PRIVACY BOUNDARIES AND INFORMATION FLOW SOLIPSISM IN THE PERSONAL FITNESS INFORMATION ECOSYSTEM
Keywords: personal fitness information, privacy, wearables, fitness trackers
AbstractFitness trackers are an increasingly popular tool for tracking health and physical activity. Their benefits hinge on ubiquitous data collection and the algorithmic processing of personal fitness information (PFI). While PFI can reveal novel insights about users’ physical activity, health, and personal habits, it also contains potentially sensitive information that third parties may access in contexts unanticipated by fitness tracker users. This paper argues while many users attempt to manage their PFI with privacy boundaries, they can also succumb to “information flow solipsism,” or being broadly unaware of how fitness tracker companies might collect and aggregate their PFI. Our mixed-methods approach involved a survey and semi-structured interviews. Most survey respondents had limited knowledge of companies’ data tracking and retention policies. Additionally, most interviewees expressed only minimal privacy concerns regarding PFI. While others recognized PFI may need boundaries to manage information flows, they did not find the information sensitive enough to require personal responsibility for the definition of such boundaries. Viewing these results through Communication Privacy Management theory, users’ conceptualizations of ownership, privacy rules, and turbulence regarding their PFI influence how they manage privacy boundaries. Inherent trust of fitness tracker companies also led users to assume privacy rules properly limit the flow of PFI. This combination suggests fitness tracker users are potentially in a state of information flow solipsism, a position of ignorance of how PFI flows across devices and platforms that creates unanticipated privacy risks.
How to Cite
Zimmer, M., Chamberlain Kritikos, K., Vitak, J., Kumar, P., & Liao, Y. (2018). PRIVACY BOUNDARIES AND INFORMATION FLOW SOLIPSISM IN THE PERSONAL FITNESS INFORMATION ECOSYSTEM. AoIR Selected Papers of Internet Research, 2018. https://doi.org/10.5210/spir.v2018i0.10516