4 - When Violations Become Vectors: Human Rights Work in the Era of Big Data

Summary

Karl Marx spent 12 years in the British Library developing both carbuncles and the intellectual framework for Das Kapital. […] It’s doubtful, however, whether he would have foreseen an automaton one day being able to look through all of the sources that he used – and millions more – within a fraction of the time he spent, and being able to present its own models of history.

– Ian Steadman, ‘Big Data and the Death of the Theorist’

Important questions in the social sciences and humanities about equality, power, voice, justice, fairness will always be around, will always require sustained and critical inquiry, and won’t ever fully be answered by computers alone.

– Mark Graham, ‘Big Data and the Death of the Theorist’

In the decades following the ‘white heat’ of the first information revolution, capitalism’s computational reconfiguration of the world has only intensified. Enabled by both exponential increases in computational power and the infrastructure of the internet (another product of Cold War military research that was only ever briefly the libertarian playground of cyberpunks), capital’s processes of exploitation and dispossession are now iteratively figured and reconfigured, worked and reworked, across the index of national spaces through the dense meshing of the network. In this emerging order, data emerges as the lifeblood of cybernetic capitalism, pouring out from an ever increasing array of devices and platform interfaces and flowing through its reticular veins into vast server farms erroneously called ‘the cloud’. Data has become a vital means of finding and capturing new value for all sectors of capital. Data on human biology and sociality, on human and non-human relations, and much else besides now feeds commercial banks and supermarket chains as much as it does social media platforms and ‘smart’ appliance manufacturers. Corporate maxims like ‘Data is everything, everything is data’ reflect this new era of big data.

Of course, it is not simply the vastness of data that makes it valuable but the new forms of data practice that, as David Beer puts it, make our data ‘speak’. Data analytics, algorithmic technologies, machine learning and artificial intelligence are overlapping terms that describe this increasingly automated set of practices which work over, order and arrange data so as to produce value.