ISACA AAIR : ISACA Advanced in AI Risk

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ISACA AAIR Exam Syllabus Topics:

ISACA Advanced in AI Risk Sample Questions:

Question #1
Which of the following is MOST important to mitigate risk when integrating third-party AI services into an organization's supply chain?

A. Centralizing AI decision authority within the IT function
B. Conducting staff training on AI data handling practices
C. Ensuring compatibility with existing organizational systems
D. Assigning contractual accountability for AI controls

Question #2
Which of the following is the PRIMARY purpose of applying thorough cleansing and normalization to AI training data?

A. Addressing statistical distortions in training data that could cause model bias
B. Reducing computational overhead and associated cost
C. Avoiding noncompliance with regulations for handling sensitive data
D. Ensuring model training processes can be efficiently executed

Question #3
Which of the following is the risk practitioner ' s FIRST course of action upon learning that an AI model has been providing responses that are outside predefined thresholds for accuracy?

A. Inform the AI development team and request a technical review.
B. Update the risk register with mitigation strategies for addressing the issue.
C. Document the anomaly for inclusion in periodic accuracy reviews.
D. Notify designated AI governance owners for decision making.

Question #4
A risk practitioner is evaluating AI model cards and documentation prior to deployment. Which of the following represents the GREATEST risk to enterprise AI governance?

A. Delays in regulatory filings
B. Decentralized version control
C. Overly detailed technical specifications
D. Inadequate explainability

Question #5
An organization plans to deploy an AI system that ingests multiple sources with varying completeness and accuracy. Which of the following is the risk practitioner ' s BEST recommendation?

A. Fine-tune model parameters to accommodate variable inputs.
B. Use synthetic data augmentation to supplement training and testing.
C. Implement continuous real-time quality assurance (QA) processes.
D. Perform post-implementation assessments to identify data integrity issues.

Solutions: