Johnson, James ORCID: 0000-0002-5203-8583 (2020) Delegating strategic decision-making to machines: Dr. Strangelove redux? Journal of Strategic Studies, 45 (3). pp. 439-477. ISSN 0140-2390
Abstract
Will the use of artificial intelligence (AI) in strategic decision-making be stabilizing or destabilizing? What are the risks and trade-offs of pre-delegating military force (or automating escalation) to machines? How might non-nuclear state and non-state actors leverage AI to put pressure on nuclear states? This article analyzes the impact of strategic stability of the use of AI in the strategic decision-making process, in particular, the risks and trade-offs of pre-delegating military force (or automating escalation) to machines. It argues that AI-enabled decision support tools, by substituting the role of human critical thinking, empathy, creativity, and intuition in the strategic decision-making process, will be fundamentally destabilizing if defense planners come to view AI’s ‘support’ function as a panacea for the cognitive fallibilities and human analysis and decision-making. The article also considers the nefarious use of AI-enhanced fake news, deepfakes, bots, and other forms of social media by non-state actors and state proxy actors, which might cause states to exaggerate a threat from ambiguous or manipulated information, increasing instability.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Uncontrolled Keywords: | U.S.-China relations; nuclear security; deterrence policy; emerging technology; strategic stability |
Subjects: | Computer Science > Artificial intelligence Computer Science > Machine learning Social Sciences > International relations Social Sciences > Political science |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Humanities and Social Science > School of Law and Government |
Publisher: | Taylor & Francis |
Official URL: | https://doi.org/10.1080/01402390.2020.1759038 |
Copyright Information: | © 2020 Taylor & Francis |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 25508 |
Deposited On: | 19 Feb 2021 11:58 by James Johnson . Last Modified 06 May 2022 12:24 |
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