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Interactions between bids to show ads online can lead to an advertiser's ad being shown to more men than women even when the advertiser does not target towards men. We design bidding strategies that advertisers can use to avoid such emergent discrimination without having to modify the auction mechanism. We mathematically analyze the strategies to determine the additional cost to the advertiser for avoiding discrimination, proving our strategies to be optimal in some settings. We use simulations to understand other settings.
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This content will become publicly available on June 23, 2026
External Evaluation of Discrimination Mitigation Efforts in Meta's Ad Delivery
The 2022 settlement between Meta and the U.S. Department of Justice to resolve allegations of discriminatory advertising resulted is a first-of-its-kind change to Meta's ad delivery system aimed to address algorithmic discrimination in its housing ad delivery. In this work, we explore direct and indirect effects of both the settlement's choice of terms and the Variance Reduction System (VRS) implemented by Meta on the actual reduction in discrimination. \newline We first show that the settlement terms allow for an implementation that does not meaningfully improve access to opportunities for individuals. The settlement measures impact of ad delivery in terms of impressions, instead of unique individuals reached by an ad; it allows the platform to level down access, reducing disparities by decreasing the overall access to opportunities; and it allows the platform to selectively apply VRS to only small advertisers. \newline We then conduct experiments to evaluate VRS with real-world ads, and show that while VRS does reduce variance, it also raises advertiser costs (measured per-individuals-reached), therefore decreasing user exposure to opportunity ads for a given ad budget. VRS thus \emph{passes the cost of decreasing variance to advertisers}. \newline Finally, we explore an alternative approach to achieve the settlement goals, that is significantly more intuitive and transparent than VRS. We show our approach outperforms VRS by both increasing ad exposure for users from \emph{all} groups and reducing cost to advertisers, thus demonstrating that the increase in cost to advertisers when implementing the settlement is not inevitable. \newline Our methodologies use a black-box approach that relies on capabilities available to any regular advertiser, rather than on privileged access to data, allowing others to reproduce or extend our work.
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- PAR ID:
- 10632615
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400714825
- Page Range / eLocation ID:
- 2616 to 2629
- Subject(s) / Keyword(s):
- best paper award
- Format(s):
- Medium: X
- Location:
- Athens Greece
- Sponsoring Org:
- National Science Foundation
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