Logo
Logo

Goldsmiths - University of London

Algorithmic States of Exception

McQuillan, Daniel. 2015. Algorithmic States of Exception. European Journal of Cultural Studies, 18(4/5), pp. 564-576. ISSN 1367-5494 [Article]

[img]
Preview
Text
mcquillan-algorithmic-states-of-exception.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (110kB) | Preview
Official URL: http://ecs.sagepub.com/

Abstract or Description

In this paper I argue that pervasive tracking and data-mining are leading to shifts in governmentality that can be characterised as algorithmic states of exception. I also argue that the apparatus that performs this change owes as much to everyday business models as it does to mass surveillance. I look at technical changes at the level of data structures, such as the move to NoSQL databases, and how this combines with data-mining and machine learning to accelerate the use of prediction as a form of governance. The consequent confusion between correlation and causation leads, I assert, to the creation of states of exception. I set out what I mean by states of exception using the ideas of Giorgio Agamben, focusing on the aspects most relevant to algorithmic regulation: force-of and topology. I argue that the effects of these states of exception escape legal constraints such as concepts of privacy. Having characterised this as a potentially totalising change and an erosion of civil liberties, I ask in what ways the states of exception might be opposed. I follow Agamben by drawing on Walter Benjamin's concept of pure means as a tactic that is itself outside the frame of law-producing or law-preserving activity. However, the urgent need to respond requires more than a philosophical stance, and I examine two examples of historical resistance that satisfy Benjamin's criteria. For each in turn I draw connections to contemporary cases of digital dissent that exhibit some of the same characteristics. I conclude that it is possible both theoretically and practically to resist the coming states of exception and I end by warning what is at stake if we do not.

Item Type: Article
Identification Number (DOI): 10.1177/1367549415577389
Keywords: algorithms, big data, datamining, machine learning, NoSQL, Michel Foucault, Giorgio Agamben, Walter Benjamin, state of exception, tracking, surveillance
Related URLs:
Departments, Centres and Research Units: Computing
Item ID: 11079
Date Deposited: 07 Jan 2015 21:34
Last Modified: 08 Mar 2016 22:37
URI: http://research.gold.ac.uk/id/eprint/11079

View statistics for this item...

Edit Record Edit Record (login required)