The emergence of a global industry of digital health platforms operated by Big Tech corporations, and its growing entanglements with academic and pharmaceutical research networks, raise pressing questions on the capacity of current data governance models, regulatory and legal frameworks to safeguard the sustainability of the health research ecosystem. In this article, we direct our attention toward the challenges faced by the European General Data Protection Regulation in regulating the potentially disruptive engagement of Big Tech platforms in health research. The (...) General Data Protection Regulation upholds a rather flexible regime for scientific research through a number of derogations to otherwise stricter data protection requirements, while providing a very broad interpretation of the notion of “scientific research”. Precisely the breadth of these exemptions combined with the ample scope of this notion could provide unintended leeway to the health data processing activities of Big Tech platforms, which have not been immune from carrying out privacy-infringing and socially disruptive practices in the health domain. We thus discuss further finer-grained demarcations to be traced within the broadly construed notion of scientific research, geared to implementing use-based data governance frameworks that distinguish health research activities that should benefit from a facilitated data protection regime from those that should not. We conclude that a “re-purposing” of big data governance approaches in health research is needed if European nations are to promote research activities within a framework of high safeguards for both individual citizens and society. (shrink)

In the Netherlands, as in many other nations, the government has proposed the use of a contact-tracing app as a means of helping to contain the spread of the corona virus. The discussion about the use of such an app has mostly been framed in terms of a tradeoff between privacy and public health. This research statement presents an analysis of the Dutch public debate on Corona-apps by using the framework of Orders of Worth by Boltanski and Thévenot (1991). It (...) argues that this framework can help us to move beyond the dichotomy of privacy vs. public health by recognizing a plurality of conceptions of the common good in the debate about contact-tracing apps. This statement presents six orders of worth present in the Dutch debate:civic, domestic, vitality, market, industrialandproject,and argues that the identification of which common goods are at stake will contribute to discussions about the use of this technology from a standpoint with a richer ethical perspective. (shrink)

The datafication and digitalization of health and medicine has engendered a proliferation of new collaborations between public health institutions and data corporations like Google, Apple, Microsoft and Amazon. Critical perspectives on these new partnerships tend to frame them as an instance of market transgressions by tech giants into the sphere of health and medicine, in line with a “hostile worlds” doctrine that upholds that the borders between market and non-market spheres should be carefully policed. This article seeks to outline the (...) limitations of this common framing for critically understanding the phenomenon of the Googlization of health. In particular, the mobilization of a diversity of non-market value statements in the justification work carried out by actors involved in the Googlization of health indicates the co-presence of additional worlds or spheres in this context, which are not captured by the market vs. non-market dichotomy. It then advances an alternative framework, based on a multiple-sphere ontology that draws on Boltanski and Thevenot’s orders of worth and Michael Walzer’s theory of justice, which I call a normative pragmatics of justice. This framework addresses both the normative deficit in Boltanski and Thevenot’s work and provides an important emphasis on the empirical workings of justice. Finally, I discuss why this framework is better equipped to identify and to address the many risks raised by the Googlization of health and possibly other dimensions of the digitalization and datafication of society. (shrink)

Applications of artificial intelligence/machine learning in health care are dynamic and rapidly growing. One strategy for anticipating and addressing ethical challenges related to AI/ml for health care is patient and public involvement in the design of those technologies – often referred to as ‘co-design’. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, AI/ml introduces challenges to co-design that are often underappreciated. Informed by perspectives from critical data studies and critical digital (...) health studies, we review the research literature on involvement in health care, and involvement in design, and examine the extent to which co-design as commonly conceptualized is capable of addressing the range of normative issues raised by AI/ml for health care. We suggest that AI/ml technologies have amplified and modified existing challenges related to patient and public involvement, and created entirely new challenges. We outline three pitfalls associated with co-design for ethical AI/ml for health care and conclude with suggestions for addressing these practical and conceptual challenges. (shrink)

Since the outbreak of COVID-19, governments have turned their attention to digital contact tracing. In many countries, public debate has focused on the risks this technology poses to privacy, with advocates and experts sounding alarm bells about surveillance and mission creep reminiscent of the post 9/11 era. Yet, when Apple and Google launched their contact tracing API in April 2020, some of the world’s leading privacy experts applauded this initiative for its privacy-preserving technical specifications. In an interesting twist, the tech (...) giants came to be portrayed as greater champions of privacy than some democratic governments. This article proposes to view the Apple/Google API in terms of a broader phenomenon whereby tech corporations are encroaching into ever new spheres of social life. From this perspective, the advantage these actors have accrued in the sphere of the production of digital goods provides them with access to the spheres of health and medicine, and more worrisome, to the sphere of politics. These sphere transgressions raise numerous risks that are not captured by the focus on privacy harms. Namely, a crowding out of essential spherical expertise, new dependencies on corporate actors for the delivery of essential, public goods, the shaping of public policy by non-representative, private actors and ultimately, the accumulation of decision-making power across multiple spheres. While privacy is certainly an important value, its centrality in the debate on digital contact tracing may blind us to these broader societal harms and unwittingly pave the way for ever more sphere transgressions. (shrink)

Medical research data is sensitive personal data that needs to be protected from unauthorized access and unintentional disclosure. In a research setting, sharing of data within the scientific community is necessary in order to make progress and maximize scientific benefits derived from valuable and costly data. At the same time, convincingly protecting the privacy of people participating in medical research is a prerequisite for maintaining trust and willingness to share. In this commentary, we will address this issue and the pitfalls (...) involved in the context of the PEP project1 that provides the infrastructure for the Personalized Parkinson’s Project,2 a large cohort study on Parkinson’s disease from Radboud University Medical Center, in cooperation with Verily life Sciences, an Alphabet subsidiary. (shrink)

During the course of the COVID-19 pandemic, a wide range of digital technologies and data analytics have been incorporated into pandemic response models globally, in the hope of better detecting, tracking, monitoring and containing outbreaks. This increased digital involvement in disease control has offered the prospect of heightened effectiveness in all of the above, but not without raising other concerns. This paper contributes to ongoing discussions of the digital transformation in disease control by proposing a materialist analysis of how such (...) control has become operative and what its effects may be, both now and in the future. Using Taiwan's digital pandemic response as a case study, the paper explores specific ways in which material processes and arrangements have shaped digital measures, as well as the actions that rendered such measures operable, with their ensuing consequences. This analysis illustrates the importance of historical, material and technological specificities and contingencies to our understanding of how digital disease control takes a particular shape. It also demonstrates how shifting regimes of practice continually reconfigure the ways in which digital disease control functions. The paper argues that paying greater attention to the materialities of digital disease control can provide a more nuanced understanding of the complex ways in which society may be protected or harmed by its use, possibly simultaneously. It is hoped that such increased attentiveness may inform more considered and careful preparation for subsequent pandemics. (shrink)

Mobile applications are increasingly regarded as important tools for an integrated strategy of infection containment in post-lockdown societies around the globe. This paper discusses a number of questions that should be addressed when assessing the ethical challenges of mobile applications for digital contact-tracing of COVID-19: Which safeguards should be designed in the technology? Who should access data? What is a legitimate role for “Big Tech” companies in the development and implementation of these systems? How should cultural and behavioural issues be (...) accounted for in the design of these apps? Should use of these apps be compulsory? What does transparency and ethical oversight mean in this context? We demonstrate that responses to these questions are complex and contingent and argue that if digital contract-tracing is used, then it should be clear that this is on a trial basis and its use should be subject to independent monitoring and evaluation. (shrink)

This paper addresses a problem that has so far been neglected by scholars investigating the ethics of Big Data and policy makers: that is the ethical implications of Big Data initiatives’ environmental impact. Building on literature in environmental studies, cultural studies and Science and Technology Studies, the article draws attention to the physical presence of data, the material configuration of digital service, and the space occupied by data. It then explains how this material and situated character of data raises questions (...) concerning the ethics of the increasingly fashionable Big Data discourses. It argues that attention should be paid to the vocabulary currently used when discussing the governance of data initiatives; the internal tension between current data initiatives and environmental policies; issues of fair distribution. The article explains how taking into account these aspects would allow for a more responsible behaviour in the context of data storage and production. (shrink)

Background Big data and AI applications now play a major role in many health contexts. Much research has already been conducted on ethical and social challenges associated with these technologies. Likewise, there are already some studies that investigate empirically which values and attitudes play a role in connection with their design and implementation. What is still in its infancy, however, is the comparative investigation of the perspectives of different stakeholders. Methods To explore this issue in a multi-faceted manner, we conducted (...) semi-structured interviews as well as focus group discussions with patients and clinicians. These empirical methods were used to gather interviewee’s views on the opportunities and challenges of medical AI and other data-intensive applications. Results Different clinician and patient groups are exposed to medical AI to differing degrees. Interviewees expect and demand that the purposes of data processing accord with patient preferences, and that data are put to effective use to generate social value. One central result is the shared tendency of clinicians and patients to maintain individualistic ascriptions of responsibility for clinical outcomes. Conclusions Medical AI and the proliferation of data with import for health-related inferences shape and partially reconfigure stakeholder expectations of how these technologies relate to the decision-making of human agents. Intuitions about individual responsibility for clinical outcomes could eventually be disrupted by the increasing sophistication of data-intensive and AI-driven clinical tools. Besides individual responsibility, systemic governance will be key to promote alignment with stakeholder expectations in AI-driven and data-intensive health settings. (shrink)

Technology corporations and the emerging digital health market are exerting increasing influence over the public healthcare agendas forming around the application of mobile medical devices. By promising quick and cost-effective technological solutions to complex healthcare problems, they are attracting the interest of funders, researchers, and policymakers. They are also shaping the public facing discourse, advancing an overwhelmingly positive narrative predicting the benefits of wearable medical devices to include personalised medicine, improved efficiency and quality of care, the empowering of under-resourced communities, (...) and delivery of health services previously unavailable to the citizens of developing countries. Typically techno-optimist in their description, the key barriers to this impending inflection point in healthcare are identified as technical issues such as short battery life and a lack of data protection. However, this tech innovation narrative is consistent with problematic ethical, social, and political assumptions that have practical and normative effects, and risk, one, undermining the real clinical potential of wearable devices and, two, designing social inequality and injustice into our mobile health interventions in global healthcare. I argue that the foundational assumptions dealing with the just distribution of healthcare ‘goods’, the individual as part of society, and the political framing of future healthcare policy devalue equity and despite what they promise cannot meet the distinctive needs of individuals and groups that do not conform to a standardised concept of care-receiver. (shrink)

In the current research landscape, there are increasing demands for research to be innovative and cutting-edge. At the same time, concerns are voiced that as a consequence of neoliberal regimes of research governance, innovative research becomes impeded. In this paper, I suggest that to gain a better understanding of these dynamics, it is indispensable to scrutinise current demands for innovativeness as a distinct way of ascribing worth to research. Drawing on interviews and focus groups produced in a close collaboration with (...) three research groups from the crop and soil sciences, I develop the notion of a project-innovation regime of valuation that can be traced in the sphere of research. In this evaluative framework, it is considered valuable to constantly re-invent oneself and take ‘first steps’ instead of ‘just’ following up on previous findings. Subsequently, I describe how these demands for innovativeness relate to and often clash with other regimes of valuation that matter for researchers’ practices. I show that valuations of innovativeness are in many ways bound to those of productivity and competitiveness, but that these two regimes are nevertheless sometimes in tension with each other, creating a complicated double bind for researchers. Moreover, I highlight that also the project-innovation regime as such is not always in line with what researchers considered as a valuable progress of knowledge, especially because it entails a de-valuation of certain kinds of long-term epistemic agendas. I show that prevailing pushes for innovativeness seem to be based on a rather short-sighted temporal imaginary of scientific progress that is hardly grounded in the complex realities of research practices, and that they can reshape epistemic practices in potentially problematic ways. (shrink)