The Influence of Transparency and Control on the Willingness of Data Sharing in Adaptive Mobile Apps

Autor: Florian Bemmann, Maximiliane Windl, Jonas Erbe, Sven Mayer, Heinrich Hussmann
Rok vydání: 2022
Předmět:
Zdroj: Proceedings of the ACM on Human-Computer Interaction. 6:1-26
ISSN: 2573-0142
Popis: 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.
Databáze: OpenAIRE