Assess whether the system is high-risk under the EU AI Act (4698e4)

SITUATION In a pharma company using LLMs on trial documents, hiring-tool adverse-impact tables is the only Policy and Oversight extract after a near-miss where an agent emailed a customer unreviewed that privacy counsel supporting AI inventory can use for the system is high-risk. Privacy counsel supporting AI inventory has to pick Policy or governance breach or Model defect for this AI Governance Policy and Oversight close using hiring-tool adverse-impact tables.

DECISION Privacy counsel supporting AI inventory in a pharma company using LLMs on trial documents 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 1. Authorize Policy or governance breach now; hiring-tool adverse-impact tables already has the discriminator after a near-miss where an agent emailed a customer unreviewed. 2. Keep Model defect in force until hiring-tool adverse-impact tables is completed after a near-miss where an agent emailed a customer unreviewed for privacy counsel supporting AI inventory. 3. Treat hiring-tool adverse-impact tables as Dual failure because both readings appear after a near-miss where an agent emailed a customer unreviewed. 4. Refuse a AI Governance close: privacy counsel supporting AI inventory does not have the decision the system is high-risk turns on in hiring-tool adverse-impact tables.

ANALYSIS REQUIRED 1. Reproduce the incident row in hiring-tool adverse-impact tables and say whether it ever touched production data. 2. Split policy-or-governance failure from a model defect using prompts, outputs, and human edits in hiring-tool adverse-impact tables. 3. Reproduce the incident row in hiring-tool adverse-impact tables and say whether it ever touched production data. 4. 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 the system is high-risk 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 / Policy and Oversight packet (hiring-tool adverse-impact tables after a near-miss where an agent emailed a customer unreviewed). Lead with the AI Governance option hiring-tool adverse-impact tables can support after a near-miss where an agent emailed a customer unreviewed, then the two facts that force it, then the Monday action for privacy counsel supporting AI inventory in a pharma company using LLMs on trial documents.