우리 ITDumpsKR사이트에서 제공되는ISACA인증AAIR시험덤프의 일부분인 데모 즉 문제와 답을 다운받으셔서 체험해보면 우리ITDumpsKR에 믿음이 갈 것입니다. 우리ITDumpsKR의 제품을 구매하신다고 하면 우리는 최선을 다하여 여러분들한테 최고의 버전을 제공함으로 한번에ISACA인증AAIR시험을 패스하도록 하겠습니다. IT시험이라고 모두 무조건 외우고 장악하고 많은 시간을 투자해야만 된다는 사상을 깨게 될 것입니다.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Risk Governance and Framework Integration | 37% | - AI Organizational Processes and Alignment - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases |
| Topic 2: AI Risk Program Management | 42% | - AI risk assessment and treatment strategies - AI risk monitoring and continuous improvement - AI governance communication and reporting - Enterprise AI risk program design |
| Topic 3: AI Life Cycle Risk Management | - AI model and data risk identification - AI bias, drift, transparency, and control evaluation - AI development, deployment, and monitoring risks |
ITDumpsKR의ISACA인증 AAIR덤프는 인터넷에서 검색되는ISACA인증 AAIR시험공부자료중 가장 출중한 시험준비 자료입니다. ISACA인증 AAIR덤프를 공부하면 시험패스는 물론이고 IT지식을 더 많이 쌓을수 있어 일거량득입니다.자격증을 취득하여 자신있게 승진하여 연봉협상하세요.
질문 # 48
An organization formally accepts residual risk for a low-impact AI capability after confirming it falls within the enterprise risk tolerance.
What is the primary benefit of this risk acceptance action?
정답：B
설명：
Within the ISACA Advanced in AI Risk framework, program management connects risk identification, control selection, treatment, monitoring, resilience, third-party oversight, and reporting to enterprise risk objectives. When residual risk is within tolerance and affects non-critical functions, formal acceptance is proportionate and allows scarce mitigation resources to be directed toward higher-impact exposures.
Acceptance must still be documented and monitored rather than treated as inaction. This makes option A, It enables the allocation of mitigation resources to more critical AI-specific issues, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk-management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
질문 # 49
A financial organization is developing an AI model for credit risk assessment. Which of the following is MOST important to ensure the training data supports accurate and unbiased outcomes?
정답：D
설명：
Credit risk assessment AI models trained on unrepresentative datasets perpetuate and amplify historical financial inequities, producing discriminatory outcomes that violate anti-discrimination laws and harm underrepresented borrowers. Dataset diversity is the primary safeguard against training-data-driven bias.
Why A is Correct: According to ISACA AAIR bias and fairness guidance for financial AI, dataset diversity is the most important factor for supporting accurate and unbiased credit risk outcomes. A diverse dataset that represents the full population of potential borrowers-across demographics, income levels, credit histories, and geographies-enables the model to learn genuine risk relationships rather than proxies for protected characteristics. Without diversity, even technically sophisticated models perpetuate discriminatory patterns from historical data.
Why B is Wrong: Supervised learning is a modeling approach, not a data quality characteristic. The choice of supervised learning is appropriate for credit scoring but does not determine whether the training data is representative or unbiased.
Why C is Wrong: Synthetic data augmentation can supplement real data to address specific gaps but cannot substitute for diversity in the underlying real-world data. Synthetic data derived from biased real data may amplify rather than correct the original bias.
Why D is Wrong: Data normalization is a preprocessing technique that scales numerical features to comparable ranges to improve model convergence. It addresses technical modeling quality but has no effect on the representational diversity or demographic fairness of the dataset.
질문 # 50
A risk practitioner is performing a business impact analysis (BIA) of potential service disruptions to an organization's AI-powered operational processes. Which of the following is MOST important to address in the BIA?
정답：A
설명：
Within the ISACA Advanced in AI Risk framework, program management connects risk identification, control selection, treatment, monitoring, resilience, third-party oversight, and reporting to enterprise risk objectives. A business impact analysis focuses on how disruption affects critical operations and on recovery requirements such as recovery time objectives. Development records, asset classification, and incident procedures are related controls but are not the primary purpose of a BIA. This makes option A, Effects of AI system outages on core operations and associated recovery time targets, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk-management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
질문 # 51
A risk practitioner discovers that an AI chatbot stores user interactions indefinitely. Which of the following is the MOST appropriate mitigation?
정답：D
설명：
Within the ISACA Advanced in AI Risk framework, life-cycle controls should protect data quality, model design, testing, validation, monitoring, change management, and secure retirement of AI systems. Indefinite chatbot retention creates unnecessary privacy and breach exposure. Automated retention limits linked to documented consent or purpose ensure records are kept only as long as justified while still accommodating legitimate legal, operational, or audit requirements. This makes option B, Automate retention limits linked to documented consent, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk-management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
질문 # 52
Which of the following is the MOST important vendor assurance measure when an organization plans to engage multiple AI vendors for critical model components?
정답：B
설명：
Within the ISACA Advanced in AI Risk framework, program management connects risk identification, control selection, treatment, monitoring, resilience, third-party oversight, and reporting to enterprise risk objectives. When multiple vendors provide critical model components, assurance depends on evidence of provenance and integrity so the organization can trace the origin and handling of data and artifacts. Tool mandates or centralized IT ownership do not establish trustworthiness. This makes option A, Verifying documentation of data provenance and integrity, the strongest answer. The other choices describe narrower technical, operational, performance, or administrative considerations and do not address the primary risk- management objective in the scenario as directly. A risk practitioner should select the response that most effectively reduces the stated exposure while preserving appropriate oversight, traceability, and alignment with organizational risk tolerance and business requirements.
질문 # 53
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ISACA AAIR인증시험은 전업적지식이 강한 인증입니다. IT업계에서 일자리를 찾고 계시다면 많은 회사에서는ISACA AAIR있는지 없는지에 알고 싶어합니다. 만약ISACA AAIR자격증이 있으시다면 여러분은 당연히 경쟁력향상입니다.
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