Gauging the acceptance of contact tracing technology: An empirical study of Singapore residents’ concerns with sharing their information and willingness to trust

Author

Ee-Ing Ong, Singapore Management UniversityFollow
Wee Ling LOO, Singapore Management UniversityFollow

Publication Type

Book Chapter

Version

submittedVersion

Publication Date

6-2022

Abstract

In response to the COVID-19 pandemic, governments began implementing various forms of contact tracing technology. Singapore’s implementation of its contact tracing technology, TraceTogether, however, was met with significant concern by its population, with regard to privacy and data security. This concern did not fit with the general perception that Singaporeans have a high level of trust in its government. We explore this disconnect, using responses to our survey (conducted pre-COVID-19) in which we asked participants about their level of concern with the government and business collecting certain categories of personal data. The results show that respondents had less concern with the government as compared to a business collecting most forms of personal data. Nonetheless, they still had a moderately high level of concern about sharing such data with the government. We further found that income, education and perceived self-exposure to AI are associated with higher levels of concern with the government collecting personal data relevant to contact tracing, namely health history, location and social network friends’ information. This has implications for Singapore residents’ trust in government collecting data and hence the success of such projects, not just for contact tracing purposes but for other government-related data collection undertakings.

Keywords

AI, contact tracing, COVID-19, empirical work, survey, data privacy, data security, surveillance, trust, Singapore, pandemics

Discipline

Asian Studies | Information Security | Privacy Law | Science and Technology Law

Research Areas

Public Interest Law, Community and Social Justice

Publication

Regulatory Insights on Artificial Intelligence: Research for Policy

Editor

Mark Findlay, Jolyon Ford, Josephine Seah, & Dilan Thampapillai

First Page

71

Last Page

101

ISBN

9781800880771

Identifier

10.4337/9781800880788.00010

Publisher

Edward Elgar

City or Country

Chelterham

Embargo Period

8-18-2021

Citation

Ong, Ee-Ing and LOO, Wee Ling. Gauging the acceptance of contact tracing technology: An empirical study of Singapore residents’ concerns with sharing their information and willingness to trust. (2022). Regulatory Insights on Artificial Intelligence: Research for Policy. 71-101.
Available at: https://ink.library.smu.edu.sg/sol_research/3282

Copyright Owner and License

Authors

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Additional URL

https://doi.org/10.4337/9781800880788.00010