How corporations surveil and influence consumers using big data tools is a major area of research and public debate. However, few studies explore it in relation to physicians in the USA, even though they have been surveilled and targeted by the pharmaceutical industry since at least the 1950s. Indeed, in 2010, concerns about the pharmaceutical industry's undue influence led to the passing of the Physician Sunshine Act, a unique piece of transparency legislation that requires companies to report their financial ties (...) to physicians and teaching hospitals in a public database. This article argues that while the Sunshine Act has clearly helped expose important commercial influences on both prescribing and the scale of industry involvement with physicians, it has also, paradoxically, fuelled further commercial surveillance and marketing. The article casts new light on innovative pharmaceutical marketing approaches and the key role of data brokers and analytics companies in the identification, targeting, managing, and surveillance of physicians. We place this analysis within the political economies of the pharmaceutical industry, surveillance-based marketing, and transparency, and argue that policies to promote increased transparency must be tightly tied to policies that impede the commodification and use of transparency data for surveillance and marketing purposes. (shrink)

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)

Education at all levels is increasingly augmented and enhanced by data mining and analytics, catalysed by the growing prevalence of automated distance learning. With an unprecedented capacity to scale both horizontally and vertically, data mining and analytics are set to be a transformative part of the future of education. We reflect on the assumptions behind data mining and the potential consequences of learning analytics, with reference to an issue brief prepared for the U.S. Department of Education entitled Enhancing Teaching and (...) Learning Through Educational Data Mining and Learning Analytics. We argue that the associated gains conceal subtle, but important risks. Data-ism, an underpinning paradigm, assigns unjustified veracity to data-driven science and the application of personalised analytics may compromise individual privacy, agency and inventiveness. This holds serious ethical implications, particularly when considering the impact on minors, rendering wholesale adoption premature. (shrink)

Most of the existing studies on Bourdieu and the digital regards the social and class distinctions in the use of digital technologies, thus presupposing a certain transparency of technologies themselves. Our proposal is to refer to this attitude as “Bourdieu outside the digital.” Yet in this paper, another perspective called “Bourdieu inside the digital” is developed, which moves the focus on the effects of some emerging technologies on social distinctions and discrimination. The main hypothesis is that algorithms of machine learning (...) are producers and reproducers of habitus. Although their results present a greater granularity with respect to the standard techniques of the past, these algorithms still reduce individuals to categories, general trends, classes, and behaviors. Such a reduction has flattening effects on the individuals’ self-understanding, especially in terms of identity and interaction with the social world. This is the phenomenon described in the article as the “personalization without personality,” whose consequences are both existential and social-political. This idea will be illustrated through qualitative and comparative analysis between the correspondence analysis and the multiple correspondence analysis used by Bourdieu in his works and some of those techniques that are performed today in big data analytics. (shrink)

This paper focuses on Precision Public Health (PPH), described in the scientific literature as an effort to broaden the scope of precision medicine by extrap- olating it towards public health. By means of the “All of Us” (AoU) research pro- gram, launched by the National Institutes of Health in the U.S., PPH is being devel- oped based on health data shared through a broad range of digital tools. PPH is an emerging idea to harness the data collected for precision medicine (...) to be able to tai- lor preventive interventions for at-risk groups. The character of these data concern genetic identity, lifestyle and overall health and therefore affect the ‘intimacy’ of personhood. Through the concept of biological citizenship, we elucidate how AoU and its recruitment tactics, by resonating ‘diversity’, at the same time appeal to and constitute identity, defining individuals as ‘data sharing subjects’. Although PPH is called for; the type of bio-citizenship that is enacted here, has a particular definition, where participant recruitment focuses on ‘citizenship’ in terms of empowerment (front), it is the ‘bio’ prefix that has become the main focus in terms of research. i.e. biosubjectivities vs biocapital. This raises the question whether the societal chal- lenges that often underlie public health issues can be sufficiently dealt with based on the way ‘diversity’ is accounted for in the program. We suggest that the AoU still risks of harming underrepresented groups based on the preconditions and the design of the program. (shrink)

Modern payment cards encompass a bewildering array of consumer technologies, from credit and debit cards to stored-value and loyalty cards. But what unites all of these financial media is their connection to recordkeeping systems. Each swipe sends data hurtling through invisible infrastructures to verify accounts, record purchase details, exchange funds, and update balances. With payment cards, banks and merchants have been able to amass vast archives of transactional data. This information is a valuable asset in itself. It can be used (...) for in-house data analytics programs or sold as marketing intelligence to third parties. This research examines the development of payment cards in the United States from the late 19th century to present, drawing attention to their fundamental relationship to identification, recordkeeping, and data mining. The history of payment cards, I argue, is not just a history of financial innovation and computing; it is also a history of Big Data and consumer surveillance. This history, moreover, provides insight into the growth of transactional data and the datafication of money in the digital economy. (shrink)

The advent of artificial intelligence (AI) challenges political theorists to think about data ownership and policymakers to regulate the collection and use of public data. AI producers benefit from free public data for training their systems while retaining the profits. We argue against the view that the use of public data must be free. The proponents of unconstrained use point out that consuming data does not diminish its quality and that information is in ample supply. Therefore, they suggest, publicly available (...) data should be free. We present two objections. First, allowing free data use promotes unwanted inequality. Second, contributors of information did not and could not anticipate that their contribution would be used to train AI systems. Therefore, charging for extensive data use is pro tanto permissible and desirable. We discuss policy implications and propose a progressive data use tax to counter the inequality arising. (shrink)

Ignorance, or the lack of knowledge, appears to be steadily spreading, despite the increasing availability of information. The notion of informed ignorance herein proposed to describe the widespread position of being exposed to an abundance of information yet lacking relevant knowledge, which is tied to the exponential growth in misinformation driven by technological developments and social media. Linked to many of societies’ most looming catastrophes, from political polarization to the climate crisis, practices related to knowledge and information are deemed some (...) of the most imminent and daunting modern threats, evidenced by the latest report of the World Economic Forum, which has named misinformation the most severe short-term global risk. This paper’s epistemic perspective links the properties of today’s information culture and the ways in which it interacts with individual capacities and limitations in current technological and socio-political contexts. Such a position is analyzed through the lens of epistemic principles as a contemporary epistemic phenotype that emerges from an environment of ill-adapted and excessive information inputs and leads to a distinctive type of social injustice that is primarily epistemic in nature. While equity and accessibility are widely discussed as important contributing factors to epistemic discrepancies, other overlooked but fundamental issues underlying epistemic injustices are considered, such as information manipulation, cognitive limitations, and epistemic degradation. To effectively face this elusive threat, we propose an inclusive viewpoint that harnesses knowledge from cognitive science, science and technology studies, and social epistemology to inform a unifying theory of its main impacts and driving forces. By adjusting a modern epistemic framework to the described phenomena, we intend to contextually outline its trajectory and possible means of containment based on a shared responsibility to maintain ethical epistemic standards. In a time of international unrest and mounting civil acts of violence, it is pertinent to emphasize the ethical principles of knowledge systems and authorities and suggest policy adaptations to maintain a social contract based on the shared values of truth and freedom. (shrink)

This paper explores how consumers’ ethical food consumption practices, mediated by mobile phone applications (apps), are transformed into digital data. Based on a review of studies on the digitalization of ethical consumption practices and food apps, we find that previous research, while valuable, fails to acknowledge and critically examine the digital labor required to perform digitalized ethical food consumption. In this paper, we call for research on how digital labor underlies the digitalization of ethical food consumption and develop a conceptual (...) framework that supports this research agenda. Our proposed conceptual framework builds on three interconnected analytical concepts—datafication, affordances and digital labor—that enable the study of digital labor as an infrastructural element of digitalized food consumption. We illustrate our conceptual framework through our previous research concerning Buycott, a US-based mobile app whose stated aim is to facilitate consumers’ ethical purchasing decisions. Using the walkthrough method, we consider how the Buycott app engages user-generated data and what implications this holds for consumers. The app’s infrastructure, we suggest, connects ethical consumption and digital labor. A richer understanding of the digital food economy, we propose, enables social scientists not only to elucidate how consumers engage in digital labor, but also to contribute to the development of new data governance structures in the digital food economy. We therefore call for social scientists interested in food, consumption and the digital economy to contribute to a new research agenda for studying everyday food digitalization by empirically examining how ethical consumption apps implicate ethical consumers’ work. (shrink)

This article discusses the political economy of AI capitalism. It considers AI as a General Purpose Technology and argues we need to investigate the power concentration of Big Tech. AI capitalism is characterised by the commodification of data, data extraction and a concentration in hiring of AI talent and compute capacity. This is behind Big Tech’s unstoppable drive for growth, which leads to monopolisation and enclosure under the winner takes all principle. If we consider AI as a GPT—technologies that alter (...) society’s economic and social structures—we need to come up with alternatives in terms of ownership and governance. The commons is proposed as an alternative for thinking about how to organise AI development and how to distribute the value that can be derived from it. Using the commons framework is also a way of giving society a more prominent role in the debate about what we expect from AI and how we should approach it. (shrink)

The current research examines the emergent literature of Critical Data Studies, and particularly aligns with Michael and Lupton’s (2016) manifesto calling for researchers to study the Public Understanding of Big Data. The aim of this paper is to explore Irish stakeholders’ narratives on data sharing in agriculture, and the ways in which their attitudes towards different data sharing governance models reflect their understandings of data, the impact that data hold in their lives and in the farming sector, as well as (...) their preferences for how data should be governed within agriculture. Seven focus groups were held in 2019 with Irish stakeholders from a variety of backgrounds, including agri-researchers, those working in SMEs, and farmers of varying ages and sectors. The primary activities carried out during these focus groups centred upon asking participants to discuss four different data sharing governance models, and to work their way through a set of value cards relating to these models. Focus group results are studied using an inductive, data-driven form of thematic analysis (Braun and Clarke 2006). Five primary themes cross-cut these focus groups: 1) Desire for a data intermediary, 2) Reversing the value chain, 3) Categorisation of data, 4) The common good, and 5) Potential danger in data sharing. These themes are explored in the paper through a detailed discussion of the focus group results, in which the authors track the manifestation of these themes across focus groups, and the ways they sometimes morphed or changed depending upon the participating stakeholder group. (shrink)

Today’s economy has transitioned from the traditional brick and mortar structure of doing business to that of digitalized economy. The latter functions with the aid of technological tools with ‘data’ being the most significant tool in today’s context. The issue has become even more critical with the advent of ‘big data’. It is argued that accumulation, analysis and usage of ‘big data’ enable creation of varied forms of entry barriers for new entrants and information asymmetries for customers which in turn (...) affect ‘market competition’ adversely (Santesteban & Longpre The Antitrust Bulletin,65(3), 459-485, 2020; Fast et al., 2021). Consequently, it is pertinent to revisit the traditional understanding of ‘market competition’ as stipulated in the antitrust laws across jurisdictions and specifically the Indian Competition Act, 2002. The existing regime being centred around neo-classical price theory is not equipped to comprehend the various dimensions of the digitalised world where ‘data’ is the new form of currency having effects on market power and, consequently, on market competition. Digital markets are multi-sided and non-linear in nature where ‘big data’ acts as a lubricant for their smooth functioning. Whether access to data provides any form of competitive advantage is the central question. A resource to provide any form of competitive advantage must be distinct, rare, inimitable, non-substitutable and valuable (Barney, 1991). If data carries such characteristics, the continuous percolation and usage of technology powered by ‘big data’ into the markets will affect the understanding of the basic competitive wrongs. Potential interdependencies between technology, data and market power also affect the understanding of ‘dominance’ as stipulated under the existing law. The unique challenges which ‘big data’ poses are not only restricted to competition policy but also extended to enforcement as they trigger overlapping constitutional concerns in relation to privacy. This demands for looking at the existing gap between competition law/policy and the ‘data’-driven challenges being faced in this ever-evolving digital economy. (shrink)

In this review, I analyse how ‘behaviour-based personalisation’ in insurance – that is, insurers’ increased interest in tracking and manipulating insureds’ behaviour with, for instance, wearable devices – has been approached in recent social scientific literature. In the review, I focus on two streams of literature, critical data studies and the sociology of insurance, discussing the new insurance schemes that utilise sensor-generated and digital data. The aim of this review is to compare these two approaches and to analyse what kinds (...) of understandings, methodologies and theoretical perspectives they apply to so-called ‘behaviour-based insurance’. The critical data studies literature emphasises the exploitative aspects of these new technologies and mobilises behaviour-based insurance to exemplify the negative outcomes of digital health. Scholars from the field of the sociology of insurance empirically analyse the practices of behavioural-based personalisation and study how regulating and ‘doing’ insurance affect attempts to personalise it. I highlight the importance of approaching insurance as a specific financial technology and argue that more research is needed to understand the practices of developing behaviour-based insurance schemes and the insureds’ experiences. (shrink)

In this article, we argue that dominant norms of demographic data are insufficient for accounting for the complexities that characterize many lesbian, gay, bisexual, transgender, and queer lives. Here, we draw from the responses of 178 people who identified as non-heterosexual or non-cisgender to demographic questions we developed regarding gender and sexual orientation. Demographic data commonly imagines identity as fixed, singular, and discrete. However, our findings suggest that, for LGBTQ people, gender and sexual identities are often multiple and in flux. (...) An overwhelming majority of our respondents reported shifting in their understandings of their sexual identities over time. In addition, for many of our respondents, gender identity was made up of overlapping factors, including the relationship between gender and transgender identities. These findings challenge researchers to reconsider how identity is understood as and through data. Drawing from critical data studies, feminist and queer digital media studies, and social justice initiatives like Data for Black Lives, we call for a reimagining of identity-based data as “queer data” or “data for queer lives.” We offer also recommendations for researchers to develop more inclusive survey questions. At the same time, we address the ways that queer perspectives destabilize the underlying logics of data by resisting classification and “capture.” For marginalized people, the stakes of this work extend beyond academia, especially in the era of algorithms and big data when the issue of who is or is not “counted” profoundly affects visibility, access, and power in the digital realm. (shrink)

The Nordic countries aim to have a unique place within the European and global health data economy. They have extensive nationally maintained and centralized health data records, as well as numerous biobanks where data from individuals can be connected based on personal identification numbers. Much of this phenomenon can be attributed to the emergence and development of the Nordic welfare state, where Nordic countries sought to systematically collect large amounts of population data to guide decision making and improve the health (...) and living conditions of the population. Recently, however, the so-called Nordic gold mine of data is being re-imagined in a wholly other context, where data and its ever-increasing logic of accumulation is seen as a driver for economic growth and private business development. This article explores the development of policies and strategies for health data economy in Denmark and Finland. We ask how nation states try to adjust and benefit from new pressures and opportunities to utilize their data resources in data markets. This raises questions of social sustainability in terms of states being producers, providers, and consumers of data. The data imaginaries related to emerging health data markets also provide insight into how a broad range of different data sources, ranging from hospital records and pharmacy prescriptions to biobank sample data, are brought together to enable “full-scale utilization” of health and welfare data. (shrink)

Current attention directed at ethical dimensions of data and Artificial Intelligence have led to increasing recognition of the need to secure and maintain public support for uses of people’s data. This is essential to establish a “Social Licence” for current and future practices. The notion of a “Social Licence” recognises that there can be meaningful differences between what is legally permissible and what is socially acceptable. Establishing a Social Licence entails public engagement to build relationships of trust and ensure that (...) practices align with public values. While the concept of the Social Licence is well-established in other sectors – notably in relation to extractive industries – it has only very recently begun to be discussed in relation to digital innovation and data-intensive industries. This article therefore draws on existing literature relating to the Social Licence in extractive industries to explore the potential approaches needed to establish a Social Licence for emerging data-intensive industries. Additionally, it draws on well-established literature relating to trust to examine the relevance of trust, and trustworthiness, for emerging practices in data-intensive industries. In doing so the article considers the extent to which pursuing a Social Licence might complement regulation and inform codes of practice to place ethical and social considerations at the heart of industry practice. We focus on one key industry: Financial Technology. We demonstrate the importance of combining technical and social approaches to address ethical challenges in data-intensive innovation and to establish relationships of trust to underpin a Social Licence for Financial Technology. Such approaches are needed across all areas and industries of data-intensive innovation to complement regulation and inform the development of ethical codes of practice. This is important to underpin culture change and to move beyond rhetorical commitments to develop best practice putting ethics at the heart of innovation. (shrink)

Controversies surrounding social media platforms have provided opportunities for institutional reflexivity amongst users and regulators on how to understand and govern platforms. Amidst contestation, platform companies have continued to enact projects that draw upon existing modes of privatized governance. We investigate how social media companies have attempted to achieve closure by continuing to set the terms around platform governance. We investigate two projects implemented by Facebook (Meta)—authenticity regulation and privacy controls—in response to the Russian Interference and Cambridge Analytica controversies surrounding (...) the 2016 U.S. Presidential Election. Drawing on Goffman’s metaphor of stage management, we analyze the techniques deployed by Facebook to reinforce a division between what is visible and invisible to the user experience. These platform governance projects propose to act upon _front-stage data relations:_ information that users can see from other users—whether that is content that users can see from “bad actors”, or information that other users can see about oneself. At the same time, these projects relegate _back-stage data relations_—information flows between users constituted by recommendation and targeted advertising systems—to invisibility and inaction. As such, Facebook renders the user experience actionable for governance, while foreclosing governance of back-stage data relations central to the economic value of the platform. As social media companies continue to perform platform governance projects following controversies, our paper invites reflection on the politics of these projects. By destabilizing the boundaries drawn by platform companies, we open space for continuous reflexivity on how platforms should be understood and governed. (shrink)

This paper considers what liberal philosopher Michael Sandel coins the ‘moral limits of markets’ in relation to the idea of paying people for data about their biometrics and emotions. With Sandel arguing that certain aspects of human life (such as our bodies and body parts) should be beyond monetisation and exchange, others argue that emerging technologies such as Personal Information Management Systems can enable a fairer, paid, data exchange between the individual and the organisation, even regarding highly personal data about (...) our bodies and emotions. With the field of data ethics rarely addressing questions of payment, this paper explores normative questions about data dividends. It does so by conducting a UK-wide, demographically representative online survey to quantitatively assess adults’ views on being paid for personal data about their biometrics and emotions via a Personal Information Management System, producing a data dividend, a premise which sees personal data through the prism of markets and property. The paper finds diverse attitudes based on socio-demographic characteristics, the type of personal data sold, and the type of organisation sold to. It argues that (a) Sandel’s argument regarding the moral limits of markets has value in protecting fundamental freedoms of those in society who are arguably least able to (such as the poor); but (b) that contexts of use, in particular, blur moral limits regarding fundamental freedoms and markets. (shrink)

Smart cities are now an established context in which data and digital technologies shape urban politics. Despite increased scholarly focus on algorithmic governance, smart cities and their data production still heavily rely on human labor, raising questions about how that labor is recruited and the implications of different recruitment strategies. In this paper, we illuminate the relations and practices mobilized to recruit the labor required to produce, analyze, and enact data that produce smart cities. We argue that smart cities recruit (...) such digital labor by producing and circulating moral values and sentiments to claim that such participation is a social good. In this article we draw on a 6-year ongoing project in Calgary, Canada to explore how these “moral economies” underwrite smart city ecosystems. We explore three projects related to data and digital labor in the Calgary smart city: a wearable technology collaborative project, a civic hacking group, and the community social media platform Nextdoor. We suggest that moral economies of smart cities signal a new juncture between urban planning and profiting from data, with the potential for creating new socio-political risks. These moral economies signal a shift toward a “new spirit of capitalism” in which labor is managed through indirect persuasion rather than direct compulsion and mandate. (shrink)

In this paper, we explore the methodologies underpinning two participatory research collaborations with Australian non-profit organisations that aimed to build data capability and social benefit in data use. We suggest that studying and intervening in data practices in situ, that is, in organisational data settings expands opportunities for improving the social value of data. These situated and collaborative approaches not only address the ‘expertise lag’ for non-profits but also help to realign the potential social value of organisational data use. We (...) explore the relationship between data literacy, data expertise and data capability to test the idea that collaborative work with non-profit organisations can be a practical step towards addressing data equity and generating data-driven social outcomes. Rather than adopting approaches to data literacy that focus on individuals – or ideal ‘data citizens’ – we target the organisation-wide data settings, goals and practices of the non-profit sector. We conclude that participatory methods can embed social value-generating data capability where it can be sustained at an organisational level, aligning with community needs to promote collaborative data action. (shrink)

Mechanism design is a form of optimization developed in economic theory. It casts economists as institutional engineers, choosing an outcome and then arranging a set of market rules and conditions to achieve it. The toolkit from mechanism design is widely used in economics, policymaking, and now in building and managing online environments. Mechanism design has become one of the most pervasive yet inconspicuous influences on the digital mediation of social life. Its optimizing schemes structure online advertising markets and other multi-sided (...) platform businesses. Whatever normative rationales mechanism design might draw on in its economic origins, as its influence has grown and its applications have become more computational, we suggest those justifications for using mechanism design to orchestrate and optimize human interaction are losing traction. In this article, we ask what ideological work mechanism design is doing in economics, computer science, and its applications to the governance of digital platforms. Observing mechanism design in action in algorithmic environments, we argue it has become a tool for producing information domination, distributing social costs in ways that benefit designers, and controlling and coordinating participants in multi-sided platforms. (shrink)

The social impacts of computer technology are often glorified in public discourse, but there is growing concern about its actual effects on society. In this article, we ask: how does “consent” as an analytical framework make visible the social dynamics and power relations in the capture, extraction, and labor of data science knowledge production? We hypothesize that a form of boundary violation in data science workplaces—gender harassment—may correlate with the ways humans’ lived experiences are extracted to produce Big Data. The (...) concept of consent offers a useful way to draw comparisons between gender relations in data science and the means by which machines are trained to learn and reason. Inspired by how Big Tech leaders describe unsupervised machine learning, and the co-optation of “revolutionary” rhetoric they use to do so, we introduce a concept we call “techniques of invisibility.” Techniques of invisibility are the ways in which an extreme imbalance between exposure and opacity, demarcated along fault lines of power, are fabricated and maintained, closing down the possibility for bidirectional transparency in the production and applications of algorithms. Further, techniques of invisibility, which we group into two categories—epistemic injustice and the Brotherhood—include acts of subjection by powerful actors in data science designed to quell resistance to exploitative relations. These techniques may be useful in making further connections between epistemic violence, sexism, and surveillance, sussing out persistent boundary violations in data science to render the social in data science visible, and open to scrutiny and debate. (shrink)

Social practices of quantification, or the production and communication of numbers, have been recognized as important foundations of organizational knowledge, as well as sources of power. With the advent of increasingly sophisticated digital tools to capture and extract numerical data from social life, however, there is a pressing need to understand the ethical stakes of quantification. The current study examines quantification from an ethical lens, to frame and promote a research agenda around the ethics of quantification. After a brief overview (...) of quantification research and its uses in state and market organization, I discuss quantification in terms of three core subprocesses—capture, specification, and appropriation, illustrating and identifying ethical concerns around each process. Linking these processes to the performative effects of measures, I present a working model of quantification from which the discussion builds ideas for developing a research agenda around quantification. (shrink)

Data science is characterized by engaging heterogeneous data to tackle real world questions and problems. But data science has no data of its own and must seek it within real world domains. We call this search for data “prospecting” and argue that the dynamics of prospecting are pervasive in, even characteristic of, data science. Prospecting aims to render the data, knowledge, expertise, and practices of worldly domains available and tractable to data science method and epistemology. Prospecting precedes data synthesis, analysis, (...) or visualization, and is constituted by the upstream work of discovering disordered or inaccessible data resources, thereafter to be ordered and rendered available for computation. Through this work, data science positions itself in the middle of all things—capable of engaging this, that, or any domain—and thus prospecting is a key driver of data science’s ongoing formation as a universal science. (shrink)

We describe how the set of tools, practices, and social relations known as “precision agriculture” is defined, promoted, and debated. To do so, we perform a critical discourse analysis of popular and trade press websites. Promoters of precision agriculture champion how big data analytics, automated equipment, and decision-support software will optimize yields in the face of narrow margins and public concern about farming’s environmental impacts. At its core, however, the idea of farmers leveraging digital infrastructure in their operations is not (...) new, as agronomic research in this vein has existed for over 30 years. Contemporary discourse in precision ag tends to favour emerging digital technologies themselves over their embeddedness in longstanding precision management approaches. Following several strands of science and technology studies research, we explore what rhetorical emphasis on technical innovation achieves, and argue that this discourse of novelty is a reinvention of precision agriculture in the context of the growing “smart” agricultural economy. We overview six tensions that remain unresolved in this promotional rhetoric, concerning the definitions, history, goals, adoption, uses, and impacts of precision agriculture. We then synthesize these in a discussion of the extent to which digital tools are believed to displace farmer decision-making and whether digital agriculture addresses the biophysical heterogeneity of farm landscapes or land itself has become an “experimental technology”—a way to advance the general development of artificial intelligence. This discussion ultimately helps us name a larger dilemma: that the smart agricultural economy is perhaps less about supporting land and its stewards than promising future tech and profits. (shrink)

Der Aufstieg der Datenökonomie impliziert erhebliche Auswirkungen auf die Gesellschaft und deren kollektive Verfasstheit. Mit der Inwertsetzung des Wissens über den Einzelnen gehen zwangsläufig auch neue Formen seiner Adressierung einher. Ob als Werbekunde, Versicherungsnehmer oder Kreditempfänger, auf der Grundlage der erfassten Dispositionen kann der Einzelne individuell oder als Teil eines Kollektivs taxiert werden. Der Beitrag fragt nach den Auswirkungen einer solchen datengestützen Kollektivbildung, die extern über ökonomische Selektionsmechanismen vorangetrieben wird. Konträr zu den vorherrschenden Mobilisierungsnarrativen im Digitalisierungszeitalter wird argumentiert, dass sie (...) das Soziale tendenziell reproduziert. (shrink)

The article explores the normative concerns raised for gig workers by algorithmic management (AM), by embracing an ethnographically sensitive approach to philosophical inquiry. Inspired by Michel de Certeau’s concept of ‘tactics’, the article suggests interpreting workers’ attempts to ‘trick the algorithm’ and escape some of AM’s constraints as ways to reclaim agency, in the absence of suitable organizational conditions for its affirmative exercise. The kind of agency specifically deployed by workers in cooperative settings is referred to as ‘contributive agency’, broadly (...) defined as workers’ control over their contribution in multiple dimensions – epistemic, relational, participatory and protective. Contributive agentic capacities are not mere properties of agents, but organizationally mediated capacities that can be more or less enabled or constrained depending on the contributive context. It is argued that below a certain threshold, AM’s agency-constraining features are objectionable and desirable agency-enabling organizational conditions are identified in the four dimensions. (shrink)

Digital systems are reshaping how we engage with music as a sounding dimension of cultural life that is capable of being transformed into a commodity. At the same time, as we increasingly engage through digital media with each other and with virtual others, attributes of music that underpin our capacity to interact communicatively are disregarded or overlooked within those media. Even before the advent of technologies of music reproduction, music was susceptible to assimilation into economic acts of exchange. What is (...) new in the digital world is the way in which modes of engagement with music are themselves being absorbed into an economy built on the datafication of virtual acts and the digital shadows of casual preferences. But music is more than just sounds that are culturally sanctioned as musical. Music is manifested as behaviours, and in interactive behaviour. Music is participatory as well as presentational, and in the participatory mode—involving collective, non-specialist, interactive real-time music-making—has significant individual and social consequences. Yet music as real-time participation is largely absent from the virtual world, with potential social costs that remain to be understood. Moreover, our everyday, face-to-face communicative—conversational—interactions are imbued with patterns between interlocutors that are musical, in that they share features with what we are happy to describe as “music”. These features are presently lacking in digital systems designed to subserve communicative functions, and this paper will consider the significant implications for our interactions with machines to which their successful incorporation into voice–user interfaces would give rise. (shrink)

In this paper, I approach the power of digital platforms by using the republican concept of domination. More specifically, I argue that the traditional, agent-relative interpretation of domination, in the case of digital domination, is best supplemented by a more radical version, on which republicans ought to give priority to structural elements. I show how radical republicanism draws attention to (1) the economic rationales and the socio-technical infrastructures that underlie and support digital platforms and to (2) the forms of influence (...) that are directed at cognitive dimensions, such as habituation and routinisation, which are particularly relevant for the power of digital platforms. These insights also imply that republicans have reason to favour a more structural response to digital platforms over more direct and individualised forms of control that fit with a ‘standard’ republican approach, such as securing exit options and requiring user consent. (shrink)

This article discusses the datafied embodiment of the Internet of Bodies (IoB) technology by applying the methodology of postphenomenology. Firstly, the author claims that the boundaries of dual distinction between real and virtual, online and offline, and embodiment and disembodiment have become increasingly blurred. Secondly, the author argues that postphenomenology can help us to study today’s emerging technologies’ mediating role in human–world relations. Thirdly, the author analyses the implication of embodiment from phenomenological and postphenomenological perspectives and then demonstrates in what (...) sense the data collected from the IoB devices can constitute our embodiment and selfhood. Fourthly, the author elucidates how the IoB devices are datafying our bodies and the whole lifeworld and how these devices mediate and transform our religious practices and experiences. Fifthly, the author points out that the Quantified Religion as the possible new religious model would smooth out the differences and diversities between religions and then create homogeneous religious data selves, which will mediate, reshape, constitute and even replace our physical selves. Ultimately, the author argues that responsible designing of the IoB devices and establishing the ownership of personal religious data can be seen as significant measures in the face of the risk of our quantified religious future. Contribution: This article contributes to understanding the potential religious transformations caused by the IoB technology. This article analyses the mediating role the IoB technology plays in the relationship between humans and the world through a postphenomenological perspective, thereby explaining how body data harvested from the IoB devices can datafy and constitute our embodiment and selfhood. The article argues that the Quantified Religion as a new religious model will emerge in the future IoB era, and it will mediate, constitute and shape our religious practices and experiences through personal data harvesting and analysis. (shrink)

Policymakers need to start considering the impact smart connected toys (SCTs) have on children. Equipped with sensors, data processing capacities, and connectivity, SCTs targeting children increasingly penetrate pervasively personal environments. The network of SCTs forms the Internet of Toys (IoToys) and often increases children's engagement and playtime experience. Unfortunately, this young part of the population and, most of the time, their parents are often unaware of SCTs’ far-reaching capacities and limitations. The capabilities and constraints of SCTs create severe side effects (...) at the technical, individual, and societal level. These side effects are often unforeseeable and unexpected. They arise from the technology's use and the interconnected nature of the IoToys, without necessarily involving malevolence from their creators. Although existing regulations and new ethical guidelines for artificial intelligence provide remedies to address some of the side effects, policymakers did not develop these redress mechanisms having children and SCTs in mind. This article provides an analysis of the arising side effects of SCTs and contrasts them with current regulatory redress mechanisms. We thereby highlight misfits and needs for further policymaking efforts. (shrink)

In response to growing concerns of bias, discrimination, and unfairness perpetuated by algorithmic systems, the datasets used to train and evaluate machine learning models have come under increased scrutiny. Many of these examinations have focused on the contents of machine learning datasets, finding glaring underrepresentation of minoritized groups. In contrast, relatively little work has been done to examine the norms, values, and assumptions embedded in these datasets. In this work, we conceptualize machine learning datasets as a type of informational infrastructure, (...) and motivate a genealogy as method in examining the histories and modes of constitution at play in their creation. We present a critical history of ImageNet as an exemplar, utilizing critical discourse analysis of major texts around ImageNet’s creation and impact. We find that assumptions around ImageNet and other large computer vision datasets more generally rely on three themes: the aggregation and accumulation of more data, the computational construction of meaning, and making certain types of data labor invisible. By tracing the discourses that surround this influential benchmark, we contribute to the ongoing development of the standards and norms around data development in machine learning and artificial intelligence research. (shrink)

The proliferation of digital data has been the impetus for the emergence of a new discipline for the study of social life: ‘computational social science’. Much research in this field is founded on the premise that society is a complex system with emergent structures that can be modeled or reconstructed through digital data. This paper suggests that computational social science serves practical and legitimizing functions for digital capitalism in much the same way that neoclassical economics does for neoliberalism. In recognition (...) of this homology, this paper develops a critique of the complexity perspective of computational social science and argues for a heterodox computational social science founded on the meta-theory of critical realism that is critical, methodological pluralist, interpretative and explanative. This implies diverting computational social science’ computational methods and digital data so as to not be aimed at identifying invariant laws of social life, or optimizing state and corporate practices, but to instead be used as part of broader research strategies to identify contingent patterns, develop conjunctural explanations, and propose qualitatively different ways of organizing social life. (shrink)

Healthcare provision, like many other sectors of society, is undergoing major changes due to the increased use of data-driven methods and technologies. This increased reliance on big data in medicine can lead to shifts in the norms that guide healthcare providers and patients. Continuous critical normative reflection is called for to track such potential changes. This article presents the results of an interview-based study with 20 German and Swiss experts from the fields of medicine, life science research, informatics and humanities (...) of digitalisation. The aim of the study was to explore expert opinions regarding current challenges and opportunities related to data-driven medicine and medical research and to provide a methodological framework for empirically grounded, continuous normative reflection. To this end, we developed a heuristic tool to map and structure empirical findings for normative analysis. Using this tool, our interview material points to a polarisation between individualistic and collectivistic orientated argumentations among experts. The study shows that a multilevel analysis is required to deal with complex normative implications of data-driven approaches in medical research and healthcare. (shrink)

Over the last decade, ‘data scientists’ have burst into society as a novel expert role. They hold increasing responsibility for generating and analysing digitally captured human experiences. The article considers their professionalization not as a functionally necessary development but as the outcome of classification practices and struggles. The rise of data scientists is examined across their discursive classification in the academic and economic fields in both the USA and Germany. Despite notable differences across these fields and nations, the article identifies (...) two common subjectivation patterns. Firstly, data scientists are constructed as hybrids, who combine generally conflictive roles as both generalists and specialists; technicians and communicators; data exploiters and data ethicists. This finding is interpreted as demonstrating a discursive distinction between data scientists and other competing and supposedly more one-dimensional professionals, such as statisticians or computer scientists. Secondly, the article uncovers a discursive construction that interpellates data scientists as discoverers of needs. They are imagined as explorative work subjects who can establish growth for digital capitalism by generating behavioural patterns that allow for personalization, customization and optimization practices. (shrink)

This article focuses on key roles that the ill-defined concept of ‘public benefit’ plays in accessing the public health data held by the UK’s National Health Service. Using the concept of the ‘trade-off fallacy’, this article argues that current data access and governance structures, based on particular construals of public benefit in the context of public health data, largely negate the possibility of effective control by individuals over future uses of personal health data. This generates a health data version of (...) the trade-off fallacy that enables widespread involvement of commercial actors in personal data, despite public concerns over commercial involvement in, and potential exploitation of, public health data. The article suggests that, despite ostensibly robust regulatory and governance structures, this publicly held data is potentially subject to similar logics of accumulation as seen elsewhere in the digital economy, highlighting the inadequacies of current data regulatory frameworks in the digital era. (shrink)

In this article, I consider how the redesign of vehicle dashboards has restructured car-related data processes. I do so by charting the emergence of two such processes enabled by the redesign of vehicle dashboards: firstly, the transformation of ‘geodata’ into ‘navigational data’ with the integration of voice-activated navigation systems into vehicle dashboards, and secondly, the transformation of ‘vehicle data’ into ‘driving data’ in the convergence, and customization, of dashboard features and functionality. Both transformations are enabled through strategic design decisions, persuading (...) drivers to participate in novel practices they might otherwise not. Firstly, in that voice-activation is depicted as a seamless, unmediated interface between the normal, natural speech of a driver, and the vehicle itself. Secondly, through the strategy of control, the driver is persuaded to believe they have full customizable power within, and of, the vehicle. The systems discussed here – a voice-activated navigation system built on the What3words platform, and a ‘widescreen’ dashboard in a range of Mercedes-Benz vehicles – are representative of broader efforts within the automotive industry to cultivate a newly ‘datafied’ driving experience. (shrink)

The Anthropocene, as one of the core concepts currently used to understand and reflect on the relationships among humans, species, and planet, has received widespread attention and discussion in the global academic community. As one of the important alternative concepts to the Anthropocene, the term Plantationocene was first proposed by Haraway et al. in October 2014. Compared to the former, it reveals the fundamental characteristics of the modern era, and continues to enrich its theoretical connotations amidst rapid shifts in social (...) concepts and practices. Tracing and sorting out the genealogy of this concept over less than a decade since its inception allows for a microhistorical study of conceptual history, revealing three key dimensions of its meaning: (i) a critique of the history of (post)colonialism and extractivism, (ii) although plantations are known worldwide for monocrop agriculture and have so-called keystone species, they are essentially a multispecies symbiotic system. From its inception, the concept of the Plantationocene inherently encompasses the idea of “multispecies entanglement and multispecies politics,“ and (iii) a metaphor for structural power relations from real word to digital world. Research indicates that the Plantationocene has become a framework for understanding the connection between ecological destruction and social inequality. In the game of global ecological politics and academic power relationships in the post-humanist era, it requires us to pay attention not only to the relationships among humans but also those among multispecies to build a more just and sustainable society in the future. (shrink)

One of the key features of the contemporary data economy is the widespread circulation of data and its interoperability. Critical data scholars have analysed data repurposing practices and other factors facilitating the travelling of data. While this approach focused on flows provides great potential, in this article we argue that it tends to overlook questions of attachment and belonging. Drawing upon ethnographic fieldwork within a Danish data-linkage infrastructure, and building upon insights from archival science, we discuss the work of data (...) practitioners enabling the repurposing of pathology samples extracted from patients for the conduct of ‘personal medicine’ – our term to discuss the so-called old-fashioned treatment of patients – towards personalised medicine. This first involves ‘getting to know’ the tissues and unpacking their previous uses and meanings, then detaching them from their original source to extract data from such tissues and making them flow towards a new container where they can be worked on and connected with other data. As data practitioners make these tissues travel, transforming them into research data, they organise the attachments of data to new agendas, persons and places. Crucially, in our case, we observe the prominence of national attachments, whereby managing tissues and data in and out of containers involves tying them to the nation to serve its interests. We thus expose how the building of data linkage infrastructures entails more than the accumulation and curation of data, but also involves crafting meanings, futures and belonging to specific communities and territories. (shrink)

This article offers a historical inquiry into behaviorism and its impact on standard of judgement concerning education policies. Drawing from Aldous Huxley’s reservation towards behaviorism as a scientific movement that naturalizes the role of control in human affairs, the paper maps the impact of behaviorism on economics of education. By tracing the influence of behaviorism in both rational (human capital theory) and quasi-rational (behavioral insight) economics, we draw attention to the activity of knowledge-making that describes and prescribes agency. The paper (...) demonstrates how policy instruments and outcomes are intimately linked to assumptions about personhood, and in the case of behavioral insight, they contribute to the scope of decision-making entrusted to government and business. Utilizing a genealogical approach, the paper invites ethical reflections on the long-term implications of behavioral economics in light of automation. (shrink)

This article illustrates how racial capitalism can enhance understandings of data, capital, and inequality through an in-depth study of digital platforms used for intervening in gender-based violence. Specifically, we examine an emergent sociotechnical strategy that uses software platforms and artificial intelligence chatbots to offer users emergency assistance, education, and a means to report and build evidence against perpetrators. Our analysis details how two reporting apps construct data to support institutionally legible narratives of violence, highlighting overlooked racialised dimensions of the data (...) capital generated through their use. We draw attention to how they reinforce property relations built on extraction and ownership, capital accumulation that reinforces benefits derived through data property relations and ownership, and the commodification of diversity and inclusion. Recognising these patterns are not unique to anti-violence apps, we reflect on how this example aids in understanding how racial capitalism becomes a constitutive element of digital platforms, which more generally extract information from users, rely on complex financial partnerships, and often sustain problematic relationships with the criminal legal system. We conclude with a discussion of how racial capitalism can advance scholarship at the intersections of data and power. (shrink)

Policymakers need to start considering the impact smart connected toys (SCTs) have on children. Equipped with sensors, data processing capacities, and connectivity, SCTs targeting children increasingly penetrate pervasively personal environments. The network of SCTs forms the Internet of Toys (IoToys) and often increases children's engagement and playtime experience. Unfortunately, this young part of the population and, most of the time, their parents are often unaware of SCTs’ far-reaching capacities and limitations. The capabilities and constraints of SCTs create severe side effects (...) at the technical, individual, and societal level. These side effects are often unforeseeable and unexpected. They arise from the technology's use and the interconnected nature of the IoToys, without necessarily involving malevolence from their creators. Although existing regulations and new ethical guidelines for artificial intelligence provide remedies to address some of the side effects, policymakers did not develop these redress mechanisms having children and SCTs in mind. This article provides an analysis of the arising side effects of SCTs and contrasts them with current regulatory redress mechanisms. We thereby highlight misfits and needs for further policymaking efforts. (shrink)

This paper reports on a two-year, field-based study set in a charter management organization, a not-for-profit educational organization that operates 18 public schools exclusively in the Black and Latinx communities of South and East Los Angeles. At CMO-LAX, the nine-member Data Team pursues the organization's avowed mission of making public schools data-driven, primarily through the aggregation, analysis, and visualization of digital data derived from quotidian educational activities. This paper draws on the theory of racialized organizations to characterize aspects of data-driven (...) management of public education as practiced by CMO-LAX. I explore two examples of how CMO-LAX shapes data to support racial projects: the reconstruction of the figure of chronic truants and the incorporation of this figure in a calculative regime of student accomplishment. Organizational uses of data support a strategy I call productive myopia, a way of pursuing racial projects via seemingly independent, objective quantifications. This strategy allows the organization to claim to mitigate racial projects and, simultaneously, to accommodate them. This paper concludes by arguing for approaches to research and practice that center racial projects, particularly when data-intensive tools and platforms are incorporated into the provision of public goods and services such as education. (shrink)