bias-fairness-assessment

What problem does it solve?

This Skill provides a framework for assessing the fairness of AI models, features, or datasets, identifying disparities and recommending mitigations to ensure equitable treatment.

Core Features & Use Cases

• Bias and Fairness Assessment: Evaluate AI for representational and allocative harms, disparate performance, and skewed refusals.
• Mitigation Recommendations: Propose data and representation fixes, reweighting, threshold adjustments, and more to address identified issues.
• Use Case: For a company developing an AI hiring tool, use this Skill to assess the tool's fairness across different demographic groups and propose improvements.

Quick Start

Run the bias-fairness-assessment skill on your AI model to evaluate for bias and fairness.