Machine learning-powered artificial intelligence in arms control

Auteurs

• Nico Lück

Paramètres

• Informatique, programmation

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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 with the use of MLpAI in arms control is highlighted in this report.

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• Année de publication: 2019