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ISACA AAIR Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Regulatory and Compliance Requirements | - Global AI regulatory landscape
|
| Topic 2: Ethics, Privacy, and Responsible AI | - Ethical AI principles and compliance
|
| Topic 3: AI Lifecycle Controls | - Controls across AI development lifecycle
|
| Topic 4: AI Governance and Strategy | - AI governance frameworks and organizational oversight
|
| Topic 5: AI Risk Management | - Risk identification and assessment for AI systems
|
ISACA Advanced in AI Risk Sample Questions:
1. An election oversight body is considering the use of AI to identify irregularities in voting patterns. Which of the following is the MOST important risk to evaluate?
A) Distrust of AI among political interest groups
B) Amplification of biases in historical data
C) Susceptibility to contextual drift
D) Identification of voter locations
2. An organization plans to deploy a generative AI system that processes sensitive personal data across multiple countries with varying privacy laws. Which of the following is the BEST course of action to manage legal and regulatory exposure?
A) Tailor organizational controls to relevant statutory requirements and preserve audit trails to prove adherence.
B) Prioritize protection of intellectual property and restrict disclosure of model operations to safeguard assets.
C) Adopt uniform global policies and implement strong encryption of personal data for all cross-border transfers.
D) Remediate regulatory gaps in each jurisdiction through iterative post-deployment updates and model retraining.
3. 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) Ethical principles can be added to AI development and usage after deployment.
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) The transparency and explainability of AI model decisions is enhanced for all stakeholder groups.
4. An organization deploys an AI credit scoring model trained on historical financial data that underrepresents certain demographic groups. Which of the following is the risk practitioner's BEST recommendation to mitigate this risk?
A) Notify stakeholders that the model may not always reflect standard loan approval thresholds.
B) Define specific inclusivity goals and expand data to a broader range of sources.
C) Use unsupervised learning to identify hidden or complex discriminatory patterns in the dataset.
D) Implement reporting for model drift and anomalous model decisions.
5. A risk practitioner is assessing risk in a newly implemented AI system integrated into an organization's business processes. Which of the following is the MOST important consideration for the risk practitioner?
A) Criticality and impact of decision-making driven by the AI system
B) AI expertise within the organization's risk management function
C) Level of existing business process automation prior to AI adoption
D) Escalation and approval protocols for AI mitigation measures
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: A |
