Assess whether vendor terms allow customer data in training (df5cc3)

SITUATION In a manufacturer sunsetting a vision model still used in QA, output-scoring rubric that never fails a high-risk output is the evidence after drift in a protected class the dashboard does not show. AI committee secretariat has to pick Policy or governance breach or Model defect for this AI Governance Layer Audit and Vendor Terms close using output-scoring rubric that never fails a high-risk output.

DECISION AI committee secretariat in a manufacturer sunsetting a vision model still used in QA must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using output-scoring rubric that never fails a high-risk output after drift in a protected class the dashboard does not show.

HYPOTHESES TO TEST 1. AI committee secretariat can defend Policy or governance breach from output-scoring rubric that never fails a high-risk output after drift in a protected class the dashboard does not show in a AI Governance Layer challenge. 2. AI committee secretariat cannot defend Policy or governance breach from output-scoring rubric that never fails a high-risk output; Model defect is what the extract actually supports after drift in a protected class the dashboard does not show. 3. Drift in a protected class the dashboard does not show never reached the population in output-scoring rubric that never fails a high-risk output — reopen intake, do not close vendor terms allow customer. 4. Two facts in output-scoring rubric that never fails a high-risk output after drift in a protected class the dashboard does not show conflict for AI committee secretariat; hold this Audit and Vendor Terms file.

ANALYSIS REQUIRED 1. Test whether drift in a protected class the dashboard does not show changed routing, logging, or human-in-the-loop on the live agent path. 2. Score whether the agent action in output-scoring rubric that never fails a high-risk output was in-policy, out-of-policy, or unlogged. 3. Confirm the inventory line still matches the running configuration in a manufacturer sunsetting a vision model still used in QA. 4. For this AI Governance Layer Audit and Vendor Terms file, read output-scoring rubric that never fails a high-risk output against drift in a protected class the dashboard does not show and write the one fact that would move vendor terms allow customer for AI committee secretariat.

RECOMMENDATION Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance Layer / Audit and Vendor Terms packet (output-scoring rubric that never fails a high-risk output after drift in a protected class the dashboard does not show). If output-scoring rubric that never fails a high-risk output cannot force a AI Governance Layer label under Audit and Vendor Terms, stop. If output-scoring rubric that never fails a high-risk output after drift in a protected class the dashboard does not show cannot support Policy or governance breach versus Model defect on this AI Governance Layer Audit and Vendor Terms close, AI committee secretariat must leave the classification unresolved and name the missing control or provenance fact.