AAIA시험패스가능한공부자료, AAIA덤프샘플다운
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Pass4Test사이트에서 제공해드리는 ISACA AAIA덤프는 실러버스의 갱신에 따라 업데이트되기에 고객님께서 구매한ISACA AAIA덤프가 시중에서 가장 최신버전임을 장담해드립니다. ISACA AAIA덤프의 문제와 답을 모두 기억하시면ISACA AAIA시험에서 한방에 패스할수 있습니다.시험에서 불합격 받으시면 결제를 취소해드립니다.
ISACA AAIA 시험요강:
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AAIA시험패스 가능한 공부자료 최신 시험 기출문제 모음 자료
Pass4Test의 ISACA인증 AAIA시험덤프는 고객님의 IT자격증을 취득하는 꿈을 실현시켜 드리는 시험패스의 지름길입니다. ISACA인증 AAIA덤프에는 실제시험문제의 거의 모든 문제를 적중하고 습니다. Pass4Test의 ISACA인증 AAIA덤프가 있으면 시험패스가 한결 간편해집니다.
최신 Advanced in AI Audit AAIA 무료샘플문제 (Q128-Q133):
질문 # 128
An IS auditor is evaluating a cybersecurity system that uses agentic AI for autonomous threat detection and incident response. Which of the following is MOST important for the auditor to consider?
- A. The agent processes data autonomously, reducing the need for analyst intervention.
- B. The agent can take automated actions that may disrupt business operations.
- C. The agent operates across systems, which might require network expansion.
- D. The agent ' s audit logs are lengthier than traditional logs.
정답:B
설명:
" Agentic AI " goes beyond simple detection; it can take actions (like shutting down a server) autonomously.
The greatest risk is that the AI might misinterpret a legitimate but unusual business activity as a threat and trigger a " kill switch, " causing massive, unplanned downtime. This is a significant operational and availability risk. Auditors must ensure there are " guardrails " or a " human-in-the-loop " for high-impact actions. While reduced intervention (Option B) is a benefit, it is also the source of the risk that the auditor must mitigate through governance and control evaluation.
질문 # 129
The PRIMARY objective of auditing AI systems is to:
- A. Maximize system efficiency and throughput.
- B. Minimize algorithm latency and information storage impacts.
- C. Identify biases and decision transparency.
- D. Optimize user experience and interface satisfaction.
정답:C
설명:
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"
질문 # 130
Which of the following would provide the BEST evidence to an IS auditor that an AI model's outputs are effectively controlled for bias?
- A. Technical details of model development processes are transparent.
- B. Model training is restricted to data containing real-world human decisions.
- C. Accuracy ranges for various demographic groups are similar.
- D. The organization's AI policies include a clear definition of fairness.
정답:C
설명:
To determine whether an AI model's outputs areeffectively controlled for bias, an auditor needsempirical performance evidenceacross demographic groups.Similar accuracy ranges across groups (A)demonstrate that the model performs equitably and does not disproportionately advantage or disadvantage specific populations. This aligns with AAIA's emphasis onfairness metrics, such as disparate error rates, equal opportunity, and demographic parity analyses.
Option B (fairness definition) is important for governance but does not prove fairness in practice. Option C may introduce historical human bias rather than mitigate it. Option D (transparency of development) supports explainability but does not validate fairness outcomes. Actualperformance parity across demographic groupsis the strongest evidence of bias control.
References:
ISACA,AAIA Exam Content Outline- Domain 1: AI Governance and Risk (fairness evaluation; bias assessments).
ISACA fairness guidance emphasizing cross-group performance comparison.
질문 # 131
Which of the following is the GREATEST challenge facing IS auditors evaluating the explainability of generative AI models?
- A. Difficulties in preventing the input of biased data
- B. Algorithms changing as AI continues to learn
- C. Performance issues due to excessive computation
- D. Differences of opinion regarding model types
정답:B
설명:
The greatest challenge for IS auditors in evaluating the explainability of generative AI models is the changing nature of algorithms as AI continues to learn (option D). Generative AI models, especially those using advanced techniques like deep learning and reinforcement learning, often employ continuous or dynamic learning, which results in models that evolve over time. This adaptability can significantly hinder explainability because the logic, parameters, or decision pathways may shift with ongoing retraining or real- time learning.
The ISACA Advanced in AI Audit™ (AAIA™) Study Guide stresses that: "Continually learning AI systems present unique audit challenges, as their internal representations and reasoning can change after deployment, making it difficult to fully capture and explain the rationale for outputs at any given point." Other options, such as bias in input data or computational performance, are significant but do not pose as fundamental a challenge to explainability as a model whose internal workings can dynamically change.
Reference:ISACA Advanced in AI Audit™ (AAIA™) Study Guide, Section: "AI Explainability and Dynamic Models"
질문 # 132
Which of the following is the BEST approach to mitigate the risk of " AI model degradation " ?
- A. Training models on both model-generated and human-generated data
- B. Continuous monitoring to identify adversarial inputs
- C. Increasing the use of synthetic data for model training
- D. Periodic human reviews of model outputs and recommendations
정답:D
설명:
Model degradation occurs as the " Freshness " of the training data wanes and real-world conditions evolve.
The most robust control is " Periodic human reviews " (Human-in-the-Loop). Human experts can identify " drift " in logic or common-sense failures that automated systems might miss. Relying on model-generated data (Option A) can lead to " Model Collapse, " where the AI begins to drift into nonsensical patterns by reinforcing its own previous outputs. Human oversight ensures the model remains grounded in reality and aligned with business objectives.
질문 # 133
......
Pass4Test의 ISACA인증 AAIA덤프를 구매하여 공부한지 일주일만에 바로 시험을 보았는데 고득점으로 시험을 패스했습니다.이는Pass4Test의 ISACA인증 AAIA덤프를 구매한 분이 전해온 희소식입니다. 다른 자료 필요없이 단지 저희ISACA인증 AAIA덤프로 이렇게 어려운 시험을 일주일만에 패스하고 자격증을 취득할수 있습니다.덤프가격도 다른 사이트보다 만만하여 부담없이 덤프마련이 가능합니다.구매전 무료샘플을 다운받아 보시면 믿음을 느낄것입니다.
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