Concepts in Complexity II - Emergence and the Difference Between Order and Organization, Jon Lawhead

29
8/13/2019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization, Jon Lawhead http://slidepdf.com/reader/full/concepts-in-complexity-ii-emergence-and-the-difference-between-order-and 1/29 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 problems—explaining 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 a tremendous number of other novel contributions to our understanding of the world. This paper explores the conceptual connection between this mathematically rigorous account of “strong emergence” (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 be done. 0. The Problem There’s a growing body of multidisciplinary research exploring complexity theory and related ideas. This field has not yet really settled down yet, and so there’s a lot of terminological confusion out there. Different people use the same terms to mean different things (witness the constellation of definitions of ‘complexity’ itself: a field that can’t even agree on what it’s 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 “the conservation of force”), or in pre-Carnot thermodynamics. That is, a lot of people have something to say, but almost no

Transcript of 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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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

8132019 Concepts in Complexity II - Emergence and the Difference Between Order and Organization Jon Lawhead

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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-

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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

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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

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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

Page 2: Concepts in Complexity II - Emergence and the Difference Between Order and Organization, Jon Lawhead

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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

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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

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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

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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

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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)

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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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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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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140

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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 (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

Page 4: 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

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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

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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

Page 5: 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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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

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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

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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

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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

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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

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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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

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

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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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

Page 11: 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

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

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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

Page 12: 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

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B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524

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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

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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 (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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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

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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

Page 14: 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

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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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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)

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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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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983127983151983154983147983155 983107983145983156983141983140A983157983161983137983150983143 983123 (1998) 983110983151983157983150983140983137983156983145983151983150983155 983151983142 983107983151983149983152983148983141983160983085983123983161983155983156983141983149983155 983124983144983141983151983154983161 C983137983149983138983154983145983140983143983141 C983137983149983138983154983145983140983143983141 983125983150983145983158983141983154983155983145983156983161 983120983154983141983155983155

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B983137983154983085983129983137983149 983129 (2004) A 983117983137983156983144983141983149983137983156983145983139983137983148 983124983144983141983151983154983161 983151983142 983123983156983154983151983150983143 E983149983141983154983143983141983150983139983141 983125983155983145983150983143 983117983157983148983156983145983085983123983139983137983148983141 983126983137983154983145983141983156983161 983107983151983149983152983148983141983160983145983156983161 1598308524

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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

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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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

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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

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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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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

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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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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

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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

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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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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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983112983151983151983147983141983154 C ( (2011) 983112983137983150983140983138983151983151983147 983151983142 983156983144983141 983120983144983145983148983151983155983151983152983144983161 983151983142 983123983139983145983141983150983139983141 983126983151983148983157983149983141 9830890983098 983120983144983145983148983151983155983151983152983144983161 983151983142 983107983151983149983152983148983141983160 983123983161983155983156983141983149983155 983119983160983142983151983154983140

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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

Page 20: 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

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

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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

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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

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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

Page 22: 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

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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

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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

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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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

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

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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

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983127983137983148983140983154983151983152 983117 (1994) 983107983151983149983152983148983141983160983145983156983161983098 983124983144983141 983109983149983141983154983143983145983150983143 983123983139983145983141983150983139983141 983137983156 983156983144983141 983109983140983143983141 983151983142 983119983154983140983141983154 983137983150983140 983107983144983137983151983155 983123983145983149983151983150 amp 983123983139983144983157983155983156983141983154

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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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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

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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

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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

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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

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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

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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

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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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