Chinese military university urged to revise AI course to ‘educate for war’
China’s military researchers have proposed a redesigned “AI principles and practice course” for graduate students with “educating for war” at its centre, embedding combat scenarios to better prepare future officers for intelligent warfare. Researchers from the National University of Defence Technology’s College of Intelligence Science and Technology outlined their proposal in the July issue of…
China's National University of Defence Technology has proposed a revised AI principles and practice course, emphasizing the cultivation of military personnel capable of utilizing artificial intelligence in future warfare. The redesigned course aims to incorporate combat scenarios and practical applications of AI in decision-making processes, target tracking, and engagement, aligning with China's strategy to train officers proficient in intelligent warfare.
The researchers argue that existing course materials lack a sufficient "military flavour" and need to be restructured to better serve the practical needs of educating for war. Existing cases fail to emphasize the practical applications of AI in military settings, and the new curriculum intends to bridge this gap by mapping course topics onto various stages of the military decision-making and targeting process.
Proposed exercises include training simulated drones to surround high-value targets, highlighting the coordination, communication, and decision-making abilities of AI systems when working in groups. The researchers have developed an online simulation platform to facilitate hands-on learning, allowing students to design maps, scenarios, and missions while training AI agents through simulated combat exercises.
The team emphasizes that while AI should serve as a decision-support tool, ultimate command authority remains human. The curriculum also includes discussions on the ethical and legal boundaries of autonomous weapons systems, fostering a sense of responsibility among students, and acknowledging AI's limitations, such as data bias, environmental sensitivity, and vulnerability to adversarial attacks.
Written by urgent.news from Reuters Business via SCMP's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
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