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ISACA Advanced in AI Risk Sample Questions:

1. Which of the following is the GREATEST concern when an organization cannot clearly explain an AI system's decision-making process and the origin of its inputs?

A) Decrease in AI adoption rates within business units who are regularly responsible for critical decisions
B) Increased dependence on external AI service providers for managing AI system risk throughout its life cycle
C) Heightened reliance on manual review resulting in approval bottlenecks and slower response times
D) Inability to detect discriminatory or inaccurate outputs that expose the organization to regulatory and reputational risk

2. Which of the following is the PRIMARY benefit of incorporating new AI-specific controls?

A) It provides a holistic approach to address conventional governance exposures and emerging AI vulnerabilities.
B) It reduces costs by eliminating redundant controls and consolidating control oversight.
C) It identifies and prioritizes compliance reporting requirements that apply to both existing and new controls.
D) It accelerates deployment timelines by enabling more efficient pre-deployment risk analysis.

3. Which of the following AI capabilities would BEST enable a forecasting system to accurately predict the point at which specific equipment components are likely to fail?

A) Post-defect identification of complex root causes
B) Recommendation of replacement products
C) Dynamic inventories of spare equipment parts
D) Real-time analysis of sensor monitoring data

4. Which of the following is MOST important when defining responsible roles for integrating third-party AI services into an organization's supply chain?

A) Aligning organizational and third-party AI security policies
B) Mandating cross-functional AI training for third-party staff
C) Designating AI governance and risk ownership
D) Standardizing migration and data transfer protocols

5. Which of the following AI system considerations BEST mitigates risk associated with model drift?

A) Implementing strong access controls based on roles and responsibilities
B) Maintaining existing levels of variance within datasets during preprocessing
C) Conducting regular retraining with new relevant datasets
D) Restricting the use of automated data validation to low-risk models

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