From Abstract Threats to Institutional Realities: A Comparative Semantic Network Analysis of AI Securitisation in the US, EU, and China

2026-01-07

arXiv.org

AI Summary

This study addresses the paradox in global AI governance, where terminological convergence coexists with fragmented institutional practices. Drawing on securitization theory and the Foucauldian concept of dispositif, the paper employs semantic network analysis to systematically compare official AI policy documents issued by the European Union, the United States, and China between 2023 and 2025. It introduces the key concept of “structural incommensurability” to elucidate how divergent ontological framings of artificial intelligence underpin governance differences: the EU conceptualizes AI as a certifiable legal product, the U.S. as an optimizable market system, and China as a state-directed sociotechnical infrastructure. These findings challenge the dominant global governance paradigm rooted in shared ethical principles and underscore the constitutive role of institutional logics in shaping regulatory frameworks.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Security and Privacy: Security and privacy of machine learning and AI applications
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data
• Responsible Web: Technology governance, policy, and regulations

Abstract

Artificial intelligence governance exhibits a striking paradox: while major jurisdictions converge rhetorically around concepts such as safety, risk, and accountability, their regulatory frameworks remain fundamentally divergent and mutually unintelligible. This paper argues that this fragmentation cannot be explained solely by geopolitical rivalry, institutional complexity, or instrument selection. Instead, it stems from how AI is constituted as an object of governance through distinct institutional logics. Integrating securitisation theory with the concept of the dispositif, we demonstrate that jurisdictions govern ontologically different objects under the same vocabulary. Using semantic network analysis of official policy texts from the European Union, the United States, and China (2023-2025), we trace how concepts like safety are embedded within divergent semantic architectures. Our findings reveal that the EU juridifies AI as a certifiable product through legal-bureaucratic logic; the US operationalises AI as an optimisable system through market-liberal logic; and China governs AI as socio-technical infrastructure through holistic state logic. We introduce the concept of structural incommensurability to describe this condition of ontological divergence masked by terminological convergence. This reframing challenges ethics-by-principles approaches to global AI governance, suggesting that coordination failures arise not from disagreement over values but from the absence of a shared reference object.

Problem

• AI governance
• institutional logics
• semantic divergence
• structural incommensurability
• ontological divergence

Innovation

• securitisation theory
• semantic network analysis
• institutional logics
• structural incommensurability
• AI governance