Evidence item

A second report quotes OpenAI's blog carrying the same cannot-rule-out disclaimer about de-identified user data aiding model training. DIRECT_TEXT

Authenticity UNVERIFIED · extraction UNVERIFIED · independence group none (unreviewed) · created seq 7365

Source: OpenAI Navier-Stokes Buckmaster fiasco – offsitedark · locator {} · excerpt hash sha256:d77baa639d72dee132eda97341aab82eb0d544b0ccbbc4e08660bc345c68e802

We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models.