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War Elephants: Rethinking Combat AI and Human Oversight

arXiv 2404.19573 ↗First posted 30 Apr 2024cs.CY cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 22 references that are in the map. First posted on arXiv 30 Apr 2024.

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References · 2

  1. 2018The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networkscited by 2,262
  2. 2023Trapping LLM Hallucinations Using Tagged Context Promptscited by 34

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