Richard Samuels

Though nativist hypotheses have played a pivotal role in the development of cognitive science, it remains exceedingly obscure how they—and the debates in which they figure—ought to be understood. The central aim of this paper is to provide an account which addresses this concern and in so doing: a) makes sense of the roles that nativist theorizing plays in cognitive science and, moreover, b), explains why it really matters to the contemporary study of cognition. I conclude by outlining a range of further implications of this account for current debate in cognitive science

Do accounts of scientific theory formation and revision have implications for theories of everyday cognition? We maintain that failing to distinguish between importantly different types of theories of scientific inference has led to fundamental misunderstandings of the relationship between science and everyday cognition. In this article, we focus on one influential manifestation of this phenomenon which is found in Fodor's well-known critique of theories of cognitive architecture. We argue that in developing his critique, Fodor confounds a variety of distinct claims about the holistic nature of scientific inference. Having done so, we outline more promising relations that hold between theories of scientific inference and ordinary cognition

In their recent and influential book Rethinking Innateness, Jeffrey Elman and his co‐authors argue that evidence from neurobiology provides us with grounds to reject representational nativism (RN). I argue that Elman et al.’s argument fails because it makes a series of unwarranted assumptions about RN and about the extent to which neurobiological data constrain claims about the innateness of mental rep‐resentations. Moreover, I briefly discuss how we ought to understand RN and argue that on two prima facie plausible approaches, far from refuting nativism, the evidence from neurobiology may not even be relevant to the question of whether or not RN is true.

Samuels and Stich explore the debate over the extent to which ordinary human reasoning and decision making is rational. One prominent cluster of views, often associated with the heuristics and biases tradition in psychology, maintains that human reasoning is, in important respects, normatively problematic or irrational. Samuels and Stich start by sketching some key experimental findings from this tradition and describe a range of pessimistic claims about the rationality of ordinary people that these and related findings are sometimes taken to support. Such pessimistic interpretations of the experimental findings have not gone unchallenged however: Samuels and Stich outline some of the research on reasoning that has been done by evolutionary psychologists and sketch a cluster of more optimistic theses about ordinary reasoning that such psychologists defend. Although Samuels and Stich think that the most dire pronouncements made by writers in the heuristics and biases tradition are unwarranted, they also maintain that the situation is rather more pessimistic than sometimes suggested by evolutionary psychologists. They conclude by defending this “middle way” and sketch a family of “dual processing” theories of reasoning which, they argue, offer some support for the moderate interpretation they advocate.

In recent years evolutionary psychologists have developed and defended the Massive Modularity Hypothesis, which maintains that our cognitive architecture—including the part that subserves ‘central processing’ —is largely or perhaps even entirely composed of innate, domain-specific computational mechanisms or ‘modules’. In this paper I argue for two claims. First, I show that the two main arguments that evolutionary psychologists have offered for this general architectural thesis fail to provide us with any reason to prefer it to a competing picture of the mind which I call the Library Model of Cognition. Second, I argue that this alternative model is compatible with the central theoretical and methodological commitments of evolutionary psychology. Thus I argue that, at present, the endorsement of the Massive Modularity Hypothesis by evolutionary psychologists is both unwarranted and unmotivated.

The concept of innateness appears in systematic research within cognitive science, but it also appears in less systematic modes of thought that long predate the scientific study of the mind. The present studies therefore explore the relationship between the properly scientific uses of this concept and its role in ordinary folk understanding. Studies 1-4 examined the judgments of people with no specific training in cognitive science. Results showed (a) that judgments about whether a trait was innate were not affected by whether or not the trait was learned, but (b) such judgments were impacted by moral considerations. Study 5 looked at the judgments of both non-scientists and scientists, in conditions that encouraged either thinking about individual cases or thinking about certain general principles. In the case-based condition, both non-scientists and scientists showed an impact of moral considerations but little impact of learning. In the principled condition, both non-scientists and scientists showed an impact of learning but little impact of moral considerations. These results suggest that both non-scientists and scientists are drawn to a conception of innateness that differs from the one at work in contemporary scientific research but that they are also both capable of 'filtering out' their initial intuitions and using a more scientific approach.

There is a venerable philosophical tradition that views human beings as intrinsically rational, though even the most ardent defender of this view would admit that under certain circumstances people’s decisions and thought processes can be very irrational indeed. When people are extremely tired, or drunk, or in the grip of rage, they sometimes reason and act in ways that no account of rationality would condone. About thirty years ago, Amos Tversky, Daniel Kahneman and a number of other psychologists began reporting findings suggesting much deeper problems with the traditional idea that human beings are intrinsically rational animals. What these studies demonstrated is that even under quite ordinary circumstances where fatigue, drugs and strong emotions are not factors, people reason and make judgments in ways that systematically violate familiar canons of rationality on a wide array of problems. Those first surprising studies sparked the growth of a major research tradition whose impact has been felt in economics, political theory, medicine and other areas far removed from cognitive science. In Section 2, we will sketch a few of the better known experimental findings in this area. We’ve chosen these particular findings because they will play a role at a later stage of the paper. For readers who would like a deeper and more systematic account of the fascinating and disquieting research on reasoning and judgment, there are now several excellent texts and anthologies available.

In this paper I defend the classical computational account of reasoning against a range of highly influential objections, sometimes called relevance problems. Such problems are closely associated with the frame problem in artificial intelligence and, to a first approximation, concern the issue of how humans are able to determine which of a range of representations are relevant to the performance of a given cognitive task. Though many critics maintain that the nature and existence of such problems provide grounds for rejecting classical computationalism, I show that this is not so. Some of these putative problems are a cause for concern only on highly implausible assumptions about the extent of our cognitive capacities, whilst others are a cause for concern only on similarly implausible views about the commitments of classical computationalism. Finally, some versions of the relevance problem are not really objections but hard research issues that any satisfactory account of cognition needs to address. I conclude by considering the diagnostic issue of why accounts of cognition in general—and classical computational accounts, in particular—have faired so poorly in addressing such research issues.Keywords: Computationalism; Frame problem; Relevance

The philosophy of cognitive science is concerned with fundamental philosophical and theoretical questions connected to the sciences of the mind. How does the brain give rise to conscious experience? Does speaking a language change how we think? Is a genuinely intelligent computer possible? What features of the mind are innate? Advances in cognitive science have given philosophers important tools for addressing these sorts of questions; and cognitive scientists have, in turn, found themselves drawing upon insights from philosophy--insights that have often taken their research in novel directions. The Oxford Handbook of Philosophy of Cognitive Science brings together twenty-one newly commissioned chapters by leading researchers in this rich and fast-growing area of philosophy. It is an indispensible resource for anyone who seeks to understand the implications of cognitive science for philosophy, and the role of philosophy within cognitive science.

During the last 25 years, researchers studying human reasoning and judgment in what has become known as the “heuristics and biases” tradition have produced an impressive body of experimental work which many have seen as having “bleak implications” for the rationality of ordinary people (Nisbett and Borgida 1975). According to one proponent of this view, when we reason about probability we fall victim to “inevitable illusions” (Piattelli-Palmarini 1994). Other proponents maintain that the human mind is prone to “systematic deviations from rationality” (Bazerman & Neale 1986) and is “not built to work by the rules of probability” (Gould 1992). It has even been suggested that human beings are “a species that is uniformly probability-blind” (Piattelli-Palmarini 1994). This provocative and pessimistic interpretation of the experimental findings has been challenged from many different directions over the years. One of the most recent and energetic of these challenges has come from the newly emerging field of evolutionary psychology, where it has been argued that it’s singularly implausible to claim that our species would have evolved with no “instinct for probability” and, hence, be “blind to chance” (Pinker 1997, 351). Though evolutionary psychologists concede that it is possible to design experiments that “trick our probability..

There is a puzzling tension in contemporary scientific attitudes towards human nature. On the one hand, evolutionary biologists correctly maintain that the traditional essentialist conception of human nature is untenable; and moreover that this is obviously so in the light of quite general and exceedingly well-known evolutionary considerations. On the other hand, talk of human nature abounds in certain regions of the sciences, especially in linguistics, psychology and cognitive science. In this paper I articulate a conception of human nature that a) captures how cognitive and behavioral scientists tend to deploy the notion whilst, b) evading standard evol-utionary objections, and c) allowing human nature – and theories thereof – to fulfill many of their traditional theoretical roles.

What are the elements from which the human mind is composed? What structures make up our _cognitive architecture?_ One of the most recent and intriguing answers to this question comes from the newly emerging interdisciplinary field of evolutionary psychology. Evolutionary psychologists defend a _massively modular_ conception of mental architecture which views the mind –including those parts responsible for such ‘central processes’ as belief revision and reasoning— as composed largely or perhaps even entirely of innate, special-purpose computational mechanisms or ‘modules’ that have been shaped by natural selection to handle the sorts of recurrent information processing problems that confronted our hunter-gatherer forebears (Cosmides and Tooby,192; Sperber, 1994; Samuels, 1998a)