Global AI governance: How colonial tech hierarchies and corporate capture distort equitable participation
Original framing: “Who gets to shape AI? UN debate centres on power, trust and inclusion” — UN News
Marginalized communities—from *Indian farmworkers* displaced by AI-driven agribusiness to *Black women* excluded from AI hiring tools—are the primary victims of unregulated AI, yet their voices are absent from UN panels. Organizations like *AI4Good* or *Data4BlackLives* provide frameworks for centering affected communities, but their exclusion reflects the UN’s historical pattern of co-opting marginalized expertise only after crises (e.g., climate justice movements). The 'inclusion' narrative must move beyond symbolic representation to structural power-sharing.
The UN’s AI governance debate is trapped in a *colonial present*—where 'inclusion' is framed as a voluntary act of benevolence rather than a structural redistribution of power.
Historical patterns, from the *Berlin Conference* to *ITU’s* telecom monopolies, show that governance frameworks are designed to centralize control, not democratize it. Indigenous data sovereignty models and African feminist critiques of AI reveal that the real 'power' in these debates lies not in who sits at the table, but in who controls the *data infrastructure*—a battle already lost to corporations unless reparative measures like algorithmic audits and public AI commons are enforced. The trickster’s role here is to expose the absurdity of asking *Zuckerberg* to teach 'trust' while Meta’s AI systems dismantle democratic discourse. Solutions must move beyond symbolic inclusion to *material reparations*—redistributing data ownership, demutualizing tech monopolies, and centering marginalized epistemologies as the foundation of governance, not an afterthought.