ISACA Advanced in AI Risk - AAIR Exam Practice Test

A. Forecasting industry-specific AI risk trends and projecting future financial and business risk

B. Comprehensive logging and documentation of unauthorized AI system access attempts

C. Early detection of latent vulnerabilities by identifying anomalous patterns within large datasets

D. Reduction of human involvement through automation of risk analyses and treatment decisions

A. Executive support for technical training and upskilling related to AI can be more effectively obtained.

B. Return on investment (ROI) for new AI services can be evaluated more accurately.

C. The transparency and explainability of AI model decisions is enhanced for all stakeholder groups.

D. Ethical principles can be added to AI development and usage after deployment.

A. Establish an ongoing review cadence and codify procedures for reassessment.

B. Centralize decision making and concentrate authority within executive leadership and technical owners.

C. Schedule annual compliance reviews and integrate audit findings into revision planning.

D. Implement systematic updates and emphasize alignment with emerging regulatory expectations.

A. Engage external providers to deliver learning content with periodic updates.

B. Incorporate the code of conduct into onboarding modules for new personnel.

C. Provide role-tailored education supplemented by scheduled refreshers.

D. Focus the training curriculum on compliance with AI-specific laws and regulations.

A. Performance metrics are frequently communicated to stakeholders.

B. Employees find the AI system easy to learn and use.

C. Access token runtime is logged and timestamped.

D. The AI system's decisions are explainable and fair.

A. Emphasize the generalization capability of algorithms.

B. Align algorithmic capabilities to intended use cases.

C. Prioritize cost reductions related to computational requirements.

D. Require the use of supervised learning for model training projects.

A. The use of synthetic data may lead to regulatory noncompliance.

B. The use of synthetic data may result in an increase in false negatives.

C. Synthetic data may be more susceptible to data poisoning attacks.

D. Synthetic data may not reflect the diversity of real-world data.

A. Customer dissatisfaction from operational delays

B. Greater likelihood of bias or inaccuracy in chatbot responses

C. Insufficient training datasets due to outdated or limited sample coverage

D. Unauthorized disclosure of sensitive records via insecure external connections

A. Routing escalations through a single point of contact and prohibiting disclosure of proprietary information

B. Creating a separate compliance program for AI obligations and maintaining distinct reporting channels

C. Retaining documentation that provides explainability for decisions and embedding controls in oversight processes

D. Restricting AI deployment to use cases with lower impact and delaying broader operational integration

A. Measuring intent-classification error rates and refining training datasets

B. Introducing explainable AI techniques and conducting periodic code reviews

C. Calculating precision and recall scores and increasing model temperature

D. Adopting vendor-recommended thresholds and conducting benchmarking