Thinking: Readings in cognitive science

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I-'. J:.~.5ohr~son-r..~ir6 aa~ P. C. Wason (Eds.), Thinkbzg: Readings in Cognitive ,5!ci~-f..ce Ca~',brid~:e Ul~iversity Press, I977. This Open r,rai ~'ersi]y Set Book is an anthology of thirty-four papers all concerned with aspects ot reaqa!.ch on thinking. Many of the papers are reprinted from other sources, ,~lthod3a n~:t ~?~ays easiiy available othel than in this book, a few are new. The articles zr~?g,:oulped into seven sections, ezch of which is given a separate note below, but pe,-haps one or twc~ ger',.~ral comments are in order first. The book is not inte'ndea as an eie~ientary introduction: to quote the Preface: "[The readings], are intended to be comprehensive and, together with the introduction to each Part, to prove.de a de~iled guide to those aspects of thinking currently under exploration. Cur ~aal was to provide an anthology that could help researchers in Psychology ant Artificial Intelligence to understand each other's work on thinking, that would make a usezal acco,~pa~fing text to courses on Cognitive Psychology, and that might p.-ovide an interesting survey of the study of higher mental processes for workers in othe] disciplines" In terms of these aims, the book succeeds remar[~faly~--~/el.I. In certain sections, one might challenge the selection of articles, but the re~der' sens'~ of what is missing is as personally biased as the editor's decision as what t,: put in, and one could certainly not claim glaring gaps. Given the lirait~ricns ;nh~'rent in trying to cover a large inter-disciplinary area ; a single volume, thei'e is enough to give the flavour of current research and to stimuYate the reade: into further reading, helped by the extensive bibliography. It ~hould be noted that the bibliography serves mainly as a citation index, and thus reflects the editor's predispositions as much as does the choice of articles. Anyone who wz~nted to go deeper into, for example, the AI areas would be well advised to suppleraent this bibliography with that of other recent sun,ey introductions (e.g. Bodeu, ,4rtificial Intelligence and Natural Man, Harvester Press, 1977, or Winston, Artificial Intelligence, Addison and Wesley, 1977). Each part of the book is prefaced by an introduction, which gives a comext to the particular area discussed in that part. The type of context given varies somewhat from section to section. Thus, the introduction to the section cn Problem Solving is essentially historical, being a description of work earlier than that described by the articles chosen, but important for their understanding, whilst the introduction to the section on Deduction consists mainly of an exposition of the first order predicate calculus. Inevitably, from. time to time an introduction which Arti.fieial Intelligence 13 (1980), 313-322 Copyright ~ 1980 by North-Holland Publishing Company

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tries to give in a very small space all the background needed to understand a varied set of articles can become contentious. This can be apnoying when contested theories are expressed as accepted ideas. There is a general introduction to the whole book called, somewhat misleadingly, An introduction to the scientific study of thinking. It turns out on closer examination to be a discussion first of methodology in psychology and then of the relationship between psychology and AI. This discussion leads to a general statement of the editors' beliefs which determined the selection of the articles in the book. "It i~ our belief that the scientific study of thinking demands the development of general theories, the construction of specific models, and the continued use of experimentation". Few AI workers could find much to quarrel with there. One final general remark: this is not a book to sit down and read from cover to cover. It is a book to be taken in small doses, over a lengthy period of time or as a reference book, looking up the particular sections as the need or desire takes one.

I. Problem solving. The introduction to this Part covers a lot of ground, starting with Wertheimer and the Gestalt school, with its emphasis on insight into problems, passing by the difficulties caused by a misleading set to the use of higher-order programming languages as tools in the analysis of inference. I found this introduction one of the most interesting in the book. The readings in this section start with a nice paper by Luchins and Luchins, Wertheimer's seminars revisited: testing for understanding of structure, about devising tests to see if children really understand about structure, touching on the classic controversy about'lQ testing. The main theme of the article concerns the importance of finding fundamental insight rather than learning a pattern by rote. The role played by inference is quite clear in the account given. Hunter's paper on Mental Calculation is interesting for its empirical investigation of knowledge organisation and use in different subjects, including a freak fast calculator. The author points out differences in knowledge organisation in different people, thus making the important point that generalisation from structures "discovered" in one person to universal structures is not necessarily valid. Newelrs paper, On the analysis of human problem solving protocols, in fact shows a tendency to make exactly this false generalisation. Although working with protocols of individuals and showing how by analysis of the protocol a production system can be built which models a particular subject's behaviour, Newell sometimes talks as though the resulting system will be of wider validity. Winograd's paper on Formalisms for knowledge I found rather disappointing. To be fair, this may be because the area is one with which I am more familiar than I am with the more psychology-oriented preceding readings in this section. Nonetheless, it seemed that the level of this contribution was noticeably more elementary than the others. It presents predicate calculus, simple programs and

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P L A ~ - l i k e languages as different means of representing knowledge, finishing up with very brief descriptions of production systems, MERLIN and semantic nets--a a sort of Cook's tour of representation techniques, and like a Cook's tour, never really stopping long enough in one place. H. Deduction. The section on deduction opens with an introduction expounding the predicate calculus and resolution theorem provers. This leads int6 an argument that syllogistic reasoning underlies much of real-life inference making, an assumption to be found liberally in the rest of the section. The rest of the introduction, apart from a brief introduction to the work of Piaget, is taken up with alternative explanations of why, if syllogistic reasoning underlies real-life reasoning, people so often get the conclusions of syllogisms wrong. Huttenlocher's paper, Constructing spatial images: a strategy in reasoning argues for a close relationship between visual imagination and reasoning in the solution of three term series problems. Clark, in Linguistic processes in deductive reasoning again discusses the solution of two and three term series problems, but offers an explanation in terms of more general processes, claiming that "the principle difficulties inherent in many reasoning problems are not due to the cognitive processes specific to these problems, but to the very language in which the problems are stated". Although it seems clear that the wording of problems is extremely important, it seems unlikely that problem specific strategies are as relatively unimportant as Clark claims. Before the problem can be solved, it must be understood, and the formulation can obviously help or hinder understanding. But once understood, the problem still has to be solved. It therefore does not seem as clear to me as it seems to Clark that he and Huttenlocher are in opposition: rather they seem to be tackling different aspects of the same problem. As might be expected, the two readings Self-contradictions (Wason) and A theoretical analysis of insight into a reasoning task (Johnson-Laird and Wason) go together. Both are concerned selection tasks, although the first is primarily interested J~: the effects of contradiction on erroneous attempted solutions. The second smz:marizes a number of studies where, in the majority of cases, wrong selections are made and presents a model of performance in terms o f information processing. The experimental results to be explained are surprising, at least for this reviewer: "the Ss initially experience no sense of difficulty. They are nearly always content to verify the rule by attending to the values explicitly mentioned in it. It is as if the values unmentioned in the rule play no part in the problem, a supposition very frequently corroborated by introspective reports. This results in error and may very well lead to striking inconsistencies between previous selection and current evaluation of the material--inconsistencies which may, or may not, be recognized, tolerated and resolved. When they are not recognized or resolved, an individual $ begins to sound almost as if he were really two different people talking". The explanatory model of performance presented gives a precise 22

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statement of the behaviour of the Ss and a!so brings out the differences in the way in which a machine and a human attempt to solve the problem. As the authors themselves point out, the model requires much more verification than can be provided by the experimental results reported here before it could be accepted or rejected as being of more general validity. Johnson-Laird's paper On reasoning with quantifiers presents a model for the representation of quantified propositions and relations between them which has some computational advantages over other representations. In his conclusion he points out the influence of context on real-life deductions. The final paper in this section, Piaget's Intellectual evolution from adolescence to adulthood is one of the most important readings in the book. It reports drastic changes in Piaget's thinking, which can best be summarized by quoting from the article itself: "It is quite true that one of the essential characteristics of formal thought appears to us to be the independence of its form from its reality content . . . . However, it is one thing to dissociate the form from the content in a field which is of interest to the subject and within which he can apply his curiosity and initiative, and it is another to be able to generalize this same spontaneity of research and comprehension to a field foreign to the subject's career and interests . . . . Briefly, we can retain the idea that the formal operations are free from their concrete content, but we must add that this is true only on the condition that for the subjects the situations involve equal aptitudes or comparable vital interests." Ill. Conceptual thinking. The introduction to this section is again initially historical, consisting of an account of a number of experiments designed to investigate conceptual thinking, and shewing how the assumptions behind the design of such experiments have changed and developed. The authors then attack conventional studies of concept attainment on the grounds that they use "the wrong sorts of concept and the wrong sorts of experimental procedure". The remainder of the introduction argues in defence of the authors' position, and, in doing so, produces an interesting discussion of the notion of conceptual prototypes. Sokal's paper Classification: purposes, principles, progress, prospects giv-.s a critical survey of classification techniques. Winston's Learning to identify toy block structures describes his work, well known in AI circles, on recognition of simple structures. It is perhaps unfortunate that he seems to be making rather grandiose claims for the program and for the "new theory of learning" embodied in it, especially since, as he himself points out, extension to a more complicated and realistic universe would involve "some expansion of the learning theory together with massive improvements in our understanding of how to describe objects and concepts in whatever new universe we choose". Is it not at least possible that the model given here is only adequate

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because the objects dealt with are simple, so that differences between them are very clear and easily stated .9 There is not sufficient evidence in this article to justify a claim that the learning theory is essentially adequate and is independent of the universe of discourse. Rosch's paper on Classification of real world objects: Origins and representations in cognition expounds the notion of a prototype in relation to the classification of concrete objects. There is much interesting discussion on categorization and the implications of the theory for other domains, which cannot be discussed in any detail here. It is clear, I think, that the notion of a prototype has proved a seminal idea; this paper provides a justification of the idea in itself and an assessment of its importance. Nelson's paper Some evidence for the cognitive primacy o::fcategorization and its functional basis reports empirical results from experiments with very young children tending to confirm the importance of categorization. She argues that although functional and perceptual properties both play a role in concept definition, the former are the more basic. Given the use made of the notion of prototype in recent AI work (e.g. in KRL), these two papers are of especial interest. Bowerman's paper The acquisition of word meaning: an investigation of some current concepts attempts to reconcile the prototype theory with representation by means of a set of features. She claims that "even very young children ate capable of performing a featural analysis upon a prototypical referent and extending a word to novel referents on the basis of this analysis". IV. Hypotheses and theories. This section is at the same time one of the most interesting and one of the most depressing in the book. The overall conclusion seems to be that people are very weak at reasoning and are full of prejudice when they try to reason: they are not good at forming alternative hypotheses and stick stubbornly to their initial ideas even when they lead to obvious contradictions. In short, they lack the flexibility which has often been claimed to be one of their chief virtues. There is plenty here to make one doubt that the way to build machine intelligence is to model it on human intelligence. The introduction discusses the formation of scientific theories and the induction/hypothetico-deduction controversy, going on to describe differences in the approaches of Kuhn and Popper. The first reading in the section, Popper's paper On hypotheses gives a fascinating account of Popper's own intellectual development, finishing with a summary of his theory of learning and a rejection of the inductive method. Kuhn's paper, A function for thought experiments begins the slide towards a pessimistic view of people's reasoning ability. He discusses "thought experiments" which lead to a conceptual conflict, where the subjects, because they were working in an established paradigm, found it di~cult to deal with the confusion by re-casting

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the paradigm. Only when the anomaly could be transformed to concrete contradiction could the subjects see what was wrong. Kuhn sets out a number of specific criteria which a thought experiment must fulfill in order to be able to play this role of catalyst in the reformulation of scientific theories. Karmiloff-Smith and Inhelder, I f you want to get ahead, get a theory tends to confirm Kulm's hypothesis via experiments with children. Children too seem "to hold on to their initial theory as long as they can. Even when they finally do take counter-examples into consideration, they first prefer to create a new theory., quite independent of the first one, before finally attempting to unify all events under a single broader theory". Wason's paper On the failure to eliminate hypotheses: a second look follows essentially the same track, reporting experiments with adults aged between 19 and 25 where once again "dogmatic thinking and the refusal to entertain the possibility of alternatives can easily result in error". Mynatt, Doherty and Tweney in Confirmation bias in a simulated research environment: an experimental study of scientific inference argues that their subjects, when confronted with unambiguous falsifying evidence, used it correctly to reject their false hypotheses. On the other hand, they did not look for and test alternative hypotheses: thus their initial hypothesis had a very strong influence on their ability to reach correct conclusions. Tversky and Kahneman Judgement under uncertainty: heuristics and biases gives a list of heuristic principles used by people to reduce the complex tasks of assessing probabilities and predicting values to simpler judgemental operations. They show how, whilst such heuristics are in general useful, they can lead to severe and systematic errors. It is this latter aspect which gives the paper its high entertainment value. V. Inference and comprehension. The introduction to this section is the one where I found most to quarrel with, although mostly over points of relative detail. For example, is a frame (~t la Minsky) really the AI analogue of the cognitive prototype discussed in Part III? It is certainly not evidently so, since a frame can be a stereotyped sequence of actions. This point seems rather fudged over by passing immediately from an interpretation of Rosch's prototypes as frames taking the default values for all its relevant variables to a discussion of the ubiquity of the frame notion and the difficulty of testing it empirically. The rest of the introduction constitutes an argument for the importance of the role of inference in comprehension, and even given the caveat above, is a tour de force. The arguments reviewed start with the inability of people to carry out verbal identification of objects without implicit inferences based on the possible function of the object, and goes on to discuss a large body of evidence that "comprehension invariably entails going beyond explicit linguistic information in order to make coherent interpretation". A number of ways in which inference

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making can be triggered are described, ranging from the use of the definite/indefini~e articles (reporting a dubious argument of 8tenning's that definite noun phrases reflect the universal quantifier, the indefinite article the existential quantifier), to the role played by the identification of a specific referent which then serves as an anchor for a whole chain of identification-reference links. (Winograd's pronoun resolution mechanisms in srmD~u are likened to this process.) A final section discusses the role of illocutionary force in an utterance and the inference making needed to determine it correctly, and the analysis of discourse in general, where inference making, at least in the examples given, rather changes its character to become invited inferences relating to the entire context of tlie discourse. Minsky's paper Frame-system theory is by now a classic in AI and has been much discussed. No further comment is needed here. Bransford and McCarroll, A sketch of a cognitive approach to comprehension: some thoughts about understanding what it means to comprehend is a nice paper presenting evidence on how world knowledge is necessary for comprehension. No solutions are offered, as the authors themselves take pains to point out, but the evidence offered is strong and is clearly explained. Miller's paper, Practical and lexical knowledge suggests that, in order to dr~v a division between practical and lexical knowledge without isolating the linguistic machinery from everything else a person knows and does, lexical knowledge should include both form and function. The functional description would then provide a "locus of interaction between practical knowledge and lexical choice". The main problem with Miller's suggestion seems to me to be the potential size of the functional description. For example, a functional description for an i~em like "car" risks turning into a large inferential structure. Clark', paper, Bridging, is also well-known in the AI world. It concerns a ~et of inferences which Clark, following Grice, calls "implicature", and the basic mechanisms underlying them. Such implicatures depend, Clark argues, on an implicit but quite specific contract between hearer and speaker, and on knowledge that goes beyond linguistic knowledge. Most interestingly, he describes a "stopping rule" which ensures that the sequence of assumptions, the "bridge", leading to the implicature is determinate. Schank and Abelson's paper, Scripts, plans and knowledge is also too well known to need comment. VL Language, culture and t h i ~ J ~ . The introduction to this section discusses magical thinking and its pervasiveness, even in so-called civilited cultures. It is pointed out that it is a mistake to make judgements about thought processes on the basis of their contents. If the premises are extraordinary enough the most rigorous and sophisticated argumentation can only lead to extraordinary cOnclusions.

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Magical thinking is defined in terms of an attempt to attribute causal relations where perhaps none exist: post hoc propter hoe adopted as a principle. The remainder of the introduction discusses the status and validity of crosscultural psychological work, and, almost inevitably, finishes up with a discussion of Whorf's "linguistic relativity" principle. This discussion is interesting in that the author starts out seeming to argue against Whorf, but finishes up stating something which sounds like a very close relation to the hypothesis that language affects thought processes: "Whatever value linguistic powers are likely to grant to the powers of thought, it seems probable that it does so, not only by enabling people to communicate, but also by furnishing them with an articulated internal representation of the world." Schweder's paper, Likeness and likelihood in everyday thought: magical thinking and everyday judgements about personality argues for the universality of the magical mode of thought, and relates it to a disinclination on the part of normal adults to employ the concept of correlation. The argument is both convincing and disconcerting, although the earlier readings in Part IV have prepared the ground and therefore lessen the shock somewhat. Cole, An ethnographic psychology of cognition gives a personal account of experiences in Liberia, and uses it to demonstrate that situational factors must be taken into account in experiment design and definition in different cultures, and makes some suggestions for how it might be done. An adequate assessment of situational factors would avoid erroneous conclusions based on poor performance, where the poor performance reflects a contextual problem rather than a genuine difference in cognition. This paper gives reinforcement to Piaget's argument in the earlier reading. Scribner, Modes of thinking and ways of speaking: culture and logic reconsidered suggests that schooling is in itself a crucial factor in developing the ability to make abstract inferences, more so than the particular culture. She uses evidence of this form cross-cultural studies to suggest that the formal approach necessary to cope with deductive problems is, in essence, a logical genre oflanguage. Rosch's paper, Linguistic relativity is an extensive attack on the Whorfian hypothesis, mainly based on evidence that colours show that the human perceptual system tends to determine linguistic categories rather than vice versa. She suggests that "the effects of most linguistic lexieal categories are probably inseparable from the effects of the factors which led to the formation and structuring of just those categories rather than some others" and that it would be more fruitful to investigate categorization itself than to worry about what determines what.

VII. Imagery and internal representation. The introduction to this final section of the book opens with a historical sketch of research into imagery, showing

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how interest moved from how imagery differs amongst individuals to questions of how imagery is used. The latter part of the introduction concentrates almost entirely on the use of imagery (and restrictions on its use), ~'jth an interesting discussion of chess as a game which provides convincing evidence for the reality of internal representation and for individuals abilities in manipulating internal representations. , Shephard and Metzler, Mental rotation of three dimensional objects reports an ingenious experiment. The subjects are instructed to transform nonsense objects mentally in a number of different ways. The time required for the subjects to determine that two two-dimensional pictures of the three dimensional objacts portray the same object is shewn by the results to be linear function of the angular difference in the portrayed orientations of the three dimensional objects. * Oatley, Inference, navigation and cognitive maps is a fascinating paper on ehe navigation tecbniques used by Polynesian islanders. Their internal representation of the world (for the purposes of navigation) involves keeping the boat stationhry and imagining that the islands are moving. By means of a dynamic representational structure, which takes into account the constellations wheeling above and the pattern of the islands moving past the boat, navigation is extremelyaccurate. The islanders are perfectly aware that the islands do not "really'? move, ,but insist that without the concept of moving islands, the navigator would be hopelessly lost. Eisenstadt and Kareev, Perception in game playing: internal representation and scanning of board positions argues that the organisational-perceptual ability wl~ich allows the construction and manipulation of an internal representation is specific to a particular game, and to a particular individual's past experience with ~ a t game. They present a model of scanning and of internal representation based, on their experimental results. Berliner, in Some necessary conditions for a master chess program does exa[tly what his title suggests. Given that the basic mechanism involved in a chess playing program will be the construction of a tree of possibilities, he attempts to define limitations to be imposed on the growth of the trees. The moral to be dra~vn~ Berliner suggests, is that it is more fruitful to generate a smaller number of lega~ moves and take time evaluating the possibilities than to generate all possible moves and do little evaluation. Whilst it is clear that programs do not play chess in the same way that hurrJns play chess (a fact which makes this paper rather the odd nian out in this particular collection of papers), this approach corresponds to the fact that human pla:~ers do not use much look-ahead. Summary. As is evident from the length of this review and the unequal treatment given to the different readings, the book contains a huge amount of very varit)us material. As an AI worker, I feel that it fulfills its aims of communicating rele~nt

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research in psychology to workers in AI rather better than its inverse aim. But, from a purely selfish point of view, this is perhaps all to the good. There is a great deal here to interest and to stimulate. M A R O ~ Kn~o Institute pour les Etudes S6mantiques et Cognitives Geneva