Foundational Papers in Complexity Science pp. 293–333
DOI: 10.37911/9781947864528.11
Turing’s Brainchild: Artificial Intelligence
Author: Daniel Dennett, Tufts University; Santa Fe Institute; and New College of the Humanities, London
Excerpt
In 1950, the mathematician Alan Turing was one of a handful of people in the world who had any experience in computer programming, and he was already coming to terms with the enormous implications of the new digital world he had helped create. He quite appropriately published his reflections in Mind, the leading philosophy journal in the English-speaking world. It became an instant classic, inspiring thousands of discussions of what soon became known as the Turing Test, the “imitation game” that he proposed as a worthy replacement for the tiresome argument that was already well under way in 1949 about whether these new machines could think—the way we human beings can.
Can machines think? Turing declared that this question is “too meaningless to deserve discussion.” Instead of taking sides in debates about how to define these terms, he restricted his attention to a crisply definable task: winning the imitation game, in which a “discrete state machine” vies with a human being to see which can convince a human judge— through a telecommunicated conversation—of its humanity. This move is often seen as behavioristic—handsome is as handsome does—but it is better seen as just scientific: whatever thinking is, it should be something we can observe unmistakably if indirectly through its objective effects in the world. We may have our doubts about the suitability of Turing’s replacement, but at least we will know whether some entity passes the test—like the net on the basketball hoop, the test would serve an important epistemological purpose, turning delicate and unreliable judgments into indisputable results.
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