TITLE:
Responsible AI Governance in Military Security: Risk Models, Compliance Metrics, and Strategic Stability
AUTHORS:
Jing Ge
KEYWORDS:
Responsible AI Governance, Military Security, Compliance Index (CI)
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.13 No.11,
November
3,
2025
ABSTRACT: Artificial Intelligence (AI) is rapidly transforming global politics and military security, offering both strategic advantages and unprecedented risks. Unlike nuclear or conventional arms, military AI is dual-use, widely accessible, and embedded in fast-evolving civilian ecosystems, complicating governance and verification. This research develops an integrated framework for responsible AI governance in defense, addressing the dual tensions between technological innovation and systemic risk. Methodologically, the research adopts three models. First, a Compliance Index (CI) measures conformity with international humanitarian law (IHL) along the dimensions of distinction, proportionality, accountability, and reversibility. Second, a Strategic Stability Network (SSN) model applies social network analysis to map governance interactions, highlighting polarized clusters and the potential role of middle powers as bridging actors. The findings confirm three dynamics. First is risk-innovation oscillation, where states pursue AI innovation while selectively mitigating risks. Second is compliance asymmetry, which produces fragmented governance landscapes. Third is network fragmentation, undermining norm diffusion and stability. Moreover, policy recommendations emphasize defining “red line” technologies, enhancing trust-building, linking AI to existing security regimes, ensuring accountability, and piloting regional governance. Overall, the research argues that responsible AI governance requires bridging technical assessments with institutional mechanisms and addressing structural great power competition to avoid instability in the age of military AI.