Big Data and the deconstruction of the academic quest for transparency

Abstract

Proponents of the implementation of big data research in the humanities—often carried out under the auspices of the 'digital humanities'—have so far argued their case by suggesting that the gathering and visualization of big data has the potential for unexpected insights into social relations and human activity. These advocates therefore claim that, even if any data visualization is necessarily bound by a set of subjective and technical choices, big data research may enrich the humanities with previously hidden perspectives on cognition, emotion, and society. Instead, opponents of this implementation in turn lament the increasing encroachment of techniques of calculation and quantification onto the humanities, and argue that such techniques signal the demise of the rich practices of close reading and the necessarily boundedness of interpretation to an embodied social and cultural context. These critics therefore also take issue with the problematic claim to objectivity and depth that the dominant discourse around big data presents, and dismiss the digital humanities in general as a largely misguided means to help humanities departments survive the onslaught of the quantification of academic practices by neoliberalism. This paper acknowledges the merit of both arguments, and subsequently proposes that the turn to big data in the humanities signals a profounder conundrum in academic research since its idealistic beginnings in Enlightenment thought. This deeper problem pivots precisely around the contradictory claims that big data equally renders its object of analysis—whether social phenomenon or cultural text—more superficial (and unknowable) as well as more penetrable (and knowable). This contradiction parallels the immanent aporia of the Enlightenment enterprise, which institutional mission of 'exposing the world and humanity to the light of truth and emancipation' (and its negative historical baggage of oppressive universalism, social scrutiny, and colonialism), has today deconstructed itself by also exposing the limits of its own idealism. This means that the quest for total knowledge has started to become a near-pervasive 'exposing-itself' of academia by way of the implementation of various forms of surveillance and sousveillance, carried out via extensive datafications of staff and student behavior and output. The problem of the university today consists therefore of the acceleration of the university's unfinishable idealistic mission by way of an enmeshment with and displacement of its aporia into technologies of calculation and prediction like big data tools.