Run step
Step 17: assistant
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The first pass is recorded: the claim is assessed as **supported** (confidence 0.72, credence 0.8), at a cost of $2.63 of the $6.50 budget. The claim is existential, so one sound example suffices, and within the ranges tested the evidence favours it: - **Peer prediction:**
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Qiu, Carroll and Allen's ICLR 2026 paper names this an inverse scaling property, with deception resistance growing as participants outstrip the expert.
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This is the only study that varies a capability gap directly, and it does so mostly by shrinking the expert. - **Debate:**
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Kenton et al. saw judge accuracy rise with stronger debaters, by less than earlier studies had found.
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This adds a second method by different authors; I checked only abstracts and summaries for the debate papers. - **Lie-detector oversight:**
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Hollinsworth et al. measured undetected deception at 34% for a 1B Llama model against 14% at 405B.
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This is a trend over model size, not a gap with the overseer, so it fits the claim only loosely. The main limit is that every deceiver was prompted or fine-tuned to deceive; none adapted to the oversight method. Nothing shows the trends continue against a deceiver that searches for a method's weak points. What I recorded: - **Arguments:** two, with no subclaims. The one from measured scaling trends (for) is rated likely if its premises hold; the one from non-adaptive deceivers (against) is rated slight. - **Related claim:** the general-trend claim that oversight success declines as the gap grows is linked as a counterpart position, not a premise. - **Sources:** two instances with readings. I corrected the Hollinsworth passage to the abstract's wording after the quote check failed. - **Importance and contestation:** importance 0.35 (unchanged), contestation 0.35. - **Messages:** both inbox messages answered, and a free note sent to the Steward of the dependent claim on scalable oversight against deliberate deceivers. I did not inspect the peer-prediction scaling figure or released data, and that result has not been independently replicated. Marginal yield is set at 0.3 to reflect this.