Digital Technologies • Years 11-13 • Ready to teach

AI Ethics Through Māori Data Sovereignty

Use this senior digital technologies lesson to explore AI ethics through Raraunga Māori, tino rangatiratanga, and culturally grounded decision-making in Aotearoa classrooms.

Teaching use

Whole-class lesson, discussion prompt, or ethics mini-unit anchor.

Best for

Senior digital technologies, AI ethics, and data sovereignty inquiry.

Prep level

Low to medium. Best with a short local context or current case study.

Next step

Adapt it in Te Wānanga or save your version to My Kete for later reuse.

Use this lesson as a starting point

This page is free to use as-is. If you want a faster class-ready variant, Te Wānanga can turn this topic into a draft tailored to your year level, context, and local examples, then pass it through Creation Studio for editing and saving.

  • Keep the kaupapa, but shift the case study to your class context.
  • Turn this into a worksheet, discussion lesson, or assessment draft.
  • Save the adapted version into My Kete for reuse next term.
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Teacher planning snapshot

  • Duration: 2 to 4 lessons of 50 to 60 minutes depending on the depth of case study and policy writing.
  • Grouping: Whole-class framing, then mixed-ability groups for case analysis and policy design.
  • Prep: Choose whether students will respond to the provided health-data case study or a local AI/data example from your context.
  • Pedagogy: Start with rights and relationships, not just technical systems, then move into policy reasoning.
🕒 Flexible 2-4 lesson sequence 👥 Discussion + collaborative policy design

Resources provided here

  • Cultural framing and key Māori concepts for the class introduction
  • Ready-to-use health-data case study and discussion questions
  • Group ethical framework activity and policy scaffold
  • Assessment rubric, glossary, and teacher implementation notes
  • Linked curriculum companion page for planning and reporting

You can add a contemporary AI example from the news, but the lesson sequence and assessment scaffold are already complete on this page.

Ngā Whāinga Ako / Learning Intentions

  • We are learning to explain why Māori Data Sovereignty matters in digital systems and AI design.
  • We are learning to evaluate AI ethics decisions using concepts such as tino rangatiratanga, manaakitanga, and kaitiakitanga.
  • We are learning to design a practical policy response that protects people, data, and relationships.

Paearu Angitu / Success Criteria

  • I can explain at least three Māori Data Sovereignty principles in my own words.
  • I can identify ethical risks in an AI system that uses Māori data.
  • I can create a policy or recommendation that is practical, respectful, and culturally grounded.

Curriculum integration / Te Marautanga alignment

This lesson should be taught with curriculum links made explicit. Use the companion curriculum page to see where this resource supports digital technologies, social sciences, and English-rich discussion and writing outcomes in the New Zealand Curriculum.

💻 Digital Technologies 🗣️ Discussion and argument 🤝 Ethics and citizenship
Open curriculum companion Explore wider curriculum coverage

Cultural Context: Tikanga Māori and Technology

The concept of Raraunga Māori (Māori Data Sovereignty) is based on the principle that data about Māori should be governed by Māori. This aligns with the broader concept of Tino Rangatiratanga (self-determination).

Key considerations:

  • Manaakitanga - Respect and care in how data is collected and used
  • Kaitiakitanga - Guardianship and protection of data
  • Whanaungatanga - Relationships and connections in data sharing
  • Tapu - The sacredness of certain knowledge and information

When developing AI systems that may use Māori data, these principles should guide ethical decision-making.

Understanding the Issues

Artificial Intelligence systems often rely on large datasets that may include information about indigenous peoples. Without proper governance, this can lead to:

  • Misrepresentation of Māori knowledge and culture
  • Commercial exploitation without benefit sharing
  • Perpetuation of biases and stereotypes
  • Loss of control over culturally sensitive information

Case Study Analysis

Scenario: A health AI system is being developed using patient data from New Zealand hospitals. The data includes significant information about Māori patients.

Questions for discussion:

  1. Who should have control over this data?
  2. How could the principles of Raraunga Māori be applied?
  3. What potential harms might occur if Māori perspectives aren't considered?
  4. How could the developers ensure ethical use of this data?

Group Activity: Ethical Framework Development

In small groups, create a 5-point ethical framework for AI developers working with Māori data. Consider:

  • Data collection methods
  • Consent processes
  • Ongoing governance
  • Benefit sharing
  • Culturally appropriate algorithms

Assessment

Task: Create a proposal for an AI ethics policy that incorporates Māori Data Sovereignty principles.

Ready-to-use policy scaffold

  1. Name the AI context or system your policy is responding to.
  2. Explain what Māori data, taonga, or relationships are affected.
  3. Identify the main ethical risk or harm.
  4. Set out the guiding principles your policy will follow.
  5. Describe the practical governance steps that must happen before the system is used.
Criteria Achieved Merit Excellence
Understanding of Raraunga Māori Basic description of concepts Clear explanation with relevant examples In-depth analysis with connections to broader indigenous rights
Application to AI Ethics Identifies some ethical considerations Develops coherent ethical guidelines Creates innovative, culturally-grounded solutions
Practical Implementation Suggests basic policy elements Develops workable policy framework Detailed implementation plan with stakeholder considerations

Self-Checklist

  • I have explained at least 3 Māori Data Sovereignty principles
  • I have identified specific AI ethics concerns related to Māori data
  • My proposal includes practical implementation steps
  • I have considered multiple stakeholder perspectives
  • My work shows cultural respect and accuracy

Teach this tomorrow

  • Use the provided health-data case study first unless your class already has enough background to transfer the ethics lens independently.
  • Print or share the glossary, discussion questions, and policy scaffold already on this page.
  • Decide whether groups will all build one shared ethical framework or compare different AI contexts.
  • Open with tikanga and respect expectations before debating data use, consent, or governance.

The key teaching materials are already here: cultural framing, glossary, case study, discussion questions, scaffold, and rubric. The extra prep is mostly about choosing how broad or how tightly guided the policy task should be for your class.

By the end of lesson one...

  • Students can explain at least two Māori Data Sovereignty principles in context.
  • Each group has identified the main ethical risks in the shared case study.
  • You can see who is ready to draft an AI policy and who still needs sentence starters or guided modelling.
  • The class is ready to turn discussion into a structured proposal in the next lesson.

Extension Activities

1. Comparative Analysis

Research how other indigenous communities (e.g., Native American tribes, Australian Aboriginal groups) approach data sovereignty. Create a Venn diagram comparing their approaches with Raraunga Māori.

2. Algorithm Audit

Select a commonly used AI system (e.g., facial recognition, recommendation algorithms) and analyze how it might impact Māori users. Consider:

  • Data sources used to train the system
  • Potential biases in the algorithms
  • Ways the system could be made more culturally responsive

3. Policy Debate

Organize a class debate on the statement: "All AI systems using Māori data should require approval from relevant iwi authorities."

Teacher Implementation Notes

Prior Knowledge: Students should have basic understanding of AI systems and data collection practices. Some familiarity with Māori perspectives is helpful but not essential.

Suggested Timing:

  • Introduction and cultural context: 1-2 periods
  • Case study analysis and activities: 2-3 periods
  • Assessment task completion: 2-3 periods
  • Extension activities: 1-2 periods each

Differentiation:

  • Support: Provide template for ethical framework with starter statements
  • Extension: Challenge students to develop technical implementations of their ethical frameworks

Cultural Safety:

  • Consult with local iwi or Māori advisors if available
  • Create space for Māori students to share perspectives if they choose
  • Ensure all discussions maintain respect for Māori knowledge systems

Support / Tautoko

  • Provide sentence starters for ethical reasoning and policy language.
  • Use the shared health-data case study before asking students to transfer their thinking to a new example.
  • Allow students to submit their policy as annotated bullet points before extended writing.

Extend / Whakawhānui

  • Challenge students to compare Māori Data Sovereignty with another indigenous data sovereignty framework.
  • Ask students to identify where an algorithm charter would still be insufficient without governance change.
  • Invite a technical appendix that explains how their policy would change system design or data collection.

Whānau and hapori connection

Invite ākonga to ask whānau how they feel about personal, cultural, or community information being stored and used by digital systems. Students can bring back one concern, one hope, or one question and test their policy against it.

Resources and References

Everything referenced for the core lesson is already on this page: the cultural framing, case study, discussion questions, policy scaffold, glossary, and assessment rubric. The links below extend or deepen the kaupapa if you want more context.

Glossary of Māori Terms:

  • Raraunga Māori - Māori Data Sovereignty
  • Tino Rangatiratanga - Self-determination, sovereignty
  • Manaakitanga - Hospitality, kindness, respect
  • Kaitiakitanga - Guardianship, stewardship
  • Whanaungatanga - Relationship, kinship
  • Tapu - Sacred, restricted
  • Iwi - Tribe, nation

After teaching this

If this lesson works for your class, the strongest next move is to save an adapted version and build your own reusable ethics/resource bank. Te Wānanga and Creation Studio are there for that continuation, not to replace the free lesson library.

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🌍 Inclusion & Accessibility

ELL / ESOL support: Pre-teach key vocabulary before the lesson. Provide bilingual glossaries where available. Allow responses in home language as a first step.

Neurodiverse learners: Chunk instructions clearly. Offer choice in how students demonstrate understanding. Use visual supports and structured templates.

Scaffold & extension: Offer scaffold tasks and entry-level supports for students who need them. Extend capable learners with open-ended extension challenges.

Curriculum alignment