Putting Fairness Principles into Practice

Author:

Beutel Alex1,Chen Jilin2,Doshi Tulsee2,Qian Hai2,Woodruff Allison2,Luu Christine2,Kreitmann Pierre3,Bischof Jonathan4,Chi Ed H.2

Affiliation:

1. Google, New York, NY, USA

2. Google, Mountain View, CA, USA

3. Google, San Bruno, CA, USA

4. Google, Seattle, WA, USA

Publisher

ACM

Reference38 articles.

1. Alekh Agarwal Alina Beygelzimer Miroslav Dud'ik John Langford and Hanna M. Wallach. 2018. A Reductions Approach to Fair Classification. CoRR Vol. abs/1803.02453 (2018). arxiv: 1803.02453 http://arxiv.org/abs/1803.02453 Alekh Agarwal Alina Beygelzimer Miroslav Dud'ik John Langford and Hanna M. Wallach. 2018. A Reductions Approach to Fair Classification. CoRR Vol. abs/1803.02453 (2018). arxiv: 1803.02453 http://arxiv.org/abs/1803.02453

2. Hana Ajakan Pascal Germain Hugo Larochelle Francc ois Laviolette and Mario Marchand. 2014. Domain-Adversarial Neural Networks. CoRR Vol. abs/1412.4446 (2014). arxiv: 1412.4446 http://arxiv.org/abs/1412.4446 Hana Ajakan Pascal Germain Hugo Larochelle Francc ois Laviolette and Mario Marchand. 2014. Domain-Adversarial Neural Networks. CoRR Vol. abs/1412.4446 (2014). arxiv: 1412.4446 http://arxiv.org/abs/1412.4446

3. Y Bechavod and K Ligett. 2017. Penalizing unfairness in binary classification. arXiv preprint arXiv:1707.00044 (2017). Y Bechavod and K Ligett. 2017. Penalizing unfairness in binary classification. arXiv preprint arXiv:1707.00044 (2017).

4. Alex Beutel Jilin Chen Zhe Zhao and Ed H. Chi. 2017a. Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations. CoRR Vol. abs/1707.00075 (2017). arxiv: 1707.00075 http://arxiv.org/abs/1707.00075 Alex Beutel Jilin Chen Zhe Zhao and Ed H. Chi. 2017a. Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations. CoRR Vol. abs/1707.00075 (2017). arxiv: 1707.00075 http://arxiv.org/abs/1707.00075

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