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This article examines the datafication of ageing by drawing on a practice approach toward care. We describe the datafication of ageing as a matter of care, achieved through the local tinkering of actors – technology designers, care staff, older adults, and highlighting the practices necessary to develop, maintain and implement data infrastructures. This paper draws on research conducted in a qualitative interview study in a LTC facility that uses AI-supported sensors to detect, predict and alarm care staff about falls of older residents. 18 interviews with developers, staff, residents and interest groups were conducted, as well as 24 h of participant observation in the care facility. The results reveal how AI-development for older target groups is characterized by absent data on these populations. Designers turn to practices that decontextualize data from the realities of older adults, relying on domain experts or synthetic data. This decontextualization of data requires recontextualization, with staff and older residents ensuring that the system functions smoothly, adapting their behavior, protecting the system from making false decisions and making existing care arrangements 'fit' the databases used to monitor activities in these arrangements. The ambivalent position of older adults in this data assemblage is further highlighted, as their caring practices are made invisible by different actors through ageist stereotypes, positioning them as being too frail to understand and engage with the system. While their bodily behavior is core for the databases, their perspective on and engagements with the operating system are marginalized, rendering some aspects of ageing hyper-visible, and others invisible. [ABSTRACT FROM AUTHOR]

Secondary data collection practices are often opaque to platform users and researchers but known to shape individuals' life chances in significant and unequal ways. In this paper, we articulate a clear relationship between invisible, unwanted data collection and its adverse, downstream consequences for marginalized groups by examining instances in the criminal justice field where social media data function as criminal evidence. We show how social media, as a now common form of courtroom evidence, may structurally work against public defense attorneys and defendants with low socioeconomic status (SES). Drawing on casework interviews with public defenders in New York City, we illustrate the mechanisms by which low-SES criminal defendants are at a disadvantage through overbroad search warrants, asymmetrical cooperation, and prejudicial evidence. We discuss the lessons and implications of our case study for platform privacy and governance research and for the courts. [ABSTRACT FROM AUTHOR]

There are currently no concerted attempts to understand the role of whistleblowers in the new social and political environment created by digital ICTs. Digital ICTs drive an accelerating visibility where elites and citizens constantly acquire new tools to track, surveil, and scrutinize each other. Moreover, these technologies make possible a new kind of invisibility. Increasingly complex modes of digital data production and usage generate grey areas that seem to escape legal jurisdiction and democratic oversight. With their privileged access inside these grey areas, conscientious employees-turned-whistleblowers are likely to become key sources for the disclosure of serious wrongdoing in the coming years. The argument is empirically illustrated through three cases that represent different types of grey areas in advanced democracies: big data surveillance (Edward Snowden), tax havens (Antoine Deltour and the Panama and Paradise Papers), and digital political profiling (Christopher Wylie). [ABSTRACT FROM AUTHOR]

Despite extensive studies on ethical data use and algorithms, little is known about the ethical perspectives of tech workers – insiders of a profession that heavily relies on data and algorithms. Nor have there been sufficient cross-national comparisons of their perspectives. Relying on interviews with 98 tech workers in China and the US, this paper is guided by two questions: (1) What are tech workers' perceptions of big data ethics, and (2) what are the cross-national similarities and differences in China and the US? The study found that there are cross-national similarities in tech workers' cautious enthusiasm about the applications of big data in their work, as well as in their complex and ambivalent ethical perspectives on the use of big data in government digital surveillance. The main cross-national differences occur in tech workers' perceptions of whether big data may reinforce social inequalities. US-based tech workers are concerned about the reinforcement of race and gender-based inequalities through the use of big data, whereas their colleagues in China are optimistic that the use of big data may reduce income-based inequalities across geographical regions. The study's findings have implications for how to leverage tech workers' influence and promote the ethical use of data and algorithms. [ABSTRACT FROM AUTHOR]

This paper discusses the relevance of Georg Lukács' 1923 book History and Class Consciousness in the context of digital capitalism. It does so by analysing how Lukács' concepts of the dialectic of subject and object, ideology, reification, reified consciousness matter today in the context of big data and digital capitalism. The essay shows that History and Class Consciousness' critique of reification, ideology, and reified consciousness remains highly topical in the age of digital capitalism and big data. Lukács' analysis allows us to critically analyse how social media, big data, and various other Internet technologies are used as tools of reification. At the same time, Lukács reminds us that only human praxis can establish alternatives. [ABSTRACT FROM AUTHOR]

In the wake of the digital revolution and connected technologies, societies store an ever-increasing amount of data on humans, their preferences, and behavior. These modern technologies create a trust challenge, insofar as individuals have to trust data collectors such as private organizations, government institutions, and researchers that their data is not misused. Privacy regulations should increase trust because they provide laws that increase transparency and allow for punishment in cases in which the trustee violates trust. The introduction of the General Data Protection Regulation (GDPR) in May 2018 – a wide-reaching regulation in EU law on data protection and privacy that covers millions of individuals in Europe – provides a unique setting to study the impact of privacy regulation on trust in data collectors. We collected survey panel data in Germany around the implementation date and ran a survey experiment with a GDPR information treatment. Our observational and experimental evidence does not support the hypothesis that the GDPR has positively affected trust. This finding and our discussion of the underlying reasons are relevant for the wider research field of trust, privacy, and big data. [ABSTRACT FROM AUTHOR]

Digital platforms and learning analytics are becoming increasingly widespread in the education sector: commercial corporations argue their benefits for teaching and learning, thereby endorsing the continuous automated collection and processing of student data for measurement, assessment, management, and identity formation. Largely missing in these discourses, however, are the potential costs of datafication for pupils' and teachers' agency and the meaning of education itself. This article explores the general discursive framing by which these surveillant practices in education have come to seem natural. Through a study of commercial suppliers of educational platforms, we show how the prevailing vision of datafication in their discourses categorises software systems, not teachers, as central to education, reimagining space, time, and agency within educational processes around the organisation of data systems and the demands of commercial data production. Not only does this legitimate the new connective environment of dataveillance (that is, surveillance through data processing), but it also naturalises a wider normative environment in which teachers and students are assigned new roles and responsibilities. In the process, the panoptic possibilities of ubiquitous commercial access to personal educational data are presented as part of a virtuous circle of knowledge production and even training for good citizenship. This broader rethinking of education through surveillance must itself be critiqued. [ABSTRACT FROM AUTHOR]

This article develops a sociotechnical conceptualisation of data literacies in relation to citizens' data practices: highlighting the agentic, contextual, critical, and social aspects of data skills and competencies, it frames data literacies as both discursive and material. In order for civil society organisations to make sense of big, small, open and other data they need multiple skills, beyond the technical; it is, therefore, unhelpful to talk about a single form of data literacy. It is more helpful to consider how such literacies in the plural develop within the material social contexts of civic cultures, and how they can progress in tandem with critical awareness about the power aspects of data, so they can become central tenets of data advocacy. The primary purpose of the article is to move forward the debate around how to conceptualise data literacy – and to question how far the concept is useful in the first place. The article draws on empirical research and starts from the premise that it is imperative to develop frameworks and training schemes that enable civil society actors and publics more generally to use open data, to make data more relevant to stakeholders, and to support their engagement in policy debates around datafication. [ABSTRACT FROM AUTHOR]