MS-2.3 AI system performance or assurance criteria are measured qualitatively or quantitatively and demonstrated for conditions similar to deployment settings, and measures are documented
AI system performance or assurance criteria are measured qualitatively or quantitatively and demonstrated for conditions similar to deployment setting(s). Measures are documented. Performance is demonstrated under condit
4
artefacts
0
held by a system
0
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
none for this control
governing documentDocuments that govern the control
- The performance or assurance criteria set for the system · Document repository
- Measurement results obtained under conditions similar to the deployment setting · Policy repository / GRC workspace
- The argument that the test conditions resemble deployment · Policy repository / GRC workspace
- Documentation of the measures used, qualitative as well as quantitative · 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
- Performance demonstrated only in silico on a static test set
- Deployment conditions asserted to be similar with no analysis
- Qualitative assurance criteria stated but never measured
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-2.2 Evaluations involving human subjects meet applicable requirements including human subject protection and are representative of the relevant population · MS-2.4 The functionality and behavior of the AI system and its components, as identified in the MAP function, are monitored when in production