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

arXiv: https://arxiv.org/abs/2501.06861 · HTML: https://mlsanity.com/paper/2501.06861/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 34 references that are in the map.
- First posted on arXiv 12 Jan 2025.

## Builds on (most cited first, 4 of 4)

- [Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities](https://mlsanity.com/paper/2111.06420/) (2021)
- [Escalation Risks from Language Models in Military and Diplomatic Decision-Making](https://mlsanity.com/paper/2401.03408/) (2024)
- [A/B Testing: A Systematic Literature Review](https://mlsanity.com/paper/2308.04929/) (2023)
- [Manifesto for the Responsible Development of Mathematical Works -- A Tool for Practitioners and for Management](https://mlsanity.com/paper/2306.09131/) (2023)

## Built on by (most cited first, 2 of 2)

- [Formalising Human-in-the-Loop: Computational Reductions, Failure Modes, and Legal-Moral Responsibility](https://mlsanity.com/paper/2505.10426/) (2025)
- [The Problem of Algorithmic Collisions: Mitigating Unforeseen Risks in a Connected World](https://mlsanity.com/paper/2505.20181/) (2025)

## Abstract (arXiv)

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.