Ai Ethics
Showing 12 of 12 projects
A curated list tracking current scary and unethical uses of AI to raise awareness of its societal misuses.
A curated list of practical resources for responsible machine learning, covering interpretability, governance, safety, and ethics.
An extensible open-source toolkit for detecting, mitigating, and explaining bias in machine learning datasets and models.
A curated collection of research papers, books, courses, and Python libraries for explainable AI (XAI) and machine learning interpretability.
A curated collection of AI guidelines, principles, ethics frameworks, regulations, and practical tools for responsible AI development.
An open-source toolkit for auditing bias and experimenting with fairness methods in machine learning models.
A curated list of resources for understanding, measuring, and mitigating fairness issues in artificial intelligence and machine learning systems.
A curated collection of papers, methods, critiques, and resources for Explainable AI (XAI) and Interpretable Machine Learning.
A Scala/Spark library for measuring fairness and mitigating bias in large-scale machine learning workflows.
A curated list of algorithms and academic papers for auditing black-box algorithms like recommendation systems and classifiers.
A tool for automatically detecting and suggesting mitigation for object, attribute, and geography-based biases in visual datasets.
A curated list of resources for tech workers to reduce technology's negative societal impacts through ethical practices.
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