List of Interesting Papers

Prospective Reading Group Papers

Winter 2020

The general topic is fairness, drawing upon work from economics, HCI, machine learning, social choice, and any other relevant fields.

February 28th:

Sam Corbett-Davies, Sharad Goel: The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning

D. Parkes and R. Vohra, 2019, Algorithmic and Economic Perspectives on Fairness

March 6th:

MK Lee, A Jain, HJ Cha, S Ojha, D Kusbit, (2019). Procedural justice in algorithmic fairness: Leveraging transparency and outcome control for fair algorithmic mediation, In CSCW 2019.

M. De-Arteaga, R. Fogliato, and A. Chouldechova. “A case for humans-in-the-loop: decisions in the presence of erroneous algorithmic scores”. (CHI 2020)

March 20th:

C. Dimitrakakis, Y. Liu, D. Parkes, and G. Radanovic, 2019, Bayesian Fairness, In AAAI 2019.

Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt: Delayed Impact of Fair Machine Learning


Fairness Towards Groups of Agents in the Allocation of Indivisible Items Benabbou, Chakraborty, Elkind, Zick. The 28th International Joint Conference on Artificial Intelligence (IJCAI’19), Aug 2019, MACAO, China

Kenneth Holstein, Jennifer Wortman Vaughan, Hal Daumé III, Miroslav Dudík, and Hanna Wallach. 2019. Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need?. In CHI Conference on Human Factors in Computing Systems Proceedings (CHI 2019), May 4–9, 2019, Glasgow, Scotland UK. ACM, New York, NY, USA, 16 pages.

Veale, M., Van Kleek, M., & Binns, R. (2018). Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making. In ACM Conference on Human Factors in Computing Systems - CHI’18. Montréal, Canada.

Woodruff, A., Fox, S. E., Rousso-Schindler, S., & Warshaw, J. (2018). A Qualitative Exploration of Perceptions of Algorithmic Fairness. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18 (pp. 1–14). New York, New York, USA: ACM Press.

D. Mulligan, J Kroll, N Kohli, R Wong, (2019). T his thing called fairness: Disciplinary confusion realizing a value in technology, In CSCW 2019.

Bo Cowgill, Catherine Tucker: Economics, Fairness and Algorithmic Bias

Anja Lambrecht, Catherine Tucker: Algorithmic Bias? An Empirical Study into Apparent Gender-Based Discrimination in the Display of STEM Career Ads

Susan Athey, Kevin Bryan, Joshua Gans: The Allocation of Decision Authority to Human and Artificial Intelligence

Pass, Rafael, and Elaine Shi. "Fruitchains: A fair blockchain." Proceedings of the ACM Symposium on Principles of Distributed Computing. 2017.

Gürcan, Önder, Antonella Del Pozzo, and Sara Tucci-Piergiovanni. "On the bitcoin limitations to deliver fairness to users." OTM Confederated International Conferences" On the Move to Meaningful Internet Systems". Springer, Cham, 2017.

Celis, L. Elisa, Lingxiao Huang, and Nisheeth K. Vishnoi. "Multiwinner voting with fairness constraints." arXiv preprint arXiv:1710.10057 (2017).

Winter 2018

We had discussed looking at papers related to group reward division, "split-a-dollar" games and contest design.

March 27, 2018

Which Is the Fairest (Rent Division) of Them All? Ya'akov (Kobi) Gal, Moshe Mash, Ariel D. Procaccia, and Yair Zick. Journal of the ACM 64(6), article 39, Nov 2017.

March 20, 2018


Effective Sampling and Learning for Mallows Models with Pairwise-Preference Data
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An optimal single-winner preferential voting system based on game theory
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A behavioral perspective on social choice
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The Computational Rise and Fall of Fairness
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Properties of Multiwinner Voting Rules
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Typical-Case Challenges to Complexity Shields That Are Supposed to Protect Elections Against Manipulation and Control
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Structure in Dichotomous Preferences
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Truthfulness, Proportional Fairness, and Efficiency
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Feel free to add papers that you would like to be discussed or you think may be of interest of the group.

Past Reading List


  • Reading group begins soon


-- HadiHosseini - 02 Jun 2012
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