Debiasing Embeddings for Reduced Gender Bias in Text Classification

Putting fairness principles into practice: Challenges, metrics, and improvements

Original

Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathan Bischof, and Ed H Chi. 2019 · 1901

Earlier work this paper cites.

Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them

Original

Hila Gonen and Yoav Goldberg. 2019 · 1903

Earlier work this paper cites.

Efficient estimation of word representations in vector space

Original

Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013

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Glove: Global vectors for word representation

Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014

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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 · 2016

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Equality of opportunity in supervised learning

Moritz Hardt, Eric Price, Nati Srebro, et al. 2016 · 2016

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Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017

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Measuring and mitigating unintended bias in text classification

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Translation tutorial: 21 fairness definitions and their politics

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Bias in bios: A case study of semantic representation bias in a high-stakes setting

Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, and Adam Tauman Kalai. 2019 · 2019

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A comparative study of fairness-enhancing interventions in machine learning

Sorelle A Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam Choudhary, Evan P Hamilton, and Derek Roth. 2019 · 2019

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Counterfactual fairness in text classification through robustness

Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, H Chi, and Alex Beutel. 2019 · 2019

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