Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-03T01:02:02.092Z Has data issue: false hasContentIssue false
  • English
  • Français

From computational indicators to law into technologies: the Internet of Things, data analytics and encoding in COVID-19 contact-tracing apps

Published online by Cambridge University Press:  10 June 2021

David Restrepo Amariles
David Restrepo Amariles*
Affiliation:
Associate Professor of Data Law and AI, HEC Paris, France, and Research Fellow at the Perelman Centre for Legal Philosophy (ULB), Belgium
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper investigates the data life-cycle of contact-tracing apps (CTAs) in the context of the COVID-19 pandemic. 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 algorithmic decision systems and to certain naive belief in technological solutionism. In particular, this paper shows, first, that technology-harvested data do not reflect an objective representation of reality, and therefore require a context within which to be understood and interpreted for policy and legal purposes; and, second, that the use of data analytics to extract insights from these data enables the production of computational indicators. By looking at how CTAs are used to implement pandemic-mitigation restrictions such as lockdowns, quarantines, social distancing and testing, the paper ultimately brings forth the ways in which technologies – and thus their bias and ways of framing social reality – become embedded in the law.

Keywords

contact-tracing appslaw and technologyInternet of Thingscomputational indicatorsCOVID-19
Type
Article
Information
International Journal of Law in Context , Volume 17 , Special Issue 2: Numbers in an emergency: The many roles of indicators in the COVID-19 crisis , June 2021 , pp. 261 - 274
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ahmed, N et al. (2020) A survey of COVID-19 contact tracing apps. IEEE Access 8, 134577–134601.CrossRefGoogle Scholar
Albrecht, M et al. (2020) Joint Statement. Available at https://drive.google.com/file/d/1uB4LcQHMVP-oLzIIHA9SjKj1uMd3erGu/view (accessed 1 February 2021).Google Scholar
Alsdurf, H et al. (2020) COVID White Paper. arXiv, Cornell University. Available at https://arxiv.org/abs/2005.08502.Google Scholar
Amit, M et al. (2020) Mass-surveillance technologies to fight coronavirus spread: the case of Israel. Nature Medicine 26, 1167–1169.CrossRefGoogle ScholarPubMed
Apple (2020) Supporting exposure notifications express. Available at https://developer.apple.com/documentation/exposurenotification/supporting_exposure_notifications_express (accessed 1 February 2021).Google Scholar
Apple (2021) ENExposureConfiguration. Available at https://developer.apple.com/documentation/exposurenotification/enexposureconfiguration (accessed 1 February 2021).Google Scholar
Apple and Google (2020) Exposure notification: Bluetooth specification. Available at https://covid19-static.cdn-apple.com/applications/covid19/current/static/contact-tracing/pdf/ExposureNotification-BluetoothSpecificationv1.2.pdf (accessed 1 February 2021).Google Scholar
Arshed, N, Meo, MS and Farooq, F (2020) Empirical assessment of government policies and flattening of the COVID19 curve. Journal of Public Affairs (Epub ahead of print. PMID: 32904924).CrossRefGoogle ScholarPubMed
Berke, A et al. (2020) Assessing disease exposure risk with location data: a proposal for cryptographic preservation of privacy. Available at https://arxiv.org/pdf/2003.14412 (accessed 1 February 2021).Google Scholar
Bradford, L, Aboy, M and Liddell, K (2020) COVID-19 contact tracing apps: a stress test for privacy, the GDPR, and data protection regimes. Journal of Law and the Biosciences 7, 1–21.CrossRefGoogle ScholarPubMed
Callaghan, S (2020) COVID-19 is a data science issue. Patterns 1, 1–3.CrossRefGoogle ScholarPubMed
Castelluccia, C et al. (2020) ROBERT: ROBust and privacy-presERving proximity Tracing. Working Paper INRIA, hal-02611265. Available at https://hal.inria.fr/hal-02611265 (accessed 1 February 2021).Google Scholar
Chen, H, Zeng, D and Yan, P (2010) Infectious Disease Informatics: Syndromic Surveillance for Public Health and Bio-Defense. New York: Springer.CrossRefGoogle Scholar
Criddle, C and Kelion, L (2020) Coronavirus contact-tracing: world split between two types of app. BBC, 7 May. Available at https://www.bbc.com/news/technology-52355028 (accessed 1 February 2021).Google Scholar
Davis, K (2014) Legal indicators: the power of quantitative measures of law. Annual Review of Law and Social Science 10, 37–52.CrossRefGoogle Scholar
Desrosières, A (1998) The Politics of Large Numbers: A History of Statistical Reasoning. Cambridge, MA: Harvard University Press.Google Scholar
Feng, F et al. (2017) Computational Social Indicators: A Case Study of Chinese University Ranking. Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Tokyo, Japan, August 2017, pp. 455–464.CrossRefGoogle Scholar
Ferretti, L et al. (2020) Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science 368, 1–7.CrossRefGoogle ScholarPubMed
Grantz, KH et al. (2020) The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology. Nature Communications 11, 1–8.CrossRefGoogle ScholarPubMed
Google (2020) COVID-19 exposure notifications service additional terms. Available at https://docs.google.com/viewer?url=https%3A%2F%2Fblog.google%2Fdocuments%2F72%2FExposure_Notifications_Service_Additional_Terms.pdf (accessed 1 February 2021).Google Scholar
Gubbi, J et al. (2013) Internet of Things (IoT): a vision, architectural elements, and future directions. Future Generation Computer Systems 29, 1645–1660.CrossRefGoogle Scholar
Hassan, S and De, Filippi P (2017) The expansion of algorithmic governance: from code is law to law is code. The Journal of Field Actions 17, 88–90.Google Scholar
Hern, A (2020) France urges Apple and Google to ease privacy rules on contact tracing. The Guardian, 21 April. Available at https://www.theguardian.com/world/2020/apr/21/france-apple-google-privacy-contact-tracing-coronavirus (accessed 1 February 2021).Google Scholar
Hinch, R et al. (2020) Effective configurations of a digital contact tracing app: a report to NHSX. Available at https://github.com/BDI-pathogens/covid-19_instant_tracing/blob/master/Report%20-%20Effective%20Configurations%20of%20a%20Digital%20Contact%20Tracing%20App.pdf (accessed 1 February 2021).Google Scholar
Hui, M (2020) How Taiwan is tracking 55,000 people under home quarantine in real time. Quartz, 1 April. Available at https://qz.com/1825997/taiwan-phone-tracking-system-monitors-55000-under-coronavirus-quarantine/ (accessed 1 February 2021).Google Scholar
Inserm (2020) Deploying cellphone data to fight COVID-19. Inserm Website, 27 March. Available at https://presse.inserm.fr/en/deploying-cellphone-data-to-fight-covid-19/38831/ (accessed 1 February 2021).Google Scholar
Iqbal, R et al. (2020) Big data analytics: computational intelligence techniques and application areas. Technological Forecasting & Social Change 153, 1–13.CrossRefGoogle Scholar
Jacoby, J (1984) Perspectives on information overload. Journal of Consumer Research 10, 432–435.CrossRefGoogle Scholar
Kaufmann, D, Kraay, A and Mastruzzi, M (2011) The worldwide governance indicators: methodology and analytical issues. Hague Journal on the Rule of Law 3, 220–246.CrossRefGoogle Scholar
Kehrer, J and Hauser, H (2013) Visualization and visual analysis of multifaceted scientific data: a survey. IEEE Transactions on Visualization and Computer Graphics 19, 495–513.CrossRefGoogle ScholarPubMed
Kelion, L (2020) Coronavirus: Apple and France in stand-off over contact-tracing app. BBC, 21 April. Available at https://www.bbc.com/news/technology-52366129 (accessed 1 February 2021).Google Scholar
L'Echo (2020) L'app Coronalert se renouvelle, voici les nouvelles fonctionnalités. L'Echo, 19 November. Available at https://www.lecho.be/dossiers/coronavirus/l-app-coronalert-se-renouvelle-voici-les-nouvelles-fonctionnalites/10266308.html (accessed 1 February 2021).Google Scholar
Merry, SE (2011) Measuring the world: indicators, human rights, and global governance. Current Anthropology 52, S83–S95.CrossRefGoogle Scholar
Ministry of Interior of France (2020) Attestations de déplacement ‘couvre-feu’. Available at https://www.interieur.gouv.fr/Actualites/L-actu-du-Ministere/Attestations-de-deplacement-couvre-feu (accessed 1 February 2021).Google Scholar
Morozov, E (2013) To Save Everything, Click Here: The Folly of Technological Solutinism. New York: Public Affairs.Google Scholar
Nelken, D (1984) Law in action or living law? Back to the beginning in sociology of law. Legal Studies 4, 157–174.CrossRefGoogle Scholar
Nellis, S and Dave, P (2020) ‘Showdown looms between Silicon Valley, U.S. states over contact tracing apps. Reuteurs, 25 April. Available at https://www.reuters.com/article/us-health-coronavirus-usa-apps/showdown-looms-between-silicon-valley-u-s-states-over-contact-tracing-apps-idUSKCN22702F (accessed 1 February 2021).Google Scholar
Norton Rose Fulbright (2020a) Contact tracing apps: a new world for data privacy. Norton Rose Fulbright, July. Available at https://www.nortonrosefulbright.com/en-kr/knowledge/publications/d7a9a296/contact-tracing-apps-a-new-world-for-data-privacy (accessed 1 February 2021).Google Scholar
Norton Rose Fulbright (2020b) Contact tracing apps in Poland. Norton Rose Fulbright, 11 May. Available at https://www.nortonrosefulbright.com/-/media/files/nrf/nrfweb/contact-tracing/poland-contact-tracing.pdf?revision=f5084dcb-404f-4c7e-90fb-c56af308ca5a&la=en-za (accessed 1 February 2021).Google Scholar
Oliver, N et al. (2020) Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle. Science Advances 6, 1–6.CrossRefGoogle ScholarPubMed
Pound, R (1910) Law in books and law in action. American Law Review 44, 12–36.Google Scholar
Rajan, S, Cylus, JD and Mckee, M (2020) What do countries need to do to implement effective ‘first, test, trace, isolate and support’ systems. Journal of the Royal Society of medicine 113, 245–250.CrossRefGoogle Scholar
Raskar, R et al. (2020) Adding location and global context to the Google/Apple exposure notification Bluetooth API. Available at arXiv:2007.02317v3 (accessed 22 March 2021).Google Scholar
Restrepo Amariles, D (2014) The mathematical turn: l'indicateur Rule of Law dans la politique de développement de la Banque Mondiale. In Frydman, B and van Waeyenberge, A (eds), Gouverner par les Standards et les Indicateurs: de Hume aux Rankings. Brussels: Bruylant, pp. 193–234.Google Scholar
Restrepo, Amariles D (2017) Supping with the Devil? Indicators and the rise of managerial rationality in law. International Journal of Law in Context 13, 465–484.Google Scholar
Restrepo Amariles, D (2021) Algorithmic decision systems: automation and machine learning in the public administration. In Barfield, W (ed.), The Cambridge Handbook of the Law of Algorithms. Cambridge: Cambridge University Press, pp. 277–300.Google Scholar
Restrepo Amariles, D and Lewkowicz, G (2020) Unpacking smart law: how mathematics and algorithms are reshaping the legal code in the financial sector. Lex Electronica 25, 171–185.Google Scholar
Restrepo Amariles, D and McLachlan, J (2018) Legal indicators in transnational law practice: a methodological assessment. Jurimetrics 58, 163–209.Google Scholar
Reynolds, C (2020) BT confirms that it's providing gov't with mobile location data. Computer Business Review, 30 March. Available at https://www.cbronline.com/news/bt-mobile-phone-location-data-lockdown (accessed 1 February 2021).Google Scholar
Schlosser, F et al. (2020) COVID-19 lockdown induces disease-mitigating structural changes in mobility networks. Proceedings of the National Academy of Sciences (pnas 2012326117), 1–8.Google ScholarPubMed
Siems, M and Nelken, D (2017) Global social indicators, law and the concept of legitimacy. International Journal of Law in Context 13, 436–449.CrossRefGoogle Scholar
Suzuki, S (2020) South Korea to adopt wristbands for quarantine violators. Nikkei Asia, 20 April. Available at https://asia.nikkei.com/Spotlight/Coronavirus/South-Korea-to-adopt-wristbands-for-quarantine-violators2 (accessed 1 February 2021).Google Scholar
Tang, Z et al. (2020) Prediction of new coronavirus infection based on a modified seir model. MEDRXiV.CrossRefGoogle Scholar
Winkler, M and Restrepo Amariles, D (Forthcoming) Governing the Disparate Effects of COVID-19 for Vulnerable Groups.Google Scholar
Xu, B et al. (2020) Epidemiological data from the COVID-19 outbreak, real-time case information. Scientific Data 7, 1–5.CrossRefGoogle ScholarPubMed
Yeung, K (2017) ‘Hypernudge’: big data as a mode of regulation by design. Information, Communication & Society 20, 118–136.CrossRefGoogle Scholar
Zuboff, S (2015) Big other: surveillance capitalism and the prospects of an information civilization. Journal of Information Technology 30, 75–89.CrossRefGoogle Scholar
Zuboff, S (2019) The age of surveillance capitalism: the fight for a human future at the new frontier of power. Public Affairs 30, 75–89.Google Scholar