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Recent privacy laws have strengthened data subjects’ right to access personal data collected by companies. Prior work has found that data exports companies provide consumers in response to Data Subject Access Requests (DSARs) can be overwhelming and hard to understand. To identify directions for improving the user experience of data exports, we conducted an online study in which 33 participants explored their own data from Amazon, Facebook, Google, Spotify, or Uber. Participants articulated questions they hoped to answer using the exports. They also annotated parts of the data they found confusing, creepy, interesting, or surprising. While participants hoped to learn either about their own usage of the platform or how the company collects and uses their personal data, these questions were often left unanswered. Participants’ annotations documented their excitement at finding data records that triggered nostalgia, but also shock about the privacy implications of other data they saw. Having examined their data, many participants hoped to request the company erase some, but not all, of the data. We discuss opportunities for future transparency-enhancing tools and enhanced laws. 

Internet companies routinely follow users around the web, building profiles for ad targeting based on inferred attributes. Prior work has shown that these practices, generally, are creepy—but what does that mean? To help answer this question, we substantially revised an open-source browser extension built to observe a user's browsing behavior and present them with a tracker's perspective of that behavior. Our updated extension models possible interest inferences far more accurately, integrates data scraped from the user's Google ad dashboard, and summarizes ads the user was shown. Most critically, it introduces ten novel visualizations that show implications of the collected data, both the mundane (e.g., total number of ads you've been served) and the provocative (e.g., your interest in reproductive health, a potentially sensitive topic). We use our extension as a design probe in a week-long field study with 200 participants. We find that users do perceive online tracking as creepy—but that the meaning of creepiness is far from universal. Participants felt differently about creepiness even when their data presented similar visualizations, and even when responding to the most potentially provocative visualizations—in no case did more than 66% of participants agree that any one visualization was creepy. 

In this research proposal, we outline our plans to examine the characteristics and affordances of ad transparency systems provided by 22 online platforms. We outline a user study designed to evaluate the usability of eight of these systems by studying the actions and behaviors each system enables, as well as users' understanding of these transparency systems. 

Advertising companies and data brokers often provide consumers access to a dashboard summarizing attributes they have collected or inferred about that user. These attributes can be used for targeted advertising. Several studies have examined the accuracy of these collected attributes or users’ reactions to them. However, little is known about how these dashboards, and the associated attributes, change over time. Here, we report data from a week-long, longitudinal study (𝑛=158) in which participants used a browser extension automatically capturing data from one dashboard, Google Ads Settings, after every fifth website the participant visited. The results show that Ads Settings is frequently updated, includes many attributes unique to only a single participant in our sample, and is approximately 90% accurate when assigning age and gender. We also find evidence that Ads Settings attributes may dynamically impact browsing behavior and may be filtered to remove sensitive interests.