Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

Artificial intelligence in nuclear warfare: a perfect storm of instability?

Johnson, James orcid logoORCID: 0000-0002-5203-8583 (2020) Artificial intelligence in nuclear warfare: a perfect storm of instability? The Washington Quarterly, 43 (2). pp. 197-211. ISSN 0163-660X

Abstract
A significant gap exists between the expectations and fears of public opinion, policymakers, and global defense communities about artificial intelligence (AI) and its actual military capabilities, particularly in the nuclear sphere. The misconceptions that exist today are largely caused by the hyperbolic depictions of AI in popular culture and science fiction, most prominently the Skynet system in The Terminator. Misrepresentations of the potential opportunities and risks in the military sphere (or “military AI”) can obscure constructive and crucial debate on these topics—specifically, the challenge of balancing the potential operational, tactical, and strategic benefits of leveraging AI, while managing the risks posed to stability and nuclear security. This article demystifies the hype surrounding AI in the context of nuclear weapons and, more broadly, future warfare. Specifically, it highlights the potential, multifaceted intersections of this disruptive technology with nuclear stability. The inherently destabilizing effects of military AI may exacerbate tension between nuclear-armed great powers, especially China and the United States, but not for the reasons you may think.
Metadata
Item Type:Article (Published)
Refereed:Yes
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:Massachusetts Institute of Technology Press
Official URL:http://dx.doi.org/10.1080/0163660X.2020.1770968
Copyright Information:© 2020 Massachusetts Institute of Technology Press
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:25512
Deposited On:19 Feb 2021 15:15 by James Johnson . Last Modified 16 Dec 2021 04:30
Documents

Full text available as:

[thumbnail of TWQ JamesJohnson (2020).pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
289kB
Metrics

Altmetric Badge

Dimensions Badge

Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record