Ethics, AI, Mass Data and Pandemic Challenges: Responsible Data Use and Infrastructure Application for Surveillance and Pre-emptive Tracing Post-crisis

51 Pages Posted: 4 May 2020

See all articles by Mark Findlay

Mark Findlay

Singapore Management University - School of Law; Singapore Management University - Centre for AI & Data Governance

Jia Yuan Loke

Singapore Management University - Centre for AI & Data Governance

Nydia Remolina

Singapore Management University - Centre for AI & Data Governance

Benjamin Tham

Singapore Management University - Centre for AI & Data Governance

Date Written: May 4, 2020

Abstract

As the COVID-19 health pandemic rages governments and private companies across the globe are utilising AI-assisted surveillance, reporting, mapping and tracing technologies with the intention of slowing the spread of the virus. These technologies have the capacity to amass personal data and share for community control and citizen safety motivations that empower state agencies and inveigle citizen co-operation which could only be imagined outside such times of real and present danger. While not cavilling with the short-term necessity for these technologies and the data they control, process and share in the health regulation mission, this paper argues that this infrastructure application for surveillance has serious ethical and regulatory implications in the medium and long term in relation to individual dignity, civil liberties, transparency, data aggregation, explainability and other governance challenges. To conduct this analysis, the paper presents the Singapore and China case studies, and offers a comparative description based on the many more initiatives implemented worldwide in order to understand the purpose, goal and risk of these infrastructures. The analysis looks at data protection and citizen integrity and reflects on other surveillance methods outside the health context, such as initiatives implemented in the financial sector, where similar challenges have arisen.

Keywords: COVID-19, ethics, data protection, data use, data privacy, artificial intelligence, surveillance, tracing, big data

Suggested Citation

Findlay, Mark James and Loke, Jia Yuan and Remolina, Nydia and Tham, Benjamin, Ethics, AI, Mass Data and Pandemic Challenges: Responsible Data Use and Infrastructure Application for Surveillance and Pre-emptive Tracing Post-crisis (May 4, 2020). SMU Centre for AI & Data Governance Research Paper No. 2020/02, Available at SSRN: https://ssrn.com/abstract=3592283 or http://dx.doi.org/10.2139/ssrn.3592283

Mark James Findlay

Singapore Management University - School of Law ( email )

55 Armenian Street
Singapore, 179943
Singapore

Singapore Management University - Centre for AI & Data Governance ( email )

55 Armenian Street
Singapore
Singapore

Jia Yuan Loke

Singapore Management University - Centre for AI & Data Governance

55 Armenian Street
Singapore
Singapore

Nydia Remolina (Contact Author)

Singapore Management University - Centre for AI & Data Governance ( email )

55 Armenian Street
Singapore
Singapore

Benjamin Tham

Singapore Management University - Centre for AI & Data Governance

55 Armenian Street
Singapore
Singapore

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
274
Abstract Views
1,122
rank
123,627
PlumX Metrics