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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Organizational Processes and Alignment - AI Models, Frameworks, Strategies, and Use Cases |
| Topic 2: AI Life Cycle Risk Management | - AI development, deployment, and monitoring risks - AI bias, drift, transparency, and control evaluation - AI model and data risk identification | |
| Topic 3: AI Risk Program Management | 42% | - AI governance communication and reporting - AI risk monitoring and continuous improvement - Enterprise AI risk program design - AI risk assessment and treatment strategies |
私たちが提供するISACA Advanced in AI Risk準備トレントは、精巧にコンパイルされ、非常に効率的です。 AAIR試験トレントを練習するのに20〜30時間しかかからず、CertJuken試験に参加できます。 仕事などで忙しいほとんどのお客様。 ただし、AAIRテスト準備を使用する場合、短時間で試験を準備して試験内容をマスターするのにISACAそれほど時間は必要ありません。 彼らがする必要があるのは、毎日学習して練習するのに1〜2時間を費やし、AAIRテスト準備で簡単に試験に合格することです。 試験に合格するための時間と労力はほとんどかかりません。
質問 # 19
Which of the following is the MOST effective approach to help ensure compliance with AI acceptable use policies?
正解：B
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. Acceptable use policies become effective when employees understand AI risks and how policy requirements apply in practice. Embedding AI risk awareness in training supports consistent user behavior, recognition of misuse, and appropriate escalation. This makes option D, Building trust by embedding AI risk awareness within organizational training, 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 control is MOST effective to prevent attackers from embedding malicious instructions within user prompts to alter model outputs?
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. Prompt injection is best addressed at runtime by validating incoming content and controlling model outputs. RBAC limits permissions, encryption protects stored data, and static filters may miss context- dependent attacks, while content validation directly addresses malicious instructions. This makes option D, Content validation, 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 the PRIMARY concern associated with AI-based attacks on systems that store personal data?
正解：C
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. AI-enabled re-identification is a direct privacy risk because models can combine attributes that appear harmless in isolation and infer an individual identity. This can defeat ordinary masking or pseudonymization and create regulatory exposure even when direct identifiers are absent. This makes option C, AI models may be able to identify combinations of attributes that can be used to re-identify individuals, 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
A risk practitioner is evaluating AI model cards and documentation prior to deployment. Which of the following represents the GREATEST risk to enterprise AI governance?
正解：D
解説：
AI governance depends on the ability of stakeholders to understand, audit, and oversee AI model decisions.
Explainability is the technical and documentation property that enables this oversight. When model cards fail to adequately document explainability, the entire governance chain is compromised.
Why B is Correct: According to ISACA AAIR, inadequate explainability in model documentation is the greatest governance risk because it prevents risk practitioners, auditors, regulators, and business owners from understanding why a model produces its outputs. Without explainability, discriminatory or erroneous decisions cannot be identified, challenged, or corrected. This undermines accountability, compliance, and responsible AI governance at the enterprise level.
Why A is Wrong: Regulatory filing delays represent a compliance timing issue that can be remediated. While risky, they do not fundamentally compromise the governance capability of understanding and overseeing AI behavior.
Why C is Wrong: Decentralized version control creates configuration management challenges and audit trail gaps. These are significant but can be remediated through governance process improvements. Explainability gaps affect the underlying ability to govern the model itself.
Why D is Wrong: Overly detailed technical specifications represent a documentation quality issue that may reduce usability but does not create a governance risk. Excessive detail is easily distilled; absent explainability cannot be reconstructed after the fact.
質問 # 23
Which of the following is the PRIMARY benefit of using AI to assist with risk scenario identification?
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. AI assists risk scenario identification primarily through rapid analysis and pattern recognition across large volumes of information. Simulation and scoring are downstream capabilities, while pattern detection expands the practitioner ' s ability to identify emerging scenarios. This makes option C, Improved real-time analysis and pattern recognition, 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 # 24
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