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ISACA AAIR Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Ethics, Privacy, and Responsible AI | - Ethical AI principles and compliance
|
| Topic 2: AI Lifecycle Controls | - Controls across AI development lifecycle
|
| Topic 3: Regulatory and Compliance Requirements | - Global AI regulatory landscape
|
| Topic 4: AI Risk Management | - Risk identification and assessment for AI systems
|
| Topic 5: AI Governance and Strategy | - AI governance frameworks and organizational oversight
|
ISACA Advanced in AI Risk Sample Questions:
An electricity provider uses an AI model to forecast and detect outages in power grids. Which of the following is the MOST important consideration to ensure the accuracy of model outputs?
- A. Continuous monitoring of model access points
- B. Geographically dispersed data processing capabilities
- C. Integration of real-time sensor data
- D. Manual entry controls and verification processes
Correct Answer: C 🗳️
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Which of the following is the MOST important consideration when an organization is decommissioning an AI system and must manage its associated datasets?
- A. Encryption of training data at rest and in transit
- B. Data owner notification and approval
- C. Register updates to reflect changes in operational AI risk
- D. Retention policies for storage of system components and artifacts
Correct Answer: D 🗳️
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Which of the following BEST mitigates risk associated with evasion attacks on AI models?
- A. Predictive analytics
- B. Feature importance weighting
- C. API rate limiting
- D. Anomaly detection
Correct Answer: D 🗳️
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Which of the following AI system considerations BEST mitigates risk associated with model drift?
- A. Conducting regular retraining with new relevant datasets
- B. Implementing strong access controls based on roles and responsibilities
- C. Maintaining existing levels of variance within datasets during preprocessing
- D. Restricting the use of automated data validation to low-risk models
Correct Answer: A 🗳️
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Which of the following is the PRIMARY benefit of defining and documenting a RACI matrix for AI solution development and deployment?
- A. It establishes responsibility and decision authority for AI project outcomes and risk management.
- B. It facilitates collaboration between operational and technical teams on AI decision making.
- C. It consolidates AI governance authority and oversight within senior organization leadership.
- D. It strengthens governance over AI technical development activities and enterprise architecture (EA).
Correct Answer: A 🗳️
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