A model developer is looking to mitigate the risk of information loss within an imbalanced data set that contains majority and minority classes. Which of the following strategies would an IS auditor consider to be MOST appropriate?
Answer(s): D
Oversampling to create new data points is the most appropriate strategy to mitigate the risk of information loss in an imbalanced data set. This ensures the minority class is better represented, improving model fairness and predictive accuracy.
When evaluating the process flowchart of an AI machine learning (ML) model, which task should be performed FIRST to provide assurance that the model will function as intended?
Answer(s): B
Splitting the data set into training and test sets should be performed first, as it ensures proper validation of the model’s performance. This prevents data leakage and provides assurance that the model will function as intended on unseen data.
Post-deployment, anomalies in logs suggest a conflict between a critical security patch and an AI model's inference engine. Which of the following is the BEST course of action?
Answer(s): A
Investigating the patch’s effect on the model is the best course of action. This approach identifies whether the patch introduced compatibility or functionality issues with the AI inference engine, ensuring both security and operational integrity are maintained.
An organization plans to deploy an AI model for real-time fraud detection in financial transactions. Which of the following is the BEST approach to manage risk associated with false negatives?
Defining clear business requirements for acceptable false negative rates is the best approach. It aligns the AI model’s performance with organizational risk tolerance and ensures fraud detection operates within acceptable boundaries for financial and regulatory risk.
Which of the following is the MOST critical consideration for incident response in AI systems?
Assigning accountability for managing and resolving AI-related incidents is the most critical consideration. Clear ownership ensures timely and effective response, coordination, and resolution when incidents occur, minimizing operational and compliance risks.
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