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The Use of Artificial Intelligence and Autonomous Weapon Systems in Military Operations.

Authors :
Cîrdei, Ionuț Alin
Source :
International Conference KNOWLEDGE-BASED ORGANIZATION; Jun2024, Vol. 30 Issue 1, p1-9, 9p
Publication Year :
2024

Abstract

In the modern era, artificial intelligence and autonomous weapon systems represent an important step in the evolution of military conflicts. The ability of these technologies to make fast and accurate decisions in real time brings significant benefits to the military, improving the efficiency of actions and protecting the lives of soldiers. Artificial intelligence can analyze vast amounts of data and information in a much shorter time than humans, thus providing critical information for decision-making in order to surprise the adversary and achieve strategic objectives. Artificial intelligence is becoming an indispensable tool for modern armed forces because it allows actions to be carried out with maximum efficiency that would involve a high consumption of human resources, time and would involve numerous risks for human operators, from data analysis to identifying enemy targets and anticipating adversary movements or even engaging adversary forces under certain conditions. At the same time, autonomous weapon systems, equipped with AI technologies, have the ability to act independently, reducing the dependence on human intervention and speeding up the response time in critical situations. These systems can detect and neutralize threats faster and more efficiently than humans could. However, the use of artificial intelligence in military conflicts raises numerous ethical and moral challenges. Concerns about the loss of control over the technology and the possibility that it could be mistakenly used against civilians or against protected targets have generated intense debate in the international community. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
24513113
Volume :
30
Issue :
1
Database :
Complementary Index
Journal :
International Conference KNOWLEDGE-BASED ORGANIZATION
Publication Type :
Conference
Accession number :
178277300
Full Text :
https://doi.org/10.2478/kbo-2024-0006