The Vulnerability Project: Migrant Workers in Singapore

32 Pages Posted: 22 Jan 2021 Last revised: 31 May 2022

See all articles by Jane Loo

Jane Loo

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

Josephine Seah

Singapore Management University - Centre for AI & Data Governance

Mark Findlay

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

Date Written: January 21, 2021

Abstract

Governments in Singapore, India, and UK have activated surveillance, restrictive pandemic control policies, and predictive technologies to tackle the spread of COVID-19. Although some of these measures have proven efficacious, many bring with them adverse effects on fundamental rights and liberties which necessitate regulatory and policy monitoring. This project is interested in scrutinizing and critically evaluating the discriminatory consequences of adopted COVID control measures on vulnerable groups in society, thereby positively influencing anti-discrimination policy outcomes and resilience-building across communities.

The project suggests that early risk prediction (and response activation) based on identifiable pre-existing social and economic vulnerabilities will reduce the necessity for constrained control responses. Prompt predictive intervention by the State will lessen the associated discriminatory outcomes that arise from pre-existing societal neglect of vulnerable populations and the infliction of intrusive control measures as a regressive policy/regulatory alternative. By further scrutinizing the control measures employed within our various jurisdictions of interest, the project aims to shed light on the interplay between discriminatory State responses and the exacerbation of pre-existing vulnerability features. Through this mapping exercise, the research will facilitate the promotion of more appropriate, ethical and equitable control strategies. The flattening of these pandemic healthcare inequalities will have positive ramifications for human dignity, autonomy, and rights across numerous vulnerable communities including migrant workers, the elderly, and racial minorities. Additionally, the economic benefits in maintaining productivity and reducing intervention costs can be significant. The amelioration of discriminatory outcomes will also enhance and restore public confidence and trust in their respective State authorities leading to more effective pandemic containment.

This project will be broken down into several distinct parts. This opening paper applies a theoretical understanding of vulnerability and the vulnerable human condition to a specific use-case. Migrant construction workers living and working in Singapore form the subject of our first empirical exercise. After evaluating the distinct features of Singapore migrant workers’ pre-existing vulnerabilities, the paper examines government control responses directed to this community and discusses potential discriminatory impacts. It is argued that these responses entrench and exacerbate structural and processual disadvantage. Our next paper in the project will provide a comparative analysis of the vulnerability features prevalent in both India and the United Kingdom’s migrant worker population. The respective discriminatory state control responses and its impact on the migrant worker group will also be given strict scrutiny. This comparative exercise will determine common vulnerability themes influencing migrant worker population and enable the generalization of our recommendations for future diagnostic risk prediction enabling earlier and better policy outcomes. Use cases to follow in the project include the elderly living in institutional care homes and those removed from the contact of extended families, and racial minorities with histories of disadvantage in the provision of predictive and preventive health services. These groups will be examined following a similar analytical format in an effort to confirm the thesis that failures to predict risk through pre-emptive prediction exacerbate vulnerabilities and lead to further discrimination through constrained control policy options.

Note: The Centre for AI & Data Governance (CAIDG) is a research institute situated in the Singapore Management University School of Law. The Centre conducts independent research on policy, regulation, governance, ethics, and other issues relating to AI and data use. As part of our COVID data regulation and policy research, the CAIDG has been researching on COVID control strategies (employing AI-assisted technologies and big data) and its relation to cycles of vulnerability and discrimination. This project is part of our much wider commentary on the efficacy and legitimacy of COVID control measures through data, and is consistent with our upcoming TUM/BIICL collaboration on the Rule of Law, Legitimacy and Effective COVID-19 control policy.

Keywords: COVID-19, vulnerability, discrimination, migrant workers, COVID-19 control strategies

Suggested Citation

Loo, Jane and Seah, Josephine and Findlay, Mark James, The Vulnerability Project: Migrant Workers in Singapore (January 21, 2021). SMU Centre for AI & Data Governance Research Paper No. 01/2021, Available at SSRN: https://ssrn.com/abstract=3770485 or http://dx.doi.org/10.2139/ssrn.3770485

Jane Loo (Contact Author)

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

55 Armenian Street
Singapore
Singapore

Josephine Seah

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

55 Armenian Street
Singapore
Singapore

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

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