Uncertainty and Privacy Management of the South Korean Public During the COVID-19 Pandemic: Adoption Intentions for AI-Based Digital Contact-Tracing Technology

Soo Jung Hong, Hichang Cho


This study explores the factors influencing the intentions of the South Korean public to adopt contact-tracing technologies during the COVID-19 pandemic. Specifically, we combined the privacy calculus model with the impact of perceived uncertainty on adoption intentions and tested it with various contextual and cognitive factors. 444 individuals were surveyed on August 1, 2020, and the data were analyzed with structural equation modeling. Privacy concerns were found to be positively associated with perceived uncertainty and negatively associated with adoption intentions. On the other hand, perceived benefits showed a positive relationship with adoption intentions. Trust in government was negatively associated with perceived uncertainty, and trust in AI technology and perceived stigma had favorable effects on adoption intentions by lowering uncertainty. Finally, perceived uncertainty was negatively associated with the intention to adopt contact-tracing technology. The findings suggest ways to increase intentions to adopt new technologies during pandemics by lowering individual uncertainty associated with digital contact-tracing technologies that involve tradeoffs between the public good and privacy risks.


contact-tracing, privacy calculus, risk perception, uncertainty, trust, stigma

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