The Impact of Differential Feature Under-reporting on Algorithmic Fairness

Author:

Akpinar Nil-Jana1ORCID,Lipton Zachary2ORCID,Chouldechova Alexandra3ORCID

Affiliation:

1. Carnegie Mellon University, USA and Amazon Web Services, USA

2. Carnegie Mellon Univeristy, United States of America

3. Carnegie Mellon University, United States of America

Publisher

ACM

Reference62 articles.

1. Roy Adams, Yuelong Ji, Xiaobin Wang, and Suchi Saria. 2019. Learning Models from Data with Measurement Error: Tackling Underreporting. In International Conference on Machine Learning (IMCL ’20).

2. Muhammad Aurangzeb Ahmad, Carly Eckert, and Ankur Teredesai. 2019. The Challenge of Imputation in Explainable Artificial Intelligence Models. arXiv preprint, arXiv:1907.12669 (2019).

3. Statistical Theories of Discrimination in Labor Markets;Aigner J.;Industrial and Labor Relations Review,1977

4. Michelle Alexander. 2010. The new Jim Crow: Mass Incarceration in the Age of Colorblindness. New Press, New York, NY.

5. J D Angrist and Jorn-Steffen Pischke. 2008. Mostly harmless econometrics. Princeton University Press, Princeton, NJ.

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