Military AI Needs Technically-Informed Regulation to Safeguard AI Research and its Applications

TL;DR

The paper addresses the regulation of AI-powered lethal autonomous weapon systems (AI-LAWS) whose behavior introduces novel risks not captured by existing frameworks. It defines AI-LAWS using two behavior-based criteria—(1) AI/ML necessity with AI-specific risks and (2) involvement in semi- or fully autonomous targeting/force decisions—shifting oversight to system behavior rather than labels. It then proposes technically grounded policy directions, including banning AI control over nuclear deployment, developing international validation standards, prohibiting AI generals, clarifying civilian AI infrastructure under international law, and establishing civil-military research boundaries, while urging active AI-researcher participation in policy. These contributions aim to align governance with real-world AI behavior to safeguard AI research, reduce escalation risk, and promote responsible innovation in military AI.

Abstract

Military weapon systems and command-and-control infrastructure augmented by artificial intelligence (AI) have seen rapid development and deployment in recent years. However, the sociotechnical impacts of AI on combat systems, military decision-making, and the norms of warfare have been understudied. We focus on a specific subset of lethal autonomous weapon systems (LAWS) that use AI for targeting or battlefield decisions. We refer to this subset as AI-powered lethal autonomous weapon systems (AI-LAWS) and argue that they introduce novel risks -- including unanticipated escalation, poor reliability in unfamiliar environments, and erosion of human oversight -- all of which threaten both military effectiveness and the openness of AI research. These risks cannot be addressed by high-level policy alone; effective regulation must be grounded in the technical behavior of AI models. We argue that AI researchers must be involved throughout the regulatory lifecycle. Thus, we propose a clear, behavior-based definition of AI-LAWS -- systems that introduce unique risks through their use of modern AI -- as a foundation for technically grounded regulation, given that existing frameworks do not distinguish them from conventional LAWS. Using this definition, we propose several technically-informed policy directions and invite greater participation from the AI research community in military AI policy discussions.

Figures (1)

• Figure 1: Military AI policy is shaped by competing narratives, but none fully address the risks posed by AI-LAWS.A. A spectrum of views on autonomy ranges from blanket bans from e.g., International Committee of the Red Cross (ICRC) and Campaign to Stop Killer Robots (CSKR), to status quo arguments that existing policy around autonomous weapons systems is sufficient. We propose AI-LAWS as a distinct category requiring technically informed oversight. B. Our rubric identifies AI-LAWS using two criteria: (1) use of AI/ML essential to system function, and (2) involvement in semi- or fully autonomous targeting or force application, with or without human oversight. These criteria are grounded in system behavior—not labels—and define the subset of military AI systems that require new governance mechanisms with AI researchers in the loop.