In this paper I criticize the most significant recent examples of the practical knowledge analysis of knowledge-how in the philosophical literature: David Carr [1979, Mind, 88, 394–409; 1981a, American Philosophical Quarterly, 18, 53–61; 1981b, Journal of Philosophy of Education, 15(1), 87–96] and Stanley & Williamson [2001, Journal of Philosophy, 98(8), 411–444]. I stress the importance of know-how in our contemporary understanding of the mind, and offer the beginnings of a treatment of know-how capable of providing insight in to the use (...) of know-how in contemporary cognitive science. Specifically, I claim that Carr’s necessary conditions for know-how fail to capture the distinction he himself draws between ability and knowing-how. Moreover, Carr ties knowing-how to conscious intent, and to an explicit knowledge of procedural rules. I argue that both moves are mistakes, which together render Carr’s theory an inadequate account both of common ascriptions of knowledge-how and of widely accepted ascriptions of knowledge-how within explanations in cognitive science. Finally, I note that Carr’s conditions fail to capture intuitions (heshares) regarding the ascription of know-how to persons lacking ability. I then consider the position advocated by Stanley & Williamson (2001), which seems avoid Carr’s commitments to conscious intent and explicit knowledge while still maintaining that “knowledge-how is simply a species of knowledge-that" (Stanley & Williamson, 2001, p. 411). I argue that Stanley and Williamson’s attempt to frame a reductionist view that avoids consciously occurrent beliefs during exercises of knowledge-how and explicit knowledge of procedural rules is both empirically implausible and explanatorily vacuous. In criticizing these theories I challenge the presuppositions of the most pervasive response to Ryle in the philosophic literature, what might be described as “the received view." I also establish several facts about knowing-how. First, neither conscious intent nor explicit representation (much less conscious representation) of procedural rules are necessary for knowing-how given the theory of cognition current in cognitive science. I argue that the discussed analyses fail to capture the necessary conditions for knowledge-how because know-how requires the instantiation of an ability and of the capacities necessary for exploiting an ability—not conscious awareness of purpose or explicit knowledge of rules. Second, one must understand knowledge-how as task-specific, i.e., as presupposing certain underlying conditions. Conceiving of know-how as task-specific allows one to understand ascriptions of know-how in the absence of ability as counterfactual ascriptions based upon underlying competence. (shrink)

In this paper, I delineate two major problems facing reliabilist approaches in epistemology. I argue that Alvin Goodman's (1986) position fails to solve either problem. I then suggest an alternative reliabilist approach that ties truth-ratio assessments to particular, well-specified cognitive tasks. I claim that a well-specified cognitive task is an empirical hypothesis about a system that involves the specification of input and output types and nomic correlations (including statistical correlations) that underlie the system's performance. On my approach, one characterizes processes (...) by reference to the system's dispositions across the situations consistent with the task. Characterization is best understood as revealing a strategy or a set of strategies for generating outputs from inputs relying on certain nomic correlations associated with the task. (shrink)

This paper examines the nomic covariationist strategy of using idealization to define representation. While the literature has focused upon the possibility of defining ideal conditions for perception, I argue that nomic covariationist appeals to idealization are pseudoscientific and contrary to a foundational and empirically well-supported methodological presupposition in cognitive science. Moreover, one major figure in this camp fails to come to grips with its role and its problems in mainstream science. Thus he forwards a false dichotomy of the sciences and (...) treats idealization as a blank check written by scientists on an unknown bank. Finally, I consider and reject alternative formulations of the nomic covariationist's idealization strategy. (shrink)

I argue that Fodor's analysis of ceteris paribus laws fails to underwrite his appeal to such laws in his sufficient conditions for representation. It also renders his appeal to ceteris paribus laws impotent against the major problem for his theory of representation. Finally, Fodor's analysis fails to provide useful solutions to the traditional problems associated with a thoroughgoing understanding of ceteris paribus clauses. The analysis, therefore, fails to bolster Fodor's position that special science laws are of necessity ceteris paribus laws (...) and that one must recognize them as scientifically legitimate. (shrink)

Most of this work is concerned with two theories that underlie cognitive science; theories which I call "the representational theory of intentionality" and "the computational theory of cognition" . While the representational theory of intentionality asserts that mental states are about the world in virtue of a representation relation between the world and the state, the computational theory of cognition asserts that humans and others perform cognitive tasks by computing functions on these representations. CTC draws upon a rich analogy between (...) the mind and digital computers, portraying cognizers as receiving input and generating outputs . ;Since researchers within cognitive science--especially within cognitive psychology, computer science, and philosophy of mind--share a common theoretic background in their adherence to the combination of RTI and CTC, what I call "computationalism" most of the work done in philosophy of mind has been aimed at either refuting or further articulating these two theories. This work is strongly within that tradition. ;RTI and CTC combine to create an explanatory framework for explanation in cognitive science. In this work, I seek to delineate the exact structure of this framework, to determine its components and their overall relationships. In my mind, this involves making implicit aspects of computational explanation explicit, providing an overall rationale for the various components and their relationships, and defending that rationale against criticism. ;In particular, the project of this work is to argue that computationalist explanations of cognition within cognitive science need to make appeals to both representation and knowledge; to distinguish the respective roles of knowledge and of representation in an overall picture of computational explanations, and to develop and argue for definitions of representation and knowledge that would allow those concepts to play their respective roles within computational explanations in cognitive science. ;The first half of this work , therefore, is devoted to theories of representation, especially to the need for, and role of representation in computational explanations. The first half of the work culminates in chapter three with a definition of representation and a picture of the structure of computational explanations. The second half of the project then becomes to generate a definition of knowledge that defines knowledge in non-epistemic language amenable to computationalism and that carries the epistemic burdens placed upon knowledge by its use in computational explanations, as well as to offer a limited defence of that definition within the framework of traditional epistemology. (shrink)

In this paper I consider Stich's principle of autonomy argument (From Folk Psychology To Cognitive Science) as an argument that computationalism is an incorrect approach to explanation and prediction in cognitive science. After considering the principle of autonomy argument in light of several computational systems and psychological examples, I conclude that the argument is unsound. I formulate my reasons for rejecting Stich's argument as unsound into the conjunction argument. Finally, I argue that the conjunction argument is sound, and that its (...) soundness adds additional plausibility to computationalism as an explanatory schema in cognitive science. (shrink)

Cognitive science, at least as done by many philosophers, seeks to develop what one might call a content-based theory of cognition. These theorists generally seek to predict/explain cognition by employing generalizations between contentful states like beliefs and desires. In his book, From Folk Psychology To Cognitive Science, Stephen Stich argues that cognitive science should not attempt to employ content-based theories in its explanations of human (and other) behavior. For the most part Stich directs his arguments towards belief/desire psychology. Some of (...) his arguments, however, are directed at content-based theories in general. In this paper, I will be concerned with one of these more general arguments—the principle of autonomy argument.The conclusion of the principle of autonomy argument is that the predictions and explanations generated by content-based theories, in so far as they are possible, do not fall within the domain of prediction and explanation in cognitive science. (shrink)