Environmental Equity of AI: An Indigenous Led Solution

By: Morgan Watters 

Everyday the prevalence of artificial intelligence (AI) in our everyday lives grows stronger. Along with this comes a rightfully troubling dialogue about the climate impacts of AI. Chances are you’re familiar with the concerns this technology sparks for our environment such as the large amount of fresh water used by data centers. It seems as though everyday facts are reposted on instagram telling us of the horrifying quantities of fresh water that we waste every time we ask simple questions to chat bots. While these numbers are concerning to read and may spark feelings of guilt they often fade to the backs of our minds as we struggle to grasp the reality of such water waste, far away from our comfortable and seemingly unaffected lives. 

This is the effect of two things. The first is a large hole in the conversation about AI’s water waste regarding who will actually experience the impacts. Much of the time this strain falls onto already burdened communities such as Indigenous people whose rights are frequently ignored in the face of technological development, an all too common form of racial capitalism. 

The second reason is a stark lack of something called geographical load balancing, a strategy in which the negative impacts of disruptive technology are shared evenly over the geographical regions of users. Currently many AI data centers are built in arid, dry areas, often near to or atop Indigenous land, despite the fact that this positions highly water dependent infrastructure on already drought-stressed land. The distribution of the environmental costs of AI parallels historical practices of settler colonialism and racial capitalism (Kak & West, 2023). 

In response to environmental concerns many initiatives are searching for strategies to increase the efficiency of these data centers however their ideas have major flaws. As stated in Harvard Business Review these strategies frequently focus on “easily measurable environmental metrics such as the total amount of carbon emissions and water consumption” and don’t sufficiently consider how AI’s environmental costs can be “equitably distributed across different regions and communities” (Ren & Weirman, 2024). 


Additionally the proposed solution of increasing data center efficiency to combat environmental impacts is challenged by something called Jevon’s Paradox. Jevon’s Paradox is a cycle of attempted increase in efficiency that has repeated over and over throughout history and ultimately is counter productive (Indigenous-led AI and data sovereignty in space, 2025). It works like this: Developers attempt to reduce resource extraction by increasing efficiency of data centers, the successful increase in efficiency significantly lowers price of technology. Increased accessibility causes demand for technology to skyrocket and creates a need to build more data centers. Increase in data centers increases extraction even further. Jevon’s Paradox seems to stump any ideas to decrease AI’s environmental impacts however, Indigenous researchers have other ideas. 

Star Nations is an Indigenous led initiative founded to support First Nations, Métis, and Inuit communities on the principle that data is kin, not oil. This ethos pushes back on colonial resource extraction from Indigenous people such as oil and insists that this pattern will not be repeated in a new form with Indigenous data. The initiative was created in response to the observed harm that AI is having on Indigenous land and the earth as a whole and the foresight that these problems will increase. Star Nations proposes an alternative path in which AI’s harm to our planet is completely avoided by moving this technology to space. This infrastructure would be an Indigenous led orbital AI system to reject big tech, protect data as a sacred trust and offer technology for collective benefit not shareholder profit. The project is currently in its capital raising phase and calling for investors to seize the opportunity to join. The roadmap calls for immediate action to develop prototypes and scale to global presence (Star Nations, n.d.). 

The development of AI is causing environmental harm to Indigenous people, violations of data sovereignty and enforcement of harmful stereotypes and cultural erasure. Initiatives like Star Nations prove that despite all this Indigenous leaders still hold innovation and knowledge to protect our planet, the same as they always have. Star Nations is the first Indigenous led AI Orbital-center to propose data sovereignty and Indigenous ownership. As stated in their ethos, “AI is for space because water is for life not machines”. If we listen to the original stewards of the land that AI feeds off of, we still have a chance to save the water for our grandchildren. 


SOURCES: 

• Kak, Amba, and Sarah Myers West. “2023 Landscape: Confronting Tech Power.” AI Now Institute, 17 June 2025, ainowinstitute.org/publications/research/2023-landscape-confronting-tech-power#contributors 
• Ren, Shaolei, and Adam Wierman. “The Uneven Distribution of Ai’s Environmental Impacts.” Harvard Business Review, 15 July 2024, hbr.org/2024/07/the-uneven-distribution-of-ais-environmental-impacts?utm_medium=paidsearch&utm_source=google&utm_campaign=domcontent_bussoc&utm_term=Non-Brand&tpcc=domcontent_bussoc&gad_source=1&gad_campaignid=20702632551&gbraid=0AAAAAD9b3uQjybSfQIEuTQBMqrdjlEr_l&gclid=Cj0KCQiAp-zLBhDkARIsABcYc6t9FZYKZfSIo07lawuw3tRXlwXHCXVJxTlOheZGZQur7famT-VsPgcaAreEEALw_wcB 
• Indigenous-led AI and data sovereignty in space. “ The Hidden Cost of AI: Why Indigenous Leaders Are Moving Data Centers to Space .” YouTube, 20 Dec. 2025, www.youtube.com/watch?v=meShMGFZ8AE 
• “Star Nations: Indigenous Ai Data Center in Space: Empower First Nations.” Star Nations – Indigenous AI & Space Data Sovereignty -, 17 Jan. 2026, starnations.space/. 
• “Star Nations: Indigenous Ai Data Centre in Space.” Star Nations | Indigenous AI Data Centre in Space, star-nations-507215718338.us-west1.run.app/.