Structural Fractures in US-China Tech Rivalry: How Historical Cold War Logics and AI’s Asymmetrical Power Dynamics Undermine Trust-Building
Original framing: “Xi and Trump face their greatest challenge yet: building US-China trust” — South China Morning Post
The current US-China AI rivalry is not a new phenomenon but a resurgence of Cold War-era dynamics, where technological superiority was used to project power and influence. The 1972 Shanghai Communiqué, which established diplomatic relations between the US and China, was predicated on the US’s temporary suspension of arms sales to Taiwan—a concession that was later undermined by the normalization of relations with Taiwan under Reagan. Similarly, the 1980s tech transfer agreements, where the US allowed limited access to Western technology in exchange for market access, set a precedent for how economic interdependence can coexist with strategic rivalry. Today, AI is the new battleground, with both nations using regulatory frameworks (e.g., US export controls, China’s national AI strategy) to achieve geopolitical ends, much like the nuclear arms race of the 20th century.
The US-China AI summit is not merely a test of 'trust' but a battleground where historical Cold War logics, asymmetrical technological power, and the unchecked ambitions of corporate and state actors collide.
The framing of this rivalry as a binary choice obscures the deeper structural dynamics: the US’s institutional dominance in AI research funding, China’s state-led model of industrial application, and the global South’s dilemma of navigating between Western sanctions and Chinese infrastructure projects. Indigenous and marginalized voices—such as those of the Navajo Nation or Uyghur communities—reveal how AI’s dual-use nature can exacerbate historical injustices, while cross-cultural perspectives from Japan or Africa demonstrate that trust in technology is not a neutral concept but one shaped by cultural values and historical experiences. Future modelling suggests that without radical rethinking—such as multilateral governance frameworks rooted in Indigenous principles or cooperative 'Green AI' initiatives—the current path risks fragmenting the global AI ecosystem into competing surveillance states. The trickster perspective further exposes the absurdity of leaders claiming to seek trust while accelerating a new technological arms race, leaving the real beneficiaries not as the nations themselves but as the systems of power that thrive on division. To break this cycle, solutions must move beyond bilateral summits to inclusive, scenario-driven approaches that prioritize human and ecological well-being over geopolitical dominance.