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| Section | Weight | Objectives |
|---|---|---|
| AI Risk Program Management | 42% | - AI Risk Monitoring and Reporting - AI Risk Response and Mitigation - AI Risk Identification and Assessment - AI Risk Assurance and Continuous Improvement |
| AI Risk Governance and Framework Integration | 37% | - AI Policies, Procedures, and Organizational Training - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases - AI Organizational Processes and Alignment - AI Regulatory Compliance and Legal Considerations - AI Trustworthiness, Ethical and Societal Implications |
| AI Life Cycle Risk Management | 21% | - AI Design, Development/Procurement, and Documentation - AI Implementation, Maintenance, and Decommissioning - AI Data and Asset Management - AI Model Training, Testing, and Validation |
AAIRのShikenPASS試験トレントを正常に支払った後、購入者は5〜10分でシステムから送信されたメールを受け取ります。その後、候補者はリンクを開いてログインし、AAIRテストトレントを使用してすぐに学習できます。時間は受験者にとって非常に重要であるため、誰もが効率的に学習できることを願っています。そのため、候補者は購入後すぐにAAIRガイドの質問を使用でき、当社製品の大きな利点になります。受験者がAAIRテストトレントを習得し、AAIR試験の準備を改善することは便利です。
質問 # 17
A risk practitioner assesses an AI model used for predictive diagnostics and finds that the system lacks automated update mechanisms. Which of the following is the GREATEST risk?
正解：D
解説：
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. A predictive diagnostic model that cannot update may continue using assumptions that no longer reflect current conditions, compromising accuracy as the environment changes. Human effort is secondary to the risk of incorrect predictions based on stale relationships. This makes option D, Compromise of predictive accuracy due to outdated model assumptions, the strongest answer.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.
質問 # 18
Which of the following is the GREATEST risk when an AI system requires a specific safeguard that cannot be put in place because of technical constraints?
正解：B
解説：
When required safeguards cannot be technically implemented, the risk they were designed to mitigate remains unaddressed. This creates a residual exposure gap where the AI system operates with known, unmitigated vulnerabilities-a fundamental risk management failure for the identified threat.
Why A is Correct: The ISACA AAIR risk treatment guidance identifies elevated residual exposure from absent controls as the greatest risk when required safeguards cannot be implemented. Every required safeguard addresses a specific risk exposure. When that safeguard is technically infeasible, the risk it was designed to prevent remains fully present. This unmitigated exposure may exceed the organization's risk tolerance and require escalation to senior management for risk acceptance or alternative treatment decisions.
Why B is Wrong: Training dataset restrictions relate to model development constraints, not directly to the inability to implement a specific runtime safeguard. This is a separate concern that may arise in some technical constraint scenarios but is not the primary risk of an absent safeguard.
Why C is Wrong: User experience degradation is an operational quality concern. Performance impacts from technical constraints are a usability issue rather than a risk exposure representing the greatest organizational concern.
Why D is Wrong: Operational inefficiency and manual process dependencies are resource and process concerns. While relevant to operational cost and effectiveness, they do not represent the primary risk of an unmitigated security or safety exposure from an absent safeguard.
質問 # 19
Which of the following BEST mitigates the risk of misaligned return on investment (ROI) in AI initiatives?
正解：A
解説：
Within the ISACA Advanced in AI Risk framework, governance decisions should align AI use with policy, accountability, stakeholder expectations, risk appetite, and applicable legal or ethical obligations. Mapping AI project outcomes to enterprise performance metrics ties investment to measurable organizational value. An inventory improves visibility and workforce metrics measure only one dimension, while a narrow focus on quantifiable benefits can miss strategic value. This makes option C, Mapping AI project outcomes to enterprise performance metrics, 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.
質問 # 20
Which of the following would BEST mitigate operational and legal risk exposure when integrating third-party AI services?
正解：A
解説：
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. Third-party AI creates shared operational and legal obligations, so a responsibility matrix should clearly define accountability for controls, data, incidents, compliance, and remediation. Delegation does not remove the organization ' s own responsibility. This makes option C, Defining a responsibility matrix and accountability for all parties, 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.
質問 # 21
Which of the following is MOST important to verify when assessing open-source AI components in an organization's supply chain?
正解：D
解説：
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. Open-source AI components should be traceable so the organization can verify origin, dependencies, integrity, licensing, and maintenance history. Geography and cost are secondary, and documentation ownership alone does not establish trustworthy provenance. This makes option A, Traceability for open-source AI artifacts, 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.
質問 # 22
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