Armament, Arms Control and Artificial Intelligence

Cover of edited volume “Armament, Arms Control and Artificial Intelligence: The Janus-faced Nature of Machine Learning in the Military Realm”, edited by Thomas Reinhold and Niklas Schörnig. Studies in Peace and Security. Series Editors: Christopher Daase, Simone Wisotzki, Anna Leander. Springer
Edited volume by Thomas Reinhold and Niklas Schörnig

Looking at a variety of arma­ment sectors, the book examines how Artifi­cial Intelli­gence (AI) impacts the fields of arma­ment and arms control, how existing arms control measures will be affected by AI, and what new approaches based on AI have been or are currently developed.

The significant increase in com­puting power, the in­creasing reliance on software, and the advent of (narrow) AI and deep-learning algo­rithms all have the poten­tial to lead to disruptive changes for military ope­rations and warfare, rendering many classical arms control instru­ments less effective, or even useless. On the other hand, AI might lead to completely new arms control approaches, raising the effective­ness and relia­bility of new verifi­cation measures. To provide a common under­standing, the book starts by presenting a general intro­duction to the state of the art in artificial intelli­gence and arms control, and how the two topics are inter­related. The second part of the book looks at examples from various fields of weapon techno­logy, including weapons of mass dest­ruction (WMD), conven­tional arma­ment, and emer­ging techno­logies. The final section offers a cross-cutting pers­pective based on the examples presen­ted in the second part.

This volume will appeal to students and scholars of inter­national relations, as well as policy-makers and practi­tioners interested in a better under­standing of peace and security studies in general, and armament and arms control in particular with a strong focus on AI. 

Bibliographic record

Reinhold, Thomas; Schörnig, Niklas. Armament, Arms Control and Artificial Intelligence. The Janus-faced Nature of Machine Learning in the Military Realm. Cham: Springer, 2022. DOI: 10.1007/978-3-031-11043-6.

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