Assess whether deprecation of a legacy scorecard creates a governance gap

Situation

Policy and Oversight work in a city using a hiring-screen algorithm now turns on deprecation of a legacy because a near-miss where an agent emailed a customer unreviewed put hiring-tool adverse-impact tables in play. Chief AI officer should say what hiring-tool adverse-impact tables proves.

Decision

Chief AI officer in a city using a hiring-screen algorithm must choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact using hiring-tool adverse-impact tables after a near-miss where an agent emailed a customer unreviewed.

Hypotheses to test

• Hiring-tool adverse-impact tables reads as Policy or governance breach once a near-miss where an agent emailed a customer unreviewed is lined up to the same AI Governance population.
• Hiring-tool adverse-impact tables is closer to Model defect after a near-miss where an agent emailed a customer unreviewed; Policy or governance breach would over-claim this Policy and Oversight extract.
• Dual failure is still live in hiring-tool adverse-impact tables for chief AI officer in a city using a hiring-screen algorithm.
• Hiring-tool adverse-impact tables is missing the fact chief AI officer needs after a near-miss where an agent emailed a customer unreviewed; stop this AI Governance close.

Analysis required

• Map the approved-use case to the system deprecation of a legacy would bind.
• Check intended purpose and inventory status against EU AI Act / exam-readiness language after a near-miss where an agent emailed a customer unreviewed.
• Map the approved-use case to the system deprecation of a legacy would bind.
• For this AI Governance Policy and Oversight file, read hiring-tool adverse-impact tables against a near-miss where an agent emailed a customer unreviewed and write the one fact that would move deprecation of a legacy for chief AI officer.

Recommendation

Choose Policy or governance breach / Model defect / Dual failure / Hold for the missing fact on this AI Governance / Policy and Oversight packet (hiring-tool adverse-impact tables after a near-miss where an agent emailed a customer unreviewed). The follow-on Policy and Oversight action is what chief AI 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 hiring-tool adverse-impact tables, then the action for chief AI officer
• Hypothesis scorecard against hiring-tool adverse-impact tables: supported / rejected / untestable
• Named option among Policy or governance breach, Model defect, Dual failure and the fact that kills the others
• Owner and next date for chief AI officer in a city using a hiring-screen algorithm