EvidenceSheet
NIST AI RMF 1.0 · MEASURE - NIST AI RMF 1.0

MS-2.10 Privacy risk of the AI system as identified in the MAP function is examined and documented

Privacy risk of the AI system – as identified in the MAP function – is examined and documented. Privacy examination covers what the AI system makes possible, inference and re-identification from training data and outputs, not only the lawfulness of the input data.

Source: NIST AI RMF 1.0, MS-2.10. The statement above is our statement of the clause, read from the published text and cited so you can check it against the official text, not the instrument verbatim. Open NIST AI RMF 1.0 in the compliance library.

4
artefacts
0
held by a system
1
at each review
hard
to go live
Policy repository / GRC workspace
where the evidence lives
teal = a system already holds it · olive = produced at each review. To go live: easy when half or more of the artefacts are already held by a system, moderate from a quarter to a half, hard below a quarter.

These are the artefacts auditors commonly ask for on this requirement, our guidance rather than text from the standard. Your assessor decides what is sufficient in your context, and asks for samples across the period when a report covers one.

system holds itEvidence a system already holds

none for this control

periodic reviewEvidence produced at each review

  • Assessment of re-identification and memorisation risk · Document repository

governing documentDocuments that govern the control

  • Privacy risk examination covering training data, inference and outputs · HR system / LMS
  • Privacy-enhancing measures applied and their assessed effect · Policy repository / GRC workspace
  • Documentation traced to the privacy risks mapping identified · Policy repository / GRC workspace

First move

No system holds this evidence for you: it is people and documents. Reminders and routing to the owner still save time. Put the document under version control with an owner and review date, and log each review as a record with reviewer and date.

Common gaps auditors find

Do this for your whole sheet

Paste the rows you run your controls from and get this mapping for every control at once, with the periodic-review ones flagged and a first move per row. No account for the first run.

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MS-2.9 The AI model is explained, validated, and documented, and AI system output is interpreted within its context… · MS-2.11 Fairness and bias as identified in the MAP function is evaluated and results are documented