What Big Tech Gets Wrong About AI And How Turing Can Make It Right

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What Big Tech Gets Wrong About AI And How Turing Can Make It Right
Alan TuringComputing Machinery And IntelligenceGoogle
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I’m a PhD philosopher and technology inventor writing about the existential, ethical and epistemological questions about what it means to be human in a tech obsessed world. I have written five books, including Questions from 2024, and invented the digital Qvest and Question Jam platforms.

... “Well, we’re fooled by their fluency, right? We just assume that if a system is fluent in manipulating language, then it has all the characteristics of human intelligence. But that impression is false. We’re really fooled by it.”that he is working to develop an entirely new generation of AI systems that he hopes will power machines with human-level intelligence within the next 10 years.reminded us of his 1999 prediction that AI will achieve human-level intelligence by 2029.

The purpose of the Turing test was never to build machines with human-level intelligence. It was to build machines capable of convincing humans that they are interacting with something that is — or is on the verge of becoming — as intelligent as themselves. This is exactly what ChatGPT and other large language models have succeeded in doing, and so LLMs have not only passed the Turing test with flying colors, as Fridman puts it, it has also turned us into fools.

Regardless of when and how tech experts predict that AI will reach human-level intelligence, they all seem to miss the fundamental premise Turing had for building intelligent machines: comparing them with humans is meaningless.While political and corporate leaders are drowning in questions about what will happen to us humans as AI becomes faster and better at everything we do, Turing did not see AI as a threat to human roles and responsibilities.

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