From “The Turing test and our shifting conceptions of intelligence” by Melanie Mitchell.
In her insightful piece, “The Turing Test and our shifting conceptions of intelligence,” Melanie Mitchell challenges the traditional view of the Turing Test as a valid measure of intelligence. She argues that while the test may indicate a machine’s ability to mimic human conversation, it fails to assess deeper cognitive abilities, as demonstrated by the limitations of large language models (LLMs) in reasoning tasks. This prompts us to reconsider what it truly means for a machine to think, moving beyond mere mimicry to a more nuanced understanding of intelligence.
Our understanding of intelligence may be shifting beyond what Turing initially imagined.
From the article:
On why Turing initially proposed the Turing Test
Turing’s point was that if a computer seems indistinguishable from a human (aside from its appearance and other physical characteristics), why shouldn’t we consider it to be a thinking entity? Why should we restrict “thinking” status only to humans (or more generally, entities made of biological cells)? As the computer scientist Scott Aaronson described it, Turing’s proposal is “a plea against meat chauvinism.”
A common criticism of the Turing Test as a measure of AI capability
Because its focus is on fooling humans rather than on more directly testing intelligence, many AI researchers have long dismissed the Turing Test as a distraction, a test “not for AI to pass, but for humans to fail.”