Abstract
I propose to consider the question, “Can machines think?”♣ This should begin with definitions of the meaning of the terms “machine” and “think”. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. 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.
♣ Harnad: Turing starts on an equivocation. We know now that what he will go on to consider is not whether or not machines can think, but whether or not machines can do what thinkers like us can do – and if so, how. Doing is performance capacity, empirically observable. Thinking is an internal state. It correlates empirically observable as neural activity (if we only knew which neural activity corresponds to thinking!) and its associated quality introspectively observable as our own mental state when we are thinking. Turing’s proposal will turn out to have nothing to do with either observing neural states or introspecting mental states, but only with generating performance capacity indistinguishable from that of thinkers like us.
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© 2009 Springer Science+Business Media B.V.
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Turing, A.M. (2009). Computing Machinery and Intelligence. In: Epstein, R., Roberts, G., Beber, G. (eds) Parsing the Turing Test. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6710-5_3
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DOI: https://doi.org/10.1007/978-1-4020-6710-5_3
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