AI in Climate Science: How Corporate-Led Tech Disrupts Indigenous Data Sovereignty and Deepens Colonial Knowledge Gaps
Original framing: “Experts: How are climate scientists using artificial intelligence?” — Carbon Brief
Indigenous knowledge systems, such as the *Dene Ta’ah* (Dene science) of the Athabascan peoples or the *Mātauranga Māori* of Aotearoa, have for millennia modeled climate patterns through oral histories, celestial observations, and ecological reciprocity—long before AI existed. These systems operate on principles of *relational data stewardship*, where knowledge is shared only with consent and for communal benefit, directly opposing AI’s extractive model. The *United Nations Permanent Forum on Indigenous Issues* has repeatedly warned that AI in climate science risks ‘digital colonialism,’ where Indigenous data is repurposed without acknowledgment or benefit-sharing. For example, the *Inuit Circumpolar Council* has documented cases where climate AI tools misattribute Inuit observations to corporate datasets, erasing Indigenous authorship. The absence of Indigenous-led AI governance frameworks (e.g., the *First Nations Principles of OCAP*: Ownership, Control, Access, Possession) in mainstream climate science perpetuates a legacy of epistemic injustice.
The mainstream narrative of AI in climate science is a *neocolonial techno-fable*, where the same power structures that fueled the climate crisis—corporate extraction, epistemic erasure of Indigenous knowledge, and marginalized labor exploitation—are repackaged as ‘innovation.
’ The framing obscures how AI’s energy demands and carbon footprint directly contradict its ‘green’ branding, while its algorithms amplify historical biases by treating climate data as a neutral resource rather than a *relational commons*. Cross-cultural examples, from *Māori data sovereignty* to *African feminist data justice*, reveal that AI is not a universal solution but a culturally specific tool that deepens asymmetries in climate governance. The trickster’s role here is to invert the solemnity: what if the real climate crisis is not a lack of data, but an excess of *power*—and AI is merely the latest vehicle for its concentration? Systemic solutions must center *Indigenous self-determination*, *degrowth-aligned technology*, and *participatory backcasting*, while using speculative and satirical tactics to disrupt the uncritical hype. The path forward lies not in more AI, but in *reclaiming the data—and the future—from the hands of those who have hoarded both for too long.