Fairness in Sequential Allocation

2/17/22 | 4:15pm | E25-111


 

 

 

 

Sid Banerjee

Associate Professor
Cornell


Abstract: In many settings, resources are allocated among people over time, without the use of monetary transfers: cloud resources among employees, food among food-banks, medical supplies between hospitals, funding between non-profit projects, etc. The underlying aim is to try and be ‘fair’ in these allocations…but what exactly do we mean?

Understanding fairness in decision-making is one of the most beautiful and yet urgent topics in OR/CS/controls today, with deep connections to market-design, optimization, and normative philosophy. In this talk, I will describe a foundational result of Varian’s that relates these approaches in one-shot decision-making settings, and that orients modern approaches for reasoning about these problems. Building on this, I will describe some of our efforts in extending these ideas to sequential settings, and in particular, focus on a new way of characterizing fundamental tradeoffs between fairness and efficiency in sequential resource allocation. I will illustrate the power of this approach with some work we have been doing with our local food-bank on providing decision-support tools for their mobile pantry, and outline some future directions for exploring tradeoffs between fairness, efficiency and information in more complex settings.

Bio: Sid Banerjee is an associate professor in the School of Operations Research at Cornell, working on topics at the intersection of data-driven decision-making, network algorithms and market design. His research is supported by grants from the NSF (including an NSF CAREER award), the ARL Network Sciences division, and Engaged Cornell. He received his PhD from the ECE Department at UT Austin, and was a postdoctoral researcher in the Social Algorithms Lab at Stanford. He also served as a technical consultant with the research science group at Lyft from 2014-18.

Event Time: 

2022 - 16:15