mirianfsilva/ai-fairness
Notes, references and materials on AI Fairness that I found useful and helped me in my academic research.
This project offers a curated collection of resources, readings, and code examples for understanding and addressing bias in artificial intelligence. It helps researchers and practitioners evaluate AI systems for fairness, identify sources of bias in data and algorithms, and explore methods to mitigate discriminatory outcomes. The resources cover academic papers, books, blog posts, and toolkits, providing a comprehensive guide for those working to build more ethical AI.
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Use this if you are an academic researcher, data scientist, or policy maker seeking to deepen your knowledge of AI fairness, understand its theoretical underpinnings, and explore practical mitigation techniques.
Not ideal if you are looking for an out-of-the-box software solution for a specific, immediate AI fairness problem without wanting to engage with the underlying research.
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May 30, 2025
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