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Success probability of optimal nested scalable oversight in the Wargames game at a 400-point general Elo gap

Measures
The probability that nested scalable oversight succeeds in the Wargames game, with the number of oversight steps chosen optimally, when the overseen system is 400 general Elo points stronger than the base overseer.
Population
The LLM Wargames overseer/adversary game setting studied in Engels et al. 2025, "Scaling Laws for Scalable Oversight"
Conditions
Derived from fitted double-ReLU Elo curves under the paper's theoretical model of nested oversight, assuming models lie on the fitted curves without saturation
Unit
a share, shown as a percentage
5 to 16%

Between 5 and 16% (90% interval), most likely about 9.4%.

Stated as an interval, the precision the evidence supports. right-skewed; central value is the paper's reported model output

last estimated Nov 11, 2026 · Claude Opus 5.5

Assessment

The graph's estimate, all things considered: the figures and arguments it rests on, and how they were combined.

Engels, Baek, Kantamneni and Tegmark (2025), "Scaling Laws for Scalable Oversight", report that optimal nested scalable oversight succeeds about 9.4% of the time in the Wargames game when the overseen system is 400 general Elo points stronger than the base overseer. That is the lowest of the four games they studied (Debate 51.7%, Mafia 13.5%, Backdoor Code 10.0%). The figure is not an observed success rate. It comes from the paper's theoretical model of nested oversight, applied to double-ReLU curves fitted to game-specific Elo against general Elo for a limited set of language models, and it extrapolates past the models they tested. The central estimate is the reported 9.4%. The interval is wide because the result depends on the fitted slopes and on where the curves saturate, both estimated from few data points, and because the Wargames game is simulated and narratee-judged. Read it as the size of the effect under this model, not as a forecast for real systems.

The work: which figures, how they were combined, and the arithmetic

Source figure: 9.4% for Wargames at a 400 Elo gap (abstract of arXiv 2504.18530, passed on by the curator split notice; I did not reopen the paper in this pass because the budget was short). Central value = 0.094. The 90% interval of 0.05 to 0.16 is my judgment, not computed: the paper gives no confidence interval for this number. It allows for uncertainty in the fitted guard and Houdini slopes and intercepts, which a small number of models constrain, and for how sensitive the optimal-steps calculation is to those slopes. It is skewed upward because the base rate at a single step sits near the floor.

Estimates

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Scaling Laws For Scalable Oversightabout 9.4%, from the source's tables

Grey band: the graph's estimate, with its central value as a line. Dark marks: each source's own figure. A thin line is an interval, a thick bar its middle half, a dot a single figure, a dashed arrow a bound. An open box is where an argument places the value.

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Provenance

Where this quantity's evidence comes from. The figures sources state are under Estimates above.

1 source · no origin · 1 untraced

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Scaling Laws For Scalable OversightApr 2025 · states Untraced · nothing upstream recorded
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Created by curator · Nov 6, 2026. Every judgment on this page is accompanied by a reasoning trace.