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ISACA AAIA Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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.

Topic 3

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.

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ISACA Advanced in AI Audit Sample Questions (Q20-Q25):

NEW QUESTION # 20
The PRIMARY purpose of maintaining an audit trail in AI systems is to:

A. Facilitate transparency and traceability of decisions.
B. Analyze model accuracy and fairness.
C. Measure computational efficiency.
D. Ensure compliance with regulatory standards for AI.

Answer: A

NEW QUESTION # 21
Which of the following is the BEST way to support the development and design of high-risk AI systems?

A. Implement multi-factor authentication (MFA) for all users accessing the AI system.
B. Conduct regular training sessions for users on data privacy.
C. Ensure the availability of trustworthy data sets.
D. Regularly back up the AI system's data to a secure, offsite location.

Answer: C

NEW QUESTION # 22
An IS auditor is auditing an organization's data governance framework. The primary objective is to provide assurance that data management practices are standardized to support a trustworthy AI system. Which of the following should be the auditor's MOST important consideration?

A. Data practices for training models
B. Retention of stored data
C. Portability of data
D. Accountability for data management

Answer: D

NEW QUESTION # 23
The GREATEST benefit of using AI auditing techniques over traditional methods is that AI auditing techniques can:

A. significantly reduce data bias.
B. identify complex data patterns.
C. ensure full compliance with regulations.
D. eliminate the need for human intervention.

Answer: B

NEW QUESTION # 24
The PRIMARY objective of machine learning (ML) in data processing is to:

A. Perform actions that would typically require human intelligence.
B. Enhance the explainability of AI model outputs.
C. Analyze data sets to identify visual patterns and trends.
D. Draw statistical inferences for creating artificial human intelligence.

Answer: A

NEW QUESTION # 25
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