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| Section | Weight | Objectives |
|---|---|---|
| AI Life Cycle Risk Management | 21% | - AI Model Training, Testing, and Validation - AI Data and Asset Management - AI Design, Development/Procurement, and Documentation - AI Implementation, Maintenance, and Decommissioning |
| AI Risk Governance and Framework Integration | 37% | - AI Organizational Processes and Alignment - AI Models, Frameworks, Strategies, and Use Cases - AI Regulatory Compliance and Legal Considerations - AI Ownership, Oversight, and Accountability - AI Policies, Procedures, and Organizational Training - AI Trustworthiness, Ethical and Societal Implications |
| AI Risk Program Management | 42% | - AI Risk Assurance and Continuous Improvement - AI Risk Monitoring and Reporting - AI Risk Identification and Assessment - AI Risk Response and Mitigation |
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NEW QUESTION # 129
An organization deploys an autonomous system that makes decisions affecting compliance with regulations.
If those decisions could potentially produce regulatory breaches, which of the following BEST helps to manage associated liability exposures?
Answer: D
Explanation:
Liability from autonomous AI decisions affecting regulatory compliance requires organizations to demonstrate accountability, oversight, and control. Documentation of decision rationale and embedded oversight controls are the primary mechanisms for demonstrating responsible governance to regulators.
Why B is Correct: The ISACA AAIR framework identifies explainability documentation and embedded oversight controls as the key liability management tools for autonomous AI systems. When the organization can demonstrate that each AI decision was explainable, that controls were in place to detect violations, and that human oversight was embedded in the process, this demonstrates due diligence-which is the legal and regulatory standard for managing liability from automated decisions.
Why A is Wrong: Separate compliance programs fragment governance and may increase rather than reduce liability by suggesting AI compliance is siloed from the enterprise compliance program. Regulators expect integrated governance.
Why C is Wrong: Restricting deployment represents risk avoidance, not liability management for already- deployed systems. If the system is already in production, deployment restriction does not address existing liability.
Why D is Wrong: Single-point escalation and non-disclosure create governance bottlenecks and conflict with regulatory transparency requirements. Restricting disclosure cannot be used to shield the organization from regulatory accountability for automated decisions.
NEW QUESTION # 130
Which of the following should be a risk practitioner's PRIMARY consideration when developing risk scenarios related to adversarial manipulation of a business-critical AI system?
Answer: C
Explanation:
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. Risk scenarios for adversarial manipulation should be classified using criteria aligned with organizational tolerance so likelihood and impact can drive proportionate treatment decisions. Attack prevalence and patch frequency are inputs, not the governing risk criterion. This makes option C, Alignment of risk classification criteria with organizational tolerance, 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.
NEW QUESTION # 131
An organization deploys an autonomous system that makes decisions affecting compliance with regulations.
If those decisions could potentially produce regulatory breaches, which of the following BEST helps to manage associated liability exposures?
Answer: D
NEW QUESTION # 132
An organization deploys an AI credit scoring model trained on historical financial data that underrepresents certain demographic groups. Which of the following is the risk practitioner's BEST recommendation to mitigate this risk?
Answer: C
Explanation:
Bias in AI models often originates from training data that does not represent the full population the model will serve. Underrepresentation of demographic groups in training data causes the model to perform poorly for those groups, producing discriminatory outcomes in high-stakes decisions like credit scoring.
Why B is Correct: The ISACA AAIR bias and fairness guidance identifies expanding training data coverage as the most effective mitigation for representation bias. Defining specific inclusivity goals ensures the data expansion targets the identified gaps, while broadening data sources introduces representative examples from underrepresented groups. This addresses the root cause-training data deficiency-rather than symptoms.
Why A is Wrong: Model drift reporting detects changes in model behavior over time but does not address existing representational bias embedded in the current model. Monitoring an already-biased model cannot remediate the bias.
Why C is Wrong: Notifying stakeholders of potential inaccuracy is a transparency measure but does not reduce harm to affected individuals. Disclosure of bias without remediation is insufficient under anti- discrimination regulations.
Why D is Wrong: Unsupervised learning can identify hidden patterns but cannot introduce the missing representative data needed to train an unbiased model. Discovering discriminatory patterns in existing data does not resolve the underlying data coverage gap.
NEW QUESTION # 133
A business unit must implement and start using an AI system immediately and cannot follow the usual approval process. Which of the following is the BEST course of action?
Answer: C
Explanation:
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. An urgent need does not justify bypassing governance without authorization. A formal exception approved by the risk owner preserves accountability and ensures the deviation, conditions, and residual risk are documented and accepted by the proper authority. This makes option C, Obtain approval from the risk owner for an exception to the policy, 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.
NEW QUESTION # 134
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