MS-2.12 Environmental impact and sustainability of AI model training and management activities as identified in the…
Environmental impact and sustainability of AI model training and management activities – as identified in the MAP function – are assessed and documented. The environmental cost of training and operating the system is assessed on stated measures, energy, water and greenhouse gas emissions, rather than treated as out of scope.
Source: NIST AI RMF 1.0, MS-2.12. 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.
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 energy consumption for training and inference · HR system / LMS
governing documentDocuments that govern the control
- Water consumption and greenhouse gas emissions attributable to the system where applicable · Document repository
- The measurement basis and any published metrics adopted · Policy repository / GRC workspace
- Documentation of the assessment and its bearing on design decisions · Document repository
First move
Common gaps auditors find
- Environmental impact declared immaterial with no measurement
- Training cost assessed while ongoing inference cost is ignored
- Assessment held by the infrastructure team with no link to the AI system record
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.
Build my evidence sheetMS-2.11 Fairness and bias as identified in the MAP function is evaluated and results are documented · MS-2.13 Effectiveness of the employed TEVV metrics and processes in the MEASURE function are evaluated and documented