Algorithmic security and conflict in a datafied world

Claudia Aradau*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

37 Downloads (Pure)

Abstract

Drawing on debates in critical security studies, this chapter explores how security and conflict are transformed by apparently mundane devices. What kinds of (in)security emerge through the algorithmic processing of large swathes of data or what has come to be known as ‘big data’? What are the implications of developing a ‘Waze for war’? This chapter argues that there are three transformations that these technologies entail for security and conflict, which can be analysed along three analytical dimensions: knowledge (prediction), othering (anomaly) and power (targeting). First, algorithms intensify the ‘predictive technoscience’ of security. Big Data and algorithms promise new powers of prediction to not just ‘connect the dots’, but also find the ‘needle in a haystack’. Second, algorithmic security is increasingly not about enemies, but about anomalies. The chapter explains how machine learning algorithms ‘hunt’ for anomalies in masses of data. Third, imaginaries of conflict and security need to be understood within a broader transformation towards what Grégoire Chamayou has called ‘targeted societies’.
Original languageEnglish
Title of host publicationDigital International Relations
Subtitle of host publicationTechnology, Agency and Order
EditorsCorneliu Bjola, Markus Kornprobst
PublisherTaylor and Francis AS
Chapter7
Pages177-197
Number of pages21
ISBN (Electronic)9781003437963
ISBN (Print)9781032571324
DOIs
Publication statusPublished - 3 Nov 2023

Fingerprint

Dive into the research topics of 'Algorithmic security and conflict in a datafied world'. Together they form a unique fingerprint.

Cite this