The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with specific and knowable outcomes, towards actions by many unaware that they may have taken actions with unintended consequences for anyone. Responses will require a rethinking of ethical choices, the lack thereof and (...) how this will guide scientists, governments, and corporate agencies in handling Big Data. This essay elaborates on the ways Big Data impacts on ethical conceptions. (shrink)

This paper builds off the Our Data Ourselves research project, which examined ways of understanding and reclaiming the data that young people produce on smartphone devices. Here we explore the growing usage and centrality of mobiles in the lives of young people, questioning what data-making possibilities exist if users can either uncover and/or capture what data controllers such as Facebook monetize and share about themselves with third-parties. We outline the MobileMiner, an app we created to consider how gaining access to (...) one’s own data not only augments the agency of the individual but of the collective user. Finally, we discuss the data making that transpired during our hackathon. Such interventions in the enclosed processes of datafication are meant as a preliminary investigation into the possibilities that arise when young people are given back the data which they are normally structurally precluded from accessing. (shrink)

This article investigates the claims and complexities involved in the platform-based economics of health and fitness apps. We examine a double-edged logic inscribed in these platforms, promising to offer personal solutions to medical problems while also contributing to the public good. On the one hand, online platforms serve as personalized data-driven services to their customers. On the other hand, they allegedly serve public interests, such as medical research or health education. In doing so, many apps employ a diffuse discourse, hinging (...) on terms like “sharing,” “open,” and “reuse” when they talk about data extraction and distribution. The analytical approach we adopt in this article is situated at the nexus of science and technology studies, political economy, and the sociology of health and illness. The analysis concentrates on two aspects: datafication and commodification. We apply these analytical categories to three specific platforms: 23andMe, PatientsLikeMe, and Parkinson mPower. The last section will connect these individual examples to the wider implications of health apps’ data flows, governance policies, and business models. Regulatory bodies commonly focus on the safety and security of apps, but pay scarce attention to health apps’ techno-economic governance. Who owns user-generated health data and who gets to benefit? We argue that it is important to reflect on the societal implications of health data markets. Governments have the duty to provide conceptual clarity in the grand narrative of transforming health care and health research. (shrink)

This introduction to the special issue on data and agency argues that datafication should not only be understood as the process of collecting and analysing data about Internet users, but also as feeding such data back to users, enabling them to orient themselves in the world. It is important that debates about data power recognise that data is also generated, collected and analysed by alternative actors, enhancing rather than undermining the agency of the public. Developing this argument, we first make (...) clear why and how the question of agency should be central to our engagement with data. Subsequently, we discuss how this question has been operationalized in the five contributions to this special issue, which empirically open up the study of alternative forms of datafication. Building on these contributions, we conclude that as data acquire new power, it is vital to explore the space for citizen agency in relation to data structures and to examine the practices of data work, as well as the people involved in these practices. (shrink)

There are growing discontinuities between the research practices of data science and established tools of research ethics regulation. Some of the core commitments of existing research ethics regulations, such as the distinction between research and practice, cannot be cleanly exported from biomedical research to data science research. Such discontinuities have led some data science practitioners and researchers to move toward rejecting ethics regulations outright. These shifts occur at the same time as a proposal for major revisions to the Common Rule—the (...) primary regulation governing human-subjects research in the USA—is under consideration for the first time in decades. We contextualize these revisions in long-running complaints about regulation of social science research and argue data science should be understood as continuous with social sciences in this regard. The proposed regulations are more flexible and scalable to the methods of non-biomedical research, yet problematically largely exclude data science methods from human-subjects regulation, particularly uses of public datasets. The ethical frameworks for Big Data research are highly contested and in flux, and the potential harms of data science research are unpredictable. We examine several contentious cases of research harms in data science, including the 2014 Facebook emotional contagion study and the 2016 use of geographical data techniques to identify the pseudonymous artist Banksy. To address disputes about application of human-subjects research ethics in data science, critical data studies should offer a historically nuanced theory of “data subjectivity” responsive to the epistemic methods, harms and benefits of data science and commerce. (shrink)