Monday, December 25, 2023

AI effect

 

AI effect

From Wikipedia, the free encyclopedia

The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not "real" intelligence.[1]

Author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'."[2] Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"[3]

Definition

"The AI effect" is that line of thinking, the tendency to redefine AI to mean: "AI is anything that has not been done yet." This is the common public misperception, that as soon as AI successfully solves a problem, that solution method is no longer within the domain of AI. Geist credits John McCarthy giving this phenomenon its name, the "AI effect".[4]

McCorduck calls it an "odd paradox" that "practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the 'failures', the tough nuts that couldn't yet be cracked."[5] It is an example of moving the goalposts.[6]

Tesler's Theorem is:

"AI is whatever hasn't been done yet."
Larry Tesler

Douglas Hofstadter quotes this[7] as do many other commentators.[8]

When problems have not yet been formalised, they can still be characterised by a model of computation that includes human computation. The computational burden of a problem is split between a computer and a human: one part is solved by computer and the other part solved by a human. This formalisation is referred to as a human-assisted Turing machine.[9]

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