The Turing Test, originally proposed as a simple operational definition of intelligence, has now been with us for exactly half a century. It is safe to say that no other single article in computer science, and few other articles in science in general, have generated so much discussion. The present article chronicles the comments and controversy surrounding Turing's classic article from its publication to the present. The changing perception of the Turing Test over the last fifty years has paralleled the (...) changing attitudes in the scientific community towards artificial intelligence: from the unbridled optimism of 1960's to the current realization of the immense difficulties that still lie ahead. I conclude with the prediction that the Turing Test will remain important, not only as a landmark in the history of the development of intelligent machines, but also with real relevance to future generations of people living in a world in which the cognitive capacities of machines will be vastly greater than they are now. (shrink)

Through the use of such "folk" concepts as belief, desire, intention, and expectation, Daniel Dennett asserts in this first full scale presentation of...

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)

Presupposing no familiarity with the technical concepts of either philosophy or computing, this clear introduction reviews the progress made in AI since the inception of the field in 1956. Copeland goes on to analyze what those working in AI must achieve before they can claim to have built a thinking machine and appraises their prospects of succeeding.There are clear introductions to connectionism and to the language of thought hypothesis which weave together material from philosophy, artificial intelligence and neuroscience. John Searle's (...) attacks on AI and cognitive science are countered and close attention is given to foundational issues, including the nature of computation, Turing Machines, the Church-Turing Thesis and the difference between classical symbol processing and parallel distributed processing. The book also explores the possibility of machines having free will and consciousness and concludes with a discussion of in what sense the human brain may be a computer. (shrink)

This paper investigates how the simulation of intelligence, an activity that has been considered the notional task of Artificial Intelligence, does not comprise its duplication. Briefly touching on the distinction between conceivability and possibility, and commenting on Ryan’s approach to fiction in terms of the interplay between possible worlds and her principle of minimal departure, we specify verisimilitude in Artificial Intelligence as the accurate resemblance of intelligence by its simulation and, from this characterization, claim the metaphysical impossibility of duplicating intelligence, (...) as neither verisimilarly nor convincingly simulating intelligence involves its duplication. To this end, we argue by a representative case of simulation that, albeit conceivable, Turing’s test for machine intelligence wrongly equates the occurrence of indistinguishable intelligence performance to intelligence duplication, which is grounded in a prima facie conceivable but metaphysically impossible view that separates intelligence from its origin. Finally, we establish the following criterion for evaluating simulation in Artificial Intelligence: simulations succeed in AI if and only if they are able to epistemically persuade human beings that intelligence has been duplicated, that is, if and only if verisimilar simulations can convincingly minimally depart from actual intelligence. (shrink)