Just data? Solidarity and justice in data-driven medicine
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(2020) 16:8
RESEARCH
Open Access
Just data? Solidarity and justice in datadriven medicine Patrik Hummel*
and Matthias Braun
* Correspondence: patrik.hummel@ fau.de Department of Theology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Kochstraße 6, 91054 Erlangen, Germany
Abstract This paper argues that data-driven medicine gives rise to a particular normative challenge. Against the backdrop of a distinction between the good and the right, harnessing personal health data towards the development and refinement of datadriven medicine is to be welcomed from the perspective of the good. Enacting solidarity drives progress in research and clinical practice. At the same time, such acts of sharing could—especially considering current developments in big data and artificial intelligence—compromise the right by leading to injustices and affecting concrete modes of individual self-determination. In order to address this potential tension, two key elements for ethical reflection on data-driven medicine are proposed: the controllability of information flows, including technical infrastructures that are conducive towards controllability, and a paradigm shift towards outputorientation in governance and policy. Keywords: Data-driven medicine, Precision medicine, Algorithm ethics, Data ethics, Justice, Solidarity, Controllability, Privacy
Introduction Digitization and datafication shape and transform health research and clinical practice. These transformations yield new opportunities and insights, but also pose challenges to individuals and society. One example is the use of COVID-19 tracing apps that alert users if they have been in contact with someone carrying the coronavirus SARS-CoV2, and for example suggest self-quarantine on this basis. Tracing apps are part of a bundle of measures to tackle the COVID-19 pandemic. One motivation for people to install and use such an app may be that they want to contribute their part to a common good, to show solidarity, and to donate their data for public health surveillance and research. Indeed, the sharing of data is essential for digital contact tracing and data-driven health applications in general to function effectively and yield sound results. Such technologies, however, can come at a price. Collecting and using (sensitive) personal data may in principle attain benefits and strengthen freedom, e.g., if lockdowns are prevented by early detection and interruption of transmission chains. However, it can also compromise privacy, social equality, © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit li
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