Visualizations of the small military drone : normalization through ‘naturalization’. / Jackman, Anna.

In: Critical Military Studies, 05.01.2021.

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Abstract

We are in the midst of a global turn to the drone. Responding to the ‘unmanning’ of contemporary warfare, interdisciplinary scholarship has interrogated the human operators and non-human actors underpinning the drone, and their wide-ranging ethical, geopolitical, and legal implications. A key facet of extant drone debates surrounds drone vision – both as it operationally visualizes and is fetishized. While comparatively nascent, scholars have begun to explore how drones are instead visualized across particular media. In this article I identify two lacuna within extant drone scholarship: first a lack of attentiveness to small military drones, which while comprising the majority of global military arsenals remain comparatively absent from scholarly analysis; and second, a need to attend to a greater diversity of visual representations of the drone. In response, this article explores promotional visualizations of small military drones as they are ethnographically-encountered at a key site through which their usage is compelled and their functioning enabled - the defence tradeshow. In so doing, I identify three central frames through which the drone is repeatedly represented therein. I argue that these frames both engage and employ visual conventions associated with ‘nature’ and the ‘natural’ in order to ‘naturalise’ and normalize the drone in as-yet unaccounted ways. Approaching the drone through the current, yet under-examined, visual milieu of the defence environments in which it is promoted, the article contributes to both interdisciplinary drone scholarship, and literatures exploring the visual cultures of militarism more widely.
Original languageEnglish
JournalCritical Military Studies
Early online date5 Jan 2021
DOIs
Publication statusE-pub ahead of print - 5 Jan 2021
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 39492902