Monoculture in Matching Markets

TL;DR

This paper develops a theoretical model to analyze the effects of algorithmic monoculture in matching markets, revealing its impact on applicant selection, match quality, and robustness to application disparities.

Contribution

It introduces a tractable model of algorithmic monoculture in two-sided markets, analyzing its effects compared to polyculture.

Findings

Monoculture selects less-preferred applicants when noise is well-behaved.

Monoculture matches more applicants to their top choices.

Monoculture is more robust to disparities in application numbers.

Abstract

Algorithmic monoculture arises when many decision-makers rely on the same algorithm to evaluate applicants. An emerging body of work investigates possible harms of this kind of homogeneity, but has been limited by the challenge of incorporating market effects in which the preferences and behavior of many applicants and decision-makers jointly interact to determine outcomes. Addressing this challenge, we introduce a tractable theoretical model of algorithmic monoculture in a two-sided matching market with many participants. We use the model to analyze outcomes under monoculture (when decision-makers all evaluate applicants using a common algorithm) and under polyculture (when decision-makers evaluate applicants independently). All else equal, monoculture (1) selects less-preferred applicants when noise is well-behaved, (2) matches more applicants to their top choice, though individual applicants may be worse off depending on their value to decision-makers and risk tolerance, and (3) is more robust to disparities in the number of applications submitted.