Adversarial artificial intelligence: Implications of strategic stability attacks on military AI systems

Strategic competition in military AI is intensifying, but governance has not kept pace. As reliance on AI-enabled decision making grows, adversarial attacks that disrupt, deny or manipulate military and critical infrastructure systems could undermine strategic stability. This study examines how such attacks may affect credibility, escalation, trust and attribution, and recommends measures to reduce their likelihood and impact worldwide.

Adversarial artificial intelligence

Implications of strategic stability attacks on military AI systems

Irene van Droffelaar, Kiran Suman-Chauhan, James Black, Thomas Kenchington, Angus Cooper, William Mitchell Reid

This research was sponsored by the UK Foreign, Commonwealth & Development Office (FCDO).

Strategic competition in artificial intelligence (AI), including in the military domain, is intensifying, while global governance has not kept pace. The tactical implications of military AI are well documented: autonomous targeting, navigation in robotic systems, and decision-support tools for commanders are relatively well understood. Growing attention is now directed toward AI’s strategic effects and its influence on strategic stability.

Although research on the strategic implications of AI and governance options is expanding, it largely focuses on the potential benefits of effective AI systems. Little attention has been paid to how the disruption or denial of AI systems could threaten strategic stability. As a result, governance proposals rarely address these risks. Yet as AI is increasingly integrated in decision making and reliance on these systems grows, the consequences of adversarial interference will likewise intensify.

This project, commissioned by the UK Foreign Commonwealth and Development Office (FCDO), offers insights into how adversarial AI attacks targeting AI systems integrated in the military or critical national infrastructure may affect strategic stability, and offers recommendations to decrease the probability and impact of adversarial attacks on AI systems.

This work was commissioned by the UK Foreign, Commonwealth, and Development Office (FCDO) and conducted by RAND Europe.

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