A financial institution is implementing Responsible AI governance across its enterprise AI deployments. The institution needs to ensure that AI models producing credit decisions do not exhibit unfair bias against protected demographic groups. Which Microsoft tool provides fairness assessment capabilities for AI models?
Select an answer to reveal the explanation.
Short Explanation
You need the Azure Responsible AI dashboard with Fairlearn integration because it provides fairness assessment metrics for machine learning models. Fairlearn checks predictions across demographic groups and flags disparities in error rates, false positive rates, and other performance metrics that could show discriminatory bias in credit decisions.
Full Explanation
The Azure Responsible AI dashboard with Fairlearn integration is correct because the dashboard integrates several open-source tools including Fairlearn, which provides fairness assessment metrics for machine learning models. Fairlearn evaluates model predictions across demographic groups, identifying disparities in error rates, false positive rates, and other performance metrics that could indicate discriminatory bias in credit decisions. Microsoft Purview Compliance Manager is wrong because it is used for regulatory compliance assessments and control tracking, not for analyzing model fairness metrics. Microsoft Sentinel UEBA is wrong because it analyzes user behavioral patterns for security threats, not AI model prediction fairness. Azure Policy for AI is wrong because it enforces infrastructure configuration standards; it does not analyze model outputs for demographic bias.