CAREER: Usable, Data-Driven Transparency and Access for Consumer Privacy

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Data collected about consumers underpins online personalization, yet raises critical privacy concerns. Mitigating these concerns requires giving consumers awareness and access to, data collected about them. To date, though, consumers have been given limited insight through these mechanisms. Attempts to provide awareness have centered on static disclosures of limited utility. Access rights for collected data have mostly been ignored or manifested as meaningless database exports. Unfortunately, consumers struggle to learn what has been collected, by whom, and especially what this collection implies for their privacy. This project aims to improve data transparency and access rights by developing novel models, user interactions, and open-source privacy tools. These techniques and tools will empower consumers to protect their privacy in a data-driven world. Furthermore, the project will enhance education and outreach. The investigator will develop a pilot program for engaging early-career students in research, create a new privacy course for underprivileged high school students, and both develop and exhibit artworks designed to provoke reflection on individual privacy, by collaborating with the School of the Art Institute of Chicago and the Chicago Museum of Science and Industry.The project will center around the intellectual development of complementary tools that give consumers data-driven insight into (i) the huge archives companies give consumers who exercise data-access rights and (ii) the online third-party tracking ecosystem. Several intellectual challenges stand in the way. First, usable transparency about voluminous data requires automatic methods that surface the information that matters most to consumers. The project will address this challenge through formative user studies and the iterative development and evaluation of a data-access tool. In addition, the project will develop new techniques for identifying, integrating, and visualizing data archives. Second, because the raw data collected about a consumer provides only partial transparency, the project will develop new methods for communicating, in an individualized manner, inferences possible from data. Third, as transparency is powerless without recourse, the project will understand the types of recourse users desire and develop tools that identify and mitigate privacy-tool-related website breakage at scale.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.