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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Life Cycle Risk Management | 21% | - AI Model Training, Testing, and Validation - AI Data and Asset Management - AI Implementation, Maintenance, and Decommissioning - AI Design, Development/Procurement, and Documentation |
| Topic 2: AI Risk Governance and Framework Integration | 37% | - AI Regulatory Compliance and Legal Considerations - AI Organizational Processes and Alignment - AI Trustworthiness, Ethical and Societal Implications - AI Policies, Procedures, and Organizational Training - AI Models, Frameworks, Strategies, and Use Cases - AI Ownership, Oversight, and Accountability |
| Topic 3: AI Risk Program Management | 42% | - AI Risk Response and Mitigation - AI Risk Assurance and Continuous Improvement - AI Risk Monitoring and Reporting - AI Risk Identification and Assessment |
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NEW QUESTION # 23
A healthcare organization plans to use synthetic records in medical research to help protect patient privacy.
Which of the following is the GREATEST risk associated with using synthetic data to train AI models?
Answer: B
Explanation:
Synthetic data is generated algorithmically to resemble real data while protecting individual privacy.
However, synthetic data generation processes may not perfectly capture the full statistical diversity of real- world populations-particularly rare conditions, edge cases, and underrepresented demographic groups.
Why A is Correct: According to ISACA AAIR data quality guidance for AI, the greatest risk of training on synthetic data is that it may not reflect real-world diversity. In healthcare, this is particularly consequential because AI models trained on non-diverse synthetic data may perform poorly for patient populations not well- represented in the original real data-potentially producing inaccurate diagnoses or treatment recommendations for vulnerable groups, perpetuating health inequities.
Why B is Wrong: While reduced diversity could contribute to increased false negatives in some scenarios, this is a specific manifestation of the broader diversity problem. The root cause-lack of real-world representativeness-is the more fundamental and comprehensive risk.
Why C is Wrong: Regulatory noncompliance from synthetic data use depends on jurisdiction-specific requirements. Many regulations explicitly encourage synthetic data to protect privacy. While compliance must be verified, it is not the greatest inherent risk of synthetic data quality.
Why D is Wrong: Synthetic data generation occurs in controlled internal environments and is not inherently more susceptible to data poisoning than other data types. Poisoning risk is a function of data pipeline controls, not whether data is synthetic or real.
NEW QUESTION # 24
Which of the following is the PRIMARY reason to lower AI model temperature?
Answer: A
Explanation:
Temperature is a hyperparameter in language model generation that controls output randomness. Lower temperatures make the model more deterministic-concentrating probability mass on the most likely tokens and producing more consistent, predictable outputs. Higher temperatures introduce more randomness and diversity.
Why B is Correct: According to ISACA AAIR model configuration guidance, lowering model temperature is primarily used to enhance consistency and accuracy of outputs. In production applications requiring reliable, reproducible responses-such as customer service, compliance reporting, or technical documentation-lower temperature ensures the model consistently generates the most appropriate response based on its learned knowledge, reducing variability and improving output quality.
Why A is Wrong: Temperature adjustment does not directly mitigate bias. Bias in AI models is a function of training data and model architecture, not output randomness. A biased model at low temperature will consistently generate biased outputs; lowering temperature may actually make bias more persistent by reducing variation.
Why C is Wrong: Diversifying ideas and recommendations is achieved by increasing temperature, not lowering it. Higher temperature is used for creative tasks where variety is valuable; lower temperature is used for tasks requiring precision and consistency.
Why D is Wrong: Model temperature has no direct relationship to computational energy consumption. Energy use is primarily driven by model size, computation requirements, and inference frequency-not the temperature parameter.
NEW QUESTION # 25
Which of the following is the GREATEST organizational risk when AI performance alerts are not escalated to decision-makers for review and decisioning?
Answer: B
Explanation:
AI performance alerts signal emerging issues with model behavior-accuracy degradation, anomalous outputs, drift-that require prompt management attention and decision-making. When these alerts are not escalated, corrective actions are delayed and AI system instability can escalate into serious operational incidents.
Why B is Correct: The ISACA AAIR operational risk management guidance identifies business disruption from delayed remediation as the greatest risk from alert escalation failures. When performance alerts are suppressed or not acted upon, unstable AI behavior continues and potentially worsens until it produces visible failures-system outages, incorrect critical decisions, customer harm-that disrupt business operations. The gap between alert generation and remediation is the window during which the AI system can cause the most damage.
Why A is Wrong: Governance reporting gaps represent a compliance and oversight concern but are secondary to the operational reality of unstable AI causing business disruption. Reporting gaps are administrative failures; operational disruption is the consequential business harm.
Why C is Wrong: Redundant mitigation activities might arise when issues are addressed without coordination, but this is an efficiency concern. The greater risk is that without escalation, no mitigation activities are initiated at all-the opposite of redundancy.
Why D is Wrong: Decision logging gaps affect traceability and auditability. While important for governance purposes, logging failures do not represent the most immediate operational risk from failing to escalate performance alerts to decision-makers.
NEW QUESTION # 26
Which of the following is the MOST important reason for a risk practitioner to classify AI risk using threat actor profiles?
Answer: A
Explanation:
Threat actor profiling characterizes the motivations, capabilities, and likely attack methods of potential adversaries. In AI risk management, understanding who the likely attackers are and what they seek enables the design of controls specifically matched to the actual threat landscape.
Why B is Correct: According to ISACA AAIR threat-based risk management guidance, the most important reason for threat actor profiling is to tailor controls to adversary motivations and capabilities. Different threat actors-nation-state attackers, criminal organizations, competitors, insiders, activists-have different objectives (espionage vs. financial gain vs. disruption), capabilities (sophisticated vs. opportunistic), and methods. Controls calibrated to actual threat actor profiles are significantly more effective than generic controls that may not address the specific threats the organization actually faces.
Why A is Wrong: Aligning AI threats with IT control taxonomy is a governance integration activity that improves control consistency but does not capture the threat actor-specific tailoring value of profiling.
Taxonomy alignment is an administrative benefit; threat-tailored controls are a security effectiveness benefit.
Why C is Wrong: Response metrics for cybersecurity incidents are developed for incident management planning. Threat actor profiling informs control design and incident response strategies but is not primarily used to develop response metrics.
Why D is Wrong: Prioritizing external threats over internal threats is a security strategy choice that threat actor profiling does not prescribe. Many AI attacks, including insider threats and social engineering, are internal. Profiling should result in appropriate prioritization based on actual threat likelihood, not a blanket prioritization of external threats.
NEW QUESTION # 27
Which of the following is the GREATEST organizational risk when AI performance alerts are not escalated to decision-makers for review and decisioning?
Answer: B
NEW QUESTION # 28
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