Into the Unknown: Accounting for Missing Demographic Data when Mitigating Ad Delivery Skew

2026-05-12

AI Summary

This study addresses the exacerbation of gender-biased ad delivery on online advertising platforms due to the exclusion of users with unspecified gender (“unknown users”), which may impede equitable access to public service information. In collaboration with a state-level government agency, the authors propose an innovative budget allocation intervention on Google Ads that systematically incorporates unknown users alongside gender-specified audiences—a first in practice—to mitigate gender bias. By implementing a tailored budget-splitting strategy, the approach balances fairness and cost-effectiveness, offering resource-constrained public-sector advertisers a viable pathway to reduce gender-directed disparities without excluding unknown users from campaign reach.

Abstract

Online advertising platforms use algorithmic systems to power the process of matching ads to users, termed ad delivery. Prior audits have demonstrated that ad delivery can be skewed by demographic attributes, such that ads are systematically under-delivered to certain groups despite advertiser intent to reach groups proportionally. This under-delivery raises a serious concern in the context of ads promoting public services, which might prevent certain groups of individuals from accessing information about resources on the basis of their demographic identity. In the absence of platform-provided solutions to skewed ad delivery, advertisers can counteract skew by targeting demographic groups directly. However, direct targeting excludes users whose demographics the platform cannot infer ("unknown users") if advertising platforms do not provide a way to target unknown users directly, as is the case on Google Ads. We collaborate with a state-level government agency to reduce gender-based skew in ad delivery with an intervention that accounts for unknown users while incorporating gender-based targeting. In particular, we design a budget split intervention that directly incorporates unknown users and targets users with Google-inferred gender labels (i.e., male, female). We find that this intervention is a valuable approach to addressing ad delivery skew without excluding unknown users, and serves as a middle ground in the trade-off between higher costs (from more granular demographic targeting) and skew (from ignoring demographics entirely). This approach is responsive to the needs of real-world, resource-constrained advertisers who are committed to the equitable distribution of public service outreach via online advertising. We conclude with recommendations for government advertisers, online advertising platforms, and researchers.

Problem

• ad delivery skew
• missing demographic data
• unknown users
• online advertising
• equitable outreach

Innovation

• ad delivery skew
• unknown users
• demographic targeting
• budget allocation
• equitable advertising