Visit
Fri 04/14
Phebe Vayanos headshot

Learning Optimal Policies for Online Allocation of Scarce Housing Resources from Data Collected in Deployment

We study the problem of allocating scarce housing resources of different types to individuals experiencing homelessness based on their observed covariates. We leverage administrative data collected in deployment to design an online policy that maximizes mean outcomes while satisfying budget and fairness requirements. We propose a policy in which an individual receives the resource maximizing the difference between their mean treatment outcomes and the resource bid price, or roughly the opportunity cost of using a resource. Our approach has nice asymptotic guarantees and is easily interpretable. We show results on real data from the Homeless Management Information System in LA: our policies improve rates of exit from homelessness by 1.2% and policies that are fair in either allocation or outcomes by race come at very low price of fairness. In addition, to help guide the discussion among stakeholders in deciding on appropriate fairness requirements to impose when allocating scarce resources, we propose a framework for evaluating fairness in such resource allocation systems and present a set of incompatibility results that investigate the interplay between them. Notably, we show that 1) fairness in allocation and fairness in outcomes are usually incompatible; 2) policies that prioritize based on a vulnerability score will usually result in unequal outcomes across groups; and 3) policies using group membership in addition to baseline risk and treatment effects are as fair as possible given all available information.

Pizza will be served at 12:15 p.m.

Speaker Bio

Phebe Vayanos is a WiSE Gabilan Assistant Professor, an Assistant Professor of Industrial & Systems Engineering and Computer Science at the University of Southern California, and an Associate Director of the CAIS Center for Artificial Intelligence in Society. She has a PhD degree in Operations Research and an MEng degree in Electrical & Electronic Engineering, both from Imperial College London. She is a recipient of the NSF CAREER award and the USC Viterbi Junior Research Award and, jointly with her students, earned the INFORMS Diversity, Equity, and Inclusion Ambassador Program Award. She is an Associate Editor for Computational Management Science and for Operations Research Letters. Her research is supported by the National Science Foundation, by the Hilton Foundation, by the Home for Good Foundation, by the Homeless Policy Research Institute, by the U.S. Army Research Laboratory’s Army Research Office, by Schmidt Futures, by the METRANS Transportation Center, and by the Zumberge Diversity & Inclusion Grant Program at USC, among others.