Without a critical approach to big data it risks becoming an increasingly sophisticated paradigm for coercion (original) (raw)
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Without a critical approach to big data it risks becoming an increasingly sophisticated paradigm for coercion blogs.lse.ac.uk /impactofsocialsciences/2017/07/05/big-data-risks-becoming-sophisticated-paradigm-for-coercion/ We are in the midst of a data revolution, one reliant on the capture, analysis, and visual representation of enlarged quantitative data, in increasingly digital formats. Hamish Robertson and Joanne Travaglia argue that big data quantification is now not only a mechanism for extracting information but has become an idea with social and political power in its own right. The lack of critique of quantitative methods and their application contributes to the existing and potentially coercive power of digital information systems and their attendant methods, and enhances the potential for " collateral damage " associated with such applications. In 2015 we wrote two articles addressing some of the problems associated with social data practices in the digital information age. One discussed the need to re-conceive how people as social entities are included, represented, and theorised in big data environments. The second addressed the long developmental history of the " big data " paradigm and how big data has been used to document and analyse the socially " manufactured " attributes of groups and populations. A key conclusion of this initial work was what we saw as the considerable potential of such data to have coercive effects on social groups identified and " managed " through such systems and technologies. This piece focuses more directly on the idea of data itself being coercive and how such coercion plays out in our emerging big data environment. Epistemic machineries and ontological effects Ian Hacking has explored the pervasive and iterative effects of category constructions in social environments. A central issue in knowledge creation today is the pervasiveness of quantification. To paraphrase Rob Kitchin, we are now in the midst of a data revolution, one which relies on the capture, analysis, and visual representation of enlarged quantitative data, in increasingly digital formats, each of which is amenable to multiple analytical and visualisation techniques. In this context the ability to quantify what was previously considered inaccessible has become so embedded in the discourse of " innovative knowledge production " as to constitute an epistemic virtue. As a result, big data quantification has not only become a mechanism for extracting information but an idea with social and political power in its own right. Over the past few years a vigorous debate has emerged about the ways in which digital technologies rely on modelling, algorithms, and related " artificial intelligence agents " for their epistemic authority and influence. In this context, the algorithm is shorthand for more complex programming and analysis problems. One issue to arise is that of analysis producing or reinforcing social prejudices entering the digital domain via algorithm design and application. Since many algorithms seek to combine and quantify complex social phenomena in a reductive manner, there may be limited scope for critical reflexivity in their production. At the same time there is an inherent risk in the application of such tools in the construction of specific " social problems " in the same way that Charles Booth created both maps of poverty and maps of " criminality " in London. An ethics of big data is also beginning to emerge in response to these types of concerns. The application of many quite conventional mathematical techniques can acquire a social and political force through their integration within information technology systems, software, and model development. This, we propose, is due in part to a lack of critical appraisal of concepts drawn from social science and social policy and their normalisation for broader political agendas.
Introduction: Politics of Big Data Special Issue, Digital Culture & Society 2:2, 2016
This special issue offers a critical dialogue around the myriad political dimen-sions of Big Data. We begin by recognising that the technological objects of Big Data are unprecedented in the speed, scope and scale of their computation and knowledge production. This critical dialogue is grounded in an equal recogni-tion of continuities around Big Data’s social, cultural, and political economic dimensions. Big Data, then, is political in the same way in which identity, the body, gender, sexuality, race and ethnicity are political, that is, as sites of struggle over meaning, interpretations, and categorisations of lived experience. Big Data is political in the way circuits of production, distribution, and consumption are political; that is, as sites where access, control and agency are unequally distrib-uted through asymmetrical power relations, including relations of data produc-tion. Big Data is political in the way contemporary politics are being reshaped by data analysis in electoral campaign strategy, and through state surveillance as strikingly evidenced by the Snowden revelations on the NSA and GCHQ. Big Data is also political in the contestation of this advanced scientific practice, wherein the generation of data at unprecedented scale promises a precise and objective measure of everyday life. However, the computational dreams of an N = all verisimilitude – that is, of datasets providing a one-to-one correspon-dence to a given phenomenon – are haunted by the normative biases embedded in all data. This is not to suggest that Big Data – more specifically processes of datafication1 – are best or at all understood as socially constructed. Indeed, discursive analysis or unreconstructed social theory cannot fully grasp how data re-articulates the social, cultural, political and economic in a deeply recursive manner. Thus, any political reckoning must equally account for the materiality of data, alongside the logic guiding its processes and the practices that deploy its tools. In short, what are the power relations animating the knowledge generated by data analytics?
The era of Big Data has begun. Computer scientists, physicists, economists, mathematicians, political scientists, bio-informaticists, sociologists, and other scholars are clamoring for access to the massive quantities of information produced by and about people, things, and their interactions. Diverse groups argue about the potential benefits and costs of analyzing genetic sequences, social media interactions, health records, phone logs, government records, and other digital traces left by people. Significant questions emerge. Will large-scale search data help us create better tools, services, and public goods? Or will it usher in a new wave of privacy incursions and invasive marketing? Will data analytics help us understand online communities and political movements? Or will it be used to track protesters and suppress speech? Will it transform how we study human communication and culture, or narrow the palette of research options and alter what ‘research’ means? Given the rise of Big Data as a socio-technical phenomenon, we argue that it is necessary to critically interrogate its assumptions and biases. In this article, we offer six provocations to spark conversations about the issues of Big Data: a cultural, technological, and scholarly phenomenon that rests on the interplay of technology, analysis, and mythology that provokes extensive utopian and dystopian rhetoric.
Social Theory and the Politics of Big Data and Method
Sociology, 2016
This article is an intervention in the debate on big data. It seeks to show, first, that behind the wager to make sociology more relevant to the digital there lies a coherent if essentially unstated vision and a whole stance which are more a symptom of the current world than a resolute endeavour to think that world through; hence the conclusion that the perspective prevailing in the debate lacks both the theoretical grip and the practical impulse to initiate a much needed renewal of social theory and sociology. Second, and more importantly, the article expounds an alternative view and shows by thus doing that other possibilities of engaging the digital can be pursued. The article is therefore an invitation to widen the debate on big data and the digital and a call for a more combative social theory.
Big Data: A Technology of Anxiety
2015
This paper proposes an understanding of big data and anxiety within Western countries as intimately coproduced and sustained within a technocratic ideological framework. With the rise of neoliberalism, which has shaped the political and economic organisation of Western societies, more ‘efficient’ systems and neopositivist ‘science’ called ‘big data’ have been created. The accumulation of information cannot however be equated with the growth of knowledge, as the data captured by new technologies is used for private ends: the accumulation of capital and control by a small elite. As such, new data can be gathered about subjectivities, bodies and performance, and used to further pressure individuals to fit into preconceived frameworks and identities as a result of the topdown creation of individualised pseudo-problems which can cause anxiety, especially when they are not tackled collectively. The paper navigates different approaches to anxiety and big data, critiquing the technocratic solutions to social problems offered by big data science. Big data will be discussed as a ‘technological’ creation, an infrastructure which defines, represents, conditions, manages, and sustains human subjectivity, corporeal affects, and the organisation of society. The ambivalence of big data will be illustrated, as it is used both as a solution and tool for producing, but also coping with anxiety. All strategies are deeply political, underlined by a feeling of anxiety which ought to be articulated politically, to encourage a cooperative search for new ways of overcoming technological control and fostering care and collective action. Sociology must remain critical in its engagement with big data in order to reveal practices of depoliticisation, quantification, standardisation, monitorisation and sanctioning, and the reduction of social reality and experience to algorithms.
2017 - Big Data: A New Empiricism and its Epistemic and Socio-Political Consequences
The paper investigates the rise of Big Data in contemporary society. It examines the most prominent epistemological claims made by Big Data proponents, calls attention to the potential socio-political consequences of blind data trust, and proposes a possible way forward. The paper's main focus is on the interplay between an emerging new empiricism and an increasingly opaque algorithmic environment that challenges democratic demands for transparency and accountability. It concludes that a responsible culture of quantification requires epistemic vigilance as well as a greater awareness of the potential dangers and pitfalls of an ever more data-driven society.