War Elephants: Rethinking Combat AI and Human Oversight

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WarElephants.pdf (3.96 MB)

Links to Files

http://arxiv.org/abs/2404.19573

Permanent Link

https://doi.org/10.48550/arXiv.2404.19573
 http://hdl.handle.net/11603/40384

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UMBC Student Collection
UMBC Information Systems Department

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0001-6164-6620

Date

2024-04-30

Type of Work

journal articles
preprints
Text

Department

Program

Citation of Original Publication

Rights

This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain

Subjects

Computer Science - Computers and Society
Computer Science - Artificial Intelligence

Abstract

This paper explores the changes that pervasive AI is having on the nature of combat. We look beyond the substitution of AI for experts to an approach where complementary human and machine abilities are blended. Using historical and modern examples, we show how autonomous weapons systems can be effectively managed by teams of human "AI Operators" combined with AI/ML "Proxy Operators." By basing our approach on the principles of complementation, we provide for a flexible and dynamic approach to managing lethal autonomous systems. We conclude by presenting a path to achieving an integrated vision of machine-speed combat where the battlefield AI is operated by AI Operators that watch for patterns of behavior within battlefield to assess the performance of lethal autonomous systems. This approach enables the development of combat systems that are likely to be more ethical, operate at machine speed, and are capable of responding to a broader range of dynamic battlefield conditions than any purely autonomous AI system could support.