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ISACA AAIR Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Life Cycle Risk Management | - AI bias, drift, transparency, and control evaluation - AI development, deployment, and monitoring risks - AI model and data risk identification | |
| Topic 2: AI Risk Program Management | 42% | - Enterprise AI risk program design - AI governance communication and reporting - AI risk monitoring and continuous improvement - AI risk assessment and treatment strategies |
| Topic 3: AI Risk Governance and Framework Integration | 37% | - AI Models, Frameworks, Strategies, and Use Cases - AI Ownership, Oversight, and Accountability - AI Organizational Processes and Alignment |
ISACA Advanced in AI Risk Sample Questions:
1. An organization seeks to implement a new AI system that uses customer information to create targeted product recommendations. Which of the following is the MOST important consideration to ensure the system complies with regulatory requirements?
A) Use of supervised learning during model training
B) Human review of system recommendations
C) Legally sourced data with appropriate consent
D) Backup and storage protocols for sensitive data
2. Which of the following is the MOST appropriate key performance indicator (KPI) for the effectiveness of a targeted AI risk awareness training program?
A) Changes in risk ratings for risk scenarios involving awareness of insider threats
B) Number of AI irregularities or potential tampering incidents reported by users
C) AI solution adoption rates among business units whose employees have taken training
D) Percentage of users who can identify the financial impact of AI outcomes
3. Which of the following is the BEST course of action to mitigate risk during model selection of supervised or unsupervised algorithms?
A) Require the use of supervised learning for model training projects.
B) Emphasize the generalization capability of algorithms.
C) Align algorithmic capabilities to intended use cases.
D) Prioritize cost reductions related to computational requirements.
4. Risk practitioners use automated tools to generate potential AI risk scenarios. Which of the following represents the GREATEST risk from that approach?
A) Scenarios may not account for all process interdependencies.
B) Impacts from model changes may be underestimated.
C) Emerging adversarial attack vectors may be overlooked.
D) Likelihood and impact scoring may be more complex.
5. Which of the following BEST mitigates risk associated with evasion attacks on AI models?
A) Predictive analytics
B) Feature importance weighting
C) Anomaly detection
D) API rate limiting
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: C |
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