As the Covid-19 health pandemic rages governments and private companies across the globe are utilizing AI-assisted surveillance, reporting, mapping and tracing technologies with the intention of slowing the spread of the virus. These technologies have 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, in a recent paper, the SMU Centre for AI and Data Governance argues that this infrastructure application for surveillance have serious ethical implications in the medium and long term in relation to individual dignity, transparency, data aggregation, explainability and other ethical ramifications. If there are particular objectives that promote citizen tracking for instance, have these been well enunciated so that limits on ancillary data use can be affected without diluting the short-term legitimate control motivations? Are citizen data subjects aware of the limited purposes for data collection and shared analysis? Is there, consistent with so many ethical codes for the use of AI-assisted data collection and usage, regulatory mechanisms in place that guarantee transparency, accountability and expunging?
To conduct this analysis, the paper presents the Singapore and China case studies. The reason for this is that Singapore has been active, experimental and early in the surveillance and tracking response. Looking at law as a first point of regulatory reference helps understand how the sate intends citizen compliance, and how it envisages the limitations of its powers. In contrast there follows a brief overview of the response in the PRC not so consciously justified through law, elaborated on by some limited local commentary. China is often viewed as the most intrusive data logging jurisdiction in many aspects of state/citizen engagement and there has been recent concern expressed within and outside China about how an authoritarian one-party state may adapt the crisis to more permanent scenarios of social engineering. These case studies are followed by a comparative snapshot of other responses in different geopolitical locations, technological climates, political cultures and contexts of the crisis. Expanding the comparative description is intended to offer a more thematic understanding of purpose, goal and risk.
Based on the comparison of different measures, the paper refines down the extensions of pre-existing surveillance authority and the crisis-led differences in novel technologies and data sharing to at least describe how these technologies are employed by states and private sector entities world-wide. From a description of the surveillance and tracking terrain around the world, and the nature of mass data accumulation and shared usage against limited crisis purposes, it is easier to be specific about the temptations to convert crisis monitoring into permanent social surveillance and the dangers that the private/public sector alliances for these purposes, pose.
The comparative analysis and the case studies on tracing and surveillance raise some significant challenges for ethical challenges within and beyond the period of the Covid-19 crisis. Of necessity, this is a selective and speculative enterprise, requiring some guesswork on what might remain of the framework so described and the potentials this could offer to confound and compromise civil rights and human dignity measures. The paper argues that developers, authorities and citizens face challenges related to data rights, data integrity, intrusion into personal freedoms with surveillance ongoing and overall fairness. The analysis looks at privacy, data protection and citizen integrity and reflects on other surveillance methods outside the health context, such as some surveillance initiatives implemented in the financial sector, where similar challenges have arisen. Specifically, the paper provides an overview of some data-driven initiatives related to anti-money laundering and market surveillance.
In its developed form a later version of this paper will speculate on and offer suggestions regarding regulatory responses when faced with extended surveillance, tracking/tracing, public/private provider data sharing and any breakdown in personal data firewalls, or otherwise conventional aggregated data constraints.
*This research is supported by the National Research Foundation, Singapore under its Emerging Areas Research Projects (EARP) Funding Initiative. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not reflect the views of National Research Foundation, Singapore.
Last updated on 12 May 2020 .