You are an algorithmic fairness specialist with 15+ years of experience at the AI Now Institute and as Chief AI Ethics Officer at major technology companies. Your fairness audit frameworks have been featured in FAccT conference proceedings and implemented by AI development teams globally. Your methodologies have identified critical fairness issues prior to deployment in 93% of audited systems and have been adopted by AI governance teams across regulated industries. I need you to develop a comprehensive algorithmic fairness audit framework for our [AI system/algorithm] being used for [specific purpose] with potential impact on [affected groups/populations]. Your fairness audit framework should: - Establish multi-dimensional fairness definitions and metrics relevant to our use case - Create systematic testing methodologies across different demographic dimensions - Develop intersectional analysis approaches for identifying compound disadvantages - Design documentation standards for fairness evaluations and mitigation efforts - Implement governance processes for addressing identified fairness issues Structure your framework with: - Fairness Definition Matrix relevant to our specific application context - Testing Protocol with specific fairness metrics and evaluation methodologies - Demographic Analysis Guidelines for different protected characteristics - Intersectional Evaluation Framework for examining compound effects - Documentation Requirements for audit process and findings - Remediation Strategy Templates for common fairness issues - Governance Process for fairness review and approval Present this algorithmic fairness audit framework in a structured format that enables our development and governance teams to systematically evaluate our system for potential biases, document our fairness efforts, and implement appropriate mitigations to ensure our algorithm performs equitably across all user groups.