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ISACA AAIR Exam Syllabus Topics:

ISACA Advanced in AI Risk Sample Questions:

1. Which of the following is the BEST way to integrate AI risk management into operational procedures?

A) Require organization-wide training on AI legal and regulatory requirements.
B) Require AI risk committee approval for changes involving automation of manual tasks.
C) Introduce AI risk assessment stages throughout the development and deployment process.
D) Engage regular third-party audits of AI process and workflow documentation.

2. A credit-scoring AI solution exhibits steadily declining accuracy despite unchanged input distributions.
Which of the following should a risk practitioner consider to be the GREATEST risk?

A) Technical delays affecting credit score updates
B) Underfitting resulting from shortened training cycles
C) Increased model retraining costs
D) Concept drift leading to faulty decisions

3. An organization has deployed an AI system that initially performs well but whose outputs deteriorate over time despite stable input characteristics. Which of the following is the BEST course of action?

A) Focus efforts on dataset cleansing and documentation prior to further system updates.
B) Establish continuous performance monitoring and scheduled system recalibration.
C) Engage periodic external audits of model source code and implement peer code reviews.
D) Replace the system's predictive capability with static rule-based controls and fixed decision logic.

4. A risk practitioner learns that a credit-scoring AI system is exhibiting bias that cannot be eliminated through further training. Which of the following is the risk practitioner's BEST recommendation?

A) Source vendors for a new credit-scoring AI solution.
B) Take the system out of production to avoid harm and potential legal liability.
C) Apply compensating controls that generate offsetting biases in the opposite direction.
D) Request a risk acceptance from senior management.

5. Which of the following is the GREATEST risk when an organization lacks clearly defined accountability mechanisms for AI outputs and decisions?

A) Intellectual property exposure
B) Reduced availability
C) Legal liability
D) Ineffective model training

Solutions: