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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 (Q80-Q85):

NEW QUESTION # 80
Which of the following is the MOST important reason to perform regular ethical reviews of AI systems?

A. To align AI system development with organizational values and principles
B. To ensure the systems align with the preservation of individual rights
C. To identify and mitigate potential data drift within models
D. To improve the accuracy and performance of the systems

Answer: B

NEW QUESTION # 81
Which of the following AI system characteristics would BEST help an IS auditor evaluate the system's algorithm?

A. The AI system algorithm uses training data to inform decision output.
B. The AI system provides transparent justification of decisions.
C. The AI system provides multiple options for model training.
D. The AI system uses archived transaction data to provide decisions.

Answer: B

NEW QUESTION # 82
When auditing an AI system, which of the following steps ensures that AI model behavior is aligned with organizational objectives?

A. Algorithm debugging
B. Model training
C. Data transformation
D. Problem framing

Answer: D

NEW QUESTION # 83
In order to streamline operations, a bank has deployed an AI application to automatically detect and prevent further fraud on accounts. However, customers have voiced concerns that their usual transactions are being rejected. Which of the following is the MOST likely cause of the false positives?

A. The hyperparameters are not optimized.
B. Data versioning controls were not developed.
C. Consent is not properly managed.
D. Compute scale training was not performed.

Answer: A

NEW QUESTION # 84
Which of the following testing techniques would BEST validate whether an organization's data governance program effectively ensures data quality and integrity for AI model training and deployment?

A. Conducting a penetration test to identify vulnerabilities in the model
B. Reviewing the organization's AI software development life cycle documentation
C. Assessing data lineage to verify the traceability of data sources
D. Performing a business impact analysis (BIA) to assess the consequences of AI model failure

Answer: C

NEW QUESTION # 85
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