Affiliation:
1. LMU Munich, Munich, Germany
Abstract
Today, adaptive mobile applications use mobile sensing and user tracking, allowing for adaptation to the users' context and needs. This raises several privacy concerns. Privacy dashboards provide transparency and sharing control; however, their impact on the users' behavior is unclear. To shed light on the effects of (a) transparency and (b) control features, we developed a mobile sensing privacy dashboard and evaluated it in the wild (N=227). We found that the pure presentation of raw logging data is rather deterring, and users tend to use the app less, but offering the user control over the data collection can compensate for that. Users used the control features rarely and, as such, did not affect the data collocation. Our work informs the design of future privacy-enhancing interfaces in applications relying on passively collected mobile sensing data. Moreover, our results encourage the adoption of privacy dashboards in the applications and relieve developers from concerns about the negative influences of transparency information on the quality of collected data.
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)
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