Melanie Mitchell

Computer scientist and complexity researcher; author of 'Artificial Intelligence: A Guide for Thinking Humans'

Santa Fe Institute

Skeptics

Mitchell studies how far today's AI really is from human-like understanding and argues predictions of imminent superintelligence repeat a 70-year pattern of over-promising. She wants regulation aimed at concrete harms—fraud, bias, surveillance—not science-fiction scenarios.

Declines to give a number

No number. "The whole history of AI has been a history of failed predictions. Back in the 1950s and 60s, people were predicting the same thing about super-intelligent AI and talking about existential risk, but it was wrong then. I'd say it's wrong now." (Munk Debate, June 22, 2023)
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On timing

Sceptical that current systems reason or abstract like humans; calls talk of imminent superintelligence 'magical thinking' (September 15, 2025).

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What they call for

  • Regulate current harms: deepfakes, bias, misinformation, surveillance, privacy
  • Rigorous evaluation of claimed reasoning abilities
  • 'reality grounded' policy rather than superintelligence scenarios

In their own words

  • "The U.S. and China need to find ways to regulate AI to avoid its current and likely future harms, such as deep fakes used for fraud and manipulation, AI bias in decisions, misinformation, surveillance, loss of privacy, and so on."

    15 September 2025

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  • Argued the 'con' side (with LeCun) against Bengio and Tegmark in the Munk Debate on whether AI R&D poses an existential threat; audience moved from 67/33 to 64/36.

    22 June 2023

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Last verified 1 September 2026

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