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The Turing Test Is Not A Trick: Turing Indistinguishability Is A Scientific Criterion

Harnad, Stevan (1992) The Turing Test Is Not A Trick: Turing Indistinguishability Is A Scientific Criterion. [Journal (Paginated)]

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Abstract

It is important to understand that the Turing Test (TT) is not, nor was it intended to be, a trick; how well one can fool someone is not a measure of scientific progress. The TT is an empirical criterion: It sets AI's empirical goal to be to generate human-scale performance capacity. This goal will be met when the candidate's performance is totally indistinguishable from a human's. Until then, the TT simply represents what it is that AI must endeavor eventually to accomplish scientifically.

Item Type:Journal (Paginated)
Keywords:computation, cognition, Turing Test, symbol grounding, consciousness, artificial intelligence, other minds problem, robotics
Subjects:Computer Science > Artificial Intelligence
Philosophy > Philosophy of Mind
ID Code:1584
Deposited By:Harnad, Stevan
Deposited On:18 Jun 2001
Last Modified:19 Dec 2009 19:17

References in Article

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Harnad, S. (ed.) (1987) Categorical Perception: The Groundwork of Cognition. New York: Cambridge University Press.

Harnad, S. (1989) Minds, Machines and Searle. Journal of Theoretical and Experimental Artificial Intelligence 1: 5-25.

Harnad, S. (1990) The Symbol Grounding Problem. Physica D 42: 335-346.

Harnad, S. (1991) Other bodies, Other minds: A machine incarnation of an old philosophical problem. Minds and Machines 1:

43-54.

Harnad, S., Hanson, S.J. & Lubin, J. (1991) Categorical Perception and the Evolution of Supervised Learning in Neural Nets. In:

Working Papers of the AAAI Spring Symposium on Machine Learning of Natural Language and Ontology (DW Powers & L

Reeker, Eds.) pp. 65-74. Presented at Symposium on Symbol Grounding: Problems and Practice, Stanford University, March

1991; also reprinted as Document D91-09, Deutsches Forschungszentrum fur Kuenstliche Intelligenz GmbH Kaiserslautern FRG.

Harnad, S. (1992) Connecting Object to Symbol in Modeling Cognition. In: A. Clarke and R. Lutz (Eds) Connectionism in

Context Springer Verlag.

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