Popular Support for Balancing Equity and Efficiency in Resource Allocation: A Case Study in Online Advertising to Increase Welfare Program Awareness

TL;DR

This study investigates community preferences for balancing efficiency and equity in resource allocation, revealing broad support for prioritizing equitable outcomes over maximizing total enrollments, especially in multilingual online advertising for welfare programs.

Contribution

It provides empirical evidence on public preferences for equity in algorithmic resource allocation, highlighting the importance of considering community values in optimization strategies.

Findings

Efficiency-focused ads underrepresent Spanish speakers due to higher costs

Survey shows broad support for prioritizing equity over total enrollments

Results challenge the dominance of efficiency-centric algorithms in resource allocation

Abstract

Algorithmically optimizing the provision of limited resources is commonplace across domains from healthcare to lending. Optimization can lead to efficient resource allocation, but, if deployed without additional scrutiny, can also exacerbate inequality. Little is known about popular preferences regarding acceptable efficiency-equity trade-offs, making it difficult to design algorithms that are responsive to community needs and desires. Here we examine this trade-off and concomitant preferences in the context of GetCalFresh, an online service that streamlines the application process for California's Supplementary Nutrition Assistance Program (SNAP, formerly known as food stamps). GetCalFresh runs online advertisements to raise awareness of their multilingual SNAP application service. We first demonstrate that when ads are optimized to garner the most enrollments per dollar, a disproportionately small number of Spanish speakers enroll due to relatively higher costs of non-English language advertising. Embedding these results in a survey (N = 1,532) of a diverse set of Americans, we find broad popular support for valuing equity in addition to efficiency: respondents generally preferred reducing total enrollments to facilitate increased enrollment of Spanish speakers. These results buttress recent calls to reevaluate the efficiency-centric paradigm popular in algorithmic resource allocation.