Hyunsoo Lee
KAIST, Daejeon, Korea, Republic of
With increased interest in leveraging personal data collected from 24/7 mobile sensing for digital healthcare research, supporting user-friendly consent to data collection for user privacy has also become important. This work proposes \emph{PriviAware}, a mobile app that promotes flexible user consent to data collection with data exploration and contextual filters that enable users to turn off data collection based on time and places that are considered privacy-sensitive. We conducted a user study (N = 58) to explore how users leverage data exploration and contextual filter functions to explore and manage their data and whether our system design helped users mitigate their privacy concerns. Our findings indicate that offering fine-grained control is a promising approach to raising users’ privacy awareness under the dynamic nature of the pervasive sensing context. We provide practical privacy-by-design guidelines for mobile sensing research.
doi.org/10.1145/3613904.3642815
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)