In July 2022, Meta launched the Fairness in Two-Sided Markets request for proposals (RFP). Today, we’re announcing the winners of this award.
Digital platforms offer a host of applications that facilitate connections in large-scale two-sided markets, both with and without money. An important concern when facilitating billions of matches between the two sides of a market is whether in aggregate the outcome is desirable or fair.
Through this RFP, we hope to support academics who are working to better define fairness and to create algorithms that have properties of fairness that are global in nature. The winners of this RFP focus on fairness in a variety of market applications, and we’re excited for the insights that their research will bring to the field.
The RFP attracted 68 proposals from 56 universities and institutions around the world. Thank you to everyone who took the time to submit, and congratulations to the winners.
Principal investigators are listed first unless otherwise noted.
Algorithmic pricing fairness: Ethics & competition
Nikhil Garg (Cornell Tech)
Community-centered design of school assignment mechanisms for equity
Niloufar Salehi (University of California, Berkeley)
Two-sided fairness in heterogeneous online matchings
Yuri Faenza, Jay Sethuraman (Columbia University)
Algorithmic approaches to fairness
Mohammad T. Hajiaghayi (University of Maryland, College Park)
Fair allocation of housing services
Nick Arnosti (University of Minnesota, Twin Cities)
Fairness-aware recommender systems for two-sided marketplaces
Yongfeng Zhang (Rutgers University)
Fair policy learning for two-sided markets
Kosuke Imai (Harvard University)