Alan Turing's biggest AI assumption may have been wrong
Computer scientist Peter J. Denning argues that Alan Turing's foundational assumptions about AI have misdirected the field for decades. He suggests that intelligence cannot be separated from a physical body and that machine learning fails to capture essential human tacit knowledge.
Why it matters
This critique challenges the current industry pursuit of Artificial General Intelligence and highlights potential risks associated with over-relying on software-based intelligence.
Alan Turing's famous ideas about artificial intelligence may have sent AI research down the wrong path for the past 75 years, according to prominent computer scientist Peter J. Denning.
In his new book, Turing's Mistake: Escaping the Yoke of Unintelligent Machines , Denning argues that two foundational assumptions made by Turing in 1950 continue to shape AI research today. The first is that intelligence can exist independently of a physical body and therefore be recreated in computer software. The second is that a machine can demonstrate intelligence by successfully imitating a human in conversation, an idea that later became known as the Turing test.
"These two claims have shaped much of AI research and development," Denning writes. "My premise is that our acquiescence to these claims has led to the AI mess in which we find ourselves today."
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