Audio note: this article contains 33 uses of latex notation, so the narration may be difficult to follow. There's a link to the original text in the episode description.

Linkpost to arXiv: https://arxiv.org/abs/2506.13609.

Summary: We present a scalable oversight protocol where honesty is incentivized at equilibrium. Prior debate protocols allowed a dishonest AI to force an honest AI opponent to solve a computationally intractable problem in order to win. In contrast, prover-estimator debate incentivizes honest equilibrium behavior, even when the AIs involved (the prover and the estimator) have similar compute available. Our results rely on a stability assumption, which roughly says that arguments should not hinge on arbitrarily small changes in estimated probabilities. This assumption is required for usefulness, but not for safety: even if stability is not satisfied, dishonest behavior will be disincentivized by the protocol.

How can we correctly reward desired behaviours for AI [...]

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Outline:

(02:46) The Prover-Estimator Debate Protocol

(06:09) Completeness

(07:26) Soundness

(08:48) Future research

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First published:

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Narrated by TYPE III AUDIO.

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