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Poster
How do fair decisions fare in long-term qualification?
Xueru Zhang · Ruibo Tu · Yang Liu · Mingyan Liu · Hedvig Kjellstrom · Kun Zhang · Cheng Zhang

Wed Dec 09 09:00 AM -- 11:00 AM (PST) @ Poster Session 3 #869

Although many fairness criteria have been proposed for decision making, their long-term impact on the well-being of a population remains unclear. In this work, we study the dynamics of population qualification and algorithmic decisions under a partially observed Markov decision problem setting. By characterizing the equilibrium of such dynamics, we analyze the long-term impact of static fairness constraints on the equality and improvement of group well-being. Our results show that static fairness constraints can either promote equality or exacerbate disparity depending on the driving factor of qualification transitions and the effect of sensitive attributes on feature distributions. We also consider possible interventions that can effectively improve group qualification or promote equality of group qualification. Our theoretical results and experiments on static real-world datasets with simulated dynamics show that our framework can be used to facilitate social science studies.

Author Information

Xueru Zhang (University of Michigan)
Ruibo Tu (KTH Royal Institute of Technology)
Yang Liu (UC Santa Cruz)
Mingyan Liu (University of Michigan, Ann Arbor)

Mingyan Liu (M'00, SM'11, F'14) received her Ph.D. Degree in electrical engineering from the University of Maryland, College Park, in 2000. She is currently a professor with the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor, and the Peter and Evelyn Fuss Chair of Electrical and Computer Engineering. Her research interests are in optimal resource allocation, performance modeling, sequential decision and learning theory, game theory and incentive mechanisms, with applications to large-scale networked systems, cybersecurity and cyber risk quantification. She has served on the editorial boards of IEEE/ACM Trans. Networking, IEEE Trans. Mobile Computing, and ACM Trans. Sensor Networks. She is a Fellow of the IEEE and a member of the ACM.

Hedvig Kjellstrom (KTH Royal Institute of Technology)
Kun Zhang (CMU)
Cheng Zhang (Microsoft Research, Cambridge, UK)

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