Big Data and Us: Human–Data Interactions

Abstract

The growth of continuously generated, large-scale datasets, and new analytics to handle them, has created expectations, in some quarters, that new insights can be generated that will help us address the biggest challenges that face us as a species and therefore can shape future societal outcomes. It is hoped that these new technologies will lead not just to new discoveries but also to new questions and thinking that will deliver significant scientific advances. Perhaps there will be some genuine scientific advances but since many of the challenges that face us reside in the human world and depend upon how humans behave, we need to turn to the humanities and the social sciences as well as the natural sciences and look at the role Big Data could play there in adding to, or shaping, our future. And here, what concerns us is not just the assumptions guiding the new analytic techniques for data mining, data merging, linking and analysis, born out of smarter AI algorithms, it is a more fundamental issue about the constraints and limitations of the kind of data inputs and outputs being appealed to in Big Data systems and whether they are well served to provide an understanding of the human world.

Big Data and the Little Big Bang: An Epistemological (R)evolution

“…Assuming that data are neutral and fully exhaustive, the problem in handling them becomes technical. In this perspective, new technologies, methods, and procedures are all that is needed to cope with big data (see Strom, 2012 ; Taylor et al, 2014 ; Trifunovic et al, 2015 ; Smith, 2019 ). On the contrary, once we recognize that data are socially created artifacts, the technological and the technical improvements are no longer enough on their own without a careful methodological and epistemological reflection.…”