Thinking Like a Machine

Alan Turing, Computation and the Praxeological Foundations of AI



As part of ongoing research bridging ethnomethodology and computer science, in this article we offer an alternate reading of Alan Turing’s 1936 paper, “On Computable Numbers”. Following through Turing’s machinic respecification of computation, we hope to contribute to a deflationary position on AI by showing that the activities attributed to AIs are achieved in the course of methodic hands-on work with computational systems and not in isolation by them. Turing’s major innovation was a demonstration that mathematical and logical operations could be broken down into elementary, mechanically executable operations, devoid of intellectual content. Drawing out lessons from a re-enactment of Turing’s methods as a means of reflecting on contemporary artificial intelligence (AI), including the way those methods disappear into the technology, we will suggest the interesting question raised in “On Computable Numbers” is less about the possibilities of designing machines that “can think” (cf. Turing, 1950), but the practical work we do, and which is made possible, when we ourselves set out to think like machines.


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Research Papers


2023-07-04 — Updated on 2024-05-15


How to Cite

Saha, D., Brooker, P., Mair, M. and Reeves, S. (2024) “Thinking Like a Machine: Alan Turing, Computation and the Praxeological Foundations of AI ”, Science & Technology Studies, 37(2), pp. 66–88. doi: 10.23987/sts.122892.