Data Solidarity Disrupted: Musings On the Overlooked Role of Mutual Aid in Data-Driven Medicine.

Abstract

Several suggestions have been made to embolden and reorient the concept of solidarity given the emergence of data-driven medicine. Recently, the European Union introduced a new consent model for so-called data altruism to motivate people to make their data available for purposes such as scientific research or improving public services. Others have introduced the alternative concept of data solidarily, which assumes that people's interests in data sharing result from a collective commitment to assist others. What those perspectives have in common is a focus on top-down organizational structures to deal with data-driven medicine. In this article, I offer an alternative reading of data solidarity, drawing on anarchist theory that highlights the disposition of mutual aid as a broader characteristic of solidarity. I begin by briefly indicating how the existing approaches to data solidarity in healthcare remain legalistic and state-centered without thoroughly considering socially critical notions of solidarity that highlight the impact of structural injustices. I then sketch out how an anarchist understanding of mutual aid could inform the conceptualization of solidarity. Finally, I focus on two implications for the practice of data-driven medicine: (1) current proposals of data altruism seem to engender a form of reversed charity; and (2) data solidarity practices could arise from the bottom-up through spontaneous order and direct action.