NIST AI RMF: MAP 3.4
Provision nist.MAP-3.4 · AI Risk Management Framework 1.0, subcategories · subcategory
Processes for operator and practitioner proficiency with AI system performance and trustworthiness – and relevant technical standards and certifications – are defined, assessed and documented.
The text is as taken from the source. In the source: https://airc.nist.gov/airmf-resources/playbook/map/#Map%203.4 (the subcategory, in the NIST AI RMF Playbook (anchor found in the page); linked 2026-11-10). The instrument: AI Risk Management Framework 1.0, subcategories, a United States government work; freely reusable; read 2026-11-10.
Who cites it
| Indicator | The fact it asks for | Kind of link | The assertion |
|---|---|---|---|
I66 | The people who work with it are trained | part: partly evidenced | Asserted in the mapping by gamma-ray@web-summit.dinis; the written basis is not recorded yet. |
A link is our assertion, not the instrument's. "Same" carries the evidence to the provision in full. "Part" marks the provision as partly evidenced: the fact is one piece of what it asks. "Negation" points the other way.
The evidence that reaches it
| Card | Through | This provision is | The evidence | How far to trust it |
|---|---|---|---|---|
| Visor.ai AI agents | I66 | partly evidenced | "We train your people to run the platform confidently" Source | π Moderate · S1·R5·A1 ×3 |
Touched never means complies.
Answer it directly
A company can answer this line item itself, in its own file at /.well-known/fact-ray.json, with the node gamma-ray:provision/nist.MAP-3.4 (how). A company that already assesses itself against NIST AI RMF can reuse that work.