SOURCE-LINKED INTELLIGENCE
Silent Revision: Measuring Undisclosed Change in the Safety Frameworks of Frontier AI Developers
Frontier AI developers publish safety frameworks that commit them to evidencing whether their models are dangerous. The European Union and California now treat these documents as instruments of accountability, and both already impose duties on their revision. Neither requires the revision to be legible, in the sense that a reader could learn from the developer's own account what changed. We introduce the silent revision rate, the share of material changes to a framework's commitments that the developer's published account does not identify, and we release the versioned, hash-pinned corpus need
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-08T14:19:56.000Z
First collected: 2026-09-20T20:02:11.508Z. This is not the publication date.