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ISACA Advanced in AI Risk Sample Questions:

1. An organization uses multiple external data sources to train its AI models. Which of the following is the risk practitioner's BEST recommendation to protect the organization from data poisoning attacks?

A) Continuous monitoring and anomaly detection for data ingestion pipelines
B) Data integrity reviews in response to indications that significant model drift has occurred
C) Enhanced regularization and training techniques to limit the influence of anomalies
D) Stringent controls over model code and deployment artifacts

2. After which of the following events is it MOST important to update risk ratings?

A) Discovery of discriminatory outputs from an AI system
B) Creation of a new AI risk oversight committee
C) Addition of new metrics tracked by automated monitoring
D) Vulnerability patch deployment for an AI system

3. Which of the following is the GREATEST risk when an organization relies only on adversarial training to protect a private AI model in a testing environment?

A) Inefficient model training cycles
B) Overfitting to limited datasets
C) Presence of unaddressed system vulnerabilities
D) Increased likelihood of exposing proprietary algorithms

4. 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) Remediate regulatory gaps in each jurisdiction through iterative post-deployment updates and model retraining.
C) Adopt uniform global policies and implement strong encryption of personal data for all cross-border transfers.
D) Prioritize protection of intellectual property and restrict disclosure of model operations to safeguard assets.

5. Which of the following poses the GREATEST challenge when performing root cause analysis for incidents involving AI systems and data?

A) Automation bias
B) Unclear system objectives
C) Lack of transparency
D) Privacy compliance

Solutions: