EvidenceSheet

MS-3.2 Risk tracking approaches are considered for settings where AI risks are difficult to assess using currently available measurement techniques or where metrics are not yet available

Risk tracking approaches are considered for settings where AI risks are difficult to assess using currently available measurement techniques or where metrics are not yet available. Where no adequate metric exists the ris

4
artefacts
0
held by a system
1
at each review
hard
to go live
Document repository
where the evidence lives
teal = a system already holds it · olive = produced at each review

system holds itEvidence a system already holds

none for this control

periodic reviewEvidence produced at each review

  • Review of whether measurement has since become possible · Document repository

governing documentDocuments that govern the control

  • Identification of risks for which adequate measurement techniques do not exist · Document repository
  • The tracking approach adopted for each such risk · Document repository
  • Any novel or qualitative measurement approaches trialled · Document repository

First move

This control is evidenced by people and documents, not systems. Put the document under version control with an owner and review date, and log each review as a record with reviewer and date. Do not try to automate it.

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.

Build my evidence sheet

MS-3.1 Approaches, personnel, and documentation are in place to regularly identify and track existing, unanticipated, and emergent AI risks based on factors such as intended and actual performance in deployed contexts · MS-3.3 Feedback processes for end users and impacted communities to report problems and appeal system outcomes are established and integrated into AI system evaluation metrics