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Māori AI Governance Framework

A framework designed by Māori AI experts for use across the New Zealand public service, extending the Māori Data Governance Model to cover AI systems specifically. It has been reported as calling for an overhaul of the Algorithm Charter.

Published by Te Kāhui Raraunga.

What it asks for

  • AI systems should not be deployed in Aotearoa without Māori authority over Māori data being realised first.
  • Regular monitoring for bias, with the ability to exit or change a system where prejudice or stereotyping shows up.
  • Clear accountability for what a system does, and transparency about where it is used at all.

What we do about it

  • Every system we build has a named human accountable for its decisions and a documented way to turn it off.
  • We build the exit in from the start: your data, your prompts, your configuration, portable and yours.
  • Outputs are traceable to their inputs, so a bias claim can be investigated rather than argued about.

Read it at the source: Te Kāhui Raraunga. We describe it here, we do not speak for it.

Building something this framework touches?

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The other frameworks we build to

This is a plain description of what these frameworks ask for and how we build to them. It is not legal advice, and it is not a claim of endorsement, accreditation or partnership. Where a framework governs your organisation, take your own advice on it.

Inference that answers to tikanga, not just to a benchmark.

We build and run inference against the six principles of Māori data sovereignty set out by Te Mana Raraunga. For an organisation holding data about its own people, that is not a line at the bottom of a page. It decides where the model runs, what it is allowed to see, and who can switch it off.

Māori data stays Māori owned. Running a model over it does not transfer it, licence it, or turn it into training data.

  • Rangatiratanga

    Authority

    You decide what the model may see and what it may do with it. Access is yours to grant and yours to withdraw, and a withdrawal takes effect at the next inference, not at the next contract review.

  • Whakapapa

    Relationships

    Every output can be traced back to the documents, the records and the rules that produced it. Nothing arrives without a provenance you can follow.

  • Whanaungatanga

    Obligations

    Data gathered for one purpose is not quietly turned to another. A new use is a new conversation with you, not a schema change on our side.

  • Kotahitanga

    Collective benefit

    The gain comes back to the people the data came from, as hours returned to their staff and services that work better for their whānau.

  • Manaakitanga

    Reciprocity

    We leave you able to run it without us. Documentation, handover and the right to take the system elsewhere are part of the build, never an exit fee.

  • Kaitiakitanga

    Guardianship

    We hold your data in trust and never take ownership of it. It does not train our models or anyone else’s, it is returned or destroyed on request, and inference runs somewhere you can point at, on-shore or inside your own tenancy.

The six principles are those of Te Mana Raraunga, the Māori Data Sovereignty Network. The commitments beside them are ours.

Built on three things we don’t bend on.

Honesty

We tell you what AI can and cannot do, then we ship the part that pays for itself.

Speed

Find the one workflow costing the most, ship it to production, prove the return.

Care

Success is hours given back to people and dollars saved. Never the size of the invoice.