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ISACA AAIA Exam Syllabus Topics:

Topic
Details

Topic 1

AI GOVERNANCE AND RISK: It encompasses understanding different AI models and their life cycles, guiding AI strategy, defining roles and policies, managing AI-related risks, overseeing data privacy and governance, and ensuring adherence to ethical practices, standards, and regulations.

Topic 2

AI Operations: It covers managing AI-specific data needs—including collection, quality, security, and classification—applying development lifecycle methodologies with privacy and security by design, change and incident management, testing AI solutions, identifying AI-related threats and vulnerabilities, and supervising AI deployments.

Topic 3

Auditing Tools and Techniques: This section of the exam measures the skills of AI auditors and centers on auditing AI systems using appropriate tools and methods. It includes audit planning and design, sampling methodologies specific to AI, collecting audit evidence, using data analytics for quality assurance, and producing AI audit outputs and reports, including follow-up and quality control measures.

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ISACA Advanced in AI Audit Sample Questions (Q58-Q63):

NEW QUESTION # 58
Which of the following controls MOST effectively helps to ensure an AI model is resilient against external threats?

A. Monitoring of AI access logs
B. AI model configuration testing
C. Monitoring of AI model developers
D. AI data set anonymization

Answer: B

NEW QUESTION # 59
A healthcare organization uses an AI model to analyze patient data and provide diagnostic recommendations. Which of the following MOST effectively detects data drift related to the model's predictions?

A. Applying overrides to allow healthcare professionals to correct the AI model's recommendations
B. Conducting periodic model retraining to ensure alignment with updated patient data
C. Using adversarial testing to simulate scenarios that stress test the model's predictions
D. Comparing incoming patient data distributions with the training data set

Answer: D

NEW QUESTION # 60
Which of the following BEST detects model drift or unexpected changes in AI model outputs?

A. Standardization of AI configurations
B. AI model documentation reviews
C. Anomaly monitoring
D. AI model retraining

Answer: C

NEW QUESTION # 61
Which of the following is the MOST important task when gathering data during the AI system development process?

A. Training the system
B. Cleaning the data
C. Stratifying the data
D. Isolating the system

Answer: B

NEW QUESTION # 62
Which of the following is MOST important to review in order to gain assurance that an AI model is performing without biases?

A. AI model adaptability
B. AI model temperature
C. AI development environment
D. AI training data

Answer: D

NEW QUESTION # 63
......

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