Assess whether explainability artifacts would survive an exam (930f8e)

Situation

Privacy counsel supporting AI inventory in a university licensing an AI proctoring vendor has one working extract — training-data provenance questionnaire — after an examiner request for the current model inventory. If training-data provenance questionnaire cannot support explainability artifacts would survive, the honest AI Governance output is hold.

Decision

Privacy counsel supporting AI inventory in a university licensing an AI proctoring vendor must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using training-data provenance questionnaire after an examiner request for the current model inventory.

Hypotheses to test

• Authorize Policy or governance breach now; training-data provenance questionnaire already has the discriminator after an examiner request for the current model inventory.
• Keep Model defect in force until training-data provenance questionnaire is completed after an examiner request for the current model inventory for privacy counsel supporting AI inventory.
• Treat training-data provenance questionnaire as Dual failure because both readings appear after an examiner request for the current model inventory.
• Refuse a AI Governance close: privacy counsel supporting AI inventory does not have the page explainability artifacts would survive turns on in training-data provenance questionnaire.

Analysis required

• Walk the model input/output path recorded in training-data provenance questionnaire and mark each hop approved, shadow, or unlogged.
• Verify data provenance and the human-oversight gate privacy counsel supporting AI inventory can actually point to.
• Walk the model input/output path recorded in training-data provenance questionnaire and mark each hop approved, shadow, or unlogged.
• For this AI Governance Bias and Training Data file, read training-data provenance questionnaire against an examiner request for the current model inventory and write the one fact that would move explainability artifacts would survive for privacy counsel supporting AI inventory.

Recommendation

Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance / Bias and Training Data packet (training-data provenance questionnaire after an examiner request for the current model inventory). If training-data provenance questionnaire cannot force a AI Governance label under Bias and Training Data, stop. If training-data provenance questionnaire after an examiner request for the current model inventory cannot support Policy or governance breach versus Model defect on this AI Governance Bias and Training Data close, privacy counsel supporting AI inventory must leave the classification unresolved and name the missing control or provenance fact.