AI model-outputs audit (Component 6)

Use when auditing the scores an AI/ML personnel assessment produces — Component 6 of the Landers & Behrend (2023) framework. Covers evaluating the quality of model predictions: reliability (consistency over time and repeated administrations), validity evidence (do scores reflect the claimed constructs and predict the outcome), appropriateness of the cross-validation given generalizability claims, and subgroup differences across protected classes and their intersections. Triggers: "evaluate AI assessment scores", "algorithm reliability and validity", "subgroup differences in algorithm scores", "intersectional bias audit", "does the AI score predict performance", "adverse i…