Welcome to the AEQUITAS Framework for AI Fairness

The AEQUITAS Framework is an innovative approach designed to ensure fairness and trust in AI-based decision support systems. It proposes a controlled experimentation environment for developers and users to:

  • Assess bias in AI systems by identifying potential sources in data, algorithms, and result interpretation.

  • Offer effective methods and engineering guidelines to repair, and mitigate bias when possible.

  • Provide fairness-by-design guidelines, methodologies, and software engineering techniques to create new, bias-free systems.

The framework includes an experimentation environment that generates synthetic datasets with various features impacting fairness, allowing laboratory tests.

Real-world use cases in healthcare, human resources, and social challenges are also provided and discussed along with different solutions and comparison.

Note

This project is under active development.

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