A provocative assessment of human thought and behavior, reissued with a new afterword, explores a range of conundrums from the ability of the mind to perceive three dimensions to the nature of consciousness, in an account that draws on ...

This essay considers what it means to understand natural language and whether a computer running an artificial-intelligence program designed to understand natural language does in fact do so. It is argued that a certain kind of semantics is needed to understand natural language, that this kind of semantics is mere symbol manipulation (i.e., syntax), and that, hence, it is available to AI systems. Recent arguments by Searle and Dretske to the effect that computers cannot understand natural language are discussed, and (...) a prototype natural-language-understanding system is presented as an illustration. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

John Searle's Chinese room argument is perhaps the most influential andwidely cited argument against artificial intelligence (AI). Understood astargeting AI proper – claims that computers can think or do think– Searle's argument, despite its rhetorical flash, is logically andscientifically a dud. Advertised as effective against AI proper, theargument, in its main outlines, is an ignoratio elenchi. It musterspersuasive force fallaciously by indirection fostered by equivocaldeployment of the phrase "strong AI" and reinforced by equivocation on thephrase "causal powers" (at least) equal (...) to those of brains." On a morecarefully crafted understanding – understood just to targetmetaphysical identification of thought with computation ("Functionalism"or "Computationalism") and not AI proper the argument is still unsound,though more interestingly so. It's unsound in ways difficult for high church– "someday my prince of an AI program will come" – believersin AI to acknowledge without undermining their high church beliefs. The adhominem bite of Searle's argument against the high church persuasions of somany cognitive scientists, I suggest, largely explains the undeserved reputethis really quite disreputable argument enjoys among them. (shrink)

Looks at accounts by Locke, Fodor, Dretske, and Millikan concerning the nature of mental representation, and discusses connectionism and representation.

Written in a highly readable, irreverent style, The Elm and the Expert provides a lively discussion of semantic issues about mental representation, with special attention to issues raised by Frege's problem, Twin cases, and the putative indeterminacy of reference. Bound to be widely read and much discussed, The Elm and the Expert, written in Jerry Fodor's usual highly readable, irreverent style, provides a lively discussion of semantic issues about mental representation, with special attention to issues raised by Frege's problem, Twin (...) cases, and the putative indeterminacy of reference. The book extends and revises a view of the relation between mind and meaning that the author has been developing since his 1975 book, The Language of Thought. There is a general consensus among philosophers that a referential semantics for mental representation cannot support a robust account of intentional explanation. Fodor has himself espoused this view in previous publications, and it is widespread (if tacit) throughout the cognitive science community. This book is largely a reconsideration of the arguments that are supposed to ground this consensus. Fodor concludes that these considerations are far less decisive than has been supposed. He offers a theory sketch in which psychological explanation is intentional, psychological processes are computational, and the semantic properties of mental representations are referential. Connections with the problem of "naturalizing" intentionality are also explored. The four lectures in The Elm and the Expert were originally delivered in Paris in the spring of 1993 to inaugurate the Jean Nicod Lecture series. The Jean Nicod Lectures are delivered annually by a leading philosopher of mind or philosophically oriented cognitive scientist. The 1993 lectures marked the centenary of the birth of the French philosopher and logician Jean Nicod (1893-1931). The lectures are sponsored by the Centre National de la Recherche Scientifique (CNRS) as part of its effort to develop the interdisciplinary field of cognitive science in France. Jean Nicod series. (shrink)

This book is largely a reconsideration of the arguments that are supposed to ground this consensus.

: Jerry Fodor proposes a solution to Quine's inscrutability–of–reference problem for certain naturalized semantic theories, thereby defending such theories from charges that they cannot discriminate meanings finely enough. His proposal, combining elements of informational and inferential–role semantics, is to eliminate non–standard interpretations by testing predicate compatibility relations. I argue that Fodor's proposal, understood as primarily aimed at Mentalese, withstands Ray's and Gates's objections but nonetheless fails because of unwarranted assumptions about ontological homogeneity of target language predicates, and problems with Fodor's (...) reliance on predicate conjunction to resolve ambiguity. Naturalized semantics thus remains without an answer to the inscrutability objection. (shrink)

Jerry Fodor (1994) proposes a solution to Quine's inscrutability–of–reference problem for certain naturalized semantic theories, thereby defending such theories from charges that they cannot discriminate meanings finely enough. His proposal, combining elements of informational and inferential–role semantics, is to eliminate non–standard interpretations by testing predicate compatibility relations. I argue that Fodor's proposal, understood as primarily aimed at Mentalese, withstands Ray's (1997) and Gates's (1996) objections but nonetheless fails because of unwarranted assumptions about ontological homogeneity of target language predicates, and problems (...) with Fodor's reliance on predicate conjunction to resolve ambiguity. Naturalized semantics thus remains without an answer to the inscrutability objection. (shrink)