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Anna: We wanted a case study that shows Indigenous communities leading their own digital futures, not being passive data subjects. Te Hiku Media is perfect because it’s iwi-owned, rooted in te ao Māori values and has built genuinely world-class AI tools while keeping sovereignty over the language assets.
Greg: Exactly. Their work illustrates that “open” doesn’t have to mean “public domain.” They use openness strategically—sharing with whānau, iwi partners and trusted researchers—while still protecting taonga. It gives us a concrete example of cultural protocols shaping a modern machine learning program.

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Anna: The organisation started as an iwi radio network in the Far North. Because they’ve been recording kaumātua voices for decades, they hold archives that Silicon Valley can’t replicate. When tech giants offered compute credits in exchange for the data, Te Hiku pushed back—they wanted partnership, not extraction.
Greg: Right, and that refusal is significant. Instead of chasing the fastest growth, they prioritised mana motuhake—self-determination. They sought funding from Māori trusts and philanthropies aligned with language revitalisation. That let them set terms before letting anyone access the corpus.

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Anna: Their governance model is anchored by the Kaitiakitanga licence, which literally says the data is a treasure held in trust for present and future iwi members. Any partner has to demonstrate reciprocity and cultural safety before touching the language assets.
Greg: And that’s backed by practice. They run hui where linguists, kaumātua and technologists review project proposals together. If whānau aren’t convinced the outcomes will uplift communities, the project pauses until the concerns are resolved. That blend of tikanga and agile delivery is what keeps sovereignty intact.

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Anna: The recording sprint they ran in 2019 is legendary—community members lined up to donate sentences in kura, marae and community centres. They paired each session with kai and cultural briefings so people understood where their voices would go.
Greg: The tech team then built a custom labeling tool because mainstream platforms couldn’t handle dialect nuances. They co-designed prompts with linguists to capture dialectical diversity, not just “standard” te reo. Contributors kept moral rights and could revoke samples, which is unheard of in most corporate datasets.

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Anna: From a technical perspective, they forked Mozilla Common Voice to jump-start infrastructure but stripped anything that conflicted with Māori governance. Storage sits in AWS Auckland zones with encryption keys controlled by Te Hiku, and every data access is logged for auditing by the board.
Greg: The roles are interesting too. They formalised “data kaitiaki” positions—people fluent in te reo who also understand privacy law. These staff sign off on data queries and review model outputs for cultural harm. It’s a career path that blends community leadership with product management skills.

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Anna: When global vendors came knocking, Te Hiku insisted on memoranda of understanding that detailed reciprocity. That included commitments to fund language revitalisation, keep infrastructure in Aotearoa and allow Te Hiku to veto secondary uses.
Greg: They also built tikanga clauses into the contracts—staff had to attend cultural safety training, and models couldn’t be repurposed for surveillance. Every partnership was staged with opt-out checkpoints so the community could walk away if promises were broken.

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Anna: The tangible results are huge. Automated transcription now captures iwi radio archives in hours instead of months, and whānau can search recordings for tīpuna names. The speech models achieved massive accuracy gains because they were trained on dialect-specific data.
Greg: Plus, the wider Indigenous tech movement took notice. Te Mana Raraunga referenced Te Hiku’s licensing approach when drafting national Māori data governance principles. Alumni from the project have moved into senior roles across government, iwi corporations and platform co-ops.

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Anna: So what should our learners copy from this? First, invest in cultural authority—make sure kaumātua, elders or cultural experts are leading alongside engineers. Second, treat licences as living documents that express consent and reciprocity, not just legal fine print.
Greg: And build career ladders. Roles like data kaitiaki, Indigenous product managers and kaupapa-aligned cybersecurity leads should have progression into senior leadership. Success metrics need to include community benefit and language vitality, otherwise the tech will drift away from its purpose.
Anna: That wraps the Te Hiku kōrero. Take a breath, capture the lessons, and then we can zoom out to mainstream open-source governance with fresh eyes—treat it as a separate toolkit you can compare and contrast, not as something that replaces the tikanga-led model we just explored.