Ad Delivery Algorithms: The Hidden Arbiters of Political Messaging

Political campaigns are increasingly turning to targeted advertising platforms to inform and mobilize potential voters. The appeal of these platforms stems from their promise to empower advertisers to select (or "target") users who see their messages with great precision, including through inferences about those users' interests and political affiliations. However, prior work has shown that the targeting may not work as intended, as platforms' ad delivery algorithms play a crucial role in selecting which subgroups of the targeted users see the ads. In particular, the platforms can selectively deliver ads to subgroups within the target audiences selected by advertisers in ways that can lead to demographic skews along race and gender lines, and do so without the advertiser's knowledge. In this work we demonstrate that ad delivery algorithms used by Facebook, the most advanced targeted advertising platform, shape the political ad delivery in ways that may not be beneficial to the political campaigns and to societal discourse. In particular, the ad delivery algorithms lead to political messages on Facebook being shown predominantly to people who Facebook thinks already agree with the ad campaign's message even if the political advertiser targets an ideologically diverse audience. Furthermore, an advertiser determined to reach ideologically non-aligned users is non-transparently charged a high premium compared to their more aligned competitor, a difference from traditional broadcast media. Our results demonstrate that Facebook exercises control over who sees which political messages beyond the control of those who pay for them or those who are exposed to them. Taken together, our findings suggest that the political discourse's increased reliance on profit-optimized, non-transparent algorithmic systems comes at a cost of diversity of political views that voters are exposed to. Thus, the work raises important questions of fairness and accountability desiderata for ad delivery algorithms applied to political ads.

政治竞选活动越来越多地转向定向广告平台，以告知和动员潜在选民。这些平台的吸引力源于它们承诺使广告商能够非常精确地选择（或“定向”）看到其信息的用户，包括通过对这些用户的兴趣和政治派别进行推断。然而，先前的研究表明，定向可能无法按预期发挥作用，因为平台的广告投放算法在选择定向用户的哪些子群体看到广告方面起着关键作用。特别是，平台可以有选择地向广告商所选定的目标受众中的子群体投放广告，这种方式可能导致在种族和性别方面的人口结构偏差，而且广告商并不知情。在这项研究中，我们表明，Facebook（最先进的定向广告平台）所使用的广告投放算法对政治广告的投放方式可能对政治竞选活动和社会话语没有益处。特别是，广告投放算法导致Facebook上的政治信息主要展示给Facebook认为已经同意广告活动信息的人，即使政治广告商以意识形态多样化的受众为目标。此外，与意识形态更一致的竞争对手相比，决心触达意识形态不一致用户的广告商被不透明地收取高额费用，这与传统广播媒体不同。我们的研究结果表明，Facebook对谁看到哪些政治信息行使控制权，这种控制权超出了为广告付费的人或接触到广告的人的控制范围。综上所述，我们的研究结果表明，政治话语对利润优化、不透明的算法系统的日益依赖是以选民所接触到的政治观点的多样性为代价的。因此，这项研究对应用于政治广告的广告投放算法提出了有关公平性和问责性期望的重要问题。