Stable Discrimination Can Hide Reliability Failures in AI Decision Support Under Distribution Shift and Changing Target Definitions
These findings show that discrimination alone is insufficient evidence for reliable AI decision support: audits should test the transportability of probability mappings, operating rules, class-specific validity, and uncertainty informativeness when deployment conditions or target meanings change.