Frequently asked questions: Artificial Intelligence (AI) in the military domain

· Source: International Committee of the Red Cross · Field: Government & Public Sector — Public Policy & Governance, Public Safety & Security, International Relations & Diplomacy · Depth: Novice, long

Summary

The International Committee of the Red Cross (ICRC) addresses frequently asked questions regarding Artificial Intelligence (AI) in the military domain, highlighting significant humanitarian concerns. AI in warfare encompasses autonomous weapon systems (AWS), military decision-support systems (DSS), and cyber operations, all subject to International Humanitarian Law (IHL). The ICRC is particularly worried about AI's potential to accelerate conflict, increase unpredictability, and diminish human control, especially given AI systems' vulnerability in adversarial environments. Three key applications raise specific risks: AWS, which can autonomously select and engage targets; AI DSS, prone to unreliability and human over-reliance; and AI in cyber operations, capable of escalating attack scale and severity. The ICRC advocates for a human-centered approach, emphasizing human responsibility and judgment, and calls for a legally binding international instrument to prohibit unpredictable and anti-personnel AWS, while restricting others, with the 7th CCW Review Conference in November 2026 offering a critical opportunity.

Key takeaway

For technology companies developing AI systems for military applications, you must proactively assess how your products and services could be used in armed conflict. Take steps to avoid contributing to International Humanitarian Law violations and mitigate risks to civilians. Engage with organizations like the ICRC to understand IHL implications and design AI systems that support human decision-making and compliance, rather than impairing or replacing it.

Key insights

AI in military applications risks escalating conflict and reducing human control, necessitating strict IHL adherence and regulation.

Principles

Method

The ICRC recommends rigorous testing, evaluation, verification, and validation for AI DSS, alongside legal reviews, high-quality data use, bias mitigation, meaningful human engagement, user training, and after-action reviews.

In practice

Topics

Best for: Policy Maker, Legal Professional, AI Ethicist

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Editorial summary, takeaway, and curation by AIssential. Original article published by International Committee of the Red Cross.