MS-2.12 Environmental impact and sustainability of AI model training and management activities as identified in the MAP function are assessed and documented
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 ass
4
artefacts
1
held by a system
2
at each review
moderate
to go live
Policy repository / GRC workspace
where the evidence lives
teal = a system already holds it · olive = produced at each review
system holds itEvidence a system already holds
- The measurement basis and any published metrics adopted · Policy repository / GRC workspace
periodic reviewEvidence produced at each review
- Assessment of energy consumption for training and inference · HR system / LMS
- Documentation of the assessment and its bearing on design decisions · Document repository
governing documentDocuments that govern the control
- Water consumption and greenhouse gas emissions attributable to the system where applicable · Document repository
First move
Start with the 1 of 4 artefacts that already live in a system (Policy repository / GRC workspace); keep the periodic reviews but log each one as a dated record with a named reviewer.
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