WE NOW LIVE IN THE AGE OF DATA, NOT FACTS
(…) One of the complaints made most frequently by liberal commentators, economists and media pundits was that the referendum campaign was being conducted without regard to ‘truth’. This isn’t quite right. It was conducted without adequate regard to facts. To the great frustration of the Remain campaign, their ‘facts’ never cut through, whereas Leave’s ‘facts’ (most famously the £350m/week price tag of EU membership) were widely accepted.
What is a ‘fact’ exactly? In her book A History of the Modern Fact, Mary Poovey argues that a new way of organising and perceiving the world came into existence at the end of the 15th century with the invention of double-entry book-keeping. This new style of knowledge is that of facts, representations that seem both context-independent, but also magically slot seamlessly into multiple contexts as and when they are needed. The basis for this magic is that measures and methodologies (such as accounting techniques) become standardised, but then treated as apolitical, thereby allowing numbers to move around freely in public discourse without difficulty or challenge. In order for this to work, the infrastructure that produces ‘facts’ needs careful policing, ideally through centralisation in the hands of statistics agencies or elite universities (the rise of commercial polling in the 1930s was already a challenge to the authority of ‘facts’ in this respect).
This game has probably been up for some time. As soon as media outlets start making a big deal about the FACTS of a situation, for instance with ‘Fact check’ bulletins, it is clear that numbers have already become politicised. ‘Facts’ (such as statistics) survived as an authoritative basis for public and democratic deliberation for most of the 200 years following the French Revolution. But the politicisation of social sciences, metrics and policy administration mean that the ‘facts’ produced by official statistical agencies must now compete with other conflicting ‘facts’. The deconstruction of ‘facts’ has been partly pushed by varieties of postmodern theory since the 1960s, but it is also an inevitable effect of the attempt (beloved by New Labour) to turn policy into a purely scientific exercise.
The attempt to reduce politics to a utilitarian science (most often, to neo-classical economics) eventually backfires, once the science in question then starts to become politicised. ‘Evidence-based policy’ is now far too long in the tooth to be treated entirely credulously, and people tacitly understand that it often involves a lot of ‘policy-based evidence’. When the Remain camp appealed to their ‘facts’, forecasts, and models, they hoped that these would be judged as outside of the fray of politics. More absurdly, they seemed to imagine that the opinions of bodies such as the IMF might be viewed as ‘independent’. Unfortunately, economics has been such a crucial prop for political authority over the past 35 years that it is now anything but outside of the fray of politics.
In place of facts, we now live in a world of data. Instead of trusted measures and methodologies being used to produce numbers, a dizzying array of numbers is produced by default, to be mined, visualised, analysed and interpreted however we wish. If risk modelling (using notions of statistical normality) was the defining research technique of the 19th and 20th centuries, sentiment analysis is the defining one of the emerging digital era. We no longer have stable, ‘factual’ representations of the world, but unprecedented new capacities to sense and monitor what is bubbling up where, who’s feeling what, what’s the general vibe.
Financial markets are themselves far more like tools of sentiment analysis (representing the mood of investors) than producers of ‘facts’. This is why it was so absurd to look to currency markets and spread-betters for the truth of what would happen in the referendum: they could only give a sense of what certain people at felt would happen in the referendum at certain times. Given the absence of any trustworthy facts (in the form of polls), they could then only provide a sense of how investors felt about Britain’s national mood: a sentiment regarding a sentiment. As the 23rd June turned into 24th June, it became manifestly clear that prediction markets are little more than an aggregative representation of the same feelings and moods that one might otherwise detect via twitter. They’re not in the business of truth-telling, but of mood-tracking. (…)