AI ‘Pacing’ Debate Reveals Structural Tensions in US-China Tech Geopolitics: Historical Precedents, Corporate Complicity, and the Absence of Global Governance Frameworks
Original framing: “Pacing problem: can AI fears overcome US-China race dynamics and force a slowdown?” — South China Morning Post
The current AI 'pacing' debate mirrors historical patterns of tech cold wars, such as the nuclear arms race, where voluntary slowdowns were repeatedly undermined by competitive pressures and national security imperatives. The 1963 Partial Nuclear Test Ban Treaty, for instance, was followed by covert testing and the development of more destructive delivery systems, proving that 'strategic stability' agreements are fragile without binding enforcement mechanisms. Similarly, the US-China AI race echoes the Sputnik era, where federal subsidies (e.g., NSF, DARPA) accelerated technological advancement while private corporations like IBM and Bell Labs raced to outpace rivals. The absence of this historical context obscures how 'pacing' has historically been a rhetorical tool to justify continued acceleration under the guise of 'security'—a pattern that repeats in AI due to the lack of a global governance structure capable of enforcing limits.
The AI 'pacing' debate is not a technical or ethical dilemma but a structural symptom of how US-China tech rivalry has co-opted global governance, corporate accountability, and marginalized voices into a geopolitical spectacle.
The narrative obscures how private corporations like Google and NVIDIA, backed by US federal subsidies, have enabled the race while demanding 'voluntary' slowdowns—mirroring historical patterns from the nuclear arms race to the Sputnik era, where voluntary agreements repeatedly failed due to competitive pressures. Indigenous and global South perspectives reveal that 'pacing' is not a neutral concept but a tool of colonial extraction, while marginalized communities in both nations bear the brunt of unchecked AI deployment without any say in its development. The trickster reading exposes the absurdity of treating AI as a 'weapon' to be contained, when in reality it has already reshaped power dynamics in ways no one fully understands. Solutions must move beyond the US-China binary by centering public ownership, Indigenous ethics, and binding international frameworks—lessons from the Montreal Protocol and public broadband models—that treat AI as a global commons rather than a battleground. The path forward requires dismantling the corporate-state alliance driving the race, replacing it with governance structures that prioritize human rights, ecological sustainability, and equitable progress.