Digital personal data is increasingly framed as the basis of contemporary economies, representing an important new asset class. Control over these data assets seems to explain the emergence and dominance of so-called “Big Tech” firms, consisting of Apple, Microsoft, Amazon, Google/alphabet, and Facebook. These US-based firms are some of the largest in the world by market capitalization, a position that they retain despite growing policy and public condemnation—or “techlash”—of their market power based on their monopolistic control of personal data. We (...) analyse the transformation of personal data into an asset in order to explore how personal data is accounted for, governed, and valued by Big Tech firms and other political-economic actors. However, our findings show that Big Tech firms turn “users” and “user engagement” into assets through the performative measurement, governance, and valuation of user metrics, rather than extending ownership and control rights over personal data per se. We conceptualize this strategy as a form of “techcraft” to center attention on the means and mechanisms that Big Tech firms deploy to make users and user data measurable and legible as future revenue streams. (shrink)

The emergence of Big Data has added a new aspect to conceptualizing the use of digital technologies in the delivery of public services and for realizing digital governance. This article explores, via the ‘value-chain’ approach, the evolution of digital governance research, and aligns it with current developments associated with data analytics, often referred to as ‘Big Data’. In many ways, the current discourse around Big Data reiterates and repeats established commentaries within the eGovernment research community. This body of knowledge provides (...) an opportunity to reflect on the ‘promise’ of Big Data, both in relation to service delivery and policy formulation. This includes, issues associated with the quality and reliability of data, from mixing public and private sector data, issues associated with the ownership of raw and manipulated data, and ethical issues concerning surveillance and privacy. These insights and the issues raised help assess the value of Big Data in government and smart city environments. (shrink)

Following the recent practice turn in privacy research, informational privacy is increasingly analyzed with regard to the “appropriate flow of information” within a given practice, which preserves the “contextual integrity” of that practice (Nissenbaum, 2010, p. 149; 2015). Such a practice-theoretical take on privacy emphasizes the normative structure of practices as well as its structural injustices and power asymmetries, rather than focusing on the intentions and moral considerations of individual or institutional actors. Since privacy norms are seen to be institutionalized (...) via the role obligations of the practice's participants, this approach can analyze structural and systematic privacy infringements in terms of “defective role performances and defective social relations” (Roessler & Mokrosinska, 2013, p. 780). -/- Unfortunately, it is still often somewhat unclear what this exactly means within the context of informational privacy, why these performances and relations are defective and for whom. This raises the common objection of a so-called “practice positivism” (Applbaum, 1999, p. 51), that is, the difficulty of practice–theoretical accounts to take a practice-independent standpoint, from which to normatively evaluate the existing practice norms themselves. For example, Nissenbaum herself initially argues for a “presumption in favor of the status quo” with respect to the appropriateness and flow of privacy norms within a practice (Nissenbaum, 2004, p. 127). Such a “practice conservatism” (Nissenbaum, 2010, p. 169) comes dangerously close to committing a naturalistic fallacy, if not undergirded by practice-external criteria (which is ultimately what she does). -/- Merely resorting to existing practice norms to assess what defective role performances amount to, only shifts the question from how to recognize an appropriate flow of information to the question of how to recognize those defective role performances and social relations. Against this backdrop, the central aim of this article is to shed light on this question without resorting to practice-independent first principles or far-reaching universalistic anthropological assumptions. For this, I will analyze the notion of “defective role performances and social relations” in terms of social pathologies.1 Doing so has two advantages: First of all, it can draw on already existing concepts and distinctions, which help to categorize the different levels of analysis that exist in informational privacy research and situate the notion of “defective role performances” within them (Section 1). Second, those concepts and distinctions can serve as a basis for establishing a typology of phenomena with regard to deficient practices of informational privacy (Section 4). (shrink)

Synthetic biology, as an engineering approach to biological systems, has the potential to disruptively innovate the development of vaccines, therapeutics, and diagnostics. Data accessibility and differences in data-usage capabilities are important factors in shaping this innovation landscape. In this paper, the data that underpin synthetic biology responses to the COVID-19 pandemic are analyzed as positional information goods—goods whose value depends on exclusivity. The positionality of biological data impacts the ability to guide innovations toward societally preferred goals. From both an ethical (...) and economic point of view, positionality can lead to suboptimal as well as beneficial situations. When aiming for responsible innovation (i.e. embedding societal deliberation in the innovation process), it is important to consider hurdles and facilitators in data access and use. Central governance and knowledge commons provide routes to mitigate the negative effects of data positionality. (shrink)

In discourses on digitization and the data economy, it is often claimed that data subjects shall beownersof their data. In this paper, we provide a problem diagnosis for such calls fordata ownership: a large variety of demands are discussed under this heading. It thus becomes challenging to specify what—if anything—unites them. We identify four conceptual dimensions of calls for data ownership and argue that these help to systematize and to compare different positions. In view of this pluralism of data ownership (...) claims, we introduce, spell out and defend a constructive interpretative proposal: claims for data ownership are charitably understood as attempts to call for theredistributionof material resources and the socio-culturalrecognitionof data subjects. We argue that as one consequence of this reading, it misses the point to reject claims for data ownership on the grounds that property in data does not exist. Instead, data ownership brings to attention a claim to renegotiate such aspects of thestatus quo. (shrink)

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)

Background The ownership status of individual-level health data affects the manner in which it is used. In this paper we analyze two competing models of the ownership status of the data discussed in the literature recently: private ownership and public ownership. Main body In this paper we describe the limitations of these two models of data ownership with respect to individual-level health data, in particular in terms of ethical principles of justice and autonomy, risk mitigation, as well as technological, economic, (...) and conceptual issues. We argue that undifferentiated application of neither private ownership nor public ownership will allow us to resolve all the problems associated with effective, equitable, and ethical use of data. We suggest that, instead of focusing on data ownership, we should focus on the institutional and procedural aspects of data governance, such as using Data Access Committees (DACs) or equivalent managed access processes, which can balance the elements of these two ownership frameworks. Conclusion Undifferentiated application of the ownership concept (private or public) is not helpful in resolving problems associated with sharing individual-level health data. DACs or equivalent managed access processes should be an integral part of data governance. They can approve or disapprove data access requests after considering the potential benefits and harms to data subjects, their communities, primary researchers, and the wider society. (shrink)

This paper serves a dual function: (1) it is intended to proffer a stable understanding of our digital engagement on the Internet as a form of labor that is co-opted by digital firms for private profit; (2) it extends the concept of participatory democracy to our digital world, arguing that our collective or common production of value for digital firms (in the form of what I call“knowledge goods”) requires the implementation of participatory democratic governance mechanisms over these digital firms and (...) the experimentation with democratic digital alternatives.Whereas others have argued in favor of democratic control over digital platforms on the basis of the power that digital firms have over user's lives (Engelmann et al.,2020), this paper adds to this discussion by arguing in favor of digital platform democratization based on the value-generating labor contributed by digital users. (shrink)

Epidemiology is a field torn between practices of surveillance and methods of analysis. Since the onset of COVID-19, epidemiological expertise has been mostly identified with the first, as dashboards of case and mortality rates took centre stage. However, since its establishment as an academic field in the early 20th century, epidemiology’s methods have always impacted on how diseases are classified, how knowledge is collected, and what kind of knowledge was considered worth keeping and analysing. Recent advances in digital epidemiology, this (...) article argues, are not just a quantitative expansion of epidemiology’s scope, but a qualitative extension of its analytical traditions. Digital epidemiology is enabled by deep and digital phenotyping, the large-scale re-purposing of any data scraped from the digital exhaust of human behaviour and social interaction. This technological innovation is in need of critical examination, as it poses a significant epistemic shift to the production of pathological knowledge. This article offers a critical revision of the key literature in this budding field to underline the extent to which digital epidemiology is envisioned to redefine the classification and understanding of disease from the ground up. Utilising analytical tools from science and technology studies, the article demonstrates the disruptive expectations built into this expansion of epidemiological surveillance. Given the sweeping claims and the radical visions articulated in the field, the article develops a tentative critique of what I call a fantasy of pathological omniscience; a vision of how data-driven engineering seeks to capture and resolve illness in the world, past, present and future. (shrink)

Personal data are produced through our daily interactions with digital technologies like search engines, social media, and online shopping, and is often referred to as our “digital exhaust.” It has been characterized as the key resource or asset for our economies in the 21st century. This paper focuses on the socio-technical imaginaries of digital personal data as a way to understand how desired forms of data governance are co-produced with collective understandings of personal data as a political-economic asset. We examine (...) the different socio-technical imaginaries that underpinned different developments in data regulations in the United States and EU from 2008 to 2016, focusing specifically on the mutual constitution of law, political economy, and technoscience. We do so in order to understand the “prehistories” of contemporary data governance. We analyze the institutional and legal context around the development of data privacy regulation and data commercialization in these two important jurisdictions and reflect on how this institutional and legal context configured their respective approaches to data governance. (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)

Artificial Intelligence-as-a-Service empowers individuals and organisations to access AI on-demand, in either tailored or ‘off-the-shelf’ forms. However, institutional separation between development, training and deployment can lead to critical opacities, such as obscuring the level of human effort necessary to produce and train AI services. Information about how, where, and for whom AI services have been produced are valuable secrets, which vendors strategically disclose to clients depending on commercial interests. This article provides a critical analysis of how AIaaS vendors manipulate the (...) visibility of human labour in AI production based on whether the vendor relies on paid or unpaid labour to fill interstitial gaps. Where vendors are able to occlude human labour in the organisational ‘backstage,’ such as in data preparation, validation or impersonation, they do so regularly, further contributing to ongoing techno-utopian narratives of AI hype. Yet, when vendors must co-produce the AI service with the client, such as through localised AI training, they must ‘lift the curtain’, resulting in a paradoxical situation of needing to both perpetuate dominant AI hype narratives while emphasising AI’s mundane limitations. (shrink)

To integrate social robots in real-life contexts, it is crucial that they are accepted by the users. Acceptance is not only related to the functionality of the robot but also strongly depends on how the user experiences the interaction. Established design principles from usability and user experience research can be applied to the realm of human–robot interaction, to design robot behavior for the comfort and well-being of the user. Focusing the design on these aspects alone, however, comes with certain ethical (...) challenges, especially regarding the user’s privacy and autonomy. Based on an example scenario of human–robot interaction in elder care, this paper discusses how established design principles can be used in social robotic design. It then juxtaposes these with ethical considerations such as privacy and user autonomy. Combining user experience and ethical perspectives, we propose adjustments to the original design principles and canvass our own design recommendations for a positive and ethically acceptable social human–robot interaction design. In doing so, we show that positive user experience and ethical design may be sometimes at odds, but can be reconciled in many cases, if designers are willing to adjust and amend time-tested design principles. (shrink)

Personal health technologies such as apps and wearables that generate health and behavior data close to the individual patient are envisioned to enable personalized healthcare - and self-care. And yet, they are consumer devices. Proponents of these devices presuppose that measuring will be helpful, and that data will be meaningful. However, a growing body of research suggests that self-tracking data does not necessarily make sense to users. Drawing together data studies and digital health research, we aim to further research on (...) data ambivalence, a term we use to refer to the ambiguities and uncertainties people experience when interpreting their own data, as well as the critical obligation towards cultivating ethically sound uses and responses to such data in context. We develop the relationship between data, interpretation, and context as a central theoretical and practical problem in the datafication of healthcare. We then show how interpretation and context matter for data ambivalence through an empirical study of heart patients with an implanted advanced pacemaker who were offered a Fitbit wristband for self-tracking as part of a research project. We argue that the hope, anxiety, and doubt connected to the promise and accuracy of data are tempered by the context and purpose of self-tracking, and by individual circumstances. Finally, we link the findings on context-sensitivity in data interpretation to questions about response-ability in cloud-based care infrastructures. We discuss the ethical dilemmas associated with the use of commercial wellness-technologies in healthcare, and with researching such emerging practices. (shrink)

This paper problematises the notions of public or common good as weighed against individual sovereignty in the context of medical research by focusing on genetic research. We propose the notion of collective good as the good of the particular collective in which the research was conducted. We conducted documentary and interview-based research with participant representatives and research leaders concerned with participant involvement in leading genetic research projects and around two recent genetic data controversies: the case of the UK Wellcome Sanger (...) Institute, accused of planning unauthorised commercialisation of African DNA samples, and the case of the company Genuity Science, which planned genetic research on brain tumour samples in Ireland with no explicit patient consent. We advocate for greater specificity in circumscribing the collective to which genetic research relates and for greater efforts in including representatives of this collective as research coleaders in order to enable a more inclusive framing of the good arising from such research. Such community-based participant cogovernance and coleadership in genetic research is vital especially when minorities or vulnerable groups are involved, and it centrally requires community capacity building to help collectives articulate their own notions of the collective good. (shrink)

Digitization of a health record changes its accessibility. An electronic health record (EHR) can be accessed by multiple authorized users. Health information from EHRs contributes to learning healthcare systems’ development. The objective of this systematic review is to answer a question: What are ethical issues concerning research using EHRs in the literature? We searched Medline Ovid, Embase and Scopus for publications concerning ethical issues of research use of EHRs. We employed the constant comparative method to retrieve common ethical themes. We (...) descriptively summarized empirical studies. The study reveals the breadth, depth, and complexity of ethical problems associated with research use of EHRs. The central ethical question that emerges from the review is how to manage access to EHRs. Managing accessibility consists of interconnected and overlapping issues: streamlining research access to EHRs, minimizing risk, engaging and educating patients, as well as ensuring trustworthy governance of EHR data. Most of the ethical problems concerning EHR-based research arise from rapid cultural change. The framing of concepts of privacy, as well as individual and public dimensions of beneficence, are changing. We are currently living in the middle of this transition period. Human emotions and mental habits, as well as laws, are lagging behind technological developments. In the medical tradition, individual patient’s health has always been in the center. Transformation of healthcare care, its digitalization, seems to have some impacts on our perspective of health care ethics, research ethics and public health ethics. (shrink)

This article provides an ethnographic account of how Big Data biology is produced, interpreted, debated, and translated in a Big Data-driven cancer clinical trial, entitled “Personalized OncoGenomics,” in Vancouver, Canada. We delve into epistemological differences between clinical judgment, pathological assessment, and bioinformatic analysis of cancer. To unpack these epistemological differences, we analyze a set of gazes required to produce Big Data biology in cancer care: clinical gaze, molecular gaze, and informational gaze. We are concerned with the interactions of these bodily (...) gazes and their interdependence on each other to produce Big Data biology and translate it into clinical knowledge. To that end, our central research questions ask: How do medical practitioners and data scientists interact, contest, and collaborate to produce and translate Big Data into clinical knowledge? What counts as actionable and reliable data in cancer decision-making? How does the explicability or translatability of genomic Big Data come to redefine or contradict medical practice? The article contributes to current debates on whether Big Data engenders new questions and approaches to biology, or Big Data biology is merely an extension of early modern natural history and biology. This ethnographic account will highlight how genomic Big Data, which underpins the mechanism of personalized medicine, allows oncologists to understand and diagnose cancer in a different light, but it does not revolutionize or disrupt medical oncology on an institutional level. Rather, personalized medicine is interdependent on different styles of thought, gaze, and practice to be produced and made intelligible. (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)