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ISACA AAIA Exam Syllabus Topics:

Topic
Details

Topic 1

• AI GOVERNANCE AND RISK: It encompasses understanding different AI models and their life cycles, guiding AI strategy, defining roles and policies, managing AI-related risks, overseeing data privacy and governance, and ensuring adherence to ethical practices, standards, and regulations.

Topic 2

• AI Operations: It covers managing AI-specific data needs—including collection, quality, security, and classification—applying development lifecycle methodologies with privacy and security by design, change and incident management, testing AI solutions, identifying AI-related threats and vulnerabilities, and supervising AI deployments.

Topic 3

• Auditing Tools and Techniques: This section of the exam measures the skills of AI auditors and centers on auditing AI systems using appropriate tools and methods. It includes audit planning and design, sampling methodologies specific to AI, collecting audit evidence, using data analytics for quality assurance, and producing AI audit outputs and reports, including follow-up and quality control measures.

 

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ISACA Advanced in AI Audit Sample Questions (Q75-Q80):

NEW QUESTION # 75
Which of the following correctly summarizes the conclusions of the model card excerpt provided?
Model Card - Electrical Grid Predictive Maintenance Model
Model Information:
Description: AI model designed to predict maintenance needs for electrical grid components, reduce unplanned downtime, and improve grid reliability.
Inputs: Real-time sensor data, historical maintenance records, and operational logs.
Outputs: Maintenance needs predictions for 60 & 90 days.Evaluation:
Approach: Cross-validation and validation of accuracy, precision, and recall.
Results: Accuracy 72%; Precision 60%; Recall 95%; F1 76%

• A. The electrical grid uptime is expected to be 72% of the time.
• B. F1 indicates that the model identifies true maintenance needs 76% of the time.
• C. Grid failure is predicted to occur after 90 days.
• D. The AI model correctly predicts maintenance needs 95% of the time.

Answer: B

 

NEW QUESTION # 76
Which of the following do supervised AI learning models PRIMARILY use to train algorithms?

• A. Unlabeled data sets
• B. Randomized data sets
• C. Clustered data sets
• D. Labeled data sets

Answer: D

 

NEW QUESTION # 77
Which of the following is MOST important for an IS auditor to review during an AI system audit in order to determine compliance with intellectual property and data rights?

• A. Data performance metrics
• B. Model runtime efficiency logs
• C. Data usage agreements
• D. Use of open-source intellectual property

Answer: C

 

NEW QUESTION # 78
A car manufacturer uses an AI model to predict maintenance needs for its vehicles. Which of the following techniques can an IS auditor apply to MOST effectively verify the AI model's decisions to stakeholders?

• A. Using local interpretable model-agnostic explanation (LIME) to analyze how specific features contribute to predictions
• B. Using K-means algorithms to group vehicles based on mileage or engine temperature for maintenance patterns
• C. Utilizing support vector machines (SVM) to classify vehicles based on maintenance urgency
• D. Using neural network visualization to show how the AI model processes data through its layers

Answer: A

 

NEW QUESTION # 79
An organization uses an AI image generation platform to create promotional materials. An IS auditor identifies that the platform includes copyrighted images in its training dat a. Which of the following is the auditor's BEST recommendation to address this issue?

• A. Use a platform that certifies the provenance and licensing of its training data.
• B. Label all AI-generated images to disclaim the possibility of third-party content.
• C. Implement a manual review process to ensure no copyrighted images are used in generated outputs.
• D. Suspend the use of the platform until the training data is sanitized.

Answer: A

 

NEW QUESTION # 80
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