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Main Author: Tran, Ha-Chi
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2601.06412
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author Tran, Ha-Chi
author_facet Tran, Ha-Chi
contents The United States-China rivalry has placed frontier dual-use technologies, particularly Artificial Intelligence (AI), at the center of global power dynamics, as techno-nationalism, supply chain securitization, and competing standards deepen bifurcation within a weaponized interdependence that blurs civilian-military boundaries. Existing research, yet, mostly emphasizes superpower strategies and often overlooks the role of middle powers as crucial actors shaping the global techno-order. This study examines Technological Swing States (TSS), middle powers with both technological capacity and strategic flexibility, and their ability to navigate the frontier technologies' uncertainty and opacity to mediate great-power techno-competition regionally and globally. It reconceptualizes AI opacity not merely as a technical deficit, but as a structural feature and strategic resource, stemming from algorithmic complexity, political incentives that prioritize performance over explainability, and the limits of post-hoc interpretability. This structural opacity shifts authority from technical demands for explainability to institutional mechanisms, such as certification, auditing, and disclosure, converting technical constraints into strategic political opportunities. Drawing on case studies of South Korea, Singapore, and India, the paper theorizes how TSS exploit the interplay between opacity and institutional transparency through three strategies: (i) delay and hedging, (ii) selective alignment, and (iii) normative intermediation. These practices enable TSS to preserve strategic flexibility, build trust among diverse stakeholders, and broker convergence across competing governance regimes, thereby influencing institutional design, interstate bargaining, and policy outcomes in global AI governance.
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publishDate 2026
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spellingShingle Brokerage in the Black Box: Swing States, Strategic Ambiguity, and the Global Politics of AI Governance
Tran, Ha-Chi
Computers and Society
The United States-China rivalry has placed frontier dual-use technologies, particularly Artificial Intelligence (AI), at the center of global power dynamics, as techno-nationalism, supply chain securitization, and competing standards deepen bifurcation within a weaponized interdependence that blurs civilian-military boundaries. Existing research, yet, mostly emphasizes superpower strategies and often overlooks the role of middle powers as crucial actors shaping the global techno-order. This study examines Technological Swing States (TSS), middle powers with both technological capacity and strategic flexibility, and their ability to navigate the frontier technologies' uncertainty and opacity to mediate great-power techno-competition regionally and globally. It reconceptualizes AI opacity not merely as a technical deficit, but as a structural feature and strategic resource, stemming from algorithmic complexity, political incentives that prioritize performance over explainability, and the limits of post-hoc interpretability. This structural opacity shifts authority from technical demands for explainability to institutional mechanisms, such as certification, auditing, and disclosure, converting technical constraints into strategic political opportunities. Drawing on case studies of South Korea, Singapore, and India, the paper theorizes how TSS exploit the interplay between opacity and institutional transparency through three strategies: (i) delay and hedging, (ii) selective alignment, and (iii) normative intermediation. These practices enable TSS to preserve strategic flexibility, build trust among diverse stakeholders, and broker convergence across competing governance regimes, thereby influencing institutional design, interstate bargaining, and policy outcomes in global AI governance.
title Brokerage in the Black Box: Swing States, Strategic Ambiguity, and the Global Politics of AI Governance
topic Computers and Society
url https://arxiv.org/abs/2601.06412