Localized AI: A Path Forward Grounded in Indigenous Practice
Around the world, the most thoughtful and sustainable uses of AI aren’t coming from Silicon Valley, but from Indigenous communities designing tools for their people, on their terms.
Look at the Māori AI ecosystems in Aotearoa, New Zealand.
Projects like Te Hiku Media’s Māori speech recognition models, built entirely from community-owned data, are globally recognized as a gold standard for how AI should be built: slow, intentional, governed by the people who are most impacted, and structured so the technology serves the community, not the other way around.
Take the Sàmi language technology efforts in Northern Europe.
Instead of building sprawling, general-purpose AI, Sàmi technologists intentionally create small, precise, culturally-aligned tools, from NLP trained specifically for endangered Sàmi dialect, to generative systems that help teachers build curriculum for communities where fluent speakers are aging. These tools don’t chase scale for scale’s sake. They’re narrow by design: built to preserve autonomy, strengthen culture, and respect the human beings who use them.
These Indigenous-led AI efforts aren’t alternatives.
Journalist Karen Hao, in Empire of AI, points to these projects as some of the clearest examples of alternative AI futures. Futures that are not extractive, not industrial-scale surveillance, but deeply local and accountable.
Here’s the point I want to add to that conversation:
These Indigenous-led AI efforts aren’t “alternatives”. They are modern expressions of a long lineage of sustainable practice.
For centuries, Indigenous communities have built ecological, agricultural social systems grounded in interdependence, long-term stewardship, and humility.
AI, when built this way, becomes a tool that:
Supports human agency
Preserves environmental and cultural knowledge
Avoids the high-energy, high-extraction arms race of modern AI
Augments the community instead of restructuring it
This is sustainability in its most contemporary form to date.
A Course-Correction We Desperately Need
We already know what happens when humanity abandons Indigenous principles of balance and restraint: climate catastrophe, mass species extinction, extractive industries that hollow out communities.
We are living the consequences of a technological worldview defined by domination, speed, and scale.
Localized, Indigenous-governed AI offers a chance to consciously choose a different path; one where we use hindsight to steer the ship before we repeat the same cycle in the digital domain.
A path where AI is small, useful, culturally-rooted, and built to last.
A path that rejects industrial scale for precise, culturally-aligned tools that are built slowly and serve human agency.
A path where humans don’t disappear inside the machine, but remain firmly in control of it.
