Cynthia Rudin
Cynthia Diane Rudin (born 1976) is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning. She is the director of the Interpretable Machine Learning Lab at Duke University, where she is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics and bioinformatics. In 2022, she won the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI) for her work on the importance of transparency for AI systems in high-risk domains.
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1
Why Are We Using Black Box Models in AI When We Don’t Need To? A Lesson From An Explainable AI Competition by Cynthia Rudin, Joanna Radin
Published 2019-11-01Get full text
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2
Broader Issues Surrounding Model Transparency in Criminal Justice Risk Scoring by Cynthia Rudin, Caroline Wang, Beau Coker
Published 2020-04-01Get full text
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Prediction, Machine Learning, and Individual Lives: an Interview with Matthew Salganik by Matthew Salganik, Lauren Maffeo, Cynthia Rudin
Published 2020-07-01Get full text
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The Age of Secrecy and Unfairness in Recidivism Prediction by Cynthia Rudin, Caroline Wang, Beau Coker
Published 2020-04-01Get full text
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Data Scientists Discuss AI Risks and Opportunities by David Banks, Gerard de Melo, Sam (Xinwei) Gong, Yongchan Kwon, Cynthia Rudin
Published 2024-08-01Get full text
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Multi-site validation of an interpretable model to analyze breast masses. by Luke Moffett, Alina Jade Barnett, Jon Donnelly, Fides Regina Schwartz, Hari Trivedi, Joseph Lo, Cynthia Rudin
Published 2025-01-01Get full text
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Multi-site validation of an interpretable model to analyze breast masses by Luke Moffett, Alina Jade Barnett, Jon Donnelly, Fides Regina Schwartz, Hari Trivedi, Joseph Lo, Cynthia Rudin
Published 2025-01-01Get full text
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