Supervision of AI Solutions (e.g., Outputs, Impacts, and Decisions) AAIA Practice Questions (Page 7)

Questions 31–33

1. 31application · medium

   A financial services firm uses an AI model to generate credit risk scores. During routine monitoring, the team detects that the model has been assigning abnormally high risk scores to a segment of customers since a recent data pipeline change. The team needs to handle this error in the AI outputs. What is the most appropriate sequence of actions?

   • AImmediately retrain the model with the latest data to correct the risk scores.
   • BLog the anomaly, investigate the root cause, remediate the data pipeline, and document the incident.
   • CNotify the customers affected by the high risk scores and apologize for the error.
   • DAdjust the model's output thresholds to bring the risk scores back to normal levels.
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2. 32foundation · easy

   Why is documentation of AI supervision activities important?

   • ATo provide evidence of compliance and support audits
   • BTo replace the need for human oversight
   • CTo make the AI model run faster
   • DTo increase the complexity of the AI system
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3. 33application · medium

   A retail company has deployed an AI system that recommends product prices. The company wants to establish clear roles and responsibilities for supervising the system's decisions. Which governance structure is most appropriate?

   • ALet the business unit that uses the system handle all supervision without involving other departments.
   • BOutsource supervision to the AI vendor that developed the system.
   • CAssign a single data scientist to be responsible for all aspects of the AI system's supervision.
   • DCreate a cross-functional oversight team that includes members from IT, legal, compliance, and business operations.
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