Assess whether explainability artifacts would survive an exam after a new use

Situation

Explainability artifacts would survive sits with EU AI Act implementation manager because a new use case bolted onto a model approved for a narrower purpose hit a university licensing an AI proctoring vendor. Evidence is training-data provenance questionnaire; write the AI Governance Inventory and Regulatory Fit option that extract can carry.

Decision

EU AI Act implementation manager 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 a new use case bolted onto a model approved for a narrower purpose.

Hypotheses to test

• A new use case bolted onto a model approved for a narrower purpose is noise around an already-controlled Inventory and Regulatory Fit process in a university licensing an AI proctoring vendor, given training-data provenance questionnaire.
• A new use case bolted onto a model approved for a narrower purpose is the event in training-data provenance questionnaire that forces Policy or governance breach for EU AI Act implementation manager under AI Governance.
• Training-data provenance questionnaire shows a one-file miss after a new use case bolted onto a model approved for a narrower purpose, not a Inventory and Regulatory Fit program failure.
• Training-data provenance questionnaire cannot decide explainability artifacts would survive yet after a new use case bolted onto a model approved for a narrower purpose; hold is the only AI Governance close a university licensing an AI proctoring vendor can defend.

Analysis required

• Split policy-or-governance failure from a model defect using prompts, outputs, and human edits in training-data provenance questionnaire.
• Reproduce the incident row in training-data provenance questionnaire and say whether it ever touched production data.
• Split policy-or-governance failure from a model defect using prompts, outputs, and human edits in training-data provenance questionnaire.
• For this AI Governance Inventory and Regulatory Fit file, read training-data provenance questionnaire against a new use case bolted onto a model approved for a narrower purpose and write the one fact that would move explainability artifacts would survive for EU AI Act implementation manager.

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