Machine Learning-powered Artificial Intelligence in Arms Control

Abstract: Artificial intelligence (AI), especially AI driven by machine learning, is on everyone’s lips. Even in armaments such systems are playing an increasingly important role: Some weapons systems are already able to identify targets independently and engage in combat with them. This poses problems for traditional forms of arms control originally designed to monitor physical objects such as mines and small arms and their internal function. In addition, important additional effects of reliable control such as confidence- building and stabilization of diplomatic relations are not addressed. It is important for arms control to address such risks as well. At the same time, the deployment of Machine Learning-powered Artificial Intelligence (MLpAI) as a tool offers tremendous potential for improving arms control processes. Here, more precise and comprehensive data processing can engender more trust between states in particular. This tension between the risks and the opportunities connected wit

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• ISBN: 9783946459514
• Umfang: Online-Ressource, 31 S.
• Sprache: Englisch
• Anmerkungen: Veröffentlichungsversion ; begutachtet

Verweise und Beziehungen

• Erschienen in: PRIF Reports ; Bd. 8

Klassifikation und Themen

• Klassifikation: Politik ; Ingenieurwissenschaften und Maschinenbau ; Informatik

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Mannheim, Frankfurt am Main
• (wer): SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V., Hessische Stiftung Friedens- und Konfliktforschung
• (wann): 2019
• Urheber: Lück, Nico
• Beteiligte Personen und Organisationen: Hessische Stiftung Friedens- und Konfliktforschung

Weitere Informationen

• URN: urn:nbn:de:0168-ssoar-69004-6
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 25.03.2025, 13:47 MEZ