Assess whether deprecation of a legacy scorecard creates a governance gap

Situation

A near-miss where an agent emailed a customer unreviewed put generative-AI acceptable-use policy draft in front of model-risk officer in a hospital deploying a sepsis-risk model. This AI Governance / Bias and Training Data close is deprecation of a legacy from generative-AI acceptable-use policy draft, and the live options are Policy or governance breach, Model defect, Dual failure.

Decision

Model-risk officer in a hospital deploying a sepsis-risk model must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using generative-AI acceptable-use policy draft after a near-miss where an agent emailed a customer unreviewed.

Hypotheses to test

• Model-risk officer can defend Policy or governance breach from generative-AI acceptable-use policy draft after a near-miss where an agent emailed a customer unreviewed in a AI Governance challenge.
• Model-risk officer cannot defend Policy or governance breach from generative-AI acceptable-use policy draft; Model defect is what the extract actually supports after a near-miss where an agent emailed a customer unreviewed.
• A near-miss where an agent emailed a customer unreviewed never reached the population in generative-AI acceptable-use policy draft — reopen intake, do not close deprecation of a legacy.
• Two facts in generative-AI acceptable-use policy draft after a near-miss where an agent emailed a customer unreviewed conflict for model-risk officer; hold this Bias and Training Data file.

Analysis required

• Walk the model input/output path recorded in generative-AI acceptable-use policy draft and mark each hop approved, shadow, or unlogged.
• Verify data provenance and the human-oversight gate model-risk officer can actually point to.
• Walk the model input/output path recorded in generative-AI acceptable-use policy draft and mark each hop approved, shadow, or unlogged.
• For this AI Governance Bias and Training Data file, read generative-AI acceptable-use policy draft against a near-miss where an agent emailed a customer unreviewed and write the one fact that would move deprecation of a legacy for model-risk officer.

Recommendation

Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance / Bias and Training Data packet (generative-AI acceptable-use policy draft after a near-miss where an agent emailed a customer unreviewed). The follow-on Bias and Training Data action is what model-risk officer does next: implement the option, assign an owner, and log the missing fact.

Command returns

• Bottom-line AI Governance option on deprecation of a legacy, then the evidence in generative-AI acceptable-use policy draft, then the action for model-risk officer
• Hypothesis scorecard against generative-AI acceptable-use policy draft: supported / rejected / untestable
• Regulatory or exam hook Bias and Training Data would cite
• Bias and Training Data finding in generative-AI acceptable-use policy draft that a second reviewer can re-perform