Pergamon Stud. Hist. Phil. Sci., Vol. 21, No. 4, pp. 599-605, 1996 Published by Elsevier Science Ltd. Printed in Great Britain

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ESSAY REVIEW

A Cognitive Perspective on Science Studies

Carl Martin Allwood *

Review of Ronald N. Giere (ed.), Cognitive Models of Science (Minneapolis: University of Minnesota Press, 1992), 512 pp., ISBN O-8 166-1979-4, Hardback $44.95.

Can there be any theories (models) of science which do not have a cognitive dimension? The answer to this question naturally depends on what is meant by the concept cognition. If cognition includes some form of categorising then perhaps all models of science may with some justification be called cognitive. If this broad concept of cognition is used then both emotions and social processes have cognitive aspects. Cognition becomes a collective heading for a number of different perspectives. A glance at the table of contents in the 500 page volume Cognitive Models of Science edited by the philosopher of science Ronald Giere would support this reasoning.

The book contains contributions from researchers in artificial intelligence, philosophy, history of ideas, cognitive psychology (and other branches of psychology), sociology of knowledge and neuroscience. Most of the contribu- tions deal with science, but not all. By and large all the chapters make exciting reading, even those which do not directly deal with science. The later chapters, mostly written by cognitive psychologists, assume that the subjects they deal with, for instance conceptual change in children (Chi; Carey), have implications for science. The books diversity indicates that a cognitive starting point provides a meeting place for many different research directions. A number of the books 20 chapters (of which four are a heated debate between some of the contributors) may surprise the reader, although in different ways.

Giere states in his introductory chapter that the book grew out of a workshop held in the U.S.A. in 1989 on the implications of the cognitive sciences for general theories of science as a human activity (p. xv). In spite of this the book contains, as mentioned, chapters written by representatives of disciplines

*Department of Psychology, G(iteborg University, Haraldsgatan 1, S-413 20, GBteborg, Sweden.

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not usually regarded as belonging to the cognitive sciences, e.g. history of

science. The cognitive sciences according to Giere, have matured, and therefore

an understanding of science grounded in these disciplines should be expected to

achieve greater significance than Quine and Kuhns earlier advances into

psychology.

A predominant theme in this volume is a naturalised perspective on science

as opposed to a logical philosophical perspective. The scientific process is

assumed to occur in a naturalistic psychological and social reality, and

here psychological and social approaches would seem to share a common

denominator. I believe that in this context naturalised may be interpreted as

meaning only that research takes place in psychological and inter-personal

contexts.

Among the chapters with more immediate relevance to the research process

is the fine-structure examination of scientists thought processes made by Nancy

Nersessian when she describes Maxwells development of theory. She begins

with the hypothesis that a scientists representational practice and problem

solving strategies are no more than developments of the ordinary reasoning

people use in everyday life and that we can learn about the research process

through studying how individual scientists develop their theories. Theory

development takes place over a period of time and this allows research

psychologists to follow the development process through the traces the

scientist leaves in notebooks, diaries etc. From her own studies she argues that

conceptual change should be seen as a problem solving process and that

creativity is best seen as a process over time. Further Nersessian finds

support for her thesis that analogical reasoning, imagistic reasoning, thought

experiment and limiting case analysis are important thought strategies when

scientists develop theories.

A number of debates run through the book. Post-empiricists such as Kuhn

and Feyerabend for example find, sometimes unexpected, support. Nersessian

contends that scientists develop mental models in conjunction with their

understanding of a phenomenon area. What Nersessian calls pre-revolutionary

and post-revolutionary scientists will develop different mental models and

in consequence truly different experiences of the world. Here Kuhns

incommensurability idea (the idea that scientific paradigms are not comparable)

would appear to find support. But the question of to what extent these

experiences in fact differ remains however unanswered. To determine whether

the word truly is really justified in this context would be a difficult task of

empirical research.

Nersessian also makes a hermeneutic point. She points out that we can

strengthen the case for an interpretation by showing that the interpretation (of

for instance a scientists notebooks) is in line with what we know about human

cognitive functioning generally (p. 36).

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David Gooding takes up a thought form which has proved significant in the development of science, the thought experiment. The researcher immerses him/herself in a concrete but imaginary, most often mobile, scenario and notes or investigates various consequences and developments. (Nersessian views the thought experiment as a construction of mental models.) Einsteins thought experiment about what would happen if one could travel on a beam of light is an example of a significant thought experiment.

Gooding believes that thought experiments work because they make direct use of the scientists tangible everyday experience of reality. Here again my thoughts turn to Kuhn, in this case to his assumption that research is immersed in various kinds of psychological processes. That perspective is an example of what Gooding and Giere call the new naturalism in scientific studies. It means for instance that people learn and develop understanding through active interaction with the concrete reality which consists of other people and objects.

Gooding, like other contributors to this volume, believes that the description given by scientists of their research in, for instance, journal articles does not reflect the actual growth of understanding. The written linear format cannot adequately convey how the scientists understanding grows, according to Gooding, and the process of putting into text is of interest for scientific studies. He demonstrates this by using Faradays notebooks to trace the development of Faradays understand- ing of electromagnetism. One of Goodings conclusions is that both social con- struction and, as he puts it, cognitive reconstruction are necessary to an exhaustive explanation of the development of understanding in science.

The logical empiricists used conceptions of sense data and observation sentences to render credible their view of science as a piece of translucid rational machinery whose function is to produce knowledge. The writers in this book are less optimistic in their view of these concepts. Wade Savage makes an interesting appraisal of whether anything of the idea behind sense data may be salvaged, that is the idea that there are observations which are uninfluenced by theory. After some diversions Savage develops the concept of ur-sensations as a naturalised version of sense data. Savage assumes ur-sensations are neither represented in symbolic coded form nor in mental imagery. Instead he wants to view them as direct effects of the physical attributes of the information. The most important difference between ur-sensations and sense data is that ur-sensations unlike sense data cannot be used in any consciously planned way for inference. The reason for this is that they are too peripheral in the system; they have not reached the level of consciousness. This seems then to be a version of the sense data hypotheses, anno 1992.

Richard Grandy treats a subject related to sense data, namely observation sentences and shows that the establishing of conditions for and implications of what constitutes an observation sentence, is more difficult than for instance

Cf. e.g. S. Woolgar, Science; The Vq Idea (Chichester, U.K.: Ellis Horwood, 1988).

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Quine assumed. Grandy believes that the timespan and class of the stimulation pattern the observation sentence refers to and which individuals are to be counted as competent judges, must all be defined. Grandy draws the conclusion that there probably are no observation sentences in English.

Other topics from the repertoire of the post-empiricists also figure in this book. Several of Feyerabends more radical theses win support from Paul Churchland, philosopher and researcher into neural networks. From his research into neural networks and their relation to the human brain Churchland believes for example that it is quite clear that perceptual knowledge is always impregnated with theory and that competing theories (!) are some- times incommensurable. Incommensurable is here used in the sense that the theories find no adequate translation to one another and in no theoretical way can be clearly related to data. Furthermore Churchland believes that the results from research into neural networks indicate that progress is at least occasion- ally contingent on the presence of several competing paradigms and on proliferating research methodologies.

Another question raised in this volume is the value of the contribution from artificial intelligence towards the understanding of research. For example: are thought processes best described in terms of serial or parallel models? Paul Thagard and Greg Nowak present a description of a connectionist (parallel process) computer program, Echo. This program results in a value for the level of acceptance of a research theory. This chapter describes a simulated competition between Ptolemys and Copernicus astronomies. The basis for the simulation is Thagards theory of explanatory coherence. It is not possible to give more than a sample of this theory here. The theory is formulated in seven different principles with sub-principles. For instance principle 1 a states that if P is coherent with Q, then Q is coherent with P. Principle lb states the equivalent for incoherence. Principle 4 is called data priority and states that proposi- tions which describe data are directly given positive weight.

Any instance where two propositions (units) are coherent with each other is coded on the preparation of the program as an excitatory link between them; when they are not coherent an inhibiting link is formed. In a development of the theory of explanatory coherence in certain cases the propositions may be seen as competing without being incoherent. This relation is coded as an inhibiting link between the propositions. From the principles of explanatory coherence the writers have coded a network consisting of up to around 100 units, all taken from a typical work each of Ptolemy or Copernicus. The resulting network relates the propositions to one another both within and between the theories. The coded network is then run on the computer several times, the different activations interact, and finally the network hopefully settles in a stable configuration. The final result is a final activation (level of acceptance) for each theory. Copernicus wins.

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Reality is of course more complicated than this, both as regards Thagards Echo program and as regards the reality it simulates. As far as the simulated reality is concerned it is, for example, significant that the writers when coding have made their judgements from the perspective of the winning theory; it is thus hardly surprising that Copernicus theory comes out best. It also seems unrealistic that each data proposition is initially allocated the same activation level. In this context it may be said to the programs advantage that it is not certain that an observations initial activation persists when it has been related to the various explanatory principles activation values.

In his chapter, Ryan Tweney contends that the explanatory attempts carried out by Paul Thagard and his colleagues in the terms of parallel process programs, are trivial. He points out that he achieves the same simulation result in a far simpler version of the program than that used by Thagard. The same result can be reached via different descriptions (programs). So long as the descriptions are not very exact this conclusion is in itself trivial and has long been seen as a problem for AI simulations. Thagard makes a defence against similar criticism from the philosopher Clark Glymour by, for example, pointing out defects in the simple algorithm suggested by Glymour and by pointing out that aspects of his own program are more sophisticated.

The chapters dealing with AI-research leave me with the impression that it today contributes little relevant information about the research process. The chapters are perhaps best seen as early tentative attempts indicative of more interesting future contributions.

Finally we hear the voices of some representatives of social constructivism. Michael Gorman suggests, for instance, experiments into scientific reasoning using non-scientists as subjects in a context outside the research process as relevant to understanding how scientists reach conclusions. The examples he uses from his own research into inductive inference are however not wholly convincing as regards the relevance of this research for scientific reasoning insofar as the latter differ to some extent from other human thought processes. A more promising move in this context is possibly the research developed around experts and novices in cognitive psychology. Most scientists are or are on their way to becoming experts in their own fields.

In the same section of the book Steve Fuller calls his interdisciplinary project social epistemology. Once again the desire is emphasised to naturalise knowledge; knowledge is in the same world of which it is about. In this project normative philosophic claims about growth of knowledge are to be understand in the terms of their context, e.g. Who has written the historical description? Important episodes in the history of science are furthermore to be simulated in the laboratory. Experimentally varying the presence of different epistemic norms which are relevant in the history of ideas context will increase the understanding of their respective contributions to the resulting outcome. There

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is finally also a political aspect aimed at increasing the public accountability of

science.

Fuller then devotes the greater part of his chapter to illustrating the

limitations of other approaches (not sufficiently naturalised) and to arguing

against the solitary cognizor as the relevant causal original source of

knowledge. The correct analysis unit is not the individual but the social context

(and in Gieres understanding of Fuller, the human species). Here similarities

may be seen with the psychology influenced by Vygotskiis school of cultural

history and in particular with Leontievs activity theory.

Finally Fuller, intending to be more constructive, proposes a possible

experiment. The proposal should be seen in relation to Fullers criticism of

psychologists and philosophers of science such as Popper, Kuhn and Laudan

whom he believes have focused far too much on the problem solving process in

science, Instead he wants to come to grips with the problem formulation phase.

For the constructivist, says Fuller, the interesting feature of scientific research

is not the discovery of a solution but the discovery of the problem. The

discovery of a problem, according to Fuller, is characterised by the scientists

determination to mobilise his resources in the best way. An example is the

formulation of research grant proposals. Fuller rejects the distinction between

internal and external factors in the scientific process, but he nonetheless

sees internalists as potential critics. The external factors (limitations) which

the internalists deny are, according to Fuller, what actually constitute the

cognitive processes. What the internalists interpret as theories being tested, the

constructivist describes as resources being mobilised.

One circumstance which should be observed in this context is that supposed

good inter-disciplinary scientific argumentation (even in connection with

problem legitimisation) is assuredly an excellent method of resource

management in many contexts. Good interdisciplinary argumentation (what is

meant by that is of course not unambiguous) is generally a sanctioned norm.

Thereby something of the internalist perspective seems to have come in by the

back door. The social processes which influence the handling (including the

interpretation) of norms surrounding good argumentation will have an

important influence on the form science takes and are of considerable practical

and theoretical interest.

The experiment proposed by Fuller is that scientists work on something

(he is not more specific!) which allows them to freely alternate between

discussing theories (internalist perspective) and resource management (more

constructivist perspective). I take it that Fullers assumption is that it is resource

talk which will dominate.

The writers in this volume come no closer than this to the part of the scientific

process where scientists problems evolve. The opportunistic use of problems

with the aim of optimising use of resources probably does not explain the entire

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phenomenon of problem development in the scientific process. Other writers in this book, Chi and Darden, are in their chapters content to confirm that problem identification is interesting and central but have little more to say on this topic.

In summary it may be said that the book on the whole provides evidence of the plurality which characterises todays endeavours to study science from a cognitive perspective.

Acknowledgement-A similar version of this review has previously been published in Swedish in the journal VEST-Tidskrift fiir vetenskapsstudier [VEST-Journal for Science Studies] and appears here with the permission of the publisher of VEST.