MS-4.3 Measurable performance improvements or declines based on consultations with relevant AI actors including affected communities, and field data about context-relevant risks and trustworthiness characteristics, are identified and documented
Measurable performance improvements or declines based on consultations with relevant AI actors including affected communities, and field data about context-relevant risks and trustworthiness characteristics, are identifi
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
system holds itEvidence a system already holds
none for this control
periodic reviewEvidence produced at each review
- Consultation records with AI actors and affected communities on observed change · Document repository
governing documentDocuments that govern the control
- Baseline measures for the trustworthiness characteristics being tracked · Policy repository / GRC workspace
- Field data showing performance over time against that baseline · Policy repository / GRC workspace
- Documented identification of improvement or decline and the action taken · 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
- No baseline, so change cannot be identified
- Field data collected but never compared across periods
- Decline attributed to data quality without investigation
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