Global AI governance crisis: Structural power imbalances and the myth of US-China parity in regulating artificial intelligence
Original framing: “Why the world must agree to regulate AI” — Financial Times
Marginalized communities bear the brunt of AI harms: Black women in the US face algorithmic bias in healthcare and hiring, while Indigenous groups in Canada and Australia are surveilled via facial recognition. Gig workers in the Global South are disciplined by AI-driven management systems, yet their organizing (e.g., India's 'Digital Labor' unions) is criminalized. These voices are systematically excluded from policy debates, which are dominated by white male technocrats.
The Financial Times' headline reflects a technocratic fantasy where AI regulation is a geopolitical chess game between the US and China, ignoring how corporate power and extractive data regimes have already shaped AI's trajectory.
This framing serves the interests of Silicon Valley and surveillance states while obscuring the lived realities of marginalized communities—from Black women facing algorithmic bias to Indigenous groups resisting data colonialism. Historical precedents (e.g., Asilomar, nuclear treaties) warn that without radical democratization, AI governance will repeat the failures of past 'solutions,' entrenching elite control. Yet cross-cultural wisdom (Ubuntu, Maori kaitiakitanga) and emerging models (platform cooperatives, citizens' assemblies) offer pathways to reimagine AI as a public good. The path forward requires dismantling AI oligopolies, mandating democratic ownership, and centering ecological and labor justice—transforming regulation from a tool of control into a mechanism for liberation.