Integrators at War: Mediating in AI-assisted Resort-to-Force Decisions

2025-01-12

AI Summary

This study addresses a critical bottleneck in human–AI collaboration for military “rules of engagement” (ROE) decision-making—the structural tensions confronting the “integrator” role, which mediates among AI developers, operational users, and military legal frameworks. Method: Drawing on socio-technical systems theory, the research integrates human–AI collaboration analysis, policy process theory, and cross-organizational role modeling to systematically define integrators’ mediating responsibilities and develop a novel “technology–role–interaction” triadic tension framework tailored to ROE decisions. Contribution/Results: The study identifies three core challenges: technological misalignment with operational requirements, ambiguous accountability boundaries, and breakdowns in human–AI trust. It proposes a role-sensitive governance approach and actionable policy recommendations to clarify responsibility chains and institutionalize ethical safeguards within military AI deployment.

Technology Category

• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Intelligent Robots: Human-Robot Interaction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

The integration of AI systems into the military domain is changing the way war-related decisions are made. It binds together three disparate groups of actors - developers, integrators, users - and creates a relationship between these groups and the machine, embedded in the (pre-)existing organisational and system structures. In this article, we focus on the important, but often neglected, group of integrators within such a sociotechnical system. In complex human-machine configurations, integrators carry responsibility for linking the disparate groups of developers and users in the political and military system. To act as the mediating group requires a deep understanding of the other groups' activities, perspectives and norms. We thus ask which challenges and shortcomings emerge from integrating AI systems into resort-to-force (RTF) decision-making processes, and how to address them. To answer this, we proceed in three steps. First, we conceptualise the relationship between different groups of actors and AI systems as a sociotechnical system. Second, we identify challenges within such systems for human-machine teaming in RTF decisions. We focus on challenges that arise a) from the technology itself, b) from the integrators' role in the sociotechnical system, c) from the human-machine interaction. Third, we provide policy recommendations to address these shortcomings when integrating AI systems into RTF decision-making structures.

Problem

• Artificial Intelligence
• Military Decision-Making
• Human-Machine Collaboration

Innovation

• Human-AI Collaboration
• Military Decision-Making
• Ethical AI Implementation