Understanding and Designing for Privacy in Wearable Fitness Platforms
Association for Computing Machinery
There has been increasing use of commercial wearable devices for tracking fitness-related activities. These devices sense and collect a variety of health and fitness data, which can be shared by users with other people and organizations. Yet, sharing personal data collected by these devices imposes several privacy concerns, ranging from private information exposure and repurposing, to aggregation and inferences. We do not fully understand people's sharing practices and privacy behaviors in the context of these ubiquitous devices. To address this limitation, my dissertation investigates the sharing of data collected by these devices in order to design solutions that support users' sharing needs and enhance their privacy. Preliminary findings indicate that users do not consider much of the data collected by these devices as sensitive, though they voice concerns about the possibility of abusing their data.