ABSTRACT
Optimistic reporting about ‘big data’ has made it easy to forget that data- driven practices have been part of the emerging information society since the nineteenth century (Beniger 1989; Porter 1996; Campbell-Kelly 2003). In lieu of an illustrative metaphor, the label ‘big data’ is used to describe a set of practices involving the collection, processing and analysis of large data sets. The term enables members of the general public to engage in debates, albeit often uninformed, on the ongoing transformation of our knowledge economy, but it disguises more than it reveals. Nevertheless, despite its vagueness, the term captures something of significance about contemporary Western societies, where economic value is generated through the processing of information and the monetization of knowledge. To develop a critical understanding of this current situation and its societal consequences, it is important to debunk the exceptionalism inherent in the ‘big data’ paradigm. For starters, we must stop feeding the hype about it and lay out what we know: the phenomenon we are dealing with is not ‘big data’, but ‘the computational turn’ (Berry 2012; Braidotti 2013). This turn began in the 1950s with the introduction of electronic computers and continues unabated today. It concerns the datafication of everything: all aspects of life are now transformed into quantifiable data (Mayer-Schönberger & Cukier 2013). As the social is extensively mined, its data are used to predict human behaviour and automate decision-making processes. As José van Dijck claims, ‘datafication as a legitimate means to access, understand and monitor people’s behaviour is becoming a leading principle, not just amongst techno-adepts, but also amongst scholars who see datafication as a revolutionary research opportunity to investigate human conduct’ (2014: 198). Data analysis promises an ‘objective’ way to grasp the complex and dynamic reality we live in. Visualized via colourful dashboards, infographics and charts, it puts forth, persuasively and seductively, a seemingly accurate and unbiased assessment of reality. However, the translation of the social into data involves a process of abstraction that compels certain compromises to be made as the data are generated, collected, selected and analysed (Langlois et al. 2015).
