Distortions

What was the role of big data in 2016’s Trump and Brexit victories? Recent reporting on Cambridge Analytica’s micro-targeting of swing voters seriously undermines the credibility of these election and referendum results. On the other hand, too much focus on the back-room proceedings of such data vendors risks over-simplifying the narrative, by fuelling the assumption that ‘big data’ alone can win elections. This talk traces some of the many ways in which journalists, philosophers and scholars have grappled with the so-called ‘post-truth’ political sphere since 2016. One difficulty in many of these discussions, I argue, is that they frequently invoke the image of ‘distortion’ to describe a post-truth political sphere – which, if not treated carefully, risks presupposing a ‘relatively truthful’ or ‘sufficiently level’ playing field prior to 2016. Given this difficulty, I suggest a few alternative ways to build the narrative: one involving a closer look at the intertwined, online circulations of ‘facts’ (credible or otherwise) and the reputations of those that proffer them; and another based on substituting the term modulation (developed by Simondon and used extensively by Deleuze) for distortion.