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What Can Fitness Apps Teach Us About Group Privacy?

Authors :
Amr El Abbadi
Scott A. Reid
Jennifer Jiyoung Suh
Miriam J. Metzger
Source :
Research Anthology on Privatizing and Securing Data ISBN: 9781799889540, Privacy Concerns Surrounding Personal Information Sharing on Health and Fitness Mobile Apps ISBN: 9781799834878
Publication Year :
2021
Publisher :
IGI Global, 2021.

Abstract

This chapter begins with a case study of Strava, a fitness app that inadvertently exposed sensitive military information even while protecting individual users' information privacy. The case study is analyzed as an example of how recent advances in algorithmic group inference technologies threaten privacy, both for individuals and for groups. It then argues that while individual privacy from big data analytics is well understood, group privacy is not. Results of an experiment to better understand group privacy are presented. Findings show that group and individual privacy are psychologically distinct and uniquely affect people's evaluations, use, and tolerance for a fictitious fitness app. The chapter concludes with a discussion of group-inference technologies ethics and offers recommendations for fitness app designers.

Details

ISBN :
978-1-79988-954-0
978-1-79983-487-8
ISBNs :
9781799889540 and 9781799834878
Database :
OpenAIRE
Journal :
Research Anthology on Privatizing and Securing Data ISBN: 9781799889540, Privacy Concerns Surrounding Personal Information Sharing on Health and Fitness Mobile Apps ISBN: 9781799834878
Accession number :
edsair.doi.dedup.....8b4015df660265eadab599cddbbe1921
Full Text :
https://doi.org/10.4018/978-1-7998-8954-0.ch104