Algorithmic war and the dangers of in-visibility, anonymity, and fragmentation.
AI-enabled systems are likely to inform future decisions to initiate war. They are well placed to manage data and deliver recommendations at speeds that far surpass human abilities. Yet, AI-enabled vision and knowledge, which inform military intelligence, surveillance, and reconnaissance practices,...
| Publicado en: | Australian Journal of International Affairs Vol. 78; no. 2; pp. 257 - 266 |
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| Formato: | Artículo |
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Taylor & Francis Ltd
Apr2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=177593940&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 177593940 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 10357718 UAF jtl: Australian Journal of International Affairs issn: 10357718 maglogo: Y pubinfo: dt: Apr2024 vid: 78 iid: 2 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 177593940 10.1080/10357718.2024.2333824 ppf: 257 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P size: 760KB tig: atl: Algorithmic war and the dangers of in-visibility, anonymity, and fragmentation. aug: au: Baggiarini, Bianca affil: Strategic and Defence Studies Centre, Australian National University, Canberra, Australia su: Machine learning Military intelligence Legitimacy of governments Decision making Hazards Anonymity Desire sug: subj: Machine learning Military intelligence Legitimacy of governments Decision making Hazards Anonymity Desire keyword: Algorithmic reason decision making democracy legitimacy transparency war ab: AI-enabled systems are likely to inform future decisions to initiate war. They are well placed to manage data and deliver recommendations at speeds that far surpass human abilities. Yet, AI-enabled vision and knowledge, which inform military intelligence, surveillance, and reconnaissance practices, curiously sustain both exposure and opacity. Machine learning algorithms are famously called black boxes even as they are in practice widening what we can see and know. While many call for greater algorithmic transparency to combat this technological opacity, I argue that this desire is misguided because it overlooks how algorithmic reason, which promises more precise knowledge and more efficient decision making, naturally conceals through political and socio-technical practices of in-visibility, anonymity, and fragmentation. Given how these practices will likely come to shape AI-enabled resort-to-force decision making, this article concludes with the suggestion that AI-enabled decisions are likely to undermine democratic legitimacy. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Australian Journal of International Affairs is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Australian Journal of International Affairs holder: Taylor & Francis Ltd dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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