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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 Regulatory Compliance and Legal Considerations - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases - AI Trustworthiness, Ethical and Societal Implications - AI Organizational Processes and Alignment - AI Policies, Procedures, and Organizational Training |
| AI Risk Program Management | 42% | - AI Risk Assurance and Continuous Improvement - AI Risk Monitoring and Reporting - AI Risk Response and Mitigation - AI Risk Identification and Assessment |
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NEW QUESTION # 59
Which risk treatment is MOST appropriate when an organization's AI system presents residual risk within tolerance and impacts non-critical functions?
Answer: A
Explanation:
Risk treatment decisions are driven by two factors: whether the residual risk falls within or outside tolerance, and the criticality of the affected function. When both conditions-risk within tolerance AND non-critical function impact-are met, formal risk acceptance is the appropriate and proportionate treatment.
Why A is Correct: According to ISACA AAIR risk treatment guidance, documented formal risk acceptance is the appropriate response when residual risk is within defined tolerance for non-critical functions. Risk acceptance acknowledges the identified exposure, documents the organization's conscious decision to accept it, and establishes accountability for that decision. This proportionate response avoids over-investing in controls for risk that the organization has determined is acceptable.
Why B is Wrong: Recommending increases to tolerance thresholds is a governance manipulation rather than a risk treatment. Adjusting thresholds upward to accommodate risk does not address the risk; it merely reclassifies it as acceptable. This approach undermines risk governance integrity.
Why C is Wrong: Enhancing monitoring to detect deviations represents additional control investment that may be disproportionate for risk that is already within tolerance affecting non-critical functions. Enhanced monitoring is more appropriate when risk is near the tolerance boundary or when trends indicate potential future breach.
Why D is Wrong: Periodic vulnerability scanning is a security assurance activity that identifies technical weaknesses. It represents an ongoing control measure rather than the appropriate risk treatment decision for a residual risk that is already within tolerance.
NEW QUESTION # 60
The PRIMARY reason to transfer residual AI risk to a third party is to:
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 transfer is used when a third party assumes defined financial or contractual consequences of residual risk that the organization cannot or chooses not to retain. It can reduce organizational liability, but it does not eliminate the organization ' s governance responsibilities. This makes option A, lower organizational liability when internal mitigations fail, 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 # 61
Which of the following is the MOST appropriate key performance indicator (KPI) for the effectiveness of a targeted AI risk awareness training program?
Answer: A
Explanation:
Training program effectiveness KPIs must measure behavioral change-whether training has actually altered how participants act in their work environment-rather than knowledge acquisition or adoption rates. The most meaningful behavioral signal for AI risk awareness training is whether trained users report suspicious activity.
Why B is Correct: According to ISACA AAIR training effectiveness measurement guidance, the number of AI irregularities and potential tampering incidents reported by users is the most appropriate behavioral KPI for risk awareness training effectiveness. When users report unusual AI behavior, this demonstrates they have internalized training concepts well enough to recognize anomalies and understand their obligation to report them. This behavioral change-from passive observation to active reporting-is the intended outcome of awareness training.
Why A is Wrong: Risk rating changes measure risk management process adjustments rather than individual behavioral change from training. Risk ratings reflect aggregate organizational risk, not the specific behavioral impact of an awareness training program.
Why C is Wrong: Ability to identify financial impacts is a knowledge assessment metric-it measures what users know rather than what they do differently as a result of training. Awareness training aims to change behavior, not just inform.
Why D is Wrong: AI adoption rates measure technology uptake, not risk awareness. Higher adoption could indicate confidence in AI systems but does not measure whether employees recognize and report AI risks- the specific objective of risk awareness training.
NEW QUESTION # 62
An organization uses an AI model that learns from live data streams. Which of the following is the BEST course of action to manage the risk of an adaptive model?
Answer: A
Explanation:
AI models that learn from live data streams continuously update their parameters based on incoming data.
This creates two specific risks: the model's behavior may drift from its validated state as data patterns change (data drift), and adversaries may deliberately introduce malicious data to manipulate the model's learning (data poisoning).
Why D is Correct: According to ISACA AAIR adaptive model risk guidance, implementing automated monitoring for both data drift and data poisoning is the most comprehensive response to live-learning model risks. Automated monitoring operates continuously at the speed of the data stream, detecting statistical changes in input distributions (drift signals) and anomalous data patterns (poisoning signals) in real time- enabling timely intervention before either risk materializes into harmful behavior.
Why A is Wrong: Defense-in-depth for model access controls who can interact with the model but does not address risks arising from the data the model learns from. Access controls are necessary but insufficient for managing adaptive learning risks.
Why B is Wrong: Restricting data sources reduces learning breadth, potentially undermining the model's adaptive capability that creates its value. Periodic inspections are too infrequent for live-learning systems where risks can emerge between inspection cycles.
Why C is Wrong: Dynamic performance thresholds detect output degradation after drift has occurred. While useful as a safety net, this reactive monitoring does not prevent drift or detect poisoning early enough for the live-learning risk context.
NEW QUESTION # 63
Which of the following is the PRIMARY risk associated with the use of unsupervised learning methods to train AI models?
Answer: A
Explanation:
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.
Unsupervised learning operates without predefined labels, making discovered patterns harder to validate and explain against known targets. This creates particular assurance challenges around interpretation, labeling, and explainability compared with supervised classification. This makes option D, Lack of labeling and explainability, 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 # 64
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