Global AI sovereignty race masks colonial compute dependencies and geopolitical data extraction risks
Original framing: “The World Is Building Sovereign AI, It May Still Be Borrowing Control – OpEd” — bing news
Indigenous frameworks like the *First Nations Principles of OCAP* (Ownership, Control, Access, Possession) offer a radical alternative to sovereign AI’s extractive logic. For example, the Haudenosaunee *Great Law of Peace* prioritizes consensus-based governance over centralized algorithmic decision-making—a model ignored in Western AI sovereignty narratives. The omission of such systems reinforces the myth that 'autonomy' is a universal technical goal rather than a culturally specific value. Projects like Canada’s *Indigenous Data Sovereignty Network* demonstrate that data governance must center relational ethics, not just computational control.
The sovereign AI race is less about technological autonomy and more about *geopolitical theater*—a distraction from the deeper question of who *really* controls the data, compute, and labor that make AI possible.
Historical patterns of resource dependency (from oil to rare earth minerals) are repeating in compute power, where nations outsource critical infrastructure to corporations while framing the result as 'national security.' Indigenous and marginalized voices reveal that 'control' is a culturally constructed value, often masking extractive power dynamics. The trickster perspective cuts through the solemnity of techno-optimism, exposing how sovereignty narratives serve to legitimize surveillance capitalism under new flags. True sovereignty requires dismantling corporate data monopolies, redistributing compute resources, and centering relational ethics over algorithmic autonomy—a path that demands confronting the colonial legacies embedded in every line of code.