Best for
Lesson 3 in Unit 7, ethics circles, values comparison, and design-thinking tasks where students must move beyond “AI is good/bad” into reasoned judgement.
Unit 7 AI Ethics • Years 7-10 • Worldview comparison • Print-ready
Te Ao Māori Values vs AI Development
Use this handout to help ākonga compare mainstream AI design assumptions with values drawn from te ao Māori. The goal is not to romanticise one system and reject the other. The goal is to ask better questions about whose values shape technology, who holds authority, and what a more tika digital future could look like in Aotearoa.
Free comparison scaffold, premium local adaptation
Run the worldview comparison as-is, then move into Te Wānanga if you want local iwi examples, younger reading levels, or a debate version built around your class context.
- Add local examples of Māori-led technology and digital innovation.
- Generate a bilingual discussion version with sentence stems and glossary support.
- Turn the design challenge into an assessed presentation or position statement.
Kaiako planning snapshot
- Use length: 35-50 minutes as a structured comparison and design task.
- Grouping: Pairs or small groups work well because students need to test and defend their interpretations of each value.
- Prep: Decide whether you will front-load the four key values or let students infer them from examples first.
- Differentiation: Support learners can complete one row well; extension learners can critique a real system and redesign it.
- Teaching move: Keep asking who defines success, who benefits, and who should hold decision-making power.
Resources already provided
- Comparison table between mainstream AI assumptions and te ao Māori values
- Short real-world case prompt using Māori-led AI development
- Design challenge with writable planning space
- Student reflection questions and teacher-only curriculum companion
What to print: one copy per student, plus one teacher-selected case study or projection slide if you want extra modelling.
Ngā Whāinga Akoranga / Learning Intentions
- We are learning how values shape the design and use of AI systems.
- We are learning how manaakitanga, kaitiakitanga, rangatiratanga, and whanaungatanga can act as design tests rather than decorative add-ons.
- We are learning how to compare different worldviews and justify our thinking with evidence.
Paearu Angitu / Success Criteria
- I can explain at least two differences between mainstream AI development and a te ao Māori values lens.
- I can apply one value to a real example and describe what would need to change.
- I can propose a more culturally responsible AI or digital-system decision.
Curriculum integration / Te Marautanga alignment
This handout works best where students are comparing systems, perspectives, and responsibilities. It bridges digital technologies, social studies, and critical reading rather than treating AI as a purely technical topic.
Why this matters in Aotearoa
AI systems are often described as neutral tools, but every system is shaped by human values, data, and power structures. In Aotearoa, questions about data, cultural knowledge, language, and authority are inseparable from Te Tiriti, tino rangatiratanga, and Māori aspirations for digital self-determination.
A useful AI question is not only “Can this system do the task?” but also “Is this system mana-enhancing, culturally safe, and accountable to the people it affects?”
Part 1: Two worldview starting points
| Question | Mainstream AI pattern | Te ao Māori values lens |
|---|---|---|
| What counts as success? | Efficiency, scale, speed, profit, and predictive accuracy. | Mana-enhancing outcomes, collective wellbeing, cultural safety, and long-term care. |
| Who decides? | Designers, companies, institutions, or investors. | Communities affected by the system, especially where taonga, data, or identity are involved. |
| How is data treated? | As a resource to collect, train on, and optimise. | As something with whakapapa, context, tikanga, and responsibilities attached. |
| Who is accountable for harm? | Often unclear or hidden behind complexity. | Responsibility must stay visible, relational, and open to challenge. |
Part 2: What if AI followed tikanga-informed design tests?
Manaakitanga
Does the system care for people well? Does it reduce harm, confusion, and exclusion?
Kaitiakitanga
Does it protect taonga, data, relationships, and future wellbeing rather than extracting from them?
Rangatiratanga
Do the people most affected have real authority over how the system is used and governed?
Whanaungatanga
Does the design strengthen relationships, trust, and mutual accountability?
Part 3: Real-world example
Te Hiku Media's Papa Reo is an important discussion point because it shows what Māori-led AI can look like when language, governance, and community purpose stay at the centre. It is not simply “AI translated into Māori”. It is a reminder that leadership, control, and cultural purpose matter in the design itself.
What makes this different?
- Māori language and community purpose are central, not an afterthought.
- The project raises questions about who owns voices, datasets, and digital taonga.
- It makes visible the difference between extraction and stewardship.
Discuss
- How is this different from a generic AI tool trained on scraped data?
- Where do you see rangatiratanga in the design choices?
- What safeguards should remain in place even when a project is community-led?
Part 4: Design challenge
Plan a digital system or AI tool that could support a whānau, kura, marae, or community need without flattening tikanga or removing human accountability.
1. The community need
2. Who needs to be consulted?
3. Which value will be hardest to uphold?
4. What safeguard is non-negotiable?
5. Sketch or describe your tikanga-informed AI idea
Teach this tomorrow
Print / share
- This handout
- One local or national Māori-led technology example for discussion
Decide before class
- Whether students compare worldviews first or start from the case study
- Whether the design task is individual, paired, or group-based
Look for by the end
- Students can explain why values shape technology decisions
- Students can move beyond generic fairness talk into tikanga-informed reasoning
Hononga Marautanga · Curriculum Alignment
Digital Technologies — Hangarau Matihiko
Level 4–5: Understand how digital systems and AI tools work; evaluate the social, cultural, and ethical implications of technology; design and apply computational thinking skills to real problems.
Social Sciences — Tikanga ā-Iwi
Level 3–4: Analyse how technology shapes relationships, power, and identity within communities; evaluate the impacts of digital innovation on society, including effects on Indigenous data sovereignty and cultural representation.
Aronga Mātauranga Māori
In te ao Māori, data and knowledge are not neutral — they carry whakapapa and obligations. Māori Data Sovereignty (Mana Motuhake i ngā Raraunga) holds that Māori have the right to govern, own, and interpret data about themselves and their communities. When digital systems are designed without this understanding, they risk perpetuating colonial patterns of extraction: taking knowledge from communities without accountability or benefit-sharing. The concept of kaitiakitanga extends naturally to the digital realm — guardianship of what is collected, stored, and shared about us is as important as guardianship of land, water, and living knowledge systems.
Ngā Rauemi Tautoko · Support Materials
This handout is designed to be used alongside the broader unit resources available at Te Kete Ako handouts library. Related resources from the same unit are linked in the unit planner. All resources are provided — no additional preparation is required to use this handout in your classroom.
Curriculum alignment
- Identity, Culture, and Organisation: Understand how cultural identity shapes participation in society — whakapapa, tikanga, and mana as foundations of Māori identity in Aotearoa New Zealand.