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NEW QUESTION # 238
Which of the following is the MOST important reason for measuring the AI system ' s performance against predefined metrics in a staging environment?
Answer: C
Explanation:
The AAIA™ Study Guide emphasizes the importance of a rigorous " Staging " or " User Acceptance Testing
" (UAT) phase in the AI lifecycle. Measuring performance against predefined metrics (such as Precision, Recall, or F1-Score) in a non-production environment is critical to " Validate that the system meets business and technical requirements prior to release " . This step prevents the deployment of models that may exhibit bias, inaccuracy, or logic errors in the real world. While privacy compliance (Option A) and dataset freshness (Option B) are vital, they are components of the broader validation process that ensures the model is functional, safe, and fit for purpose before impacting live operations.
NEW QUESTION # 239
Which of the following is the MOST appropriate control for ensuring accountability when an AI system makes an erroneous high-impact decision?
Answer: C
Explanation:
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.
NEW QUESTION # 240
Which of the following is the BEST recommendation to mitigate excessive agency when implementing an AI system as a browser extension?
Answer: C
Explanation:
Excessive agencyoccurs when AI systems act too autonomously, making decisions without appropriate human oversight. To mitigate this in a browser extension, the BEST approach is tominimize functionality (A), ensuring the extension performs only narrowly defined, controlled actions. This aligns with AAIA's guidance onlimiting AI autonomy, applying least-privilege principles, and restricting unnecessary actions.
Removing user access entirely (B) is overly restrictive. Maximizing functionality (C) increases risk. Open- source extensions (D) improve transparency but do not inherently control excessive agency.Scope limitation is the most targeted and effective mitigation.
References:
ISACA,AAIA Exam Content Outline- Domain 1: Governance, AI Autonomy, and Risk Controls.
NEW QUESTION # 241
An AI audit tool incorrectly flagged that business decisions were biased, leading to inappropriate management action plans. Which of the following can BEST prevent this risk?
Answer: A
Explanation:
AI tools can produce "False Positives" in bias detection if they misinterpret the data. To prevent management from acting on incorrect audit findings, "Explainable AI (XAI) validation methods" (like SHAP or LIME) should be applied. XAI allows the auditor to see why the tool flagged a specific decision as biased. If the tool's reasoning is flawed (e.g., it ignored a valid business justification), the auditor can correct the finding before it reaches management. This adds a necessary layer of "Auditor skepticism" and human validation to AI-driven audit insights.
NEW QUESTION # 242
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 AAIATM 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."
NEW QUESTION # 243
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