Māori Data and AI – guidance for business
Māori Data and AI Guidance for Business
This high-level guidance introduces basic concepts for businesses handling Māori data and artificial intelligence in New Zealand. It explains what Māori data and Māori data sovereignty are, outlines practical steps to protect and respect Māori data, and details core values like mana whakahaere and kaitiakitanga. The document emphasizes avoiding harm, ensuring collective benefit, and involving Māori in decision-making and AI development.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This is for business leaders, developers, and deployers using artificial intelligence who need to understand how to ethically handle Māori data.
What the document contains
The document covers high-level principles, practical business actions, and definitions concerning Māori data and artificial intelligence. It addresses data collection, risk identification, stakeholder engagement, transparency, and data sovereignty principles.
The document does not provide binding legal enforcement mechanisms, detailed technical auditing procedures, or formal regulatory compliance penalties.
- Māori data includes any digital information about or from Māori people, language, culture, resources, or environments, and is considered a taonga.
- Businesses must look beyond basic data ownership to avoid harms like bias, discrimination, and stigmatisation when using Māori data for AI.
- Engaging diverse teams, establishing Māori partnerships early, and ensuring human oversight are essential operational practices.
- Guiding values such as mana whakahaere, kaitiakitanga, manaakitanga, whakapapa, and he waka eke noa provide ethical foundations for working with Māori data.
- Businesses should establish clear boundaries for data use, respect data sensitivity, and ensure that AI applications provide collective benefit to communities.
· About this guidance · Māori Data and AI · What is Māori Data · Data as a Taonga · What to do practically (Do no harm and ensure Māori benefit from the use of their data) · Identify and understand what Māori data you collect or use · Be transparent and explain how AI uses Māori data · What is Māori Data Sovereignty · What to do practically (Invite representation of Māori views in decision-making, Set clear boundaries on Māori data use, Grow your business capability) · Guiding values · Start the journey
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
2/5Clear responsibility for AI outcomes
Māori Data Governance incorporates principles, structures, accountability mechanisms, legal instruments, and policies through which Māori exercise control over their data.
What is Māori Data Sovereignty
screening score · 2026-10-24
Fairness
4/5Non-discrimination and equitable treatment
There is a higher likelihood that bias, discrimination, inaccuracy, and other harms could materialise for Māori in your AI use.
What to do practically
screening score · 2026-10-24
Human Dignity
0/5Respect for the inherent worth of persons
N/A
screening score · 2026-10-24
Human Oversight
4/5Humans remain in control of consequential decisions
Always have a person in the process to assess for unintended consequences.
What to do practically
screening score · 2026-10-24
Privacy
4/5Protection of personal data and private life
Regardless of how you are using the data, there is an obligation to keep the data safe, protect its privacy and confidentiality, and ensure appropriate use.
Kaitiakitanga – Guardianship
screening score · 2026-10-24
Transparency
4/5Openness about how AI systems work and are used
Be able to explain how Māori data is used, for what purpose, and how it was used by the AI. Document all decision-making and data usage in ways that are transparent and accessible.
What to do practically
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-24
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
Identify potential risks or harms that could occur, such as discrimination or stigmatisation, such as from biased or unrepresentative data. Have a plan to mitigate these risks.
What to do practically
screening score · 2026-10-24