From Computational Indicators to Law into Technologies: The Internet of Things, Data Analytics and Encoding in COVID-19 Contact Tracing Apps

Abstract

COVID-19 has revealed the critical role data is playing and will increasingly play in the exercise of social control. This article investigates the data life cycle of Contact Tracing Apps—namely, the collection, collation and analysis of data—as a tool of epidemiological surveillance in light of the International Health Regulations (IHR). It highlights the socio-legal implications resulting from the design and technology choices that software developers inevitably make. These choices are often neglected by policy makers due to the inherent technical complexity of the systems and to certain naïve belief in technological solutionism. In particular, this article shows, first, that technology-harvest data does not reflect an objective representation of reality, and therefore requires additional context to be understood and interpreted for policy and legal purposes, and second, that the use of data analytics to extract insights from this data makes possible the production of computational indicators, which in turn, enable the development of novel computational applications in the legal domain (law into technologies). In particular, it illustrates how encoding and data representation enable novel computational forms of social control, for instance, through the use of social graphs. By looking at how governments use CTAs to implement pandemic mitigation restrictions (PMRs) such as lockdowns, quarantines, social distancing and testing, it brings forth the ways in which technologies—and thus their bias and ways of framing social reality—become embedded in the law.

Keywords: Law, Computational social science, Indicators, COVID-19, Contact-tracing

JEL Classification: K10, 035