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ISACA AAIR Exam Syllabus Topics:

ISACA Advanced in AI Risk Sample Questions:

1. Which of the following is the MOST important consideration when managing changes to an AI model in production?

A) Expediting rollout of changes in production to ensure service continuity and minimize downtime
B) Conducting rigorous validation to assess effects on predictive accuracy and model bias
C) Allowing operational teams to adjust configuration parameters for real-time performance tuning
D) Implementing stringent approval processes for user access to new model functionalities

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

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

3. Which of the following would be of GREATEST concern to a risk practitioner reviewing the testing and validation of an AI-driven technical support system?

A) Inaccurate outputs resulting from model drift
B) Infrequent incorporation of updated training datasets
C) Excessive dependence on manual sampling
D) Insufficient encryption of data at rest and in transit

4. An organization is integrating AI systems into core business operations and has decided to establish a formal process to align AI initiatives with corporate values. Which of the following is the GREATEST benefit of this decision?

A) The transparency and explainability of AI model decisions is enhanced for all stakeholder groups.
B) Return on investment (ROI) for new AI services can be evaluated more accurately.
C) Executive support for technical training and upskilling related to AI can be more effectively obtained.
D) Ethical principles can be added to AI development and usage after deployment.

5. A risk practitioner reviews an AI model that ingests diverse external feeds and determines that their reliability is not consistent. Which of the following BEST mitigates this risk?

A) Updating to the latest model version to accurately reflect real-world data changes
B) Establishing data provenance and implementing stage gate quality reviews
C) Reducing the diversity of the external feeds and the number of classes
D) Weighting historical records over recent samples to limit induced variance

Solutions: