Privacy challenges of automated vehicles: Merging contextual integrity and responsible innovation frameworks

Abstract

Privacy has become a central issue in automated vehicles (AVs). Questions around who owns data, who manages data, and how to access data are some of the key concerns around AVs, mobility data justice. This study broadens the understanding of privacy challenges for AVs by introducing a multilevel contextual integrity (MCI) model. MCI considers contextual integrity (CI) in tandem with societal preferences and individual level preferences, which is captured using demographic data. Therefore, it captures the individual-level, group-level, and societal-level factors that drive peoples’ preferences regarding AV privacy. Empirical insights into the relationships among the social forces captured at these three levels are drawn from survey data collected in South Korea. The findings reveal that although social goals and demographic variables initially show some association, the introduction of CI parameters significantly diminishes this relationship, highlighting the primacy of informational contexts in shaping AV privacy attitudes. This paper nuances current understandings of AV privacy by linking informational norms with overarching societal values and goals. By advancing the CI framework to include social goals, this study contributes to the broader discourse on responsible innovation, offering a robust approach to managing privacy challenges in emerging technologies.