Skip to content
Accessible Unlicensed Requires Authentication Published by transcript Verlag December 24, 2016

Big Data and the Paradox of Diversity

Bernhard Rieder
From the journal Digital Culture & Society

Abstract

This paper develops a critique of Big Data and associated analytical techniques by focusing not on errors - skewed or imperfect datasets, false positives, underrepresentation, and so forth - but on data mining that works. After a quick framing of these practices as interested readings of reality, I address the question of how data analytics and, in particular, machine learning reveal and operate on the structured and unequal character of contemporary societies, installing “economic morality” (Allen 2012) as the central guiding principle. Rather than critiquing the methods behind Big Data, I inquire into the way these methods make the many differences in decentred, non-traditional societies knowable and, as a consequence, ready for profitable distinction and decision-making. The objective, in short, is to add to our understanding of the “profound ideological role at the intersection of sociality, research, and commerce” (van Dijck 2014: 201) the collection and analysis of large quantities of multifarious data have come to play. Such an understanding needs to embed Big Data in a larger, more fundamental critique of the societal context it operates in.

Published Online: 2016-12-24
Published in Print: 2016-12-1

© 2016 by transcript Verlag