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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
  • 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 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.

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ISACA Advanced in AI Audit Sample Questions (Q85-Q90):

NEW QUESTION # 85
Which of the following is the MOST important reason to establish AI governance structures that extend beyond regulatory compliance?

Answer: D

Explanation:
While regulatory compliance is essential, AAIA underlines that ethical integrity must guide AI design, deployment, and monitoring. Regulations often lag behind technological capabilities; thus, relying solely on compliance leaves gaps in areas such as fairness, transparency, human dignity, and societal impact. The MOST important reason to extend governance structures beyond compliance is to ensure ethical integrity throughout the AI life cycle (C) -- from data collection and model design to deployment, monitoring, and retirement.


NEW QUESTION # 86
Which of the following is the GREATEST risk when an organization uses publicly available social media data to train its AI model without obtaining explicit user consent?

Answer: D

Explanation:
Using social media data without consent raises severe legal and ethical concerns. According to the AAIA™ manual, the greatest risk is the " Violation of data privacy regulations " (such as GDPR or CCPA), which can result in significant legal penalties, mandatory deletion of models, and litigation. Even if the data is " public, " privacy laws often restrict the use of personal information for automated decision-making or profiling without a clear legal basis (like consent). While data quality (Option A) and labeling (Option B) are operational risks, they do not pose the same existential threat to the organization as regulatory non-compliance and the resulting loss of license to operate.


NEW QUESTION # 87
Which of the following is the PRIMARY purpose of an AI acceptable use policy?

Answer: C


NEW QUESTION # 88
An IS auditor is reviewing a dataset used by a university. Which of the following MOST likely indicates a risk that the model could not process all data and make necessary correlations?

Answer: A

Explanation:
In machine learning, " Data Typing " is foundational. If a numerical field (like Grade Percent) is stored as an " Object " (string/text), the AI model cannot perform mathematical operations on it, such as calculating correlations or averages. According to the AAIA™ manual, this is a " Data Quality " failure that leads to " Feature Exclusion, " where the model simply ignores the variable or treats each number as a unique text label, losing all quantitative meaning. The other formats (Integer, Float, Boolean) are appropriate for their respective data types.


NEW QUESTION # 89
The PRIMARY objective of auditing AI systems is to:

Answer: A

Explanation:
The AAIA™ Study Guide outlines the primary goal of auditing AI systems as ensuring that they operate ethically, transparently, and fairly. This includes identifying potential biases in decision-making and confirming that the rationale behind outcomes can be explained and understood.
"The key focus of an AI audit is to evaluate whether the system performs within the parameters of fairness, legality, and accountability. This involves testing for bias and ensuring decision-making transparency." Options B, C, and D refer to performance and usability concerns, which are secondary to the ethical and governance-focused purpose of AI audits.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI in Audit Processes," Subsection: "Purpose and Scope of AI Audits"


NEW QUESTION # 90
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