GV-5.1 Organizational policies and practices are in place to collect, consider, prioritize, and integrate feedback from those external to the team that developed or deployed the AI system regarding the potential individual and societal impacts related to AI risks
Organizational policies and practices are in place to collect, consider, prioritize, and integrate feedback from those external to the team that developed or deployed the AI system regarding the potential individual and
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
- Records of stakeholder engagement activity, including who was engaged · Document repository
governing documentDocuments that govern the control
- Policy establishing how external feedback on AI impacts is collected · Policy repository / GRC workspace
- The prioritisation basis applied to feedback received · Document repository
- Traceability from a specific piece of feedback to a change made · 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
- Feedback channel published with no process behind it
- Engagement limited to existing customers, missing affected non-users
- Feedback logged with no evidence any of it was acted on
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 sheetGV-4.3 Organizational practices are in place to enable AI testing, identification of incidents, and information sharing · GV-5.2 Mechanisms are established to enable AI actors to regularly incorporate adjudicated feedback from relevant AI actors into system design and implementation