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dc.contributor.authorIhagama, IGMKT
dc.contributor.authorFernando, KERL
dc.date.accessioned2025-04-09T10:25:46Z
dc.date.available2025-04-09T10:25:46Z
dc.date.issued2024-09
dc.identifier.urihttp://ir.kdu.ac.lk/handle/345/8396
dc.description.abstractMany scholars predict the futuristic application of AI in the military and even robot armies and wars. Thus, these lack an explanation of ‘why’. Therefore, to answer this question via academic foundations, this paper investigates the correlation between military manpower and AI in Futures Studies. Thus, Possible Futures will be focused on investigating the complex correlation between futuristic demographic challenges and military manpower. The problem of this study is to answer ‘why will the military manpower of future armies shift from humans to robots?’. The methodology adopted in this task will be the future studies research methodology of Six Pillars approach and the research tool of back-casting. Further, case studies of the three largest militaries, China, India, and the United States (US) will be considered in data collection and demographic trends trends including population growth rate, population median age, total fertility rate as well as birth rate, and its impact on military recruitment and force composition will be evaluated as research variables. The purpose of this paper is to highlight the paradigm shift in military manpower from the traditional recruitment of humans towards the integration of robot soldiers in the Possible Futures with a special focus on analyzing the potentiality of AI to address recruitment challenges arising from demographic shifts.en_US
dc.language.isoenen_US
dc.subjectPossible futuresen_US
dc.subjectMilitary manpoweren_US
dc.subjectAIen_US
dc.subjectRobot soldiersen_US
dc.subjectChinaen_US
dc.subjectIndiaen_US
dc.subjectUndited Statesen_US
dc.subjectDemographyen_US
dc.titleThe Evolving Landscape of Military Manpoweren_US
dc.title.alternative:Evaluating the Rise of AI in Possible Futuresen_US
dc.typeArticle Full Texten_US
dc.identifier.facultyFDSSen_US
dc.identifier.journalKDU 17th IRCen_US
dc.identifier.pgnos46-50en_US


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