Datafication and discrimination

Abstract

Popular accounts of datafied ways of knowing implied in the ascendance of big data posit that the increasingly massive volume of information collected immanently to digital technologies affords new means of understanding complex social processes. The development of novel insights is attributed precisely to big data’s unprecedented scale, a scale that enables what Viktor Mayer-Schönberger and Kenneth Cukier note is a shift away from causal inferences to modes of analysis based rather on ‘the benef its of correlation’ (2013: 18). Indicating the vast implications of this shift, Mayer-Schönberger and Cukier’s influential framing of big data describes a revolutionary change in the ways ‘we live, work and think’, as phrased by the book’s subtitle. But the ‘we’ in this proclamation tends to go unspecif ied. Who exactly benef its from a shift toward correlative data analysis techniques in an age of big data? And by corollary, who suffers?