New Research Article (Preprint): “Discrimination Through Optimization: How Facebook’s Ad Delivery Can Lead to Skewed Outcomes”
The following article (preprint) was recently shared on arXiv.
Title
Discrimination Through Optimization: How Facebook’s Ad Delivery Can Lead to Skewed Outcomes
Authors
Muhammad Ali
Northeastern University
Piotr Sapiezynski
Northeastern University
Miranda Boge
Upturn
Aleksandra Korolova
University of Southern California
Alan Mislove
Northeastern University
Aaron Rieke
Upturn
Source
via arXiv
Abstract
The enormous financial success of online advertising platforms is partially due to the precise targeting features they offer. Although researchers and journalists have found many ways that advertisers can target—or exclude—particular groups of users seeing their ads, comparatively little attention has been paid to the implications of the platform’s ad delivery process, comprised of the platform’s choices about who should see an ad.
It has been hypothesized that this process can “skew” ad delivery in ways that the advertisers do not intend, making some users less likely than others to see particular ads based on their demographic characteristics.
In this paper, we demonstrate that such skewed delivery occurs on Facebook, due to market and financial optimization effects as well as the platform’s own predictions about the “relevance” of ads to different groups of users. We find that both the advertiser’s budget and the content of the ad each significantly contribute to the skew of Facebook’s ad delivery. Critically, we observe significant skew in delivery along gender and racial lines for “real” ads for employment and housing opportunities despite neutral targeting parameters.
Our results demonstrate previously unknown mechanisms that can lead to potentially discriminatory ad delivery, even when advertisers set their targeting parameters to be highly inclusive. This underscores the need for policymakers and platforms to carefully consider the role of the ad delivery optimization run by ad platforms themselves—and not just the targeting choices of advertisers—in preventing discrimination in digital advertising.
Direct to Full Text Article
15 pages; PDF.
Media Coverage
Facebook Delivers Ads Based on Race and Gender Stereotypes, Researchers Discover (via CNBC)
Facebook’s Ad System Seems to Discriminate by Race and Gender (via The Economist)
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About Gary Price
Gary Price (gprice@gmail.com) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com.