ISACA AAIR : ISACA Advanced in AI Risk

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ISACA Advanced in AI Risk Sample Questions:

1. A risk practitioner is reviewing an organization's implementation of a business-critical AI decision system.
Which of the following would be of GREATEST concern?

A) Lack of cross-functional AI incident identification and escalation training
B) Risk threshold acceptance criteria that do not require 100% decision accuracy
C) Reliance on conventional third-party security providers for system monitoring
D) Insufficient scenario-based testing of system failure modes and recovery procedures

2. Which of the following BEST helps to ensure adherence to data minimization principles when using an AI model whose training dataset contains personal information?

A) Pseudonymization
B) Data encryption
C) Data loss prevention (DLP)
D) Role-based access control (RBAC)

3. Which of the following is the PRIMARY benefit of aligning AI risk management with existing organizational governance frameworks?

A) It promotes consistent enterprise-level oversight of AI activities and aligns decisioning with strategic objectives.
B) It emphasizes the development of specialized functional roles and clarifies AI risk responsibility boundaries.
C) It expedites approval processes for compliance with AI laws and regulations.
D) It standardizes AI acquisition processes across organizational business units.

4. An organization seeks to implement a new AI system that uses customer information to create targeted product recommendations. Which of the following is the MOST important consideration to ensure the system complies with regulatory requirements?

A) Use of supervised learning during model training
B) Human review of system recommendations
C) Legally sourced data with appropriate consent
D) Backup and storage protocols for sensitive data

5. Which of the following is the PRIMARY benefit of implementing a comprehensive data pipeline for AI model training, testing, and validation?

A) Enhanced auditability of outputs to provide evidence of regulatory compliance
B) Automation of complex tasks in early stages of the data pipeline
C) Sharing of governance risk with external data and service providers
D) Reduced risk of introducing errors into the final AI model

Solutions: