Abstract
This paper examines privacy and data protection concerns of the public in relation to COVID-19 contact tracing apps. In addition, the role played by these concerns in the adoption of contact tracing apps has been investigated. Further emphasis has been directed at the limitations of contact tracing apps that could stem from privacy and data protection accommodations. Regarding socio-technical system design, this paper attempts to identify mechanisms preserving privacy in contact tracing apps. It has been a further research aim to determine factors that assist and hinder adoption.
A mixed methods approach utilising a survey including both qualitatively and quantitatively evaluable questions was employed. Contact tracing apps have been a highly topical subject during the COVID-19 pandemic. This research found that privacy and data protection are indeed important factors in people’s decision-making about whether to use a contact tracing app. While certain privacy trade-offs are inevitable when it comes to contact tracing, this research found that a decentralised design approach characterised by full anonymity for users and the largest amount of data possible remaining on the device is best suited to achieve widespread adoption and approval with a privacy-conscious public that is concerned with data protection.
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Roesler, M., Liston, P. (2022). Privacy and Data Protection in COVID-19 Contact Tracing Apps: An Analysis from a Socio-Technical System Design Perspective. In: Meiselwitz, G., et al. HCI International 2022 - Late Breaking Papers. Interaction in New Media, Learning and Games. HCII 2022. Lecture Notes in Computer Science, vol 13517. Springer, Cham. https://doi.org/10.1007/978-3-031-22131-6_10
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