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Khadija Baig, Reham Mohamed, Anna-Lena Theus, Sonia Chiasson, School of Computer Science, Carleton University, 1125 Colonel By Dr, Ottawa, ON K1S 5B6, Canada
At-home DNA testing enables individuals to gain ancestry and health information, and connect with others who share their DNA. Associated databases have been used in police investigations to solve cases, and by pharmaceutical companies to develop medication. The media has also reported genetic discrimination against individuals and has discussed potential discrimination by insurance companies or immigration officials. Previous research has identified reasons behind DNA-testing, but whether users understand the associated privacy risks remains unclear. Do users have reasonable mental models of how these systems work? Do users have privacy concerns? What do they understand as the benefits and risks involved? We conducted a study with 27 users of at-home DNA tests to address these questions. Each participant completed an interview and questionnaire. We asked about: perceived and desired data (i) use, (ii) management, (iii) sharing, and (iv) controls. We conducted quantitative analysis of the questionnaire data and thematic analysis of the interviews. We found that many users have inconsistent or incomplete mental models. Several have “no idea” for how long their data is kept, or what happens to it after processing. Users equate their DNA data to other types of personal data (e.g., browser cookies), and generally feel secure because “nothing bad has happened yet”. Most dismissed privacy concerns or had not considered privacy when making a choice. Those who did consider privacy often set aside their concerns to achieve their primary goal (e.g., genealogy research). Many ignored the privacy of others who share their DNA; it had either never occurred to them, or they justified that the benefits outweighed the risks. Despite this, users desired clarity and total transparency from the companies regarding data practices. They also wanted the ability to control their data. We discuss the implications of our findings and proposed future work.
Presenter: Khadija Baig
Institution: Carleton University
Type: Oral
Subject: Computer Science
Status: Approved
