Ethologists and others studying animal behavior in a spirit are in need of a descriptive language and method that are neither anachronistically bound by behaviorist scruples nor prematurely committed to particular Just such an interim descriptive method can be found in intentional system theory. The use of intentional system theory is illustrated with the case of the apparently communicative behavior of vervet monkeys. A way of using the theory to generate data - including usable, testable data - is sketched. The (...) underlying assumptions of this approach can be seen to ally it directly with theorizing in evolutionary biology, which has recently come under attack from Stephen Gould and Richard Lewontin, who castigate it as the Their arguments, which are strongly analogous to B. F, Skinner's arguments against point to certain pitfalls that attend the careless exercise of such thinking (and rival varieties of thinking as well), but do not constitute a fundamental objection to either adaptationist theorizing or its cousin, intentional system theory. (shrink)

What is a bias? Standard philosophical views of both implicit and explicit bias focus this question on the representations one harbours, for example, stereotypes or implicit attitudes, rather than the ways in which those representations are manipulated. I call this approach representationalism. In this paper, I argue that representationalism taken as a general theory of psychological social bias is a mistake, because it conceptualizes bias in ways that do not fully capture the phenomenon. Crucially, this view fails to capture a (...) heretofore neglected possibility of bias, one that influences an individual’s beliefs about or actions toward others, but is, nevertheless, nowhere represented in that individual’s cognitive repertoire. In place of representationalism, I develop a functional account of psychological social bias which characterizes it as a mental entity that takes propositional mental states as inputs and returns propositional mental states as outputs in a way that instantiates social-kind inductions. This functional characterization leaves open which mental states and processes bridge the gap between the inputs and outputs, ultimately highlighting the diversity of candidates that can serve this role. (shrink)

Behavior that solves a problem is distinguished by the fact that it changes another part of the solver's behavior and is strengthened when it does so. Problem solving typically involves the construction of discriminative stimuli. Verbal responses produce especially useful stimuli, because they affect other people. As a culture formulates maxims, laws, grammar, and science, its members behave more effectively without direct or prolonged contact with the contingencies thus formulated. The culture solves problems for its members, and does so by (...) transmitting the verbal discriminative stimuli called rules. Induction, deduction, and the construction of models are ways of producing rules. Behavior that solves a problem may result from direct shaping by contingencies or from rules constructed either by the problem solver or by others. Because different controlling variables are involved, contingency-shaped behavior is never exactly like rule-governed behavior. The distinction must take account of a system which establishes certain contingencies of reinforcement, such as some part of the natural environment, a piece of equipment, or a verbal community; the behavior shaped and maintained by these contingencies; rules, derived from the contingencies, which specify discriminative stimuli, responses, and consequences, and the behavior occasioned by the rules. (shrink)

In this article, I defend an account of linguistic comprehension on which meaning is not cognized, or on which we do not tacitly know our language's semantics. On this view, sentence comprehension is explained instead by our capacity to translate sentences into the language of thought. I explain how this view can explain our capacity to correctly interpret novel utterances, and then I defend it against several standing objections.

In her recent (2009) book, The Origins of Concepts, Susan Carey argues that what she calls ‘Quinean Bootstrapping’ and processes of analogy in children show that the expressive power of a mind can be increased in ways that refute Jerry Fodor's (1975, 2008) ‘Mad Dog’ view that all concepts are innate. I argue that it is doubtful any evidence about the manifestation of concepts in children will bear upon the logico-semantic issues of expressive power. Analogy and bootstrapping may be ways (...) to bring about the former, but only by presupposing the very expressive powers Carey is claiming they explain. Analogies must be understood, and bootstrapping involves confirmation of hypotheses already expressible; otherwise they can't select among an infinitude of hypotheses compatible with the finite data the child has encountered, a fact rendered vivid by Goodman's ‘grue’ paradox and Chomsky's poverty of stimulus argument. The problems have special application to minds, since there is no reason to expect a child's concepts to be ‘projectible’ or to correspond to mind-independent natural kinds. I conclude with an ecumenical view that concepts are reasonably regarded as both innate and often learned, and that what is learned can in fact increase what really concerns Carey, the functioning psychological expressive power of the child, even if it leaves untouched what concerns Fodor, the semantic expressive power. Less ecumenically: maybe Fodor (2008) miscast the debate, and the real issue that bothers people concerns not nativism, but an issue on which Carey and Fodor surprisingly agree, his conceptual Atomism, or the view that all mono-morphemic concepts are primitive and unanalyzable. The issue deserves further discussion independently of Mad-doggery. (shrink)

There is a prevalent notion among cognitive scientists and philosophers of mind that computers are merely formal symbol manipulators, performing the actions they do solely on the basis of the syntactic properties of the symbols they manipulate. This view of computers has allowed some philosophers to divorce semantics from computational explanations. Semantic content, then, becomes something one adds to computational explanations to get psychological explanations. Other philosophers, such as Stephen Stich, have taken a stronger view, advocating doing away with semantics (...) entirely. This paper argues that a correct account of computation requires us to attribute content to computational processes in order to explain which functions are being computed. This entails that computational psychology must countenance mental representations. Since anti-semantic positions are incompatible with computational psychology thus construed, they ought to be rejected. Lastly, I argue that in an important sense, computers are not formal symbol manipulators. (shrink)

Recent discussions in the philosophy of psychology have examined the use and legitimacy of such notions as “representation”, “content”, “computation”, and “inference” within a scientific psychology. While the resulting assessments have varied widely, ranging from outright rejection of some or all of these notions to full vindication of their use, there has been notable agreement on the considerations deemed relevant for making an assessment. The answer to the question of whether the notion of, say, representational content may be admitted into (...) a scientific psychology has often been made to hinge upon whether the notion can be squared with our “ordinary” or “folk” style of psychological explanation, with its alleged commitment to the idiom of beliefs and desires. In this article, I proceed the other way around, starting with experimental psychology itself and asking whether such notions as the above play a legitimate role within a particular area of contemporary theory, the psychology of perception. My conclusion will be that especially the first three have a legitimate place in theories of perception, albeit one that differs from that ascribed to them in a significant portion of the philosophical literature. Along the way I develop a notion of noncognitive functional analysis, which separates the notion of contentful perceptual processing and perceptual representation from cognitive or conceptual content. (This paper has been reprinted, with stylistic revisions, in Perception and Cognition, Essays in the Philosophy of Psychology, Oxford, Clarendon Press, 2009, pp. 50-87.). (shrink)

In this paper, I argue for a modified version of what Devitt calls the Representational Thesis. According to RT, syntactic rules or principles are psychologically real, in the sense that they are represented in the mind/brain of every linguistically competent speaker/hearer. I present a range of behavioral and neurophysiological evidence for the claim that the human sentence processing mechanism constructs mental representations of the syntactic properties of linguistic stimuli. I then survey a range of psychologically plausible computational models of comprehension (...) and show that they are all committed to RT. I go on to sketch a framework for thinking about the nature of the representations involved in sentence processing. My claim is that these are best characterized not as propositional attitudes but, rather, as subpersonal states whose representational properties are determined by their functional role. Finally, I distinguish between explicit and implicit representations and argue that the latter can be drawn on as data by the algorithms that constitute our sentence processing routines. I conclude that skepticism concerning the psychological reality of grammars cannot be sustained. (shrink)

Along with the increasing popularity of connectionist language models has come a number of provocative suggestions about the challenge these models present to Chomsky's arguments for nativism. The aim of this paper is to assess these claims. We begin by reconstructing Chomsky's argument from the poverty of the stimulus and arguing that it is best understood as three related arguments, with increasingly strong conclusions. Next, we provide a brief introduction to connectionism and give a quick survey of recent efforts to (...) develop networks that model various aspects of human linguistic behavior. Finally, we explore the implications of this research for Chomsky's arguments. Our claim is that the relation between connectionism and Chomsky's views on innate knowledge is more complicated than many have assumed, and that even if these models enjoy considerable success the threat they pose for linguistic nativism is small. (shrink)

In this article, I argue that if tacit knowledge of grammar is analyzable in functional‐computational terms, then it cannot ground linguistic meaning, structure, or sound. If to know or cognize a grammar is to be in a certain computational state playing a certain functional role, there can be no unique grammar cognized. Satisfying the functional conditions for cognizing a grammar G entails satisfying those for cognizing many grammars disagreeing with G about expressions' semantic, phonetic, and syntactic values. This threatens the (...) Chomskyan view that expressions have such values for speakers because they cognize grammars assigning them those values. For if this is true, semantics, syntax, and phonology must be indeterminate, thanks to the indeterminacy of grammar‐cognizing (qua functional‐computational state). So, the fact that a speaker cognizes a grammar cannot explain the determinate character of their language. (shrink)

My purpose in this essay is to clarify the notion of explanation by computer simulation in artificial intelligence and cognitive science. My contention is that computer simulation may be understood as providing two different kinds of explanation, which makes the notion of explanation by computer simulation ambiguous. In order to show this, I shall draw a distinction between two possible ways of understanding the notion of simulation, depending on how one views the relation in which a computing system that performs (...) a cognitive task stands to the program that the system runs while performing that task. Next, I shall suggest that the kind of explanation that results from simulation is radically different in each case. In order to illustrate the difference, I will point out some prima facie methodological difficulties that need to be addressed in order to ensure that simulation plays a legitimate explanatory role in cognitive science, and I shall emphasize how those difficulties are very different depending on the notion of explanation involved. (shrink)

This is the introductory essay for the 80 or so philosophy articles in MITECS, covering philosophy's contribution to the cognitive sciences.

The areas of philosophy that contribute to the cognitive sciences are various, including the philosophy of mind, language, and science. This introduction to the 80 or so philosophy articles in MITECS provides an overview of that contribution.

There is general agreement that from the first few months of life, our apprehension of physical objects accords, in some sense, with certain principles. In one philosopher's locution, we are 'perceptually sensitive' to physical principles describing the behavior of objects. But in what does this accordance or sensitivity consist? Are these principles explicitly represented or merely 'implemented'? And what sort of explanation do we accomplish in claiming that our object perception accords with these principles? My main goal here is to (...) suggest answers to these questions. I argue that the object principles are not explicitly represented, first addressing some confusion in the debate about what that means. On the positive side, I conclude that the principles supply a competence account, at Marr's computational level, and that they function like natural constraints in vision. These are among their considerable explanatory benefits - benefits endowed by rules and principles in other cognitive domains as well. Characterizing the explanatory role of the object principles is my main project here, but in pursuing certain sub-goals I am led to other conclusions of interest in their own right. I address an argument that the object principles are explicitly represented which assumes that object perception is substantially thought-like. This provokes a jaunt off the main path which leads to interesting territory: the boundary between thought and perception. I argue that object apprehension is much closer to perception than to thought on the spectrum between the two. (shrink)