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To partly address people's concerns over web tracking, Google has created theAd Settings webpage to provide information about and some choice over theprofiles Google creates on users. We present AdFisher, an automated tool thatexplores how user behaviors, Google's ads, and Ad Settings interact. AdFishercan run browser-based experiments and analyze data using machine learning andsignificance tests. Our tool uses a rigorous experimental design andstatistical analysis to ensure the statistical soundness of our results. We useAdFisher to find that the Ad Settings was opaque about some features of auser's profile, that it does provide some choice on ads, and that these choicescan lead to seemingly discriminatory ads. In particular, we found that visitingwebpages associated with substance abuse changed the ads shown but not thesettings page. We also found that setting the gender to female resulted ingetting fewer instances of an ad related to high paying jobs than setting it tomale. We cannot determine who caused these findings due to our limitedvisibility into the ad ecosystem, which includes Google, advertisers, websites,and users. Nevertheless, these results can form the starting point for deeperinvestigations by either the companies themselves or by regulatory bodies.

Automated Experiments on Ad Privacy Settings: A Tale of Opacity, Choice, and Discrimination