Applied and Computational Engineering

- The Open Access Proceedings Series for Conferences


Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

Series Vol. 4 , 30 May 2023


Open Access | Article

Military AI’s impacts on international strategic stability

Yifan Yu * 1
1 International School of Belgrade, Temišvarska 19, Beograd 11040

* Author to whom correspondence should be addressed.

Applied and Computational Engineering, Vol. 4, 20-25
Published 30 May 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yifan Yu. Military AI’s impacts on international strategic stability. ACE (2023) Vol. 4: 20-25. DOI: 10.54254/2755-2721/4/20230339.

Abstract

Technological revolution brought major changes in the system framework of strategic stability. Artificial intelligence (AI) thrives internationally as a disruptive technology and is applied to many fields in the 21st century. This paper evaluates the strength, limitations, and impacts of AI-empowered military application on international strategic stability. Applications of AI technology for military purpose brings both positive and negative impact on nations’ defending and offending, so the international strategic stability. However, the impact of AI on international strategic stability is mainly negative. For facing stability challenges, nations shall formulate systematic governance of military AI; the global community shall promote friendly multilateral cooperation between each other. In the end, this view offers significant implications for maintaining international strategic stability and improving AI governance capabilities in the foreseeable future.

Keywords

Artificial Intelligence, Strategic Stability, Arm Race

References

1. Leys, N. (2018). Autonomous Weapon Systems and International Crises. Strategic Studies Quarterly, 12(1), 48–73. http://www.jstor.org/stable/26333877

2. Johnson, J. S. (2020). Artificial Intelligence: A Threat to Strategic Stability. Strategic Studies Quarterly, 14(1), 16–39. https://www.jstor.org/stable/26891882

3. Özkaya, Umut. Automatic Target Recognition (ATR) from SAR Imaginary by Using Machine Learning Techniques. In arXiv

4. Price, M., Walker, S., & Wiley, W. (2018). The Machine Beneath: Implications of Artificial Intelligence in Strategic Decision making. PRISM, 7(4), 92–105. https://www.jstor.org/stable/26542709

5. Cataleta, M. S. (2020). Humane Artificial Intelligence: The Fragility of Human Rights Facing AI. East-West Center. http://www.jstor.org/stable/resrep25514

6. Cuihong, C., & Liting, D. (2022). The Role of Artificial Intelligence in Influencing the Stability of Composite Strategies: a Model-Based Examination. In Journal of International Security Studies. China National Knowledge Infrastructure.

7. Huang, Z., & Yanyun, D. (2021). The Development of Global Autonomous Weapons Systems and Their Impact on Strategic Stability. In International Forum. China National Knowledge Infrastructure.

8. Xuegong, Z. (2006). Nuclear Weapons and the Soviet-American Cold War. In Zhejiang Academic Journal. China National Knowledge Infrastructure.

9. Bai, J. (2000). On the Role of Nuclear Weapons in the Occurrence, Development and End of the Cold War. In Journal of Shaanxi Normal University (Vol. 29).

10. Qi, C., & Rongsheng, Z. (2020). Why Worry about Artificial Intelligence Impacting International Security. In People’s Tribune. China National Knowledge Infrastructure.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
ISBN (Print)
978-1-915371-55-3
ISBN (Online)
978-1-915371-56-0
Published Date
30 May 2023
Series
Applied and Computational Engineering
ISSN (Print)
2755-2721
ISSN (Online)
2755-273X
DOI
10.54254/2755-2721/4/20230339
Copyright
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated