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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
  • 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.
主題 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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最新的 Advanced in AI Audit AAIA 免費考試真題 (Q314-Q319):

問題 #314
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?

答案：D

解題說明：
Using social media data without consent raises severe legal and ethical concerns. According to the AAIATM 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).


問題 #315
Which of the following is the BEST approach to mitigate the risk of AI model degradation?

答案：A

解題說明：
"Model degradation" (or model decay) happens when a model's performance slowly worsens because the real-world environment has changed since its last training. The most effective safeguard is "Periodic human reviews." Humans can identify "contextual shifts" or "common- sense errors" that automated monitoring might miss. This "Human-in-the-Loop" (HITL) control ensures that the AI's decisions remain grounded, justifiable, and accurate over time.


問題 #316
A manufacturing company installs an AI system to control robotic arms on its assembly line. The system learns over time, adjusting its movements based on production results to improve accuracy. What type of learning is the robot MOST likely using?

答案：D

解題說明：
Reinforcement Learning (RL) is characterized by an " agent " (the robot) that learns to achieve a goal in a dynamic environment through trial and error. It receives " rewards " for correct movements and " penalties " for errors, allowing it to optimize its " Policy Function " over time. Unlike supervised learning (Option A), which requires a pre-labeled dataset, RL allows for continuous improvement based on real-time feedback. The ISACA AAIA™ Study Guide identifies RL as the standard for robotics and autonomous systems where the " correct " action depends on the state of the physical environment.


問題 #317
Which of the following is the BEST recommendation to mitigate excessive agency when implementing an AI system as a browser extension?

答案：B

解題說明：
Excessive agency occurs when AI systems act too autonomously, making decisions without appropriate human oversight. To mitigate this in a browser extension, the BEST approach is to minimize functionality (A), ensuring the extension performs only narrowly defined, controlled actions. This aligns with AAIA's guidance on limiting AI autonomy, applying least-privilege principles, and restricting unnecessary actions.


問題 #318
Which use case for an AI model to be used by a food delivery service would pose ethical risk to the organization?

答案：A

解題說明：
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." A, C, and D involve business optimization without directly affecting individual employment rights. Therefore, B poses the greatest ethical risk.
Reference: ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "Ethical and Legal Considerations in AI," Subsection: "Human Impact and Workforce Automation Ethics"


問題 #319
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