Big Data, Big World: Knowledge Development in a Time of Transition

• In Event: Critical Data Studies: Ethics and Human Contexts of Data Science III

Abstract

The ethics of big data and especially algorithm use are now an established part of discourse in social science and technology studies environments. The transition from an analogue era of quantification in the social sciences and social policy domains, to a fully digital one is producing new problems and extending the scope of knowledge in the applied social sciences. One of the key problems here is the continuing dominance of the small data paradigm and the politics of population that it helped produce and regulate. Many social scientists have deep epistemic commitments to the small data paradigm and struggle to reconcile emerging methods with the ideological positions established under small data approaches.

In this paper we discuss and explore how this shift in quantification and its associated technologies is effecting the field of applied social science, including social policy practices. Drawing on STS and geographic theory, we examine some of the spatial and epistemic contradictions resulting from this period of transition. We refer explicitly to the politics of counting and the role that quantification, as an epistemic technology, has played in social policy practices over the past two centuries. Digitisation runs the risk of encouraging a false objectivity in an increasingly globalised and digitised social policy environment. We conclude by discussing how the rise of digital technologies and methods are potentially destabilising the established small data paradigm and the risks of and opportunities for big data moving forward.

Authors

• Hamish Robertson, University of Technology Sydney

• Joanne Travaglia, University of Technology Sydney

• Nick Nicholas, University of Technology Sydney