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ISACA Advanced in AI Audit Questions 161–165 (page: 34)

Updated On: 12-Sep-2026

Which of the following evaluation criteria is the HIGHEST priority when auditing an organization's management of AI vendors?

  1. Model interpretability for explainable AI decisions and audit trails
  2. Supplier contracts generated via natural language processing (NLP)
  3. Service level objective used to measure AI vendor performance
  4. Hardware requirements for efficient AI model interference

Answer(s): C

Explanation:

Service level objectives define measurable performance, availability, and reliability expectations for the AI vendor, providing the primary basis for governance, oversight, and accountability in vendor management.



A health organization has deployed an AI model to analyze chest X-rays. The model reports high accuracy, but thresholds for classifying results are unclear and performance is not broken down by different patient demographics.
Which of the following is the PRIMARY reason to avoid relying only on overall accuracy to evaluate this model?

  1. The model may perform poorly for certain patient groups, leading to hidden fairness or safety risk.
  2. Performance may vary across demographic subgroups, requiring stratified evaluation.
  3. A high accuracy score always indicates low false positives and false negatives.
  4. Accuracy can only be calculated on structured tabular datasets, not medical images.

Answer(s): A

Explanation:

Overall accuracy can mask poor performance on specific demographic groups, which can introduce significant fairness and patient safety risks if the model underperforms for certain populations.



An IS auditor is planning for an audit of an organization’s use of AI to screen applicants for open positions.
Which of the following is MOST important to include within the audit scope?

  1. Historical hiring trends within the organization
  2. Detailed code review of AI models
  3. Sources of data used for candidate evaluation
  4. Retention of data from candidates who were not selected

Answer(s): C

Explanation:

The data sources used for candidate evaluation directly influence model behavior and potential bias, making them critical to assess for fairness, legality, and compliance in AI-driven hiring decisions.



Which of the following is the GREATEST risk when an organization uses publicly available social media data to train its AI model without obtaining explicit user consent?

  1. Data with questionable labelling
  2. Introduction of inaccurate and incomplete data
  3. User distrust caused by lack of transparency in AI model training
  4. Violation of data privacy regulations leading to legal penalties

Answer(s): D

Explanation:

Using personal data without explicit consent can violate data privacy laws and regulations, exposing the organization to significant legal penalties and compliance risks.



An IS auditor identified that an AI model was optimized to approve more loans to meet growth targets, which led to a rise in defaults and expected losses.
Which action will BEST address this situation?

  1. Require developers to adopt a model scorecard.
  2. Align model reward function with long-term risk metrics.
  3. Add more recent loan application data to retrain the model.
  4. Decrease the acceptance threshold used by the model.

Answer(s): B

Explanation:

The issue stems from misaligned optimization objectives, where the model prioritizes short-term approvals over long-term credit risk. Aligning the reward function with long-term risk metrics ensures decisions balance growth with sustainable risk outcomes.



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