AI Regulatory Compliance CRAGE Practice Questions (Page 6)

Questions 26–30

1. 26application · medium

   A financial institution is preparing for an internal compliance audit of its credit-scoring AI model. The model was developed in-house and is used to make lending decisions. The audit team needs to verify compliance with the EU AI Act and GDPR. Which audit procedure is most essential to include?

   • ACheck that the model's predictions are accurate by comparing them to historical loan outcomes.
   • BConfirm that the model is deployed on a private cloud to ensure data security.
   • CInterview the data scientists to ask if they followed best practices during development.
   • DReview the model's technical documentation, including training data sources, feature importance, and testing results, and verify that a DPIA was completed.
   Reveal Solution Discussion Select an answer first
2. 27application · medium

   A retail company has implemented an AI system for dynamic pricing. The system is not classified as high-risk under the EU AI Act, but the company wants to ensure ongoing compliance with GDPR and internal governance policies. Which ongoing monitoring practice is most appropriate?

   • ASet up a daily automated check that verifies the model's accuracy against a holdout dataset.
   • BConduct a one-time compliance review at deployment and then rely on the model's stability.
   • CRequire the data science team to submit a monthly report on model performance to the CTO.
   • DSchedule periodic audits of the system's data processing activities and update the records of processing activities (RoPA) whenever new data sources are added.
   Reveal Solution Discussion Select an answer first
4. 28expert · medium

   A global e-commerce company uses an AI recommendation system that processes customer data across multiple jurisdictions. The system is not high-risk under the EU AI Act, but it is subject to GDPR and various US state privacy laws. The company is planning a compliance audit. The audit team has limited resources and must prioritize. Which approach is most effective?

   • APrioritize auditing the system's data processing activities against GDPR and the most restrictive US state laws, then apply those findings to other jurisdictions
   • BAudit only GDPR compliance because it is the most comprehensive regulation
   • CHire a third-party auditor to audit every jurisdiction separately
   • DDelay the audit until the EU AI Act is fully enforced
   Reveal Solution Discussion Select an answer first
5. 29expert · medium

   A government agency is deploying an AI system for public benefits eligibility. The system uses personal data and makes automated decisions. The agency must comply with GDPR and the EU AI Act. The system is high-risk. The agency has a limited budget and must choose between investing in bias mitigation or in transparency measures. Which choice is most appropriate?

   • AInvest in both bias mitigation and transparency, but prioritize bias mitigation because it addresses the highest risk of harm
   • BDelay both investments until the system is fully deployed
   • CInvest only in transparency because it is explicitly required by the EU AI Act
   • DInvest only in bias mitigation because transparency is not required for high-risk systems
   Reveal Solution Discussion Select an answer first
6. 30expert · medium

   A healthcare provider is using an AI system to prioritize organ transplant waiting lists. The system uses patient data and is high-risk under the EU AI Act. The provider is also subject to GDPR. The system has been criticized for potential bias against certain ethnic groups. The provider must address this issue while maintaining the system's utility. Which approach is most appropriate?

   • AConduct a fairness audit, involve diverse stakeholders, and adjust the model's decision criteria to reduce bias while preserving clinical utility
   • BReplace the AI system with a manual process to avoid bias
   • CIgnore the criticism because the system is approved by regulators
   • DRemove ethnicity data from the model to eliminate bias
   Reveal Solution Discussion Select an answer first