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Empirical Investigations: Reflecting on Turing and Wittgenstein on Thinking Machines

Livengood, Jonathan and Sytsma, Justin (2017) Empirical Investigations: Reflecting on Turing and Wittgenstein on Thinking Machines. [Preprint]

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Abstract

In the opening paragraph of “Computing Machinery and Intelligence” Alan Turing (1950, 433) famously notes that “if the meaning of the words ‘machine’ and ‘think’ are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, ‘Can machines think?’ is to be sought in a statistical survey such as a Gallup poll.” He then immediately responds, “But this is absurd.” But why is this absurd, if indeed it is? We think that the suggested method is absurd because the answer to the question might not follow from the meaning of the words alone—it might critically depend on what machines can be built to do. Further, the ordinary use of the terms might display shallow biases or superstitions that we want to set aside, or overcome, in pursuing a science or philosophy of mind. However, we do not think that the method is absurd insofar as we are interested in getting clear on “the normal use of the words,” as Turing puts it. And we believe that getting clear on the normal use of words like “machine” and “think” is relevant even if we then want to move beyond the ordinary usage in our theorizing. But the best way to figure out how ordinary people use language is via empirical investigation.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Livengood, Jonathan
Sytsma, Justin
Additional Information: Penultimate draft, to appear in Turing and Wittgenstein on Mind and Mathematics, D. Proudfoot (ed), OUP.
Subjects: Specific Sciences > Cognitive Science
Specific Sciences > Computer Science > Artificial Intelligence
Depositing User: Justin Sytsma
Date Deposited: 23 May 2017 13:34
Last Modified: 14 Jun 2017 19:11
Item ID: 13060
Subjects: Specific Sciences > Cognitive Science
Specific Sciences > Computer Science > Artificial Intelligence
Date: 23 May 2017
URI: http://philsci-archive.pitt.edu/id/eprint/13060

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