the argument goes) to imagine that causation might happen in the
other direction Changes in electrons might cause changes in economies (for instance as when a
surge in electrons fries the computers on the New York Stock Exchange) but itrsquos not even clear
what it would mean for a change in an economy to cause a change in electrons On careful
analysis Kim argues all the real causal ldquooomphrdquo drains away to the lowest level like water
seeping through loose topsoil to collect on the solid bedrock below it To argue for strong
emergence on this view is to argue for downward causationmdashto argue for the behavior of the
whole affecting the behavior of the parts in a way that doesnrsquot turn out to be attributable to the
parts just affecting one another
11 Emergence as a State-Constraint
All of this is just a rehearsal of some very well-known moves in contemporary analytic
metaphysics However this is not a paper in analytic metaphysics (at least not traditionally
construed) so let us now turn to the task of translating this discussion into a language that is
more amenable to the kind of work wersquore concerned with doing heremdashletrsquos see if we can recast
3 At least virtually everyone who isnrsquot a compositional nihilist (who by their own account donrsquot exist anyway)
would agree to this
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 229
one is quite sure how best to say it The importance of getting this stuff clear is becoming more
widely-appreciated by the daymdashcomplexity theory has contributions to make in very many fields
of scientific inquirymdashbut the progress so far has been piecemeal with individual scientists
cobbling together tools as they go along This approach has been successful to a point but
tinkering can only take us so far if the field is to move forward as a coherent focused unified
body of research then it is vital that we start to do the very difficult work of conceptual
clarification A good understanding of how central concepts in complexity theory fit together
will go a long way toward facilitating continued progress in applying those concepts to real-
world social and scientific problems
The purpose of this essay is to call attention to one set of these terminological confusions and to
begin the work of clarifying it I have treated two other conceptsmdashnon-linearity and chaosmdashin
the first part of this paper1 and would now like to turn to two more emergence and self-
organization These two concepts both have a central role to play in the discussion of
complexity yet there is much confusion about how they relate to one another and what they
might suggest about the study of real-world physical systems Much progress has already been
made in giving an account of emergence in rigorous termsmdashthe work by Yaneer Bar-Yam and
his colleagues at the New England Complex Systems Institute has been particularly ground-
breakingmdashbut this progress has received precious little attention in the philosophical literature a
place where it has the potential to have a truly spectacular impact
While discussions of organization also abound (mostly in the literature surrounding dynamical
systems theory and cybernetics) there is even less agreement about what it means for a system to
be organized or how organization actually takes place While there is a cluster of conceptual
1Lawhead (2012)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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confusion surrounding the use of ldquoorganizationrdquo I would like to focus here on one problem in
particular the (almost ubiquitous) conflation of organization and order This problem is
particularly salient when it comes to self-organizationmdasha phenomenon that arises inmany
discussions of complexity as well as in contemporary work in biology cognitive neuroscience
and economics (just to name a few)mdashwhere the terms ldquoorderrdquo and ldquoorganizationrdquo are
consistently used as if they were interchangeable The central thesis of this essay is that they are
very much not interchangeable and that a careful examination of the differences between
ordered systems and organized systems will shed quite a lot of light on the nature of both
concepts
Herersquos how this paper will go In Section 1 I will give a brief survey of the concept of
emergence which has a long and storied history in philosophy Rather than focusing primarily
on the traditional metaphysical debates about emergence though we will spend most of the
section exploring the recent advances that systems-theoretic thinking has made in giving an
account of emergence with strong mathematical underpinnings Getting a handle on this view of
emergence is essential for what will follow the complexity-theoretic account of emergence treats
the phenomenon as the genesis of certain restrictions on the possible states into which a system
can evolve and I will argue that organization is very closely related to the source (and nature) of
those sorts of restrictions Our discussion here will include only as much mathematics as is
necessary appreciate the force of this new way of looking at emergence Readers interested in
pursuing the mathematical foundations in more detail will referred to a number of secondary
sources
In Section 2 we will explore the implications of the complexity-theoretic account of
emergence with respect to organization Wersquoll think about the effects of emergence on real-
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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world physical systems and see how this account of emergence suggests a natural way to
understand the metaphysics of self-organization in the natural world Wersquoll also see how a clear
understanding of the physical interpretation of the mathematics underlying this sense of
emergence highlights the difference between order and organization Finally wersquoll think about
how organization might impact a systemrsquos interactions with its environment and suggest some
directions for future work on the metaphysics of self-organized complex systems
1 Emergence A Step Toward Organization
lsquoEmergencersquo is a heavily loaded term in philosophy laden with conflicting interpretations and
figuring prominently (one way or another) into many metaphysical theories In some ways the
term has never recovered from the discrediting damage done to it by the failure of vitalism and
the ldquostrong emergencerdquo program of the 19th and 20thcenturies2 The common rallying cry of
these two camps was that the analytic approach championed by mainstream science was
inevitably doomed to fail as some aspect of the natural world (living things for example) were
sui generis in that their behavior was not governed by (or perhaps just not deducible from) the
behavior of their parts but rather anomalously emerged in certain circumstances The last major
stronghold for this viewmdashlifemdashwas dealt a critical blow by the advent of molecular biology the
discovery of genetic molecules showed that living things were not anomalous sui generis
systems but rather were just as dependent on the coordinated action of simpler constituents as
any physical system Biology might be messy and but it isnrsquot magic By the middle of the 20th
century vitalism had fallen far out of favor and most mainstream scientists and philosophers
held at least a vaguely reductionistic view of the world While quantum mechanics was busy
2 See for instance Morgan (1921)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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overthrowing other pillars of classical science it seemed to only reinforce this one the whole is
nothing more than the sum of its parts While the behavior of that sum may be difficult (or even
impossible) to predict sometimes just by looking at the parts therersquos nothing fundamentally
newto be learned by looking at systems any higher-level scientific laws are just special cases
course-grainings or simplifications of the story that fundamental physics has to tell It would
perhaps be preferable to introduce an entirely new term for the property that we will be
considering here but unnecessarily idiosyncratic multiplication of terminology has in no small
part led to the kind of confusion that Irsquom trying to start clearing away in this paper Moreover
(as wersquoll see) this old approachmdashwhile misguided and ultimately incorrectmdashwasnrsquot grasping at
nothing it would just be another century (or so) before the concerns of the strong emergentists
could be stripped of their ldquospookyrdquo trappings and given a place in the project of understanding
the world Rather than try to coin my own term then I have chosen to stick with lsquoemergencersquo
and will attempt to elucidate what aspects of the constellation of related definitions are worth
salvaging and which would be better jettisoned into the history books
I have already used the term ldquostrong emergencerdquo several times in this paper without
explanation and it is perhaps advisable to begin with a clear definition of what this means and
how it differs (historically) from weak emergence At the risk of oversimplifying things
somewhat we might cast the distinction between weak and strong emergence as being a
distinction between epistemic emergence and metaphysical emergence That is we might
understand strongly emergent features of a system as being metaphysically genuine (whatever
that might mean) features that are distinct are distinct from the features of the parts that
constitute the system Weak emergence on the other hand can be seen as merely a restriction on
our knowledge about the behavior of a system It is possible to hold a completely reductionistic
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 629
metaphysical view and still admit this sort of weak emergence even the most hardened
reductionist can admit that it might be impossible to predict the behavior of (say) a human being
by treating only the behavior of his most basic proper parts (the quarks composing his body
say) The utility of the special sciences as independent from fundamental physics requires only
this sort of weak emergence even if the impossibility of predicting the behavior of a whole from
knowledge of its parts is a practical rather than principled one system-level behavior (and
properties) might be said to be weakly emergent
The compatibility of this kind of weak emergence with strong ontological reductionism
means that it is rather uninteresting philosophically Virtually no one would deny weak
(epistemic) emergence and so the position is worth very little consideration It is a truism that
physics is not always the most practical way to study the physical world If wersquore to say
something interesting then we should restrict ourselves here to a discussion of strong
emergence I argue that contrary to some prejudice in the existing philosophical literature the
notion of strong emergence is not only conceptually tractable but that complexity-theoretic
considerations give us reason to think that it is straightforwardly scientifically tractable as well
I have said that we can think of strong emergence as being about the emergence of system-
level features that are not just reducible to features the individual parts of the system but what
exactly does that mean The evocative notion of ldquocausal drainagerdquo that appears in the
philosophy of mind literature can help to clarify things here if only by presenting a neat
statement of a view opposed to this kind of strong emergence so perhaps that is the best place to
start
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The ldquocausal drainagerdquo argument is perhaps most clearly and forcefully argued for in Kim
(1998) and (2003) The claim goes something like this ldquoUpward causationrdquo is uncontroversial
in the following sense everyone agrees that the actions of parts can have real tangible effects on
the behavior of wholes3 That is everyone agrees that shifting the positions of a few electrons
can have an effect on an atomrsquos chemical properties (say its propensity to form covalent bonds
with other atoms) or that changes in the structure of a single cell can have an effect on an
organismrsquos biological fitness (say by triggering the formation of a fatal malignancy) On the
other hand it would be absurd (the argument goes) to imagine that causation might happen in the
other direction Changes in electrons might cause changes in economies (for instance as when a
surge in electrons fries the computers on the New York Stock Exchange) but itrsquos not even clear
what it would mean for a change in an economy to cause a change in electrons On careful
analysis Kim argues all the real causal ldquooomphrdquo drains away to the lowest level like water
seeping through loose topsoil to collect on the solid bedrock below it To argue for strong
emergence on this view is to argue for downward causationmdashto argue for the behavior of the
whole affecting the behavior of the parts in a way that doesnrsquot turn out to be attributable to the
parts just affecting one another
11 Emergence as a State-Constraint
All of this is just a rehearsal of some very well-known moves in contemporary analytic
metaphysics However this is not a paper in analytic metaphysics (at least not traditionally
construed) so let us now turn to the task of translating this discussion into a language that is
more amenable to the kind of work wersquore concerned with doing heremdashletrsquos see if we can recast
3 At least virtually everyone who isnrsquot a compositional nihilist (who by their own account donrsquot exist anyway)
would agree to this
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 929
space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1029
system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2729
This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 329
confusion surrounding the use of ldquoorganizationrdquo I would like to focus here on one problem in
particular the (almost ubiquitous) conflation of organization and order This problem is
particularly salient when it comes to self-organizationmdasha phenomenon that arises inmany
discussions of complexity as well as in contemporary work in biology cognitive neuroscience
and economics (just to name a few)mdashwhere the terms ldquoorderrdquo and ldquoorganizationrdquo are
consistently used as if they were interchangeable The central thesis of this essay is that they are
very much not interchangeable and that a careful examination of the differences between
ordered systems and organized systems will shed quite a lot of light on the nature of both
concepts
Herersquos how this paper will go In Section 1 I will give a brief survey of the concept of
emergence which has a long and storied history in philosophy Rather than focusing primarily
on the traditional metaphysical debates about emergence though we will spend most of the
section exploring the recent advances that systems-theoretic thinking has made in giving an
account of emergence with strong mathematical underpinnings Getting a handle on this view of
emergence is essential for what will follow the complexity-theoretic account of emergence treats
the phenomenon as the genesis of certain restrictions on the possible states into which a system
can evolve and I will argue that organization is very closely related to the source (and nature) of
those sorts of restrictions Our discussion here will include only as much mathematics as is
necessary appreciate the force of this new way of looking at emergence Readers interested in
pursuing the mathematical foundations in more detail will referred to a number of secondary
sources
In Section 2 we will explore the implications of the complexity-theoretic account of
emergence with respect to organization Wersquoll think about the effects of emergence on real-
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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world physical systems and see how this account of emergence suggests a natural way to
understand the metaphysics of self-organization in the natural world Wersquoll also see how a clear
understanding of the physical interpretation of the mathematics underlying this sense of
emergence highlights the difference between order and organization Finally wersquoll think about
how organization might impact a systemrsquos interactions with its environment and suggest some
directions for future work on the metaphysics of self-organized complex systems
1 Emergence A Step Toward Organization
lsquoEmergencersquo is a heavily loaded term in philosophy laden with conflicting interpretations and
figuring prominently (one way or another) into many metaphysical theories In some ways the
term has never recovered from the discrediting damage done to it by the failure of vitalism and
the ldquostrong emergencerdquo program of the 19th and 20thcenturies2 The common rallying cry of
these two camps was that the analytic approach championed by mainstream science was
inevitably doomed to fail as some aspect of the natural world (living things for example) were
sui generis in that their behavior was not governed by (or perhaps just not deducible from) the
behavior of their parts but rather anomalously emerged in certain circumstances The last major
stronghold for this viewmdashlifemdashwas dealt a critical blow by the advent of molecular biology the
discovery of genetic molecules showed that living things were not anomalous sui generis
systems but rather were just as dependent on the coordinated action of simpler constituents as
any physical system Biology might be messy and but it isnrsquot magic By the middle of the 20th
century vitalism had fallen far out of favor and most mainstream scientists and philosophers
held at least a vaguely reductionistic view of the world While quantum mechanics was busy
2 See for instance Morgan (1921)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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overthrowing other pillars of classical science it seemed to only reinforce this one the whole is
nothing more than the sum of its parts While the behavior of that sum may be difficult (or even
impossible) to predict sometimes just by looking at the parts therersquos nothing fundamentally
newto be learned by looking at systems any higher-level scientific laws are just special cases
course-grainings or simplifications of the story that fundamental physics has to tell It would
perhaps be preferable to introduce an entirely new term for the property that we will be
considering here but unnecessarily idiosyncratic multiplication of terminology has in no small
part led to the kind of confusion that Irsquom trying to start clearing away in this paper Moreover
(as wersquoll see) this old approachmdashwhile misguided and ultimately incorrectmdashwasnrsquot grasping at
nothing it would just be another century (or so) before the concerns of the strong emergentists
could be stripped of their ldquospookyrdquo trappings and given a place in the project of understanding
the world Rather than try to coin my own term then I have chosen to stick with lsquoemergencersquo
and will attempt to elucidate what aspects of the constellation of related definitions are worth
salvaging and which would be better jettisoned into the history books
I have already used the term ldquostrong emergencerdquo several times in this paper without
explanation and it is perhaps advisable to begin with a clear definition of what this means and
how it differs (historically) from weak emergence At the risk of oversimplifying things
somewhat we might cast the distinction between weak and strong emergence as being a
distinction between epistemic emergence and metaphysical emergence That is we might
understand strongly emergent features of a system as being metaphysically genuine (whatever
that might mean) features that are distinct are distinct from the features of the parts that
constitute the system Weak emergence on the other hand can be seen as merely a restriction on
our knowledge about the behavior of a system It is possible to hold a completely reductionistic
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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metaphysical view and still admit this sort of weak emergence even the most hardened
reductionist can admit that it might be impossible to predict the behavior of (say) a human being
by treating only the behavior of his most basic proper parts (the quarks composing his body
say) The utility of the special sciences as independent from fundamental physics requires only
this sort of weak emergence even if the impossibility of predicting the behavior of a whole from
knowledge of its parts is a practical rather than principled one system-level behavior (and
properties) might be said to be weakly emergent
The compatibility of this kind of weak emergence with strong ontological reductionism
means that it is rather uninteresting philosophically Virtually no one would deny weak
(epistemic) emergence and so the position is worth very little consideration It is a truism that
physics is not always the most practical way to study the physical world If wersquore to say
something interesting then we should restrict ourselves here to a discussion of strong
emergence I argue that contrary to some prejudice in the existing philosophical literature the
notion of strong emergence is not only conceptually tractable but that complexity-theoretic
considerations give us reason to think that it is straightforwardly scientifically tractable as well
I have said that we can think of strong emergence as being about the emergence of system-
level features that are not just reducible to features the individual parts of the system but what
exactly does that mean The evocative notion of ldquocausal drainagerdquo that appears in the
philosophy of mind literature can help to clarify things here if only by presenting a neat
statement of a view opposed to this kind of strong emergence so perhaps that is the best place to
start
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The ldquocausal drainagerdquo argument is perhaps most clearly and forcefully argued for in Kim
(1998) and (2003) The claim goes something like this ldquoUpward causationrdquo is uncontroversial
in the following sense everyone agrees that the actions of parts can have real tangible effects on
the behavior of wholes3 That is everyone agrees that shifting the positions of a few electrons
can have an effect on an atomrsquos chemical properties (say its propensity to form covalent bonds
with other atoms) or that changes in the structure of a single cell can have an effect on an
organismrsquos biological fitness (say by triggering the formation of a fatal malignancy) On the
other hand it would be absurd (the argument goes) to imagine that causation might happen in the
other direction Changes in electrons might cause changes in economies (for instance as when a
surge in electrons fries the computers on the New York Stock Exchange) but itrsquos not even clear
what it would mean for a change in an economy to cause a change in electrons On careful
analysis Kim argues all the real causal ldquooomphrdquo drains away to the lowest level like water
seeping through loose topsoil to collect on the solid bedrock below it To argue for strong
emergence on this view is to argue for downward causationmdashto argue for the behavior of the
whole affecting the behavior of the parts in a way that doesnrsquot turn out to be attributable to the
parts just affecting one another
11 Emergence as a State-Constraint
All of this is just a rehearsal of some very well-known moves in contemporary analytic
metaphysics However this is not a paper in analytic metaphysics (at least not traditionally
construed) so let us now turn to the task of translating this discussion into a language that is
more amenable to the kind of work wersquore concerned with doing heremdashletrsquos see if we can recast
3 At least virtually everyone who isnrsquot a compositional nihilist (who by their own account donrsquot exist anyway)
would agree to this
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this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
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space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
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system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
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983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
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983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
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983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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world physical systems and see how this account of emergence suggests a natural way to
understand the metaphysics of self-organization in the natural world Wersquoll also see how a clear
understanding of the physical interpretation of the mathematics underlying this sense of
emergence highlights the difference between order and organization Finally wersquoll think about
how organization might impact a systemrsquos interactions with its environment and suggest some
directions for future work on the metaphysics of self-organized complex systems
1 Emergence A Step Toward Organization
lsquoEmergencersquo is a heavily loaded term in philosophy laden with conflicting interpretations and
figuring prominently (one way or another) into many metaphysical theories In some ways the
term has never recovered from the discrediting damage done to it by the failure of vitalism and
the ldquostrong emergencerdquo program of the 19th and 20thcenturies2 The common rallying cry of
these two camps was that the analytic approach championed by mainstream science was
inevitably doomed to fail as some aspect of the natural world (living things for example) were
sui generis in that their behavior was not governed by (or perhaps just not deducible from) the
behavior of their parts but rather anomalously emerged in certain circumstances The last major
stronghold for this viewmdashlifemdashwas dealt a critical blow by the advent of molecular biology the
discovery of genetic molecules showed that living things were not anomalous sui generis
systems but rather were just as dependent on the coordinated action of simpler constituents as
any physical system Biology might be messy and but it isnrsquot magic By the middle of the 20th
century vitalism had fallen far out of favor and most mainstream scientists and philosophers
held at least a vaguely reductionistic view of the world While quantum mechanics was busy
2 See for instance Morgan (1921)
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overthrowing other pillars of classical science it seemed to only reinforce this one the whole is
nothing more than the sum of its parts While the behavior of that sum may be difficult (or even
impossible) to predict sometimes just by looking at the parts therersquos nothing fundamentally
newto be learned by looking at systems any higher-level scientific laws are just special cases
course-grainings or simplifications of the story that fundamental physics has to tell It would
perhaps be preferable to introduce an entirely new term for the property that we will be
considering here but unnecessarily idiosyncratic multiplication of terminology has in no small
part led to the kind of confusion that Irsquom trying to start clearing away in this paper Moreover
(as wersquoll see) this old approachmdashwhile misguided and ultimately incorrectmdashwasnrsquot grasping at
nothing it would just be another century (or so) before the concerns of the strong emergentists
could be stripped of their ldquospookyrdquo trappings and given a place in the project of understanding
the world Rather than try to coin my own term then I have chosen to stick with lsquoemergencersquo
and will attempt to elucidate what aspects of the constellation of related definitions are worth
salvaging and which would be better jettisoned into the history books
I have already used the term ldquostrong emergencerdquo several times in this paper without
explanation and it is perhaps advisable to begin with a clear definition of what this means and
how it differs (historically) from weak emergence At the risk of oversimplifying things
somewhat we might cast the distinction between weak and strong emergence as being a
distinction between epistemic emergence and metaphysical emergence That is we might
understand strongly emergent features of a system as being metaphysically genuine (whatever
that might mean) features that are distinct are distinct from the features of the parts that
constitute the system Weak emergence on the other hand can be seen as merely a restriction on
our knowledge about the behavior of a system It is possible to hold a completely reductionistic
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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metaphysical view and still admit this sort of weak emergence even the most hardened
reductionist can admit that it might be impossible to predict the behavior of (say) a human being
by treating only the behavior of his most basic proper parts (the quarks composing his body
say) The utility of the special sciences as independent from fundamental physics requires only
this sort of weak emergence even if the impossibility of predicting the behavior of a whole from
knowledge of its parts is a practical rather than principled one system-level behavior (and
properties) might be said to be weakly emergent
The compatibility of this kind of weak emergence with strong ontological reductionism
means that it is rather uninteresting philosophically Virtually no one would deny weak
(epistemic) emergence and so the position is worth very little consideration It is a truism that
physics is not always the most practical way to study the physical world If wersquore to say
something interesting then we should restrict ourselves here to a discussion of strong
emergence I argue that contrary to some prejudice in the existing philosophical literature the
notion of strong emergence is not only conceptually tractable but that complexity-theoretic
considerations give us reason to think that it is straightforwardly scientifically tractable as well
I have said that we can think of strong emergence as being about the emergence of system-
level features that are not just reducible to features the individual parts of the system but what
exactly does that mean The evocative notion of ldquocausal drainagerdquo that appears in the
philosophy of mind literature can help to clarify things here if only by presenting a neat
statement of a view opposed to this kind of strong emergence so perhaps that is the best place to
start
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The ldquocausal drainagerdquo argument is perhaps most clearly and forcefully argued for in Kim
(1998) and (2003) The claim goes something like this ldquoUpward causationrdquo is uncontroversial
in the following sense everyone agrees that the actions of parts can have real tangible effects on
the behavior of wholes3 That is everyone agrees that shifting the positions of a few electrons
can have an effect on an atomrsquos chemical properties (say its propensity to form covalent bonds
with other atoms) or that changes in the structure of a single cell can have an effect on an
organismrsquos biological fitness (say by triggering the formation of a fatal malignancy) On the
other hand it would be absurd (the argument goes) to imagine that causation might happen in the
other direction Changes in electrons might cause changes in economies (for instance as when a
surge in electrons fries the computers on the New York Stock Exchange) but itrsquos not even clear
what it would mean for a change in an economy to cause a change in electrons On careful
analysis Kim argues all the real causal ldquooomphrdquo drains away to the lowest level like water
seeping through loose topsoil to collect on the solid bedrock below it To argue for strong
emergence on this view is to argue for downward causationmdashto argue for the behavior of the
whole affecting the behavior of the parts in a way that doesnrsquot turn out to be attributable to the
parts just affecting one another
11 Emergence as a State-Constraint
All of this is just a rehearsal of some very well-known moves in contemporary analytic
metaphysics However this is not a paper in analytic metaphysics (at least not traditionally
construed) so let us now turn to the task of translating this discussion into a language that is
more amenable to the kind of work wersquore concerned with doing heremdashletrsquos see if we can recast
3 At least virtually everyone who isnrsquot a compositional nihilist (who by their own account donrsquot exist anyway)
would agree to this
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this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
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space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
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system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 529
overthrowing other pillars of classical science it seemed to only reinforce this one the whole is
nothing more than the sum of its parts While the behavior of that sum may be difficult (or even
impossible) to predict sometimes just by looking at the parts therersquos nothing fundamentally
newto be learned by looking at systems any higher-level scientific laws are just special cases
course-grainings or simplifications of the story that fundamental physics has to tell It would
perhaps be preferable to introduce an entirely new term for the property that we will be
considering here but unnecessarily idiosyncratic multiplication of terminology has in no small
part led to the kind of confusion that Irsquom trying to start clearing away in this paper Moreover
(as wersquoll see) this old approachmdashwhile misguided and ultimately incorrectmdashwasnrsquot grasping at
nothing it would just be another century (or so) before the concerns of the strong emergentists
could be stripped of their ldquospookyrdquo trappings and given a place in the project of understanding
the world Rather than try to coin my own term then I have chosen to stick with lsquoemergencersquo
and will attempt to elucidate what aspects of the constellation of related definitions are worth
salvaging and which would be better jettisoned into the history books
I have already used the term ldquostrong emergencerdquo several times in this paper without
explanation and it is perhaps advisable to begin with a clear definition of what this means and
how it differs (historically) from weak emergence At the risk of oversimplifying things
somewhat we might cast the distinction between weak and strong emergence as being a
distinction between epistemic emergence and metaphysical emergence That is we might
understand strongly emergent features of a system as being metaphysically genuine (whatever
that might mean) features that are distinct are distinct from the features of the parts that
constitute the system Weak emergence on the other hand can be seen as merely a restriction on
our knowledge about the behavior of a system It is possible to hold a completely reductionistic
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 629
metaphysical view and still admit this sort of weak emergence even the most hardened
reductionist can admit that it might be impossible to predict the behavior of (say) a human being
by treating only the behavior of his most basic proper parts (the quarks composing his body
say) The utility of the special sciences as independent from fundamental physics requires only
this sort of weak emergence even if the impossibility of predicting the behavior of a whole from
knowledge of its parts is a practical rather than principled one system-level behavior (and
properties) might be said to be weakly emergent
The compatibility of this kind of weak emergence with strong ontological reductionism
means that it is rather uninteresting philosophically Virtually no one would deny weak
(epistemic) emergence and so the position is worth very little consideration It is a truism that
physics is not always the most practical way to study the physical world If wersquore to say
something interesting then we should restrict ourselves here to a discussion of strong
emergence I argue that contrary to some prejudice in the existing philosophical literature the
notion of strong emergence is not only conceptually tractable but that complexity-theoretic
considerations give us reason to think that it is straightforwardly scientifically tractable as well
I have said that we can think of strong emergence as being about the emergence of system-
level features that are not just reducible to features the individual parts of the system but what
exactly does that mean The evocative notion of ldquocausal drainagerdquo that appears in the
philosophy of mind literature can help to clarify things here if only by presenting a neat
statement of a view opposed to this kind of strong emergence so perhaps that is the best place to
start
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The ldquocausal drainagerdquo argument is perhaps most clearly and forcefully argued for in Kim
(1998) and (2003) The claim goes something like this ldquoUpward causationrdquo is uncontroversial
in the following sense everyone agrees that the actions of parts can have real tangible effects on
the behavior of wholes3 That is everyone agrees that shifting the positions of a few electrons
can have an effect on an atomrsquos chemical properties (say its propensity to form covalent bonds
with other atoms) or that changes in the structure of a single cell can have an effect on an
organismrsquos biological fitness (say by triggering the formation of a fatal malignancy) On the
other hand it would be absurd (the argument goes) to imagine that causation might happen in the
other direction Changes in electrons might cause changes in economies (for instance as when a
surge in electrons fries the computers on the New York Stock Exchange) but itrsquos not even clear
what it would mean for a change in an economy to cause a change in electrons On careful
analysis Kim argues all the real causal ldquooomphrdquo drains away to the lowest level like water
seeping through loose topsoil to collect on the solid bedrock below it To argue for strong
emergence on this view is to argue for downward causationmdashto argue for the behavior of the
whole affecting the behavior of the parts in a way that doesnrsquot turn out to be attributable to the
parts just affecting one another
11 Emergence as a State-Constraint
All of this is just a rehearsal of some very well-known moves in contemporary analytic
metaphysics However this is not a paper in analytic metaphysics (at least not traditionally
construed) so let us now turn to the task of translating this discussion into a language that is
more amenable to the kind of work wersquore concerned with doing heremdashletrsquos see if we can recast
3 At least virtually everyone who isnrsquot a compositional nihilist (who by their own account donrsquot exist anyway)
would agree to this
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
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space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 629
metaphysical view and still admit this sort of weak emergence even the most hardened
reductionist can admit that it might be impossible to predict the behavior of (say) a human being
by treating only the behavior of his most basic proper parts (the quarks composing his body
say) The utility of the special sciences as independent from fundamental physics requires only
this sort of weak emergence even if the impossibility of predicting the behavior of a whole from
knowledge of its parts is a practical rather than principled one system-level behavior (and
properties) might be said to be weakly emergent
The compatibility of this kind of weak emergence with strong ontological reductionism
means that it is rather uninteresting philosophically Virtually no one would deny weak
(epistemic) emergence and so the position is worth very little consideration It is a truism that
physics is not always the most practical way to study the physical world If wersquore to say
something interesting then we should restrict ourselves here to a discussion of strong
emergence I argue that contrary to some prejudice in the existing philosophical literature the
notion of strong emergence is not only conceptually tractable but that complexity-theoretic
considerations give us reason to think that it is straightforwardly scientifically tractable as well
I have said that we can think of strong emergence as being about the emergence of system-
level features that are not just reducible to features the individual parts of the system but what
exactly does that mean The evocative notion of ldquocausal drainagerdquo that appears in the
philosophy of mind literature can help to clarify things here if only by presenting a neat
statement of a view opposed to this kind of strong emergence so perhaps that is the best place to
start
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The ldquocausal drainagerdquo argument is perhaps most clearly and forcefully argued for in Kim
(1998) and (2003) The claim goes something like this ldquoUpward causationrdquo is uncontroversial
in the following sense everyone agrees that the actions of parts can have real tangible effects on
the behavior of wholes3 That is everyone agrees that shifting the positions of a few electrons
can have an effect on an atomrsquos chemical properties (say its propensity to form covalent bonds
with other atoms) or that changes in the structure of a single cell can have an effect on an
organismrsquos biological fitness (say by triggering the formation of a fatal malignancy) On the
other hand it would be absurd (the argument goes) to imagine that causation might happen in the
other direction Changes in electrons might cause changes in economies (for instance as when a
surge in electrons fries the computers on the New York Stock Exchange) but itrsquos not even clear
what it would mean for a change in an economy to cause a change in electrons On careful
analysis Kim argues all the real causal ldquooomphrdquo drains away to the lowest level like water
seeping through loose topsoil to collect on the solid bedrock below it To argue for strong
emergence on this view is to argue for downward causationmdashto argue for the behavior of the
whole affecting the behavior of the parts in a way that doesnrsquot turn out to be attributable to the
parts just affecting one another
11 Emergence as a State-Constraint
All of this is just a rehearsal of some very well-known moves in contemporary analytic
metaphysics However this is not a paper in analytic metaphysics (at least not traditionally
construed) so let us now turn to the task of translating this discussion into a language that is
more amenable to the kind of work wersquore concerned with doing heremdashletrsquos see if we can recast
3 At least virtually everyone who isnrsquot a compositional nihilist (who by their own account donrsquot exist anyway)
would agree to this
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1029
system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 729
The ldquocausal drainagerdquo argument is perhaps most clearly and forcefully argued for in Kim
(1998) and (2003) The claim goes something like this ldquoUpward causationrdquo is uncontroversial
in the following sense everyone agrees that the actions of parts can have real tangible effects on
the behavior of wholes3 That is everyone agrees that shifting the positions of a few electrons
can have an effect on an atomrsquos chemical properties (say its propensity to form covalent bonds
with other atoms) or that changes in the structure of a single cell can have an effect on an
organismrsquos biological fitness (say by triggering the formation of a fatal malignancy) On the
other hand it would be absurd (the argument goes) to imagine that causation might happen in the
other direction Changes in electrons might cause changes in economies (for instance as when a
surge in electrons fries the computers on the New York Stock Exchange) but itrsquos not even clear
what it would mean for a change in an economy to cause a change in electrons On careful
analysis Kim argues all the real causal ldquooomphrdquo drains away to the lowest level like water
seeping through loose topsoil to collect on the solid bedrock below it To argue for strong
emergence on this view is to argue for downward causationmdashto argue for the behavior of the
whole affecting the behavior of the parts in a way that doesnrsquot turn out to be attributable to the
parts just affecting one another
11 Emergence as a State-Constraint
All of this is just a rehearsal of some very well-known moves in contemporary analytic
metaphysics However this is not a paper in analytic metaphysics (at least not traditionally
construed) so let us now turn to the task of translating this discussion into a language that is
more amenable to the kind of work wersquore concerned with doing heremdashletrsquos see if we can recast
3 At least virtually everyone who isnrsquot a compositional nihilist (who by their own account donrsquot exist anyway)
would agree to this
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 829
this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 929
space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1029
system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 829
this conception of strong emergence in the language of dynamical systems theory and search for
any insights that might be revealed by this translation4 My hope is that some of the issues that
are obscured in the traditional vocabulary become more amenable to analysis after translation
Letrsquos start by seeing if we can capture the spirit of downward causation in dynamical
language without a direct reference to causation itself While we canrsquot jettison the metaphysical
baggage that comes with lsquoemergencersquo we should at least try to engage with the topic without
miring ourselves in related metaphysical quagmires the language of cause and effect comes
loaded with problems about metaphysical necessity temporal ordering and other things that I
donrsquot want to engage with here Whatrsquos the systems-theoretic analog of downward causation
then Whatrsquos the best translation of the concept It might be helpful to begin by thinking about
what upward causation looks like on the DST view When we talk about upward causation in
circumstances like this onemdashthat is in contexts like Kimrsquos where itrsquos contrasted with downward
causationmdashit seems that wersquore concerned not just with particular events but with ensembles of
events Consider the difference between talk of ldquostandardrdquo single-event causationmdashstatements
like ldquothe baseballrsquos hitting the window caused the glass to breakrdquomdashand the kinds of claims that
wersquore interested in here When Kim worries that causal power ldquodrains awayrdquo to the lowest level
hersquos not concerned just with tracing out the order of explanation of particular events but with
describing how the possible states of system constituents relate to possible states of the system
considered as a whole That is claiming that all the causal power is in the ldquoupwardrdquo direction
from (say) neurons to brains just is claiming that therersquos an asymmetric relationship of constraint
between neuron-states and brain-states the space of possible brain states is constrained by the
4 There has already been a bit of work done in articulating a general metaphysical theory that takes systems and
processes (rather than objects and states) as being the fundamental object of analysis While our project here is
definitely closely related to that work a digression into systems metaphysics in general would take us too far afield
Even our present discussion of emergence is only intended as a prelude to our examination of self-organization For
a good contemporary examination of systems metaphysics see Bickhard (2011)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
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httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1029
system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 929
space of possible neuron states but the reverse is not true This seems to be what most
philosophers mean when they say that brain-states supervene on neuron-states that the nature of
the state-constraint is asymmetrical
This might seem like a trivial point but emphasizing this way of looking at the problem
highlights a natural translation from talk of causation into DST-friendly vocabulary When
wersquore interested in whether or not a system exhibits what the metaphysical literature calls
ldquodownward causationrdquo wersquore interested in whether or not the states of that systemrsquos parts are
constrained in any way by the state of the system as whole Of course not just any constraints
will do wersquore interested in constraints that donrsquot just turn out on examination to stem from the
actions of the constituents as isolated parts But what does it mean for the constraint to ldquostemrdquo
from the actions of the constituents in this sense We have to be careful here lest we tip over
into the mystical strong emergence of the vitalists wersquove already discarded Unless we want to
discard physicalism entirely (which we surely donrsquot) there has to be some sense in which the
behavior of any systemmdashcomplex or otherwisemdashis the result of the actions of its parts That is
we surely donrsquot want to demand that downward causation in the sense wersquore exploring here
exclude upward causation if therersquos genuine emergent behavior to be found in the world it must
exist alongside run-of-the-mill non-emergent behavior Systems of interest to us would be those
which exhibit both downward and upward causationmdashsystems in which there are both system-
level and constituent-level constraints on behavior present
Wersquore getting somewhere but our target is still not clear enough The language of constraints
and boundary conditions seems like the right one to capture the spirit behind discussions of
emergence and downward causation but wersquove yet to articulate any precise conditions
demarcating when the phenomenon can be appropriately said to be taking place in a particular
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1029
system I would like to suggest the following criteria Emergence (or downward causation) is
present in a system when the following conditions are satisfied (1) States of the systemrsquos
constituent parts are constrained by the state of the system as a whole (2) the constraint(s) on the
systemrsquos constituent parts are not present if the parts are isolated from the rest of the system In
other words for each constituent part of the system that partrsquos place in the system as a whole
issufficient for the constraint in question to be operative5 If this is the case then the system can
be said to exhibit downward causation
This can all be made far clearer with a concrete example Consider the following (strikingly
simple) case from a woefully under-cited 2004 research paper by the New England Complex
System Institutersquos Yaneer Bar-Yam6 Suppose wersquove got a system of three bits that can be either
on or off (it can be helpful to visualize this as an array of three lights that are either lit or not lit)
Suppose further that the following constraint is in place the only allowable states of the system
are those in which an odd number of bits are in the ldquoonrdquo state7
While this is a constraint on the
allowable state of the entire (ie 3-bit) system it is interesting to note that it is not a constraint on
any subset of the system including both single bitsand pairs of bits Thank about why given
two bits set to any arbitrary value the value of the third bit is dictated by the global constraint
However it isnrsquot correct to say that any particular bit in the system was impacted by the global
constraint for if we were to examine any two-bit (or single-bit) subset the impact of the global
constraint would be totally indiscernible given a complete three-bit state the question ldquowhich
5 Whether or not it is also necessary is a sticky issue The multiple-realizability of many emergent constraints
suggests that the componentrsquos place in this particular system is not a necessary condition on its operating under the
constraint in question but that itrsquos place in some system thatrsquos relevantly similar to this system is a necessary
condition The explanation for this will become clear as we go forward so I can only ask for a bit of patience Stick
with me here and wersquoll return to this point6Bar-Yam (2004) This piece received moderate attention from complexity theorists and physicists but virtually no
attention from philosophers despite being a strikingly novel approach to a time-tested philosophical chestnut7 That is states like 110 and 010 would be permitted but states like 000 and 111 would not be The
argument given here can be generalized to systems of n bits but the point is most obviously striking in 3-bit
systems
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1329
as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
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983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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bitrsquos state was caused by the overall constraintrdquo makes no sense The constraint is only apparent
when we examine ensembles of system-states to see which are allowed and which are not This
is despite the fact that the constraint affects the state of individual bits
But this has the air of being vaguely contradictory On one hand we are saying that the
constraint is globally important only and that the state of any one or two-bit subsystem is not
affected On the other hand it seems obvious that the global constraint must somehow be
affecting the value of individual bitsmdashgiven two bits set arbitrarily the constraint tells us what
the third bit must be So are individual bits affected or arenrsquot they Is there downward
causation here or not Resolving this apparent contradiction requires us to shift our attention yet
againmdashwe need to attend not just to bit states or 3-bit system states but ensembles of system
states Bar-Yam writes
The value of the individual bit is impacted by the values of the rest of the bits as far as a single state is
concerned but not as far as an ensemble is concerned This is the opposite of what one would say about the
entire system which is impacted in the ensemble picture but not in the state picture8
Letrsquos take a minute to unpack this because understanding this point is critical Return again
to the 3-bit system Notice that with or without the constraint the set of possible states of the
system is such that the probability of finding any single bit in a particular state is the same This
is obvious if we just list out all the allowable states of the system with and without the constraint
(see thatrsquos why wersquore only using a 3-bit system)
Allowed States
Constrained 001 010 100
111
Unconstrained 000 001 010
011 100 111
8Op cit page 20
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1229
101 110
In each case each individual bit is ldquoonrdquo in 50 of states and each pairing of on-off states
across two bits (eg ldquofirst bit off last bit onrdquo) is present in 25 of states That is from the
perspective of the ensemble of possible states of the system the presence or absence of the
constraint has absolutely no impact on the value of individual bits However if we pick out
particular states the presence or absence of the constraint matters a great deal it will dictate the
allowable values of any bit in the state given a specification of the value of the others The
ensemble statistics for particular bits are not impacted by the constraint despite the fact that for
any given state each bitrsquos value is in fact constrained On the other hand the ensemble statistics
for states of the system are most certainly impacted despite the fact that the constraint operates
on bits rather than on system-states directly
Itrsquos important to emphasize that while there is an epistemic aspect to this case it is not a
purely epistemic problem While it is indeed true that each bit is constrained (in the sense
described above) in a way that could never be discerned through the observation of any number
of one or two-bit subsystems therersquos more going on here than the kind of epistemic (weak)
emergence we discussed earlier The problem in other words is not just that we canrsquot predict
what the system will do given information about the allowable states of individual bits (though
thatrsquos certainly true) The problem is that we canrsquot make that prediction even in principle wersquore
not limited by computational concerns or uncertainty in measurement or anything like that
Therersquos a genuine causally efficacious (in the sense associated with ldquoupward causationrdquo)
constraint operating There is genuine downward causation here both (1) and (2) are satisfied
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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as the constraint helps to determine the state of each bit in a complete 3-bit state but the impact
of the constraint disappears when we look at the behavior of particular bits (or proper sub-sets of
bits) outside the context of the system
Bar-Yamrsquos example is striking but it is still a toy system and does little more than emphasize
the conceptual (and mathematical) tractability of strong emergence How might this apply to
more real-world systems At bottom this is an empirical question though this toy example is
telling in a number of ways The most important point to emphasize I think is that this example
suggests what kind of thing we ought to look for when wersquore searching for emergence and it
suggests methodological guidelines for conducting that search Constraints of the kind present in
this proof-of-concept example are (again) genuine and yet are not detectable (or even sensibly
present) in subsystems considered in isolation In Bar-Yamrsquos example the constraint operates
on each bit and yet is not reducible to a constraint on individual bits and does not result from
the mutual influence of pairs of bits on one another Generalized to more real-world systems
this suggests the possibility of constraints that operate on physical systems and yet are not
reducible to the behaviors of proper parts or even relations between proper parts It suggests the
possibility of emergence that is both ldquostrongrdquo in the sense described above and yet consistent
with a broadly physicalist (or naturalist) view of the world To avoid opening the totally separate
can of worms that is the question of how to make sense of ldquopropertiesrdquo let us just call things like
the parity-bit condition given in this example ldquoemergent constraintsrdquo on the behavior of the
system In the next section I would like to explore some of the implications of the existence of
emergent constraints with particular attention to how they relate to order organization and
(ultimately) self-organized behavior
20 Order and Organization Introduced
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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Discussions of self-organization abound in the complexity theory literature9 but getting a clear
definition of organization (never mind the ldquoselfrdquo part for now) is startlingly difficult Most
authors seem to take it for granted that we have an intuitive grasp on what it means for a system
to be organized Perhaps the most succinct definition comes from physicist Sunny Auyang who
says that organization is the ldquoformation of new structures in the symmetry breaking of
equilibrium systems10
rdquoAnother good suggestion is given by Cliff Hooker who writes that self-
organization is ldquoa process where dynamical form is no longer invariant across dynamical states
but is rather a (mathematical) function of them11rdquo Both of these are actually pretty good
characterizations of the phenomenon and therersquos a sense in which each of them captures an
important feature of organization Wersquoll return to them in a moment but itrsquos going to take quite a
bit of unpacking to figure out just what even these two characterizations are driving at and to
articulate how they relate to the kind of emergence wersquove been discussing so far Whatrsquos
ldquostructurerdquo in the relevant sense What does it have to do with symmetry breaking What does
it mean for the dynamical form of a system to be a function of its dynamical states What are the
mechanisms by which these things happen and whatrsquos the connection to emergence
Before we begin to tackle those questions one other major issue is worth flagging as being
worthy of our attention Just as few authors come right out and give a direct definition of
lsquoorganizationrsquo there is a wide-spread(and very casual) conflation of order and organization The
fact that lsquoorderedrsquo and lsquoorganizedrsquo as used so similarly within the popular discourse as to be
virtually synonymous is perhaps to be expected (and excusable) More distressing is the degree
9 Waldrop (1992) Kauffman (1993) Auyang (1998) Strevens (2003) Gribbin (2004) Mitchell (2009) Hooker
(2011) and Johnson (2009) all contain significant discussions of self-organization but this even this list only
scratches the surface of what is out there Virtually every work on complexity theory written in the last 25 years
includes some treatment of the phenomenon of self-organization10
Auyang (1998) p 24211
Hooker (2011) p 212
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
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983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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to which the mistake pervades even the professional literature Auyang makes it referring to
self-organization as ldquothe spontaneous appearance of order which is common in complex
systems12rdquo but shersquos far from the only guilty party Stuart Kaufmann one of the founding-
fathers of modern complexity theory is even guilty of the mistake in the title of his
groundbreaking book on the subject The Origins of Order Self-Organization and Selection in
Evolution In the preface to that same work he writes ldquoSimple and complex systems can exhibit
powerful self-organization Such spontaneous order is available to natural selection and random
drift for the further selective crafting of well-wrought designs or the stumbling fortuity of
historical accident13
rdquo Indeed it is entirely possible that this initial equivocation of the two terms
in such a seminal work is to a very large degree responsible for the persistence of this confusion
for such a long time Kaufmann used the terms lsquospontaneous orderrsquo and lsquoself-organizationrsquo as if
they were synonymous (or very nearly so) and the conflation has remained largely
uninvestigated to this day with very few exceptions14
Even when the two concepts are
differentiated therersquos been virtually no attempt in the literature to give careful definitions of each
term let alone explore how they relate to one another As we shall see this is more than a mere
semantic issuemdashmore than philosophical logic-chopping The difference between order and
organization is metaphysically (and physically) very significant and understanding why
represents a big step toward understanding complexity itself
Bar-Yamrsquos 3-bit system discussed in Section 1 is a good proof-of-concept for the possibility of
genuine emergence in a toy system It is however also somewhat limited Because the system
12 Ibid p 32
13 Kaufmann (1993) p 1
14 Most notably Hooker (2011) seems to escape the trap noting that ldquoCrystal formation is rather an instance of the
formation of orderedness rather than of organizationrdquo (op cit p 211) This remake is made en passant though
and it isnrsquot clear that Hooker recognizes the significance of his observation or its connection to emergence and the
broader metaphysics of complex systems
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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is so simplemdashbecause it consists of states of only three bits each of which can take on only one
of two possible valuesmdashit is not obvious how to translate Bar-Yamrsquos formal insight into an
insight about the workings of real-world physical systems Letrsquos start then by thinking about
how to generalize the lessons from Section 1 in such a way that they might shed some light on
the significantly messier systems of the natural world
21 Dynamical Systems Metaphysics
It might be helpful to visualize Bar-Yamrsquos system as an abstract space of possible states of
the system Every point in the space represents a possible state of the complete systemmdasha
specific value for each of the three bits This approach should be familiar to most readers it is
the notion of a state-space or configuration space thatrsquos commonly employed in many sciences
If we had some facts about the dynamics of Bar-Yamrsquos systemmdashsome kind of pattern that
described how the states transition from one to anothermdashthen wersquod be able to plot out a map of
the system If the dynamics were totally deterministic then for any starting position in the space
wersquod have a path through the space that represents the succession of states the system would
proceed through if it started in a given state15 Given a picture like this how do we understand
the kind of system-wide constraint that Bar-Yam describes The answer should be fairly
obvious the constraint represents points (or regions) of the state-space which are so to speak
ldquoout of boundsrdquomdashstates that the system simply canrsquot get into no matter what its dynamics are or
15 Note for that for a space just like this totally deterministic dynamics would have to be pretty boring If the
dynamics for some system are deterministic then the legal paths through the state can never cross If they did that
would imply that there is some possible state (the point where the paths cross) for which there are two (or more)
possible successor-states but (by definition) that canrsquot happen in a deterministic system Bar-Yamrsquos system given
some deterministic dynamics would have to settle fairly quickly into some kind of steady state either one or more
fixed-point attractors toward which a number initial states move (and then stay put once theyrsquore there) or one or
more limit-cycle attractors (closed orbits that states can never break out of once theyrsquore inside) or possibly some of
each
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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where it starts at least so long as the emergent constraint remains in place Thatrsquos just what it
means to be an emergent constraint
Note that this constraint is different in kind from either initial-condition or boundary-
condition constraints The difference between an emergent constraint and an initial-condition
constraint is clear while the difference between an emergent constraint and a constraint imposed
by a boundary condition is a bit less obvious The difference is most obvious if we think about
the sort of state-space that we just describedmdashthe one representing Bar-Yamrsquos three-bit
systemmdashas being embedded in a larger state space representing a system of n bits If we were to
define some dynamics for the system16
a boundary condition would define a topologically
connected sub-space (or in the case of the specific example at hand a sub- graph) to which we
should restrict our attention The only restriction a boundary condition places on perturbations
of some system state is that those perturbations cannot take the system as a whole outside the
sub-spacemdashie into regions of the space where more than three bits have possible values It has
nothing whatsoever to say about transitions of individual bits within that space Contrast that
with the emergent parity constraint in Bar-Yamrsquos case in addition to restricting states of the
system as a whole the emergent constraint (as we saw) also plays an important role in
determining the state of individual bits when they appear in contextWe can see this even more
clearly when we ask how much information we need to specify the successor-state to some given
system-state Given a state of three bits we can ask ldquoif I were to flip one bit at random whatrsquos
the probability that the resulting state will be one that is permitted by the constraints operating on
16 This is necessary to make the notions of ldquoinitialrdquo and ldquoboundaryrdquo conditions make any sense at all since both of
those are dynamical notions that require the definition of a path (or possible path) through the state-space to be
applicable Without some temporal aspect ldquoinitialrdquo loses its meaning and the solutions to the differential (or
difference) equation that boundary conditions by definition restrict do not exist (since to give some
differentialdifference equations is to define a temporalized path through the state space)
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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the systemrdquo The kind of boundary condition we just suggested would have nothing at all to say
about this question while the emergent parity constraint would definitely play a role in our
calculationWhile both traditional boundary conditions and emergent constraints restrict the
time-evolution of the system in various ways they are distinct concepts with distinct physical
interpretations17
Whatrsquos going on here Whatrsquos the difference between order and organization Whatrsquos going
on when we add an emergent constraint to a system Notice to begin that in adding a constraint
like this one wersquore increasing the pattern richness of the space of possible states into which the
system can transition If multiple constraints are operative on the same system at the same time
theyrsquoll have to be mutually-consistent if the system is to be able to do anything at all Consider
for example the stipulation that in addition to the first constraint given on Bar-Yamrsquos parity
system we add the constraint ldquothe sum of the values of all of the bits must be onerdquo Clearly this
additional restriction constrains the available states of the system even furthermdashnow only
100 010 and 001 are legal On the other hand adding the constraint ldquothe number of
lsquoonrsquo bits must be evenrdquo is (manifestly) not allowed as itrsquos being in place is ruled out by the
original emergent constraint given by Bar-Yam Therersquos just no way for the system to get into a
state where both of those constraints are satisfiedMultiple restrictions placed on the same space
restrict the possible states that the system can get in to That is fairly obvious What is perhaps
17 In the vast majority of cases the boundaries defined by boundary conditions on differential equations employed in
the natural sciences carve out continuous connected (and often path-connected) regions It is intriguing to consider
whether this preponderance of topologically-connected boundaries holds for emergent conditions as well I suspect
it does not and thus that real-world physical systems with emergent constraints will often be restricted to states
which are not connected (or a fortiori path-connected) with one another this might be a way to make the
metaphysical notion of ldquomultiple realizeabilityrdquo more precise Further exploration of this question (and its
implications) would likely yield some fruitful material for further work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1929
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2329
represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2729
This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1929
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2029
what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
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983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
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983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
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983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
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983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
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983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2029
what it meansto say that the space is ldquowell-mappedrdquo It means we know a tremendous amount
about the dynamics of the system that the patterns that underlie the motion of points inside the
state-space corresponding to Newtonian Mechanics are fairly well-understood Next consider
what it means to say that Newtonian mechanics applies to my apartment in the first place As we
said above a set of dynamics for a given state space provides a set of directions for moving from
any point in the phase space to any other pointmdashit provides a map identifying where in the space
a system whose state is represented by some point at t 0 will end up at a later time t 1 This map is
interesting largely in virtue of being valid for any point in the space no matter where the system
starts (as long as it starts somewhere in the space more on this in a moment) at t 0 the dynamics
will describe a set of patterns in how its state changes That is given a list of points
[a0 b0 c0 d 0hellipz0] the dynamics give us a corresponding list of points [a1 b1 c1 d 1hellipz1] that the
system will occupy after a given time interval has passed (again assuming that in the interim the
systemrsquos path didnrsquot take it outside the space wersquoll discuss this point shortly)
As we said though this is not the only approach to prediction In addition to the possibility of
choosing a different kind of state-space with which to describe my apartment (if wersquore
masochists maybe a Fock space18) it might be (and in fact is) the case that there are also
patterns to be discerned in how certain regions of our chosen spacemdash the Newtonian phase
space in this casemdashevolve over time That is we might be able to describe patterns of the
18 If yoursquore optimistic about the future of physics you might suspect that we could eventually discover a set of
patterns and a state-space which would let us represent (and predict the future behavior of) absolutely any physical
system out there This does indeed seem to be the tacit goal of fundamental physics finding patterns that apply to
more and more of the world Whether or not this ldquotheory of everythingrdquo is out there is not immediately relevant for
our concerns here I will just say that even if we were to discover such a theory it seems clear that it would often
not be the optimal theory for actual day-to-day prediction Depending on our goals wersquore often willing to trade
restricted domain of applicability for ease of use particularly when our interest is generally restricted to a relatively
small set of similar systems If wersquore interested primarily in how insects behave it makes more sense to work with
entomology than with quantum mechanics and the objection that quantum mechanics describes insects and also
electrons carries little weight For more on this point see Dennett (199xxx) Lawhead (2011) and Lawhead (2012)
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following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2129
following sort if the room starts off in any point in region P0 it will after a given interval of
time end up in another region P1 This is in fact the form of the statistical-mechanical
explanation for the Second Law of Thermodynamics This is clearly not a description of a
pattern that applies to the space in general there might be a very large number (perhaps even a
continuous infinity if the space in question is continuous) of points that do not lie inside P0 and
for which the pattern just described thus just has nothing to say This is not necessarily to say
that the project of identifying patterns like P0 P1 isnrsquot interesting though Suppose the
generalization identified looks like this if the room is in a region corresponding to ldquothe kitchen
contains a pot of boiling water and a normal human being who sincerely intends to put his hand
in the pot19rdquo at t 0 then evolving the system (say) 10 seconds forward will result in the roomrsquos
being in a region corresponding to ldquothe kitchen contains a pot of boiling water and a human
being in great pain and with blistering skinrdquo
With a good understanding of this view of prediction in hand letrsquos return to the main thread
of the essay What does all this have to do with the metaphysics of emergence and organization
Well consider what it means to say that for some system S there are a number of different state
spaces we might choose from to represent it For a normal living human brain for instance we
might choose the space defined by neurobiology (in which points in the space represent action
potentials neurotransmitter location ampc) or we might choose the space defined by organic
chemistry (in which points in the space represent the position and velocity of chemical
molecules ampc) or we might choose the space defined by good old Newtonian mechanics
19 We can think of the ldquosincerely intends to put his hand in the potrdquo as being an assertion about location of the
system when its state is projected onto a lower-dimensional subspace consisting of the configuration space of the
personrsquos brain Again this location will (obviously) be a regional rather than precise one there are a large number
of points in this lower-dimensional space corresponding to the kind of intention we have in mind here
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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(which wersquore already familiar with) and so on We might even choose the space defined by
cognitive neuroscience in which points in the space represent information-processing states of
functional collections of brain regions
The multiplicity of interesting (and useful) ways to represent the same systemmdashthe fact that
precisely the same physical system can be represented in very different state spaces and that
interesting patterns about the time-evolution of that system can be found in each of those state
spacesmdashhas tremendous implications Each of these patterns of course represents a constraint
on the behavior of the system in question if some systemrsquos state is evolving in a way that is
described by some pattern then (by definition) its future states are constrained by that pattern
As long as the pattern continues to describe the time-evolution of the system then states that it
can transition into are limited by the bounds set by the presence of the constraints To put the
point another way patterns in the time-evolution of systems just are constraints on the system
Itrsquos worth emphasizing that these constraints can (and to some degree must ) apply to all the
spaces in which a particular system can be represented After all the choice of a state space in
which to represent a system is just a choice of how to describe that system and so to notice that
a systemrsquos behavior is constrained in one space is just to noticethat the systemrsquos behavior is
constrained period Of course itrsquos not always the case that the introduction of a new constraint at
a particular level will result in a new constraint in every other space in which the system can be
described For a really basic example visualize the following scenario
Suppose we have three parallel Euclidean planes stacked on top of one another with a rigid rod
passing through the three planes perpendicularly (think of three sheets of printer paper stacked
with a pencil poking through the middle of them) If we move the rod along the axisthatrsquos
parallel to the planes we can think of this as representing a toy multi-level system the rod
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2329
represents the system the planes represent the different state-spaces we could use to describe the
systemrsquos position (ie by specifying its location along each plane) Of course if the paper is
intact wersquod rip the sheets as we dragged the pencil around Suppose then that the rod can only
move in areas of each plane that have some special propertymdashsuppose that we cut different
shapes into each of the sheets of paper and mandate that the pencil isnrsquot allowed to tear any of
the sheets The presence of the cut-outsections on each sheet representsthe constraints based on
the patterns present on the systemrsquos time-evolution in each state-space the pencil is only allowed
in areas where the cut-outs in all three sheets overlap
Suppose the cut-outs look like this On the top sheet almost all of the area is cut away
except for a very small circle near the bottom of the plane On the middle sheet the paper is cut
away in a shape that looks vaguely like a narrow sine-wave graph extending from one end to
another On the bottom sheet a large star-shape has been cut out from the middle of the sheet
Which of these is the most restrictive For most cases itrsquos clear that the sine-wave shape is if
the pencil has to move in such a way that it follows the shape of the sine-wave on the middle
sheet there are vast swaths of area in the other two sheets that it just canrsquot access no matter
whether therersquos a cut-out there or not In fact just specifying the shape of the cut-outs on two of
the three sheets (say the top and the middle) is sometimes enough to tell us that the restrictions
placed on the motion of the pencil by the third sheet will likely be relatively unimportantmdashthe
constraints placed on the motion of the pencil by the top sheet are quite stringent and those
placed on the pencil by the bottom sheet are quite lax There are comparatively few ways to
craft constraints on the bottom sheet then which would result in the middle sheetrsquos constraints
dominating here most cut-outs will be more restrictive than the top sheet and less restrictive than
the middle sheet
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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The lesson here is that while the state of any given system at a particular time has to be
consistent with all applicable constraints (even those resulting from patterns in the state-spaces
representing the system at very different levels of analysis) itrsquos not quite right to say that the
introduction of a new constraint will always affect constraints acting on the system in all other
applicable state spaces Rather we should just say that every constraint needs to be taken into
account when wersquore analyzing the behavior of a system
The fact that some systems exhibit interesting patterns at many different levels of analysismdashin
many different state-spacesmdashmeans that some systems operate under far more constraints than
others The lesson to take from our discussion in Section 1 about Bar-Yamrsquos toy system is that
ldquoemergencerdquo just means the introduction of a new constraint (albeit one of a very particular kind)
on allowable states of the system This explains why emergent phenomena seem to exhibit
features that have been traditionally associated with ldquodownward causationrdquo they are restricting
the allowable states of the system and this restriction can manifest in changes to the dynamical
formmdashthe patterns in its state-transitionmdashof the system at multiple levels of analysis Unless we
appreciate the relationship between the patterns at different levels this can look incredibly
mysteriousmdasheven anomalous Once we see that any systemrsquos behavior must be consistent with
all the patterns that describe its behaviormdashand that in order to see some of those patterns we
must shift our perspective as we did when we started paying attention to ensembles of states
rather than single states (or single bits) in Bar-Yamrsquos systemmdashthe mystery becomes a good deal
less mysterious The practical task of identifying all the relevant patterns for particular
systemsmdasha task that includes figuring out how to design state spaces that will make those
patterns most amenable to identificationmdashis a very hard problem indeed but it is the scientistrsquos
problem not the metaphysicianrsquos and I leave her to her work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
983124983144983141983151983154983161 983137983150983140 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2011983137) C983144983137983152983156983141983154 983124983159983151 983127983144983137983156983155 983156983144983141 983123983145983143983150983145983142983145983139983137983150983139983141 983151983142 C983151983149983152983148983141983160983145983156983161 983105983140983137983152983156 983137983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983137983150983140
983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983148983145983149983137983156983141 983123983139983145983141983150983139983141 C983151983148983157983149983138983145983137 983125983150983145983158983141983154983155983145983156983161
983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2529
22 Order and Organization at Last
After all this though we still havenrsquot explained organization Happily I think that the road
from here is relatively easy for the philosopher Wersquove assembled all the tools we need to tackle
this problem most of the heavy lifting has already been done in the preceding pages
Organization is the process by which a system comes to operate under a greater number of
emergent constraints than it did before
20
By organizing a system does two things it increases
the pattern-richness of its behavior and (necessarily) reduces the number of different states in
which it can be The existence of a real pattern in one of a systemrsquos state-spaces represents a
restriction on the movement of the same system in other of its state-spaces (though not
necessarily in all of them) The more patterns that exist in a system the more narrow the field of
possible states that the system can transition to
At this point wersquore also in a position to say why lsquoorganizationrsquo cannot possibly be the same
thing as lsquoorderrsquo A system that is highly ordered is in some sense also a boring system As
Hooker notes21
crystals are highly ordered structures Crystals are highly symmetric low-
entropy and highly static systems They are quite stable but only in virtue of lacking a large
number of interesting patterns that describe their time-evolution Crystals have the same
response to a fairly wide class of environmental perturbations just sit there (and maybe resonate
a little bit) By contrast highly organized systems tend to be very interesting and dynamic
20 Elsewhere I have suggested that we should use the term lsquodynamical complexityrsquo to refer to the quantitative
pattern-richness of a particular system The process of organization then just is the process by which a systemrsquos
dynamical complexity is increased For an introduction to the concept of dynamical complexity (and the
mathematical formalism of ldquoeffective complexityrdquo that underlies it) see Lawhead (2011a)
21Op cit
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
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983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
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983116983137983159983144983141983137983140 983114 (2012) 983107983151983150983139983141983152983156983155 983145983150 983107983151983149983152983148983141983160983145983156983161 983113983098 983118983151983150983085983116983145983150983141983137983154983145983156983161 983137983150983140 983107983144983137983151983155 983122983141983156983154983145983141983158983141983140 05 20 2012 983142983154983151983149 A983139983137983140983141983149983145983137983141983140983157
9831449831569831569831529831399831519831489831579831499831389831459831379831379831399831379831409831419831499831459831379831419831409831579831149831519831509831169831379831599831449831419831379831409831209831379831529831419831549831551257114983116983137983159983144983141983137983140983135983085983135C983151983150983139983141983152983156983155983135983145983150983135C983151983149983152983148983141983160983145983156983161
983116983137983159983144983141983137983140 983114 (2012983137) 983111983141983156983156983145983150983143 983110983157983150983140983137983149983141983150983156983137983148 A983138983151983157983156 D983151983145983150983143 983120983144983161983155983145983139983155 983145983150 983124983144983141 B983145983143 B983137983150983143 983124983144983141983151983154983161 983113983150 D 983115983151983159983137983148983155983147983145 983124983144983141 983106983145983143
983106983137983150983143 983124983144983141983151983154983161 983137983150983140 983120983144983145983148983151983155983151983152983144983161 (983152983152 99983085111) 983112983151983138983151983147983141983150 983118983114 B983148983137983139983147983159983141983148983148
983117983145983156983139983144983141983148983148 983117 (2009) 983107983151983149983152983148983141983160983145983156983161983098 983105 983111983157983145983140983141983140 983124983151983157983154 983118983141983159 983129983151983154983147 983119983160983142983151983154983140 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
983117983151983154983143983137983150 C 983116 (1923) 983109983149983141983154983143983141983150983156 983109983158983151983148983157983156983145983151983150 983116983151983150983140983151983150 983127983145983148983148983145983137983149983155 983137983150983140 983118983151983154983143983137983156983141
983122983151983155983155 D (2000) 983122983137983145983150983142983151983154983141983155983156 983122983141983137983148983145983155983149 A D983141983150983150983141983156983145983137983150 983124983144983141983151983154983161 983151983142 E983160983145983155983156983141983150983139983141 983113983150 D 983122983151983155983155 A B983154983151983151983147 amp D ( 983124983144983151983149983152983155983151983150
983108983141983150983150983141983156983156983155 983120983144983145983148983151983155983151983152983144983161983098 983105 983107983151983149983152983154983141983144983141983150983155983145983158983141 983105983155983155983141983155983155983149983141983150983156 (983152983152 147983085168) 983124983144983141 983117983113983124 983120983154983141983155983155
983123983156983154983141983158983141983150983155 983117 (2003) 983106983145983143983143983141983154 983156983144983137983150 983107983144983137983151983155983098 983125983150983140983141983154983155983156983137983150983140983145983150983143 983107983151983149983152983148983141983160983145983156983161 983156983144983154983151983157983143983144 983120983154983151983138983137983138983145983148983145983156983161 983110983145983154983155983156 983112983137983154983158983137983154983140 983120983154983141983155983155
983127983137983148983140983154983151983152 983117 (1992) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983118983141983159 983129983151983154983147 983123983145983149983151983150 amp
983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2629
systems The multiple inter-influencing patterns present in their time-evolution make it possible
for them to respond to a diverse class of environmental perturbations with different behaviors
At the same time the presence of the constraints on the time-evolution of organized systems
prevents them from responding strongly to just any environmental input an organized system
can match its range of possible actions to an active environment It can be highly sensitive
capable of nuanced responses to small changes in the world around it but (in virtue of the variety
of constraints operating on it) only sensitive to the right kinds of inputsThe initial conflation of
order and organization likely stems from the fact that both highly ordered (low-entropy) systems
and highly organized systems occupy positions in their state spaces that are in some sense
ldquospecialrdquo A highly ordered system is one with very low entropymdashone that is in a microstate
corresponding to a low-volume macrostate A highly organized systemrsquos location in state space
is also unusual but it is unusual in a very different sense rather than corresponding to a very
low-volume macrostate it is a location that is pattern rich (and remains so in a variety of
different choices of state space) A highly organized system might also be a low-entropy system
(and dissipative systems will have to pay for their increased organization through an increase in
environmental entropy just as they would with any other state-transition) but a system that is
low-entropy and highly organized is special in two very different senses To put the point
succinctly highly organized systems can look before they leap while ordered systems rarely
leap at all22
22 We might also say that wholly chaotic systems leap before they look as a chaotic system is one which is highly
sensitive to environmental perturbations but lacks the kind of channeling that the presence of a large number of
emergent constraints provides This account of the relationship between order organization patternhood
complexity and information suggests a possible explanation for Stuart Kaufmannrsquos famous observation that life
thrives ldquoat the edge of chaosrdquo perhaps biological evolution represents a constantly fine-tuned balancing act between
too much order (and thus a lack of flexibility) and too little organization (and thus an inability to coordinate
behavioral responses through the careful application of multi-level constraints on state-transition)
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2729
This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155
B983137983154983085983129983137983149 983129 (2003) 983117983157983148983156983145983155983139983137983148983141 983126983137983154983145983141983156983161 983145983150 C983151983149983152983148983141983160 983123983161983155983156983141983149983155 983107983151983149983152983148983141983160983145983156983161 3798308545
B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524
B983145983139983147983150983137983154983140 983117 (2011) 983123983161983155983156983141983149983155 983137983150983140 983120983154983151983139983141983155983155 983117983141983156983137983152983144983161983155983145983139983155 983113983150 C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141
983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 91983085104) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983111983154983145983138983138983145983150 983114 (2004) 983108983141983141983152 983123983145983149983152983148983145983139983145983156983161983098 983106983154983145983150983143983145983150983143 983119983154983140983141983154 983156983151 983107983144983137983151983155 983137983150983140 983107983151983149983152983148983141983160983145983156983161 983118983141983159 983129983151983154983147 983122983137983150983140983151983149 983112983151983157983155983141
983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140
E983148983155983141983158983145983141983154
983112983151983151983147983141983154 C (2011) C983151983150983139983141983152983156983157983137983148983145983162983145983150983143 983122983141983140983157983139983156983145983151983150 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 E983149983141983154983143983141983150983139983141 983145983150 C983151983149983152983148983141983160 D983161983150983137983149983145983139983137983148 983123983161983155983156983141983149983155 983113983150
C ( 983112983151983151983147983141983154 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 (983152983152 195983085
222) 983119983160983142983151983154983140 E983148983155983141983158983145983141983154
983114983151983144983150983155983151983150 983118 (2009) 983123983145983149983152983148983161 983107983151983149983152983148983141983160983145983156983161983098 983105 983107983148983141983137983154 983111983157983145983140983141 983156983151 983107983151983149983152983148983141983160983145983156983161 983124983144983141983151983154983161 983119983150983141983159983151983154983148983140
983115983137983157983142983149983137983150983150 983123 (1993) 983124983144983141 983119983154983145983143983145983150983155 983151983142 983119983154983140983141983154983098 983123983141983148983142983085983119983154983143983137983150983145983162983137983156983145983151983150 983137983150983140 983123983141983148983141983139983156983145983151983150 983145983150 983109983158983151983148983157983156983145983151983150 983118983141983159 983129983151983154983147 983119983160983142983151983154983140
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983116983137983159983144983141983137983140 983114 (2011) C983144983137983152983156983141983154 983119983150983141 983127983144983151 A983154983141 983129983151983157 983137983150983140 983127983144983137983156 A983154983141 983129983151983157 D983151983145983150983143 983112983141983154983141 983105983140983137983152983156 983105983150983140 983116983141983137983154983150983098 983107983151983149983152983148983141983160983145983156983161
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2929
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2729
This suggests an adaptive benefit to increased organization at least to a point By managing the
relationship between the constrained states and common environmental perturbations highly
organized systems are capable of being very sensitive (and thus responsive) but sensitive (and
responsive) in particular ways only The right combination of sensitivity and restrictions might
well lead to increasingly nuanced responses to the environment though highly organized
systems are likely to be more vulnerable to certain kinds of damage too as external influences
that force the system into a state that is not compatible with one (or more) of its emergent
constraints might well have disastrous consequences for the system suggesting that organization
might represent a trade-off between flexibility and stability Exploring this point however
remains a task for another time
30 Further Directions
All this still needs a tremendous amount of work to be fleshed out and there are a tremendous
number of implications to be explored The relationship between environmental selection and
increased organization (is evolution an organization-increasing process Does increased
organization always confer an adaptive advantage) is one pressing lingering problem as is the
relationship between chaotic behavior and organization (is chaos the result of the kind of
sensitivity organized systems display but without the operation of the emergent constraints
present in those systems) There are also practical implications what can we do to encourage
organization Under what conditions is self -organization likely to arise Can we engineer
organized systems to perform particular tasks
I donrsquot know the answers to these questions but I am excited to help find them I hope I
have at least made it clear that this field is ripe and ready for philosophical work
8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
httpslidepdfcomreaderfullconcepts-in-complexity-ii-emergence-and-the-difference-between-order-and 2829
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead
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