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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 (Q53-Q58):
NEW QUESTION # 53
The PRIMARY objective of auditing AI systems is to:
- A. Identify biases and decision transparency.
- B. Maximize system efficiency and throughput.
- C. Minimize algorithm latency and information storage impacts.
- D. Optimize user experience and interface satisfaction.
Answer: A
NEW QUESTION # 54
Which of the following is the PRIMARY objective of AI governance?
- A. Defining clear roles and responsibilities for AI development, use, and oversight
- B. Implementing compliance and ethics controls for AI initiatives
- C. Promoting a positive return on investment (ROI) from AI projects
- D. Ensuring controls over AI are designed well and operate effectively
Answer: A
NEW QUESTION # 55
An IS auditor is interviewing management about implemented controls around machine learning (ML) models deployed in the production environment. Which of the following schedules for reviewing the performance of a deployed model would be of GREATEST concern to the auditor?
- A. One time prior to migrating to production
- B. After changes to hardware and software platforms
- C. On an annual recurring basis
- D. After functionality changes
Answer: A
NEW QUESTION # 56
Which of the following controls helps mitigate the risk of competitors poisoning data utilized by a machine learning (ML) model performing sentiment analysis of product reviews?
- A. Augmenting the unbalanced product review data set with the use of oversampling by the model developer
- B. Peer reviewing code that acquires product reviews from social media posts
- C. Hiring a marketing firm to text links to customers requesting product reviews for monetary compensation
- D. Requiring customers to authenticate access to their accounts prior to writing product reviews
Answer: D
NEW QUESTION # 57
Which of the following strategies used by modelers to enhance data accuracy has the GREATEST risk of bias and information loss?
- A. Separating multiple data attributes within one field into individual attribute columns
- B. Identifying and deleting duplicate entries in the data set
- C. Filling blank attributes in records with the mean, median, or mode within a grouping
- D. Placing numerical data into bins or buckets for a manageable quantity of correlations and result analyses
Answer: C
NEW QUESTION # 58
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