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ISACA Advanced in AI Risk Sample Questions:

1. A risk practitioner learns that an organization's AI inventory includes separate listings of AI systems, models, and datasets. Which of the following is the risk practitioner's BEST recommendation to improve AI governance?

A) Assign inventory oversight to the AI risk committee.
B) Include information about model training frequency.
C) Automate inventory reconciliation steps.
D) Map interdependencies between AI assets continuously.

2. Which of the following is the MOST important consideration when managing changes to an AI model in production?

A) Implementing stringent approval processes for user access to new model functionalities
B) Expediting rollout of changes in production to ensure service continuity and minimize downtime
C) Conducting rigorous validation to assess effects on predictive accuracy and model bias
D) Allowing operational teams to adjust configuration parameters for real-time performance tuning

3. A risk practitioner learns that an AI system used by a manufacturer for quality control (QC) has produced inaccurate responses that could potentially impact user safety. Which of the following is the risk practitioner's BEST recommendation to mitigate this risk?

A) Implement human-in-the-loop reviews.
B) Conduct bias and fairness testing.
C) Augment the model with synthetic data.
D) Provide AI prompt engineering training.

4. Which of the following is the BEST way to integrate AI risk management into operational procedures?

A) Engage regular third-party audits of AI process and workflow documentation.
B) Require AI risk committee approval for changes involving automation of manual tasks.
C) Require organization-wide training on AI legal and regulatory requirements.
D) Introduce AI risk assessment stages throughout the development and deployment process.

5. A risk practitioner is concerned that an AI model's responses have become more inaccurate over time, leading to diminished customer trust. Which of the following should the risk practitioner recommend be done FIRST?

A) Take the model offline and perform a full backup.
B) Revise validation processes to add more review cycles.
C) Determine the impact on critical features and model outputs.
D) Fully retrain the model with a more recent dataset.

Solutions: