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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01bv73c371f
Title: My Data, My Choice? An Analysis of the Data Broker Industry and the Exercise of Privacy Choices
Authors: Elmlinger, Katherine
Advisors: Kernighan, Brian
Department: Computer Science
Class Year: 2023
Abstract: Data brokers are the shady, inconspicuous actors operating under the radar within the Big Data economy—collecting, analyzing and selling the data of millions of users. These businesses thrive due largely to a lack of public awareness, limited industry-specific legislation, and the policy vacuum governing data privacy within the United States. Through my research, I provide a comprehensive overview of the industry, policy landscape, and the main threats that data brokers pose to society. Building off of this contextual background, I devised a research study for evaluating privacy choices offered by data brokers—specifically, exercising the “right to access.” The results of this interactive survey illustrate that such privacy choices are largely unusable, ineffective, and generally disturb consumers attempting to exercise them. Beyond this research study, I performed a case study analysis of six data brokers to provide a structured argument of common flaws in the industry. The six data brokers investigated in this case study demonstrate evidence of: concerning partnerships & affiliations, dark patterns used in cookie consent interfaces, dark patterns used by people search sites more broadly, and ineffective consumer access reports. The survey in conjunction with this case study provides a basis for my analysis of the most urgent and immediate concerns relating to data brokers. This analysis informs my conclusions and overarching recommendations, including: more usable and effective privacy choices, shifting the burden from the consumer to businesses, and greater oversight and enforcement mechanisms.
URI: http://arks.princeton.edu/ark:/88435/dsp01bv73c371f
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Computer Science, 1987-2024

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