Second Prize: Coded Conflict: Algorithmic and Drone Warfare in US Security Strategy

Benjamin Johnson

Abstract


This paper examines drone and algorithmic warfare and argues that they are an expression of and an indivisible tool for the “never-ending” war that is now propelling US security rhetoric. Recent security strategy discourse implies a trend towards the complete mobilization of society in a new type of war, an algorithmic total war. Both mainstream and critical accounts of modern warfare with respect to the use of drones and algorithms remain limited. Mainstream accounts of drones and algorithms typically focus on the instrumental-technical aspects of their use whereas critical accounts often discuss their legal-normative implications and the construction of certain people as ‘threats’ within new regimes of surveillance and violence. Further, these limitations are compounded by the fact that that both mainstream and critical analyses retain a preoccupation with a post-9/11 framework that understands power confrontations as a thing of the past (pre-Cold War) whereas new conflicts are contoured by intra-state breakdown, asymmetry and terrorism. In sum, with a few notable exceptions, the use of drones and algorithms are rarely considered in a holistic manner and even less so with respect to the evolving rhetoric of US security policy, which once again positions long-term power rivalries as the key imperative shaping American interests. This paper offers a sketch of the broader concerns animated by these changes. Given the significance and further implications of these concerns, this endeavour is important as algorithmic and drone warfare are part of a much larger set of practices that encompass but are not limited to the focus on surveillance and targeted killings.


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JMSS is a publication of the Centre for Military, Security and Strategic Studies at the University of Calgary.

JMSS gratefully acknowledges the financial support of the Social Science and Humanities Research Council.