Assess whether vendor terms allow customer data in training (d07f68)

SITUATION Output-scoring rubric that never fails a high-risk output arrived with a scorecard that rated 100% of outputs 'acceptable' for content-attribution program lead. That is a AI Governance Layer Lifecycle and Accountability decision on vendor terms allow customer in a firm whose vendor MSA is silent on training rights.

DECISION Content-attribution program lead in a firm whose vendor MSA is silent on training rights 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 a scorecard that rated 100% of outputs 'acceptable'.

HYPOTHESES TO TEST 1. Authorize Policy or governance breach now; output-scoring rubric that never fails a high-risk output already has the discriminator after a scorecard that rated 100% of outputs 'acceptable'. 2. Keep Model defect in force until output-scoring rubric that never fails a high-risk output is completed after a scorecard that rated 100% of outputs 'acceptable' for content-attribution program lead. 3. Treat output-scoring rubric that never fails a high-risk output as Dual failure because both readings appear after a scorecard that rated 100% of outputs 'acceptable'. 4. Refuse a AI Governance Layer close: content-attribution program lead does not have the decision vendor terms allow customer turns on in output-scoring rubric that never fails a high-risk output.

ANALYSIS REQUIRED 1. Test whether a scorecard that rated 100% of outputs 'acceptable' 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 firm whose vendor MSA is silent on training rights. 4. For this AI Governance Layer Lifecycle and Accountability file, read output-scoring rubric that never fails a high-risk output against a scorecard that rated 100% of outputs 'acceptable' and write the one fact that would move vendor terms allow customer for content-attribution program lead.

RECOMMENDATION Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance Layer / Lifecycle and Accountability packet (output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable'). If output-scoring rubric that never fails a high-risk output cannot force a AI Governance Layer label under Lifecycle and Accountability, stop. If output-scoring rubric that never fails a high-risk output after a scorecard that rated 100% of outputs 'acceptable' cannot support Policy or governance breach versus Model defect on this AI Governance Layer Lifecycle and Accountability close, content-attribution program lead must leave the classification unresolved and name the missing control or provenance fact.