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CIS Seminar: “Challenges of Incorporating Algorithms into Decision Making: Fairness, Welfare and Disparate Interactions”

December 1, 2020 at 3:00 PM - 4:00 PM

Algorithms have entered the center of many decision making processes, either by providing predictions or assessments to facilitate human decision making or, in some scenarios, suggesting decisions directly. More and more attention has been placed to ensure algorithms satisfy some desirable notion of fairness, which is an important step forward. In this talk, I will discuss the importance of examining algorithmic decision-making and algorithm-facilitated decision making in the broader context of intended applications and in the lens of human-algorithm interactions. I will first present a welfare-based analysis of fair classification algorithms to assess the welfare impact of fairness-constrained classification algorithms in the context of financial lending. Our analysis shows that applying stricter  fairness constraints in the algorithms can worsen welfare outcomes of all groups. Then, I’ll discuss a sequence of controlled human-subject experiments studying how the interactions between people and algorithms influence human decision making. In our experiments in two contexts (pretrial release and financial lending), when presented with algorithmic risk assessments, participants exhibited additional bias in their decisions and showed a change in their decision-making process by increasing risk aversion.
This talk is based on joint works with Lily Hu and Ben Green.

Yiling Chen

Computer Science Dept. Harvard University

Yiling Chen is a Gordon McKay Professor of Computer Science at Harvard University. She received her Ph.D. in Information Sciences and Technology from the Pennsylvania State University. Prior to working at Harvard, she spent two years at Yahoo! Research in New York City. Her research focuses on topics in the intersection of computer science, economics and other social sciences. She was a recipient of NSF Career award and and The Penn State Alumni Association Early Career Award, and was selected by IEEE Intelligent Systems as one of “AI’s 10 to Watch” in 2011. Her work received best paper awards at ACM EC, AAMAS, ACM FAccT and ACM CHI conferences. She has co-chaired the 2013 Conference on Web and Internet Economics (WINE’13), the 2016 ACM Conference on Economics and Computation (EC’16) and the 2018 AAAI Conference on Human Computation and Crowdsourcing (HCOMP’18) and has served as an associate editor for several journals.


December 1, 2020
3:00 PM - 4:00 PM
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Computer and Information Science
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