Big Data New Connections: An Investigation into Big Data and the Production of Subjectivity

Abstract

Big data is becoming more and more popular. Companies use it to get new insights and improve their operations. Consumers engage with Big Data through the internet on social media. This thesis answers the question of how Big Data produces subjectivity and how Big Data in the recent data scandal involving Facebook and Cambridge Analytica produces subjectivity. This investigation is done through utilizing Deleuze and Guattari’s concept of the machine as well as Lazzarato’s notions on machinic enslavement and social subjection. Big data produces subjectivity through two machines: an expansion-machine and a datatrust-machine. The former produces subjectivity in how it enables the ones interacting with it to engage in expanding activities such as enlarging datasets, finding new datasets, finding new uses for Big Data, etc. The data-trust-machine produces subjectivity in how it enables actions of trust towards big datasets and Big Data solutions which can be hard to comprehend. The thesis also shows that the expansion-machine works in the domain of machinic enslavement where people find themselves in an automatic state of constant expansion. Furthermore, the data-trust-machine works in the domain of social subjection as it produces subjectivity by establishing the binary options of being someone who trusts Big Data or not. In the case of Facebook and Cambridge Analytica, this thesis explored how subjectivity was created through the expansion-machine in the domain of machinic enslavement and the data-trust-machine in the domain of social subjection. Prior to the scandal, the parties involved in the case (Facebook, Aleksandr Kogan, Facebook users, and Cambridge Analytica) all operated in machinic enslavement connected to the expansion-machine. Their subjectivity was produced as they engaged in expanding activities such as enlarging datasets, expanding personal online profiles, converting Facebook profiles into usable data, and using data to influence the US presidential election in 2016 through new Big Data practices. The thesis then examines what happened when consumer trust towards Big Data broke down, as the whole incident want public. This examination focused on Mark Zuckerberg’s congressional hearing where he made a binary distinction of blaming him for the incident or not. This establishment will re- 3 connect the data-trust-machine as data will be overlooked in the event. This binary distinction set up by Zuckerberg produced subjectivity in the domain of social subjection by enabling the audience to make a choice between blaming him or blaming Big Data.