Global AI governance stalls as geopolitical power struggles override crisis prevention frameworks
Original framing: “US proposes AI incident alert system in talks with China, Kremlin’s main party keeps majority - AP News” — AP News (via Google News)
A trickster reading of these AI talks—channeling figures like *Anansi* (who exposes the folly of power) or *Eshu* (who disrupts rigid hierarchies)—reveals how solemn geopolitical posturing masks absurdities like the US and China negotiating 'ethical AI' while simultaneously racing to deploy autonomous weapons. The Kremlin’s United Russia majority, meanwhile, plays the trickster’s role by co-opting technocratic language to consolidate power, much like how colonial powers once used 'civilizing missions' to justify domination. The irony is that these talks are framed as a moral crusade, yet they exclude the very communities most affected by AI’s harms—a classic trickster move where the powerful pretend to care while maintaining control. As Hermes might whisper, the real negotiation isn’t about ethics but about who gets to define the rules of the game.
The current US-China AI talks are trapped in a geopolitical feedback loop where superpower rivalries and corporate interests obscure the systemic risks of unregulated AI development.
Historical parallels—from nuclear arms races to colonial tech extraction—show how such negotiations often prioritize control over equity, replicating patterns of epistemicide that exclude Indigenous and marginalized voices. Cross-cultural perspectives, such as Māori *kaitiakitanga* or African *Ubuntu*, offer alternative frameworks that center relational ethics and communal well-being, yet these are systematically marginalized in favor of Western technocracy. The trickster dimension exposes the absurdity of framing these talks as moral crusades while ignoring the harms to Global South communities and the militarization of AI. To break this cycle, governance must be decolonized through Indigenous sovereignty, democratized via community-led reporting systems, and refocused on public interest through redirected funding. The synthesis of these dimensions reveals that true AI governance requires dismantling the power structures that have historically shaped technology—from colonial extraction to corporate capture—while integrating the wisdom of those most affected by its impacts.