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ISACA Advanced in AI Risk Sample Questions:

1. Which of the following is the PRIMARY purpose of maintaining comprehensive model cards and documentation?

A) Preserving audit trails
B) Justifying model use cases
C) Providing model transparency
D) Listing technical specifications

2. A risk practitioner is evaluating AI model cards and documentation prior to deployment. Which of the following represents the GREATEST risk to enterprise AI governance?

A) Inadequate explainability
B) Delays in regulatory filings
C) Decentralized version control
D) Overly detailed technical specifications

3. An organization deploys an autonomous system that makes decisions affecting compliance with regulations.
If those decisions could potentially produce regulatory breaches, which of the following BEST helps to manage associated liability exposures?

A) Routing escalations through a single point of contact and prohibiting disclosure of proprietary information
B) Retaining documentation that provides explainability for decisions and embedding controls in oversight processes
C) Creating a separate compliance program for AI obligations and maintaining distinct reporting channels
D) Restricting AI deployment to use cases with lower impact and delaying broader operational integration

4. A risk practitioner is concerned that an AI model's responses have become more inaccurate over time, leading to diminished customer trust. Which of the following should the risk practitioner recommend be done FIRST?

A) Take the model offline and perform a full backup.
B) Determine the impact on critical features and model outputs.
C) Revise validation processes to add more review cycles.
D) Fully retrain the model with a more recent dataset.

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

Solutions: