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Is the Turing Test Good Enough? The Fallacy of Resource-Unbounded Intelligence

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Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 545-549.

Abstract

This goal of this paper is to defend the plausibility of the argument that passing the Turing test is a sufficient condition for the presence of intelligence. To this effect, we put forth new objections to two famous counter-arguments: Searle's Chinese Room and Block's Aunt Bertha. We take Searle's argument to consist of two points: 1) intelligence is not merely an ability to manipulate formal symbols; it is also the ability of relating those symbols to a multi-sensory real-world experience; and 2) intelligence presupposes an internal capacity for generalization. On the first point, while we concede that multi-sensory real-world experience is not captured by the test, we show that intuitions about the relevance of this experience to intelligence are not clear-cut. Therefore, it is not obvious that the Turing test should be dismissed on this basis alone. On the second point, we strongly disagree with the notion that the test cannot distinguish a machine with internal capacity for generalization from a machine which has no such capacity. This view is best captured by Ned Block, who argues that a sufficiently large look-up table is capable of passing any Turing test of finite length. We claim that, contrary to Block's assumption, it is impossible to construct such a table, and show that it is possible to ensure that a machine relying solely on such table will fail an appropriately constructed Turing test.

Virginia Savova, and Leonid Peshkin. 2007. Is the Turing Test Good Enough? The Fallacy of Resource-Unbounded Intelligence. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07. IJCAI, 545–549. https://ijcai.org/proceedings/2007/86
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