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ISACA AAIR Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Risk Governance and Framework Integration | 37% | - AI Ownership, Oversight, and Accountability - AI Models, Frameworks, Strategies, and Use Cases - AI Organizational Processes and Alignment |
| Topic 2: AI Risk Program Management | 42% | - AI governance communication and reporting - AI risk assessment and treatment strategies - AI risk monitoring and continuous improvement - Enterprise AI risk program design |
| Topic 3: AI Life Cycle Risk Management | - AI bias, drift, transparency, and control evaluation - AI model and data risk identification - AI development, deployment, and monitoring risks |
ISACA Advanced in AI Risk Sample Questions:
1. A risk practitioner discovers that autonomous agents have been creating temporary HR system identities.
Which of the following poses the GREATEST risk?
A) Ineffective credential management
B) Delays in breach identification and response
C) Increased staffing needs for human validation
D) Identities are not incorporated into the federated system
2. 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) Use unsupervised learning to identify hidden or complex discriminatory patterns in the dataset.
B) Define specific inclusivity goals and expand data to a broader range of sources.
C) Implement reporting for model drift and anomalous model decisions.
D) Notify stakeholders that the model may not always reflect standard loan approval thresholds.
3. Which of the following is MOST important when defining responsible roles for integrating third-party AI services into an organization's supply chain?
A) Mandating cross-functional AI training for third-party staff
B) Designating AI governance and risk ownership
C) Standardizing migration and data transfer protocols
D) Aligning organizational and third-party AI security policies
4. 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) Reducing the diversity of the external feeds and the number of classes
C) Weighting historical records over recent samples to limit induced variance
D) Updating to the latest model version to accurately reflect real-world data changes
5. 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) Concept drift leading to faulty decisions
B) Increased model retraining costs
C) Technical delays affecting credit score updates
D) Underfitting resulting from shortened training cycles
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: A |

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