In the rapidly evolving landscape of global technology governance, the rivalry between the United States and China has thrust frontier dual-use technologies, particularly Artificial Intelligence (AI), into the spotlight. This competition has intensified techno-nationalism, supply chain securitization, and the emergence of competing standards, deepening the bifurcation within a weaponized interdependence that blurs the lines between civilian and military applications. While much of the existing research focuses on the strategies of these superpowers, a critical aspect often overlooked is the role of middle powers as autonomous actors shaping the techno-order.
Ha-Chi Tran, in their groundbreaking study, introduces the concept of Technological Swing States (TSS), referring to middle powers that possess both technological capacity and strategic flexibility. These states are uniquely positioned to navigate the uncertainty and opacity surrounding frontier technologies, thereby mediating great-power techno-competition on both regional and global scales. Tran’s research reconceptualizes AI opacity not merely as a technical deficit but as a structural feature and strategic resource. This opacity arises from algorithmic complexity, political incentives that prioritize performance over explainability, and the inherent limits of post-hoc interpretability.
The structural opacity of AI shifts the authority from technical demands for explainability to institutional mechanisms such as certification, auditing, and disclosure. This shift converts technical constraints into strategic political opportunities. By examining case studies of South Korea, Singapore, and India, Tran’s study theorizes how TSS exploit the interplay between opacity and institutional transparency through three key strategies: delay and hedging, selective alignment, and normative intermediation. These practices enable TSS to preserve strategic flexibility, build trust among diverse stakeholders, and broker convergence across competing governance regimes.
Delay and hedging involve temporarily withholding commitments to specific technological standards or alliances, allowing TSS to maintain flexibility and adapt to evolving geopolitical dynamics. Selective alignment entails strategically aligning with one superpower in certain areas while maintaining autonomy in others, thereby balancing influence and avoiding over-dependence. Normative intermediation involves promoting and mediating between different governance frameworks, fostering dialogue and collaboration among diverse stakeholders to achieve mutually beneficial outcomes.
The implications of Tran’s research are profound for global AI governance. By leveraging their technological capacity and strategic flexibility, TSS can significantly influence institutional design, interstate bargaining, and policy outcomes. Their ability to navigate the complexities of AI opacity and institutional transparency positions them as crucial brokers in the global techno-order. As the world grapples with the challenges and opportunities presented by AI, the role of TSS in shaping a balanced and inclusive governance framework cannot be overstated.
Tran’s study underscores the importance of recognizing and understanding the agency of middle powers in the global technology landscape. By doing so, we can better appreciate the nuanced dynamics of international relations and the collective efforts required to address the multifaceted challenges of AI governance. As the U.S.-China rivalry continues to reshape the global techno-order, the strategic maneuvers of TSS will be pivotal in fostering a more equitable and stable technological future. Read the original research paper here.