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ISACA AAIA Exam Syllabus Topics:

TopicDetails
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 (Q133-Q138):

NEW QUESTION # 133
Which use case for an AI model to be used by a food delivery service would pose ethical risk to the organization?

Answer: C

Explanation:
Using AI to make employment decisions such as driver termination or retention introduces significant ethical risks. If based solely on performance metrics without context or human review, such systems can lead to unfair treatment or discrimination--violating principles of transparency and due process.
"Automating workforce decisions must be approached cautiously to prevent discriminatory outcomes. Ethical AI governance requires oversight when AI is used for employment-impacting decisions."


NEW QUESTION # 134
A bank uses a video-based know your customer (KYC) verification process. Cybercriminals exploit this process by using deepfake technology to impersonate bank customers. Which of the following countermeasures is the BEST way for the bank to mitigate this risk?

Answer: C


NEW QUESTION # 135
Which of the following is MOST important for an IS auditor to review during an AI system audit in order to determine compliance with intellectual property and data rights?

Answer: B

Explanation:
To assess compliance with intellectual property (IP) and data rights, the IS auditor must review documented data usage agreements that specify ownership, licensing, consent, and limitations of use. The AAIA™ Study Guide underscores the importance of verifying that the data used to train or feed AI models is obtained and utilized within legal and contractual boundaries.
"Auditors must review data usage agreements to validate whether the organization has appropriate rights to use, distribute, or transform data inputs, especially where third-party or sensitive data is involved." While open-source usage (C) is a concern, only B provides legal clarity. Metrics (A) and logs (D) reflect performance-not legal compliance.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Data Rights, Licensing, and Intellectual Property"


NEW QUESTION # 136
During an audit of a bank's AI credit scoring system, an IS auditor discovers that applicants were not informed about automated decision-making. Which of the following should the auditor do FIRST?

Answer: D

Explanation:
Transparency is a fundamental legal and ethical requirement for AI systems, particularly under regulations like GDPR, which mandate that data subjects be informed of automated decision- making. If an auditor finds that applicants were not informed, the immediate "First" step is to
"Evaluate transparency controls" to determine why the notification process failed and to assess the scope of the non-compliance. This includes reviewing user agreements, privacy notices, and communication procedures.


NEW QUESTION # 137
Which of the following controls would MOST effectively mitigate worst-case service disruption scenarios affecting an AI-based application system?

Answer: D

Explanation:
Including AI-specific disruption scenarios in the organization's Disaster Recovery Plan (DRP) ensures preparedness for worst-case events affecting AI systems. The AAIA™ Study Guide recommends tailoring business continuity and DR strategies to cover model unavailability, data corruption, and AI-specific dependencies.
"AI disruptions can arise from unique causes such as model corruption, adversarial attacks, or drift.
Integrating these into the DRP allows for effective, scenario-specific responses and minimizes downtime." Tabletop exercises (A) are valuable for preparedness but are less comprehensive than scenario planning. Kill chains (B) are security-specific. KRIs (C) aid in monitoring but don't ensure recovery. Therefore, D offers the most robust mitigation.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Business Continuity and Disaster Recovery Planning for AI"


NEW QUESTION # 138
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