Reformulating National Defense Policy Through Artificial Intelligence: Enhancing Strategic Decision Making and Ethical Governance

Authors

  • Syarif Hidayatullah Universitas Pertahanan, West Java, Indonesia
  • Asep Adang Supriyadi Universitas Pertahanan, West Java, Indonesia
  • Ignatius Eko Djoko Purwanto Research and Development Agency (Balitbang) of the Ministry of Defense of the Republic of Indonesia
  • Guntur Eko Saputro Universitas Pertahanan, West Java, Indonesia

DOI:

https://doi.org/10.52690/jswse.v6i1.1069

Keywords:

Artificial Intelligence, Defense Policy, Explainable AI, National Security, Strategic Decision Making

Abstract

This study examines the role of artificial intelligence (AI) in reformulating national defense policy to enhance strategic decision making. Utilizing a qualitative, descriptive methodology supported by literature reviews and expert interviews, the research analyzes how AI can support data driven policy making, improve risk assessment, and optimize military resources. The research aims to examine how AI can improve operational efficiency, predictive analysis, and response capability against emerging threats. The study applies SWOT and Technology Readiness Level (TRL) frameworks to assess the strategic integration of AI in defense systems. Findings highlight both the opportunities and ethical concerns associated with AI adoption. The findings suggest that AI significantly supports data driven decision-making, enhances risk assessment, and optimizes military resource management. However, ethical and accountability concerns persist, necessitating the inclusion of explainable AI frameworks. The research proposes a structured model for ethical and inclusive AI governance and underscores the need for international cooperation in defense AI development.

References

Adobor, H., & Yawson, R. M. (2022). The Promise of Artificial Intelligence in Combating Public Corruption in the Emerging Economies: A Conceptual Framework. Science and Public Policy, 50(3), 355–370. https://doi.org/10.1093/scipol/scac068

Alaja, A., & Sorsa, V. (2020). The Evolution of the National Innovation System as Programmatic Policy Idea in Finland. Science and Public Policy, 47(6), 834–843. https://doi.org/10.1093/scipol/scaa045

Aleksandrova, A., Ninova, V., & Zhelev, Z. (2023). A Survey on AI Implementation in Finance, (Cyber) Insurance and Financial Controlling. Risks, 11(5), 91. https://doi.org/10.3390/risks11050091

Alrabiah, A., & Drew, S. (2020). Proactive Management of Regulatory Policy Ripple Effects via a Computational Hierarchical Change Management Structure. Risks, 8(2), 49. https://doi.org/10.3390/risks8020049

Baum, K., Mantel, S., Schmidt, E., & Speith, T. (2022). From Responsibility to Reason-Giving Explainable Artificial Intelligence. Philosophy & Technology, 35(1). https://doi.org/10.1007/s13347-022-00510-w

Chen, L., Alwi, H., Edwards, C., & Sato, M. (2022). Flight Evaluation of an LPV Sliding Mode Observer for Sensor FTC. Ieee Transactions on Control Systems Technology, 30(3), 1319–1327. https://doi.org/10.1109/tcst.2021.3096946

Dowding, K., & Taylor, B. R. (2024). Algorithmic Decision-Making, Agency Costs, and Institution-Based Trust. Philosophy & Technology, 37(2). https://doi.org/10.1007/s13347-024-00757-5

Galliott, J., & Wyatt, A. (2021). Considering the Importance of Autonomous Weapon System Design Factors to Future Military Leaders. Australian Journal of International Affairs, 76(2), 219–244. https://doi.org/10.1080/10357718.2021.1940093

Giubilini, A., & Savulescu, J. (2017). The Artificial Moral Advisor. The “Ideal Observer” Meets Artificial Intelligence. Philosophy & Technology, 31(2), 169–188. https://doi.org/10.1007/s13347-017-0285-z

Guardia, F. H. de la, Grant, S., & Miguel, E. (2020). A Framework for Open Policy Analysis. Science and Public Policy, 48(2), 154–163. https://doi.org/10.1093/scipol/scaa067

Guerra, P., & Castelli, M. (2021). Machine Learning Applied to Banking Supervision a Literature Review. Risks, 9(7), 136. https://doi.org/10.3390/risks9070136

Ho, J., & O’Sullivan, E. (2019). Addressing the Evolving Standardisation Challenges of ‘Smart Systems’ Innovation: Emerging Roles for Government? Science and Public Policy, 46(4), 552–569. https://doi.org/10.1093/scipol/scz008

Holmes, M., & Wheeler, N. J. (2024). The Role of Artificial Intelligence in Nuclear Crisis Decision Making: A Complement, Not a Substitute. Australian Journal of International Affairs, 78(2), 164–174. https://doi.org/10.1080/10357718.2024.2333814

Jauernig, J., Uhl, M., & Walkowitz, G. (2022). People Prefer Moral Discretion to Algorithms: Algorithm Aversion Beyond Intransparency. Philosophy & Technology, 35(1). https://doi.org/10.1007/s13347-021-00495-y

Kalogiannidis, S., Kalfas, D., Papaevangelou, O., Giannarakis, G., & Chatzitheodoridis, F. (2024). The Role of Artificial Intelligence Technology in Predictive Risk Assessment for Business Continuity: A Case Study of Greece. Risks, 12(2). https://doi.org/10.3390/risks12020019

King, T. C., Aggarwal, N., Taddeo, M., & Floridi, L. (2020). Artificial Intelligence Crime: An Interdisciplinary Analysis of Foreseeable Threats and Solutions. In Science and Engineering Ethics (Vol. 26, Issue 1). Springer Netherlands. https://doi.org/10.1007/s11948-018-00081-0

Kotaridis, I., & Benekos, G. (2023). Integrating Earth Observation IMINT With OSINT Data to Create Added-Value Multisource Intelligence Information: A Case Study of the Ukraine–Russia War. Security and Defence Quarterly, 43(3), 1–21. https://doi.org/10.35467/sdq/170901

Krügel, S., Ostermaier, A., & Uhl, M. (2022). Zombies in the Loop? Humans Trust Untrustworthy AI-Advisors for Ethical Decisions. Philosophy & Technology, 35(1). https://doi.org/10.1007/s13347-022-00511-9

Lepri, B., Oliver, N., Letouzé, E., Pentland, A., & Vinck, P. (2017). Fair, Transparent, and Accountable Algorithmic Decision-Making Processes. Philosophy & Technology, 31(4), 611–627. https://doi.org/10.1007/s13347-017-0279-x

List, C. (2021). Group Agency and Artificial Intelligence. Philosophy & Technology, 34(4), 1213–1242. https://doi.org/10.1007/s13347-021-00454-7

Makridis, C., Borkowski, A., & Alterovitz, G. (2024). Perspectives on Advancing Innovation and Human Flourishing Through a Network of AI Institutes. Science and Public Policy, 51(3), 557–562. https://doi.org/10.1093/scipol/scad088

Mitrović, M. (2021). Assessments and Foreign Policy Implementation of the National Security of Republic of Serbia. Security and Defence Quarterly, 34(2), 7–19. https://doi.org/10.35467/sdq/135592

Naeem, H., & Hauser, J. (2024). Should We Discourage AI Extension? Epistemic Responsibility and AI. Philosophy & Technology, 37(3). https://doi.org/10.1007/s13347-024-00774-4

Nallakaruppan, M. K., Chaturvedi, H., Grover, V., Balusamy, B., Jaraut, P., Bahadur, J., Meena, V. P., & Hameed, I. A. (2024). Credit Risk Assessment and Financial Decision Support Using Explainable Artificial Intelligence. Risks, 12(10), 164. https://doi.org/10.3390/risks12100164

O’Shaughnessy, M., Schiff, D., Varshney, L. R., Rozell, C. J., & Davenport, M. A. (2022). What Governs Attitudes Toward Artificial Intelligence Adoption and Governance? Science and Public Policy, 50(2), 161–176. https://doi.org/10.1093/scipol/scac056

Owens, E., Sheehan, B., Mullins, M., Cunneen, M., Ressel, J., & Castignani, G. (2022). Explainable Artificial Intelligence (XAI) in Insurance. Risks, 10(12), 230. https://doi.org/10.3390/risks10120230

Paglieri, F. (2024). Expropriated Minds: On Some Practical Problems of Generative AI, Beyond Our Cognitive Illusions. Philosophy & Technology, 37(2). https://doi.org/10.1007/s13347-024-00743-x

Radičić, D., & Pugh, G. (2016). R&D Programmes, Policy Mix, and the ‘European Paradox’: Evidence From European SMEs. Science and Public Policy, scw077. https://doi.org/10.1093/scipol/scw077

Rahman, M. M., Pokharel, B. P., Sayeed, S. A., Bhowmik, S., Kshetri, N., & Eashrak, N. (2024). riskAIchain: AI-Driven IT Infrastructure—Blockchain-Backed Approach for Enhanced Risk Management. Risks, 12(12), 206. https://doi.org/10.3390/risks12120206

Ruiter, A. de. (2021). The Distinct Wrong of Deepfakes. Philosophy & Technology, 34(4), 1311–1332. https://doi.org/10.1007/s13347-021-00459-2

Shkalenko, A. V, & Nazarenko, A. (2024). Integration of AI and IoT Into Corporate Social Responsibility Strategies for Financial Risk Management and Sustainable Development. Risks, 12(6), 87. https://doi.org/10.3390/risks12060087

Sio, F. S. d., & Mecacci, G. (2021). Four Responsibility Gaps With Artificial Intelligence: Why They Matter and How to Address Them. Philosophy & Technology, 34(4), 1057–1084. https://doi.org/10.1007/s13347-021-00450-x

Taddeo, M., McNeish, D., Blanchard, A., & Edgar, E. (2021). Ethical Principles for Artificial Intelligence in National Defence. Philosophy and Technology, 34(4), 1707–1729. https://doi.org/10.1007/s13347-021-00482-3

Taylor, I. (2024). Collective Responsibility and Artificial Intelligence. Philosophy & Technology, 37(1). https://doi.org/10.1007/s13347-024-00718-y

Vaassen, B. (2022). AI, Opacity, and Personal Autonomy. Philosophy & Technology, 35(4). https://doi.org/10.1007/s13347-022-00577-5

Vold, K. (2024). Human-AI cognitive teaming: using AI to support state-level decision making on the resort to force. Australian Journal of International Affairs, 78(2), 229–236. https://doi.org/10.1080/10357718.2024.2327383

Wang, S., Xia, M., Shi, X., Hou, B., & Lu, S. (2024). China’s Distinctive Civil–military Integration Policy and Firm Innovation. Science and Public Policy, 51(5), 761–779. https://doi.org/10.1093/scipol/scae013

Weissmann, M. (2025). Future Threat Landscapes: The Impact on Intelligence and Security Services. Security and Defence Quarterly. https://doi.org/10.35467/sdq/197248

Whetsell, T. A., Leiblein, M. J., & Wagner, C. S. (2019). Between Promise and Performance: Science and Technology Policy Implementation Through Network Governance. Science and Public Policy, 47(1), 78–91. https://doi.org/10.1093/scipol/scz048

Xu, Z., Chu, B., Geng, H., Nian, X., & Zhang, C. (2024). Model-Guided Learning for Wind Farm Power Optimization. Ieee Transactions on Control Systems Technology, 32(2), 428–439. https://doi.org/10.1109/tcst.2023.3315547

Zobi, M. K. A., & Jarah, B. A. F. (2023). The Role of Internal Auditing in Improving the Accounting Information System in Jordanian Banks by Using Organizational Commitment as a Mediator. Risks, 11(9), 153. https://doi.org/10.3390/risks11090153

Downloads

Published

2025-04-28

How to Cite

Hidayatullah, S., Supriyadi, A. A., Purwanto, I. E. D., & Saputro, G. E. (2025). Reformulating National Defense Policy Through Artificial Intelligence: Enhancing Strategic Decision Making and Ethical Governance. Journal of Social Work and Science Education, 6(1), 180–200. https://doi.org/10.52690/jswse.v6i1.1069

Similar Articles

<< < 6 7 8 9 10 11 12 13 14 > >> 

You may also start an advanced similarity search for this article.