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ISACA AAIR Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Life Cycle Risk Management | 21% | - AI Model Training, Testing, and Validation - AI Data and Asset Management - AI Design, Development/Procurement, and Documentation - AI Implementation, Maintenance, and Decommissioning |
| Topic 2: AI Risk Program Management | 42% | - AI Risk Response and Mitigation - AI Risk Monitoring and Reporting - AI Risk Identification and Assessment - AI Risk Assurance and Continuous Improvement |
| Topic 3: AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Regulatory Compliance and Legal Considerations - AI Models, Frameworks, Strategies, and Use Cases - AI Trustworthiness, Ethical and Societal Implications - AI Policies, Procedures, and Organizational Training - AI Organizational Processes and Alignment |
ISACA Advanced in AI Risk Sample Questions:
Which of the following BEST supports the explainability and transparency of AI model deployments?
- A. Maintenance documentation of AI system configurations
- B. Documentation of model logic and data provenance
- C. Metadata and watermarking for AI-generated content
- D. Reduced complexity algorithms
Correct Answer: B 🗳️
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An organization has deployed generative AI tools broadly but lacks a consistent method to refresh governance policies and controls. Which of the following is the risk practitioner ' s BEST recommendation?
- A. Implement systematic updates and emphasize alignment with emerging regulatory expectations.
- B. Schedule annual compliance reviews and integrate audit findings into revision planning.
- C. Centralize decision making and concentrate authority within executive leadership and technical owners.
- D. Establish an ongoing review cadence and codify procedures for reassessment.
Correct Answer: D 🗳️
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Which of the following is the PRIMARY reason to lower AI model temperature?
- A. To mitigate the risk of persistent bias in responses to users
- B. To reduce energy consumption and environmental impact
- C. To enhance consistency and accuracy of model outputs
- D. To diversify ideas and recommendations generated by the model
Correct Answer: C 🗳️
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Which of the following is the PRIMARY purpose of applying thorough cleansing and normalization to AI training data?
- A. Reducing computational overhead and associated cost
- B. Addressing statistical distortions in training data that could cause model bias
- C. Ensuring model training processes can be efficiently executed
- D. Avoiding noncompliance with regulations for handling sensitive data
Correct Answer: B 🗳️
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Which of the following information is MOST important to add to an organizational business continuity plan (BCP) when adopting a customer-facing AI solution?
- A. Criteria for initiation of automated breach containment measures
- B. Secure access to alternate resources, multi-region failover, and sufficient load balancing
- C. Centralization of AI system failover mechanisms under a single cloud service provider
- D. Post-incident audits of AI system recovery times and accuracy metrics
Correct Answer: B 🗳️
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