AI and – Indigenous leaders say AI can help monitor forests and fires—but data centers also raise water, energy, and land risks that fuel extraction. Consent and Indigenous control are key.
Artificial intelligence is increasingly being used to help Indigenous communities safeguard forests, water, and biodiversity. But UN experts warn it can also intensify the very pressures—resource extraction and surveillance—that Indigenous peoples have fought for decades.
MISRYOUM reports that Indigenous leaders at the UN Permanent Forum on Indigenous Issues are grappling with a paradox: how to use AI’s protective capabilities without creating new harms.. The concern is not whether AI can detect illegal logging or wildfires; it’s what happens behind the scenes—where the computing power comes from. and who bears the environmental and social costs.
A study discussed by Hindou Oumarou Ibrahim. Mbororo and a former chair of the UNPFII. frames AI as both a potential ally and a risk multiplier.. Ibrahim argues that Indigenous Peoples have long protected some of the world’s most intact ecosystems through stewardship grounded in local knowledge.. AI could strengthen that work, she says, but only if it is applied on Indigenous terms, in culturally appropriate ways.
The case for AI as a conservation tool is already visible across different regions.. AI can help communities monitor biodiversity. spot deforestation and illegal mining. track wildfires. and identify water contamination using satellite imagery. sensors. and pattern-based analysis.. When paired with Indigenous knowledge. MISRYOUM notes. it can also support climate impact prediction. wildlife movement tracking. and faster land-use planning—especially when communities need to respond quickly to threats.
In Brazil’s Acre state. for example. agroforestry agents in the Katukina/Kaxinawá Indigenous Reserve use AI-linked forecasting tools to understand deforestation risk.. For the agents. the practical goal is simple and urgent: being able to detect invasions. illegal wood removal. hunting activity. and fires close to their lands.. AI here functions less like a replacement for governance and more like an early warning layer.
MISRYOUM also highlights similar hybrid approaches elsewhere.. In Nunavut, Inuit knowledge and predictive modeling are used to help locate fishing areas as climate change shifts fish availability.. In Chad. Indigenous pastoralists combine participatory mapping. satellite data. and predictive AI to anticipate severe droughts and protect transhumance routes—an approach aimed at strengthening resilience before conditions worsen.
But the warning from UN experts centers on a second reality: the infrastructure that powers AI.. Data centers require substantial energy to run and significant water for cooling.. That demand can increase pressure for electricity generation and for critical minerals and other resources—often extracted from or located near Indigenous territories.. In Thailand. residents in areas facing data center expansion have raised fears about water shortages and pollution tied to wastewater management and cooling needs.. Similar worries are echoed in communities in other countries, where expansion can bring higher costs and environmental stress.
Environmental impact isn’t the only concern.. The study also points to gaps that can undermine fairness and control.. Some Indigenous communities face limited infrastructure, weak legal protection, or insufficient institutional capacity to defend digital rights.. There is also the risk that AI tools—and the remote sensing. drones. and mapping technologies they rely on—can expose sensitive information such as the locations of sacred sites or ecologically strategic areas. particularly if deployments occur without prior consultation.
This is where the UN-linked message becomes more than a technical critique.. MISRYOUM frames AI not just as software. but as part of a broader economic system that can replicate old extractive patterns.. Ibrahim argues AI becomes harmful when it is imposed without free, prior, and informed consent.. In that context. she warns. AI can lead to appropriation—of land. of data. and even of knowledge—while leaving Indigenous communities without the benefits. protections. or credit they should hold.
The strongest counterweight, experts say, is Indigenous governance and sovereignty over both data and decisions.. Technology on its own does not stop deforestation, wildfire ignition, or illegal expansion; people do, guided by authority and accountability.. For project leaders involved in Indigenous territory protection. the emphasis is on community-led monitoring and on using AI outputs to trigger real-world action—combined with the ability for communities to control how data is collected and how it is used.
There is also an operational challenge that rarely appears in general AI discussions: capacity.. In the Arctic. for instance. leaders working with Sámi communities say the constraint is not interest or expertise. but funding and scale.. If communities cannot access the resources needed to build AI aligned with their norms and priorities. they may remain dependent on external systems that do not reflect their worldview.
Looking ahead. MISRYOUM sees a clear policy direction emerging from the UN-linked discussion: governments and project developers must prevent land-grabbing. water exploitation. and mining linked to AI energy and supply chains. while respecting Indigenous rights at every step.. The goal is not to choose between “AI for protection” and “no AI.” It’s to ensure AI is deployed in a way that strengthens stewardship without shifting new burdens—environmental. legal. or cultural—onto the communities that have protected ecosystems for generations.
In the end. the warning is grounded in a straightforward principle: if AI is to help protect Indigenous lands. it has to be governed by Indigenous consent. Indigenous priorities. and Indigenous control—otherwise. MISRYOUM reports. it risks repeating the very extraction dynamics that Indigenous peoples have long resisted.