AAIA資訊 - AAIA考古題

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ISACA AAIA 考試大綱：

主題簡介
主題 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.
主題 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.
主題 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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AAIA考古題，AAIA熱門證照

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最新的 Advanced in AI Audit AAIA 免費考試真題 (Q34-Q39):

問題 #34
Which of the following is the MOST important reason to conduct regular threat modeling exercises for AI systems and data?

答案：C

解題說明：
Regular threat modeling allows organizations to proactively identify vulnerabilities specific to AI, such as:
Data poisoning
Model inversion attacks
Membership inference attacks
Prompt injection
Unauthorized model manipulation
AAIA highlights AI threat modeling as essential for anticipating and mitigating AI-specific security risks that traditional IT threat modeling does not fully address.


問題 #35
An organization's system development process has been enhanced with AI. Which of the following features presents the GREATEST risk?

答案：D

解題說明：
Allowing AI to autonomously generate code without human review introduces significant risks, including security vulnerabilities, logic errors, and noncompliance with organizational development standards. The AAIA™ Study Guide strongly advocates for human-in-the-loop oversight, particularly in automated development contexts.
"AI-assisted development must include manual code reviews to ensure functionality, compliance, and security. Autonomous code generation without validation increases the risk of introducing undetected flaws." While A, B, and C involve operational risks or inefficiencies, only D constitutes a direct breach of secure development life cycle principles.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Fundamentals and Technologies," Subsection: "AI in Software Development and Associated Risks"


問題 #36
A healthcare AI tool recommends treatments with high success rates but significant risk. The hospital prioritizes patient safety over innovation. What is the BEST course of action?

答案：C

解題說明：
AI systems must align with the organization's risk appetite and ethical principles, especially in healthcare where patient safety is paramount. The BEST action is to adjust the AI's parameters (A) so the recommendations reflect the hospital's conservative risk tolerance, reducing the frequency of high-risk suggestions. AAIA stresses AI governance alignment with organizational risk appetite, treatment guidelines, and ethical priorities.


問題 #37
Which of the following is the GREATEST risk when a generative AI tool used for threat detection produces inaccurate or misleading information?

答案：B

解題說明：
In the context of cybersecurity and threat detection, the "accuracy" of AI outputs is a matter of organizational safety. The greatest risk of inaccurate information (such as false negatives) is that
"Potential threats may be overlooked," leading to undetected breaches or system compromises.
This occurs when the model fails to flag a genuine anomaly as suspicious.


問題 #38
Which of the following is the MOST appropriate control for ensuring accountability when an AI system makes an erroneous high-impact decision?

答案：B

解題說明：
Accountability requires a defined process -- someone must be responsible for reviewing, explaining, and remediating erroneous high-impact AI decisions; disclaimers alone do not constitute a control.


問題 #39
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