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ISACA Advanced in AI Audit Sample Questions (Q51-Q56):

NEW QUESTION # 51
Which of the following is the MOST important purpose of conducting a risk assessment for AI models within an organization?

Answer: A

Explanation:
Risk assessments identify potential threats and vulnerabilities in AI systems and support the development of mitigation strategies. According to the AAIA™ Study Guide, the main objective is not just identification of risks but to proactively design controls that minimize impact and ensure ethical and regulatory compliance.
"The output of an AI risk assessment should lead to actionable mitigation strategies, supporting the secure and responsible deployment of AI solutions across business processes." Options A, C, and D are components of governance and monitoring, but B addresses the core intent of risk assessments.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Risk Assessment and Mitigation for AI Systems"


NEW QUESTION # 52
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?

Answer: D


NEW QUESTION # 53
An IS auditor is evaluating an organization's incident management program to ensure it is sufficiently prepared to manage AI-related incidents. Which of the following is MOST important for the auditor to validate?

Answer: C

Explanation:
AI-related incidents often differ significantly from traditional IT incidents due to their dependence on data, model behavior, and algorithm performance. According to the AAIA™ Study Guide, incident management programs must include capabilities specifically tailored to AI, such as detecting and mitigating model drift and safeguarding against data poisoning or integrity attacks.
"AI incident response frameworks must account for issues unique to machine learning, including model drift, adversarial inputs, and data integrity breaches. An effective program incorporates detection, response, and recovery mechanisms for these AI-specific threats." While options A and B contribute to improving incident response over time, and option D suggests best- practice alignment, only option C directly addresses active response capabilities for high-risk, real-time AI vulnerabilities.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Incident and Risk Management in AI Contexts"


NEW QUESTION # 54
An AI social media platform uses an algorithm to increase user engagement that could unintentionally promote divisive content. Which of the following is the BEST course of action to mitigate this risk?

Answer: D

Explanation:
The AAIA™ Study Guide emphasizes that regular algorithmic audits are critical for identifying unintended consequences such as the promotion of harmful or biased content. This proactive approach helps maintain trust and ensure that algorithmic decisions align with organizational values and ethical standards.
"Auditing and monitoring AI models regularly helps detect and correct bias, drift, or other unintended behavior. It is essential for high-impact AI systems like content recommendation engines." While content customization (A) and user consent (C) are helpful, they don't prevent bias propagation.
Suspension (B) may halt engagement and isn't sustainable. Therefore, D is the most balanced and strategic solution.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Governance and Risk Management," Subsection: "Model Monitoring and Risk Mitigation Strategies"


NEW QUESTION # 55
Which of the following BEST ensures that an AI system complies with user data ownership rights under privacy regulations?

Answer: A

Explanation:
A transparent data consent management process ensures users are informed about how their data will be used, and enables them to exercise their rights to consent, access, rectify, or delete their data. This is a core requirement under regulations such as GDPR and CCPA.
"Consent management is fundamental to respecting data ownership rights. Organizations must clearly disclose data usage purposes, provide opt-in/out capabilities, and maintain audit trails of user interactions." While anonymization and retention policies support compliance, they don't address user control. Performance testing (D) relates to model accuracy, not user rights. Thus, C is the best answer.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "User Data Rights and Consent Management"


NEW QUESTION # 56
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