Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits

Author:

Deng Wesley Hanwen1,Nagireddy Manish2,Lee Michelle Seng Ah3,Singh Jatinder3,Wu Zhiwei Steven2,Holstein Kenneth2,Zhu Haiyi2

Affiliation:

1. Human-Computer Interaction Institute, Carnegie Mellon University, USA

2. Carnegie Mellon University, USA

3. University of Cambridge, United Kingdom

Funder

Carnegie Mellon University Block Center for Technology and Society Award

Aviva and the UK Engineering and Physical Science Research Council

Jacob Foundation for CERES network

National Science Foundation

Publisher

ACM

Reference114 articles.

1. 2017. Facets - visualizations for ML datasets.arXiv:1810.01943https://pair-code.github.io/facets/ 2017. Facets - visualizations for ML datasets.arXiv:1810.01943https://pair-code.github.io/facets/

2. 2021. People AI Guidebook. (2021). https://pair.withgoogle.com/guidebook/ 2021. People AI Guidebook. (2021). https://pair.withgoogle.com/guidebook/

3. Martín Abadi and Ashish Agarwal et al.2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https://www.tensorflow.org/ Software available from tensorflow.org. Martín Abadi and Ashish Agarwal et al.2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https://www.tensorflow.org/ Software available from tensorflow.org.

4. Julius  A Adebayo 2016. FairML: ToolBox for diagnosing bias in predictive modeling. Ph. D. Dissertation . Massachusetts Institute of Technology . Julius A Adebayo 2016. FairML: ToolBox for diagnosing bias in predictive modeling. Ph. D. Dissertation. Massachusetts Institute of Technology.

5. Yongsu Ahn and Yu-Ru Lin . 2019 . Fairsight: Visual analytics for fairness in decision making . IEEE transactions on visualization and computer graphics 26, 1(2019), 1086–1095. Yongsu Ahn and Yu-Ru Lin. 2019. Fairsight: Visual analytics for fairness in decision making. IEEE transactions on visualization and computer graphics 26, 1(2019), 1086–1095.

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