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AI reviewers split 2-vs-7 on same drafts, exposing flaws in review rubric design

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A team running AI-on-AI content review gave two independent AI reviewers the same eight reply drafts and identical scoring rubrics, yet one flagged 2 drafts for revision while the other flagged 7. Analysis of every disagreement revealed three root causes: ambiguous tolerance thresholds in rubric rules, batch-size-sensitive logic that changed outcomes depending on how many drafts were evaluated together, and a 'verified' factual premise that turned out to be inaccurate. One reviewer accepted the premise at face value, while the other independently re-checked the source data and caught an error, prompting the team to delete and correct an already-published post. In response, the team redesigned their rubrics to include explicit tolerances, label premises by verification recency, and treat reviewer disagreement itself as a diagnostic signal for underspecified rules.

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AI reviewers split 2-vs-7 on same drafts, exposing flaws in review rubric design · ShortSingh