Muhammad Ali
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 which users see which ads. 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.
References
- Alan Agresti and Brent A Coull. 1998. Approximate Is Better Than "exact" For Interval Estimation Of Binomial Proportions. The American Statistician, Vol. 52, 2 (1998), 119--126.Google Scholar
- Athanasios Andreou, Márcio Silva, Fabrício Benevenuto, Oana Goga, Patrick Loiseau, and Alan Mislove. 2019. Measuring The Facebook Advertising Ecosystem. In Network and Distributed System Security Symposium. San Diego, California, USA.Google Scholar
- Athanasios Andreou, Giridhari Venkatadri, Oana Goga, Krishna P. Gummadi, Patrick Loiseau, and Alan Mislove. 2018. Investigating Ad Transparency Mechanisms In Social Media: A Case Study Of Facebook's Explanations. In Network and Distributed System Security Symposium. San Diego, California, USA.Google ScholarCross Ref
- Tolga Bolukbasi, Kai-Wei Chang, James Y. Zou, Venkatesh Saligrama, and Adam T. Kalai. 2016. Man Is To Computer Programmer As Woman Is To Homemaker? Debiasing Word Embeddings. In Neural and Information Processing Systems. Barcelona, Spain.Google Scholar
- Joy Buolamwini and Timnit Gebru. 2018. Gender Shades: Intersectional Accuracy Disparities In Commercial Gender Classification. In Conference on Fairness, Accountability, and Transparency. New York, New York, USA.Google Scholar
- Robert J. Cabin and Randall J. Mitchell. 2000. To Bonferroni Or Not To Bonferroni: When And How Are The Questions. Bulletin of the Ecological Society of America, Vol. 81, 3 (2000), 246--248.Google Scholar
- Le Chen, Aniko Hannak, Ruijin Ma, and Christo Wilson. 2018. Investigating The Impact Of Gender On Rank In Resume Search Engines. In Annual Conference of the ACM Special Interest Group on Computer Human Interaction. Montreal, Canada.Google Scholar
- Geff Cumming and Sue Finch. 2005. Inference By Eye: Confidence Intervals And How To Read Pictures Of Data. American Psychologist, Vol. 60, 2 (2005), 170.Google ScholarCross Ref
- Amit Datta, Anupam Datta, Jael Makagon, Deirdre K. Mulligan, and Michael Carl Tschantz. 2018. Discrimination In Online Personalization: A Multidisciplinary Inquiry. In Conference on Fairness, Accountability, and Transparency. New York, New York, USA.Google Scholar
- Amit Datta, Michael Carl Tschantz, and Anupam Datta. 2015. Automated Experiments On Ad Privacy Settings: a Tale Of Opacity, Choice, And Discrimination. In Privacy Enhancing Technologies Symposium. Philadelphia, Pennsylvania, USA.Google Scholar
- Nicholas Diakopoulos, Daniel Trielli, JenniferStark, and Sean Mussenden. 2018. I Vote Fortextemdashhow Search Informs Our Choice Of Candidate. In Digital Dominance: The Power of Google, Amazon, Facebook, and Apple, M. Moore and D. Tambini (Eds.). Oxford University Press.Google Scholar
- Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. 2012. Fairness Through Awareness. In Proceedings of the 3rd Innovations in Theoretical Computer Science Conference. ACM, 214--226.Google ScholarDigital Library
- Cynthia Dwork and Christina Ilvento. 2018. Fairness Under Composition. In 10th Innovations in Theoretical Computer Science Conference (ITCS 2019) (Leibniz International Proceedings in Informatics (LIPIcs)), Vol. 124. 33:1--33:20. https://doi.org/10.4230/LIPIcs.ITCS.2019.33Google Scholar
- Irfan Faizullabhoy and Aleksandra Korolova. 2018. Facebook's Advertising Platform: New Attack Vectors And The Need For Interventions. Computing Research Repository (March 2018). https://arxiv.org/abs/1803.10099, Workshop on Technology and Consumer Protection (ConPro).Google Scholar
- Avijit Ghosh, Giridhari Venkatadri, and Alan Mislove. 2019. Analyzing Facebook Political Advertisers' Targeting. In Workshop on Technology and Consumer Protection. San Francisco, California, USA.Google Scholar
- Ben Green and Yiling Chen. 2019. Disparate Interactions: An Algorithm-in-the-loop Analysis Of Fairness In Risk Assessments. In Conference on Fairness, Accountability, and Transparency. Atlanta, Georgia, USA.Google ScholarDigital Library
- Aniko Hannak, Gary Soeller, David Lazer, Alan Mislove, and Christo Wilson. 2014. Measuring Price Discrimination And Steering On E-commerce Web Sites. In ACM Internet Measurement Conference. Vancouver, Canada.Google Scholar
- Aniko Hannak, Claudia Wagner, David Garcia, Alan Mislove, Markus Strohmaier, and Christo Wilson. 2017. Bias In Online Freelance Marketplaces: Evidence From Taskrabbit And Fiverr. In ACM Conference on Computer Supported Cooperative Work. Portland, Oregon, USA.Google ScholarDigital Library
- Matthew Kay, Cynthia Matuszek, and Sean A. Munson. 2015. Unequal Representation And Gender Stereotypes In Image Search Results For Occupations. In Annual Conference of the ACM Special Interest Group on Computer Human Interaction.Google Scholar
- Larry Kim. 2011. The Most Expensive Keywords In Google Adwords. http://www.wordstream.com/blog/ws/2011/07/18/most-expensive-google-adwords-keywords/.Google Scholar
- Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum, and Gal Yona. 2019. Preference-informed Fairness. https://arxiv.org/abs/1904.01793.Google Scholar
- Aleksandra Korolova. 2018. Facebook's Illusion Of Control Over Location-related Ad Targeting. Medium. https://medium.com/@korolova/facebooks-illusion-of-control-over-location-related-ad-targeting-de7f865aee78.Google Scholar
- Juhi Kulshrestha, Motahhare Eslami, Johnnatan Messias, Muhammad Bilal Zafar, Saptarshi Ghosh, Krishna Gummadi, and Karrie Karahalios. 2017. Quantifying Search Bias: Investigating Sources Of Bias For Political Searches In Social Media. In ACM Conference on Computer Supported Cooperative Work. Portland, Oregon, USA.Google ScholarDigital Library
- Anja Lambrecht and Catherine E. Tucker. 2018. Algorithmic Bias? An Empirical Study Into Apparent Gender-based Discrimination In The Display Of Stem Career Ads. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2852260.Google Scholar
- Mathias Lecuyer, Guillaume Ducoffe, Francis Lan, Andrei Papancea, Theofilos Petsios, Riley Spahn, Augustin Chaintreau, and Roxana Geambasu. 2014. Xray: Enhancing The Web's Transparency With Differential Correlation. In USENIX Security Symposium. San Diego, California, USA.Google Scholar
- Mathias Lecuyer, Riley Spahn, Yannis Spiliopolous, Augustin Chaintreau, Roxana Geambasu, and Daniel Hsu. 2015. Sunlight: Fine-grained Targeting Detection At Scale With Statistical Confidence. In ACM Conference on Computer and Communications Security.Google ScholarDigital Library
- Yabing Liu, Chloe Kliman-Silver, Balachander Krishnamurthy, Robert Bell, and Alan Mislove. 2014. Measurement And Analysis Of Osn Ad Auctions. In ACM Conference on Online Social Networks. Dublin, Ireland.Google Scholar
- Nico Neumann, Catherine E. Tucker, and Timothy Whitfield. 2018. How Effective Is Black-box Digital Consumer Profiling And Audience Delivery?: Evidence From Field Studies. Social Science Research Network Working Paper Series (2018).Google Scholar
- Javier Parra-Arnau, Jagdish Prasad Achara, and Claude Castelluccia. 2017. Myadchoices: Bringing Transparency And Control To Online Advertising. ACM Transactions on the Web, Vol. 11 (2017).Google ScholarDigital Library
- Ronald E. Robertson, Shan Jiang, Kenneth Joseph, Lisa Friedland, David Lazer, and Christo Wilson. 2018. Auditing Partisan Audience Bias Within Google Search. In Annual Conference of the ACM Special Interest Group on Computer Human Interaction.Google Scholar
- Diego Saez-Trumper, Yabing Liu, Ricardo Baeza-Yates, Balachander Krishnamurthy, and Alan Mislove. 2014. Beyond Cpm And Cpc: Determining The Value Of Users On Osns. In ACM Conference on Online Social Networks. Dublin, Ireland.Google ScholarDigital Library
- Christian Sandvig, Kevin Hamilton, Karrie Karahalios, and Cedric Langbort. 2014. Auditing Algorithms: Research Methods For Detecting Discrimination On Internet Platforms. In International Communication Association Conference.Google Scholar
- Piotr Sapiezynski, Wesley Zeng, Ronald E. Robertson, Alan Mislove, and Christo Wilson. 2019. Quantifying The Impact Of User Attention On Fair Group Representation In Ranked Lists. In Workshop on Fairness, Accountability, Transparency, Ethics, and Society on the Web. San Francisco, California, USA.Google Scholar
- Till Speicher, Muhammad Ali, Giridhari Venkatadri, Filipe Nunes Ribeiro, George Arvanitakis, Fabrício Benevenuto, Krishna P. Gummadi, Patrick Loiseau, and Alan Mislove. 2018. On The Potential For Discrimination In Online Targeted Advertising. In Conference on Fairness, Accountability, and Transparency. New York, New York, USA.Google Scholar
- Latanya Sweeney. 2013. Discrimination In Online Ad Delivery. Commun. ACM, Vol. 56, 5 (2013), 44--54.Google ScholarDigital Library
- Giridhari Venkatadri, Yabing Liu, Athanasios Andreou, Oana Goga, Patrick Loiseau, Alan Mislove, and Krishna P. Gummadi. 2018a. Privacy Risks With facebook's Pii-based Targeting: Auditing A Data Broker's Advertising Interface. In IEEE Symposium on Security and Privacy. San Francisco, California, USA.Google Scholar
- Giridhari Venkatadri, Elena Lucherini, Piotr Sapiezy'nski, and Alan Mislove. 2019 a. Investigating Sources Of Pii Used In facebook's Targeted Advertising. In Privacy Enhancing Technologies Symposium. Stockholm, Sweden.Google ScholarCross Ref
- Giridhari Venkatadri, Alan Mislove, and Krishna P. Gummadi. 2018b. Treads: Transparency-enhancing Ads. In Workshop on Hot Topics in Networks. Redmond, Washington, USA.Google Scholar
- Giridhari Venkatadri, Piotr Sapiezy'nski, Elissa M. Redmiles, Alan Mislove, Oana Goga, Michelle Mazurek, and Krishna P. Gummadi. 2019 b. Auditing Offline Data Brokers Via Facebook's Advertising Platform. In International World Wide Web Conference. San Francisco, California, USA.Google Scholar
- Craig E. Wills and Can Tatar. 2012. Understanding What They Do With What They Know. In Workshop on Privacy in the Electronic Society.Google Scholar
Index Terms
Discrimination through Optimization: How Facebook's Ad Delivery Can Lead to Biased Outcomes
Comments