AI Threatens Indigenous Data Sovereignty and Digital Self-Determination

Author: Margaret Yun-Pu Tu, Policy Options

AI Threatens Indigenous Data Sovereignty and Digital Self-Determination examines AI development through an international Indigenous lens, arguing that without meaningful Indigenous leadership in AI governance, the technology risks becoming a new form of colonization. Written by Margaret Yun-Pu Tu, a Pangcah/Amis scholar from Taiwan and PhD candidate in law at the University of Washington, this article explores how Canada and Taiwan could collaborate to build Indigenous-centered AI innovation models.

It documents Canada's steps toward embedding Indigenous perspectives in AI development, including requiring CIFAR researchers and AI professionals to complete Indigenous perspectives training, while noting these efforts remain insufficient. The article explains how AI systems increasingly rely on Indigenous languages, traditional knowledge, and oral histories, often collected without consent and used to train commercial algorithms that provide no benefit to Indigenous communities. It highlights the OCAP principles (ownership, control, access, possession) as foundational to Indigenous data sovereignty, then asks the critical question: will these principles be meaningfully embedded in national AI policy, or merely acknowledged in principle?