"Mitigating Bias in Algorithmic Hiring: Evaluating Claims and Practices."

Manish Raghavan, Solon Barocas, Jon Kleinberg, and Karen Levy. In Proceedings of the 2020 ACM Conference on Fairness, Accountability, and Transparency, New York, NY: January 2020. Download Paper.

"Roles for Computing in Social Change."

Rediet Abebe, Solon Barocas, Jon Kleinberg, Karen Levy, Manish Raghavan, and David G. Robinson. In Proceedings of the 2020 ACM Conference on Fairness, Accountability, and Transparency, New York, NY: January 2020. Download Paper.

"The Hidden Assumptions Behind Counterfactual Explanations and Principal Reasons."

Solon Barocas, Andrew D. Selbst, and Manish Raghavan. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, New York, NY: January 2020. Download Paper.

"Challenges for Mitigating Bias in Algorithmic Hiring."

Manish Raghavan, and Solon Barocas. In The Brookings Institution’s Artificial Intelligence and Emerging Technology (AIET) Initiative, Washington, DC: December 2019.

"Hiring Under Uncertainty."

Manish Purohit, Sreenivas Gollapudi, and Manish Raghavan. In Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA: June 2019. Supplementary Material. Download Paper.

"The Externalities of Exploration and How Data Diversity Helps Exploitation."

Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, and Zhiwei Steven Wu. In Proceedings of the 31st Conference on Learning Theory, edited by Philippe Rigollet, Sébastien Bubeck, and Vianney Perchet. Stockholm, Sweden: July 2018. Download Paper.