2022, Vol.5, No.3

Journal of Advances in Military Studies 2025 KCI Impact Factor : 1.0

pISSN : 2635-5531 / eISSN : 2636-1329
https://journal.kci.go.kr/jams

The application of artificial-intelligence technology to weapon systems, is difficult to use in military applications for such reasons as killing or wounding problems, ethical problems, and field environment considerations; therefore, more-sophisticated techniques and development are required for testing and evaluation. There is an increasing demand for advanced weapon systems that incorporate new technologies, such as artificial intelligence, and for electrification, and a new paradigm that can confirm and verify the performance required for field operations is required. Therefore, through case studies on digital twins, a plan for field testing and initial operational capability in future weapon systems was developed. Five development directions were identified, including policies and systems, organization, establishment of infrastructure, and utilization plans, to establish a field test and initial operational capability. In addition, studies on economic ripple effects and cost-effectiveness were conducted based on application cases of digital twins in the private sector. An optimal method for users to safely verify performance by utilizing the digital twin method to overcome the difficulties of testing and evaluating weapon systems with new technologies from the time when the weapon system requirements are determined to mass production is proposed.

Nations with advanced military capabilities are now focusing on developing AI algorithms for weapon system intellectualization development to retain their dominance. However, such endeavors are expensive in terms of time, effort, and resources, so it is necessary to develop it using open source to expand sharing and cooperation with industry–academic–government research and development collaboration. This study is aimed at elaborating the need for adoption of it and suggesting future implementation and improvement of open source SW in military despite the negative impact of security vulnerabilities when applied to the military weapon system. For this, the present study was design to investigate the benefit (intercommunity and cooperation) and harm (military sovereignty and technology vulnerability) of this open source platform through analysis of domestic and international case with defense area. The results of the study indicate that establishing an appropriate platform can help secure military sovereignty and prevent technology subordination, increase the efficiency of AI R&D, ensure collaboration and connectivity between weapons systems, and strengthen software security.

The Korean military's defense research and development (R&D) policy was often shortsighted because of environmental changes, such as the Korea–U.S. alliance, security policies under the regime, and limited budgets. In addition, there was a lack of prior research focusing on identifying the determinants of defense R&D policy, making it difficult for stakeholders in defense R&D policies to determine the appropriateness or validity of decision making. To this end, the purpose of the present study was to suggest a basic reference for defense R&D decision making through the conceptualization of determinants in defense R&D policy and development of measurement items. For this, we developed operational definitions of influencing factors and preliminary items related to defense R&D policy decisions, considering the Republic of Korea Armed Forces. To test reliability and validity, we performed exploratory and confirmatory factor analyses based on discussions with experts. The results show a six-factor structure (security policy, defense posture, technological ambition, dominant and shifting paradigm, science and technology, industry knowledge base, and resources) and 24 items. It is concluded that the use of questionnaire results might better reflect multiple aspects of decision making in defense R&D policy. Future studies need to elaborate on the measurement indicators for defense R&D policy determinants and theorize on policy directions according to changes in future defense and private technology development.