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Recently, there has been a lot of interest in ensuring algorithmic fairness in machine learning where the central question is how to prevent sensitive information (e.g.
A national map of the regional dialects of american english.(telsur project.) department of linguistics, university of pennsylvania, 1997
William Labov, Sharon Ash, and Charles Boberg · 1997
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Yelp dataset challenge, 2010
Yelp · 2010
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Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Lstm neural networks for language modeling
Martin Sundermeyer, Ralf Schlüter, and Hermann Ney · 2012
Earlier work this paper cites.
Speech recognition with deep recurrent neural networks
Alex Graves, Abdel-rahman Mohamed, and Geoffrey Hinton · 2013
Earlier work this paper cites.
Learning fair representations
Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork · 2013
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Certifying and removing disparate impact
Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian · 2015
Cited alongside, same era.
Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom · 2015
Cited alongside, same era.
User review sites as a resource for large-scale sociolinguistic studies
Dirk Hovy, Anders Johannsen, and Anders Søgaard · 2015
Cited alongside, same era.
Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai · 2016
Cited alongside, same era.
Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, Nati Srebro, et al · 2016
Cited alongside, same era.
Inherent trade-offs in the fair determination of risk scores
Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang · 2017
Later among the works it cites.
Fairness in criminal justice risk assessments: The state of the art
Richard Berk, Hoda Heidari, Shahin Jabbari, Michael Kearns, and Aaron Roth · 2018
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Fairness definitions explained
Sahil Verma and Julia Rubin · 2018
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A guide to deep learning in healthcare
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar, Volodymyr Kuleshov, Mark DePristo, Katherine Chou, Claire Cui, Greg Corrado, Sebastian Thrun, and Jeff Dean · 2019
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Hila Gonen and Yoav Goldberg · 2019
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Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2016
Cited alongside, same era.
Counterfactual fairness
Matt J Kusner, Joshua Loftus, Chris Russell, and Ricardo Silva · 2017
Cited alongside, same era.
Determine the gender of a name
Genderize.io
Cited in the paper.
Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang
Cited in the paper.
Learning gender-neutral word embeddings
Jieyu Zhao, Yichao Zhou, Zeyu Li, Wei Wang, and Kai-Wei Chang
Cited in the paper.
Reducing gender bias in word-level language models with a gender-equalizing loss function
Yusu Qian, Urwa Muaz, Ben Zhang, and Jae Won Hyun · 2019
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A framework for understanding unintended consequences of machine learning
Harini Suresh and John V Guttag · 2019
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