The importance of digital technologies for social and economic developments and a growing focus on data collection and privacy concerns have made the Internet a salient and visible issue in global politics. Recent developments have increased the awareness that the current approach of governments and business to the governance of the Internet and the adjacent technological spaces raises a host of ethical issues. The significance and challenges of the digital age have been further accentuated by a string of highly exposed (...) cases of surveillance and a growing concern about issues of privacy and the power of this new industry. This special issue explores what some have referred to as the “Internet-industrial complex”—the intersections between business, states, and other actors in the shaping, development, and governance of the Internet. (shrink)

Transparency is an increasingly prominent area of research that offers valuable insights for organizational studies. However, conceptualizations of transparency are rarely subject to critical scrutiny and thus their relevance remains unclear. In most accounts, transparency is associated with the sharing of information and the perceived quality of the information shared. This narrow focus on information and quality, however, overlooks the dynamics of organizational transparency. To provide a more structured conceptualization of organizational transparency, this article unpacks the assumptions that shape the (...) extant literature, with a focus on three dimensions: conceptualizations, conditions, and consequences. The contribution of the study is twofold: On a conceptual level, we provide a framework that articulates two paradigmatic positions underpinning discussions of transparency, verifiability approaches and performativity approaches; on an analytical level, we suggest a novel future research agenda for studying organizational transparency that pays attention to its dynamics, paradoxes, and performative characteristics. (shrink)

Digital transformations and processes of “datafication” fundamentally reshape how information is produced, circulated and given meaning. In this article, we provide a concept of “datastructuring” which seeks to capture this reshaping as both a product of and productive of social activity. To do this we focus on how new forms of social action map onto and are enabled by technological changes related to datafication, and how new forms of datafied social action constitute a form of knowledge production which becomes embedded (...) in technologies themselves. We illustrate the potential of the datastructuring concept with empirical examples which also serve to highlight some new avenues for research and some empirical questions to explore further. We suggest a focus on datastructuring can ignite scholarly debates across disciplines that may share an interest in the technological configurations, sorting activities, and other socio-material forces that shape digital spaces, but which are rarely brought together. Such cross-disciplinary conceptualizations may give more attention to how information is structured and organized, becomes “algorithmically recognizable”, and emerges as visible in digital, datafied spaces. Such a concept, we suggest, may help us better understand the novel ways in which “backstage datawork” and “data sorting processes” gain traction in political interventions, commercial processes, and social ordering. (shrink)

Policy discussions and corporate strategies on machine learning are increasingly championing data reuse as a key element in digital transformations. These aspirations are often coupled with a focus on responsibility, ethics and transparency, as well as emergent forms of regulation that seek to set demands for corporate conduct and the protection of civic rights. And the Protective measures include methods of traceability and assessments of ‘good’ and ‘bad’ datasets and algorithms that are considered to be traceable, stable and contained. However, (...) these ways of thinking about both technology and ethics obscure a fundamental issue, namely that machine learning systems entangle data, algorithms and more-than-human environments in ways that challenge a well-defined separation. This article investigates the fundamental fallacy of most data reuse strategies as well as their regulation and mitigation strategies that data can somehow be followed, contained and controlled in machine learning processes. Instead, the article argues that we need to understand the reuse of data as an inherently entangled phenomenon. To examine this tension between the discursive regimes and the realities of data reuse, we advance the notion of reuse entanglements as an analytical lens. The main contribution of the article is the conceptualization of reuse that places entanglements at its core and the articulation of its relevance using empirical illustrations. This is important, we argue, for our understanding of the nature of data and algorithms, for the practical uses of data and algorithms and our attitudes regarding ethics, responsibility and regulation. (shrink)

While we witness a growing belief in transparency as an ideal solution to a wide range of societal problems, we know less about the practical workings of transparency as it guides conduct in organizational and regulatory settings. This article argues that transparency efforts involve much more than the provision of information and other forms of ‘sunlight’, and are rather a matter of managing visibilities than providing insight and clarity. Building on actor-network theory and Foucauldian governmentality studies, it calls for careful (...) attention to the ways in which transparency ideals are translated into more situated practices and become associated with specific organizational and regulatory concerns. The article conceptualizes transparency as a force that shapes conduct in organizational and socio-political domains. In the second section, this conceptualization of transparency as a form of ‘ordering’ is substantiated further by using illustrations of the effects of transparency efforts in the internet domain. (shrink)

This paper argues that the dichotomization of technological determinism and social constructivism in parts of the literature on the technology-society nexus conceals that the two approaches study different objects. On the backdrop of the argument that technological determinists concern themselves with material aspects and social constructivists with ideational aspects of the relationship between technology and society, the paper presents two alternative approaches, which provide a focus on both materiality and ideation. Finally, the paper exemplifies briefly the relevance of this approach (...) for investigations of the governance of new information- and communication technologies, such as the Internet. (shrink)

Framing datafication as new form of knowledge production has become a trope in both academic and commercial contexts. This special theme examines and ultimately rejects the familiar grand claims of datafication, to instead pay attention to emergent conversations that seek to take a more nuanced stock of the status and nature of datafied knowledge production. The articles in this special theme thus engage with datafied knowledge production through elaborate explorations of how datafied knowledge depends on the contexts of its production (...) and the forms of knowledge production that precede it in those contexts. Our basic argument is that while the resources, material features and analytical operations involved in datafied knowledge production may be different, many fundamental concerns about epistemology, ontology and methods remain relevant to understand what shapes it. We still need to understand and explicate the assumptions, operations and consequences of emergent forms of knowledge production. If datafied knowledge production is neither a clean revolutionary break with past forms of knowledge production nor a balloon of pure hype, the articles in this special theme ask: what does the phenomenon of datafied knowledge production look like? Which digital and datafied infrastructures support its future development? And what potentialities and limits do such forms of analysis and knowledge production contain? (shrink)