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Machine learning (ML) models are increasingly used for high-stake applications that can greatly impact people's lives.
Machine Bias — ProPublica
Julia Angwin, Jeff Larson, Surya Mattu, and Lauren Kirchner · 2016
Earlier work this paper cites.
Equality of Opportunity in Supervised Learning
Moritz Hardt, Eric Price, and Nathan Srebro · 2016
Earlier work this paper cites.
Optimized Pre-Processing for Discrimination Prevention
Flavio Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, and Kush R Varshney · 2017
Earlier work this paper cites.
A Convex Framework for Fair Regression
Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth · 2017
Earlier work this paper cites.
Amazon scraps secret AI recruiting tool that showed bias against women
Jeffrey Dastin · 2018
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Matt J. Kusner, Joshua R. Loftus, Chris Russell, and Ricardo Silva · 2018
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Path-Specific Counterfactual Fairness
Silvia Chiappa and Thomas P. S. Gillam · 2018
Earlier work this paper cites.
Mitigating Unwanted Biases with Adversarial Learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell · 2018
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Fairness-aware Classification: Criterion, Convexity, and Bounds
Yongkai Wu, Lu Zhang, and Xintao Wu · 2018
Earlier work this paper cites.
Rachel K. E. Bellamy, Kuntal Dey, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, Seema Nagar, Karthikeyan Natesan Ramamurthy, John Richards, Diptikalyan Saha, Prasanna Sattigeri, Moninder Singh, Kush R. Varshney, and Yunfeng Zhang · 2018
Cited alongside, same era.
Exploiting reject option in classification for social discrimination control
F. Kamiran, Sameen Mansha, Asim Karim, and X. Zhang · 2018
Cited alongside, same era.
Millions of black people affected by racial bias in health-care algorithms
Heidi Ledford · 2019
Cited alongside, same era.
Understanding the Origins of Bias in Word Embeddings
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson, and Richard Zemel · 2019
Cited alongside, same era.
https://blog.google/technology/ai/responsible-ai-principles/, June 2019
Responsible AI: Putting our principles into action · 2019
Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI
Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, and Hanna Wallach · 2020
Later among the works it cites.
Fairway: A way to build fair ML software
Joymallya Chakraborty, Suvodeep Majumder, Zhe Yu, and Tim Menzies · 2020
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A Responsible Machine Learning Workflow with Focus on Interpretable Models, Post-hoc Explanation, and Discrimination Testing
Navdeep Gill, Patrick Hall, Kim Montgomery, and Nicholas Schmidt · 2020
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https://ffiec.cfpb.gov/data-browser/data/2020?category=states
HMDA Data Browser · 2020
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A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan · 2021
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Cited alongside, same era.
The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems
Raja Chatila and John C. Havens · 2019
Cited alongside, same era.
Building trust in human-centric AI
Stephanie Weiser · 2019
Cited alongside, same era.
https://2019.ase-conferences.org/home/explain-2019
EXPLAIN 2019 - ASE 2019 · 2019
Cited alongside, same era.
Aequitas: A Bias and Fairness Audit Toolkit
Pedro Saleiro, Benedict Kuester, Loren Hinkson, Jesse London, Abby Stevens, Ari Anisfeld, Kit T. Rodolfa, and Rayid Ghani · 2019
Cited alongside, same era.
Black Loans Matter: Fighting Bias for AI Fairness in Lending
Mark Weber, Mikhail Yurochkin, Botros Sherif, and Markov Vanio
Cited in the paper.
https://gulfnews.com/technology/microsoft-trust-in-fate-to-keep-ai-safe-1.2289745
Microsoft trust in FATE to keep AI safe
Cited in the paper.
Facebook says it has a tool to detect bias in its artificial intelligence
Dave Gershgorn
Cited in the paper.
Using Adversarial Debiasing to Remove Bias from Word Embeddings
Dana Kenna · 2021
Closest in time.
Bias in machine learning software: Why? how? what to do?
Joymallya Chakraborty, Suvodeep Majumder, and Tim Menzies · 2021
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Predictably Unequal? the Effects of Machine Learning on Credit Markets
Andreas Fuster, Paul Goldsmith-Pinkham, Tarun Ramadorai, and Ansgar Walther · 2021
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Algorithmic Fairness in Mortgage Lending: From Absolute Conditions to Relational Trade-offs
Michelle Seng Ah Lee and Luciano Floridi · 2021
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