disaggregated-evaluation

What problem does it solve?

This Skill addresses the critical need to evaluate AI model performance not just overall, but specifically across different demographic subgroups, ensuring fairness and identifying potential biases.

Core Features & Use Cases

• Disaggregated Performance Metrics: Analyze model accuracy, precision, recall, etc., for various demographic segments.
• Bias Detection: Identify performance disparities that may indicate unfair treatment of certain groups.
• Compliance Assessment: Helps meet regulatory requirements like the EU AI Act's Art. 10 and Art. 15 by providing evidence of fair AI system operation.
• Use Case: A financial institution uses this Skill to check if their loan approval model performs equally well for applicants of different ethnicities and genders, flagging any significant performance gaps.

Quick Start

Use the disaggregated-evaluation skill to assess model performance across different demographic subgroups.