Assess whether the system is high-risk under the EU AI Act after a customer

SITUATION After a customer complaint that a chatbot invented a refund policy, shadow-IT chatbot connected to customer PII is what model-risk officer can touch in a hospital deploying a sepsis-risk model. AI Governance will live with Policy or governance breach versus Model defect on this Bias and Training Data file.

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 shadow-IT chatbot connected to customer PII after a customer complaint that a chatbot invented a refund policy.

HYPOTHESES TO TEST 1. A customer complaint that a chatbot invented a refund policy is noise around an already-controlled Bias and Training Data process in a hospital deploying a sepsis-risk model, given shadow-IT chatbot connected to customer PII. 2. A customer complaint that a chatbot invented a refund policy is the event in shadow-IT chatbot connected to customer PII that forces Policy or governance breach for model-risk officer under AI Governance. 3. Shadow-IT chatbot connected to customer PII shows a one-file miss after a customer complaint that a chatbot invented a refund policy, not a Bias and Training Data program failure. 4. Shadow-IT chatbot connected to customer PII cannot decide the system is high-risk yet after a customer complaint that a chatbot invented a refund policy; hold is the only AI Governance close a hospital deploying a sepsis-risk model can defend.

ANALYSIS REQUIRED 1. Reproduce the incident row in shadow-IT chatbot connected to customer PII 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 shadow-IT chatbot connected to customer PII. 3. Reproduce the incident row in shadow-IT chatbot connected to customer PII and say whether it ever touched production data. 4. For this AI Governance Bias and Training Data file, read shadow-IT chatbot connected to customer PII against a customer complaint that a chatbot invented a refund policy and write the one fact that would move the system is high-risk 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 (shadow-IT chatbot connected to customer PII after a customer complaint that a chatbot invented a refund policy). 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 the system is high-risk, then the evidence in shadow-IT chatbot connected to customer PII, then the action for model-risk officer - Hypothesis scorecard against shadow-IT chatbot connected to customer PII: 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 model-risk officer in a hospital deploying a sepsis-risk model