Date: Wednesday, October 20th, 2021
9:00 am – 10:00 am Pacific Time
12:00 pm – 1:00 pm Eastern Time
Location: Weekly Seminar, Zoom
Title: Predictions, Promises and Pseudomarkets – Reasoning about Fairness in Sequential Decision-Making
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 sequential decision-making is one of the most beautiful and relevant topics 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, and that (for me) serves as a lodestar for reasoning about these problems. Building on this, I will describe some of our work in understanding pseudo-market mechanisms and online optimization approaches for fair allocation. Time-permitting, I will try and discuss some of my concerns with these approaches, and where I think we should be going in this area.
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.