Gerdus Benade (BU, Harvard): Towards Rawlsian Justice in Food Rescue

Towards Rawlsian Justice in Food Rescue

We study a problem faced by a national food rescue platform that matches each donation to the first recipient who claims it. Recipients have very different response rates, leading to a few highly responsive recipients claiming the bulk of the donations. We ask whether priority lists, which control when the donation is announced to each recipient, are a remedy for inequitable outcomes. We give efficient algorithms to find the n-stage and binary priority lists that optimize a class of Rawlsian objective functions focusing on the worst-off recipients. The simple idea is to give higher priority to recipients who have received less in the past and to those who were slower in responding to notifications. This can be codified into an index by which to rank order eligible recipients. Computational experiments calibrated by historical data confirm that even binary priority lists lead to significantly more fair allocations than the existing first-come-first-serve allocation system.