AI accelerates wildlife tracking but risks entrenching extractive conservation models and sidelining Indigenous data sovereignty
Original framing: “AI cuts wildlife tracking time from months to days” — Phys.org
If unchecked, AI-driven wildlife tracking could lead to a future where biodiversity data is controlled by tech corporations and conservation elites, exacerbating global inequities in conservation funding and decision-making. Scenario modeling suggests that without Indigenous data sovereignty and decentralized governance, AI could enable new forms of 'green colonialism,' where Western institutions profit from global biodiversity while local communities bear the costs. Conversely, a future where AI is co-designed with Indigenous communities could democratize conservation and integrate diverse knowledge systems.
The Phys.org headline frames AI as a neutral efficiency tool, but this obscures its role in perpetuating colonial conservation logics and sidelining Indigenous knowledge.
Historically, wildlife tracking has been a tool of control, used to justify land dispossession and resource extraction, and AI risks entrenching this legacy by centralizing data in Western institutions. Cross-culturally, Indigenous perspectives view animals as kin and teachers, not data points, and their exclusion from AI-driven conservation reinforces epistemic injustice. Future scenarios suggest that without structural safeguards, AI could enable new forms of 'green colonialism,' where biodiversity data is commodified while local communities bear the costs. The solution lies in centering Indigenous data sovereignty, decentralizing conservation governance, and co-designing hybrid knowledge systems that integrate AI with traditional wisdom. This requires dismantling the power structures that have long dominated conservation, from colonial-era wildlife management to Silicon Valley's extractive techno-optimism.