AIORG-W022 Standards & frameworks

Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile

NIST AI 600-1 · GenAI Profile

official profile publication

Recorded claims
2
coded from the inspected source
Evidence classes
1
normative-authority
Recorded limitations
4
stated, never hidden

From the wave-0 evidence ledger

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

The GenAI Profile identifies cross-sector risks including confabulation, data privacy, harmful bias/homogenization, human-AI configuration, information integrity and security, intellectual property, harmful content, environmental impacts, and value-chain/component integration.

confidence: high for taxonomy normative-authority

Scope: Cross-sector generative-AI risks; relevance and severity vary by use case.

The profile maps suggested actions to Govern, Map, Measure, and Manage across the lifecycle, making predeployment evaluation, provenance, monitoring, incident response, and supplier/value-chain review recurring operating processes rather than a one-time model approval.

confidence: high for profile content normative-authority

Scope: Recommended risk-management actions, not legal requirements or certification.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • Voluntary companion profile
  • Risk categories are broad and context-dependent
  • No control-effectiveness estimates
  • Technology and threat environment evolve

Source independence

US government cross-sector profile; normative risk taxonomy and actions, not an audit of deployments.