AIORG-W021 Standards & frameworks

Artificial Intelligence Risk Management Framework (AI RMF 1.0)

NIST AI 100-1 · AI RMF Core · AI RMF Playbook

official framework 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.

AI RMF 1.0 organizes organizational risk work into four functions—Govern, Map, Measure, and Manage—and treats governance as cross-cutting across the AI lifecycle.

confidence: high for framework content normative-authority

Scope: Voluntary, rights-preserving, use-case-agnostic risk management.

The Core and Playbook call for defined roles and training, AI inventories and decommissioning, explicit human-AI role boundaries, monitoring and incident handling, testing/evaluation, and third-party contingencies.

confidence: high for stated practices normative-authority

Scope: Organization-level control objectives to adapt by context.

Boundaries

Limitations & independence

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

Recorded limitations

  • Voluntary and use-case agnostic
  • Version 1.0 was under revision at cutoff
  • Practices do not demonstrate compliance or effectiveness
  • Implementation must be risk- and context-specific

Source independence

US government voluntary framework developed through a public process; normative authority, not empirical control-effectiveness evidence.