Te Kete Ako
Unit 7: Digital Technologies & AI Ethics Lesson 1 of 5

Understanding AI Through Te Ao Māori: Intelligence, Wisdom, and Cultural Values

Duration: 75 minutes Year Level: 9-13 Curriculum Areas: Digital Technologies, Te Ao Māori, Science

🌅 Karakia & Cultural Opening

"Kia mohio ai tātou" - That we may understand

Opening Protocol (5 minutes)

  1. Knowledge Acknowledgment: Honoring both traditional Māori knowledge systems and contemporary technological innovation
  2. Wisdom Intention: Setting intention to approach AI with wisdom and cultural grounding
  3. Human-Centered Values: Remembering that technology serves people, not the reverse

🎯 Learning Objectives & Success Criteria

By the end of this lesson, ākonga will be able to:

  • Define: Explain artificial intelligence in accessible, non-technical language
  • Compare: Contrast machine learning with traditional Māori knowledge systems
  • Analyze: Examine AI through Te Ao Māori values and ethical frameworks
  • Evaluate: Assess potential benefits and risks of AI for Indigenous communities

Success Criteria - Ākonga will demonstrate:

  • ✓ Clear understanding of what AI is and isn't
  • ✓ Recognition of both opportunities and threats AI presents
  • ✓ Application of cultural values to technology assessment
  • ✓ Critical thinking about AI's impact on Indigenous communities

Phase 1: AI Demystification - What Actually IS Artificial Intelligence? (20 minutes)

Interactive AI Understanding Workshop

15 minutes exploration + 5 minutes synthesis

AI Myth-Busting Activity (8 minutes):

Students work in pairs to categorize statements about AI as "Fact," "Fiction," or "Complicated":

Statements to Categorize:
  • "AI can think like humans"
  • "AI is just very sophisticated pattern recognition"
  • "AI will replace all human jobs"
  • "AI can be biased against certain groups of people"
  • "AI is completely objective and neutral"
  • "AI can create art and write stories"
  • "AI understands the meaning of what it says"
  • "AI systems learn from the data they're trained on"
  • "AI is conscious and has feelings"
  • "AI can make decisions that affect real people's lives"

Hands-On AI Exploration (7 minutes):

Students interact with simple AI tools to understand how they work:

Station 1: Language AI
  • Use ChatGPT or similar to ask questions about Māori culture
  • Observe what it gets right/wrong
  • Notice how it responds to questions it doesn't know
Station 2: Image Recognition
  • Use Google Lens or similar to identify objects
  • Test with cultural objects or images
  • Notice what it recognizes vs. what it misses
Station 3: Recommendation Systems
  • Examine Netflix, Spotify, or TikTok recommendations
  • Discuss how the algorithm "learns" preferences
  • Consider what influences these recommendations

Synthesis Discussion (5 minutes):

Whole class discussion to build shared understanding:

  • What surprised you about how AI actually works?
  • What can AI do well? What are its limitations?
  • How is AI different from human intelligence?
  • What questions do you still have about AI?

Phase 2: Mātauranga Māori vs Machine Learning - Different Ways of Knowing (25 minutes)

Comparative Knowledge Systems Analysis

Knowledge System Comparison Framework (10 minutes):

Working in groups of 4, students create comparative analysis using provided framework:

Mātauranga Māori (Traditional Māori Knowledge)
How is knowledge created?
  • Observation of natural patterns over generations
  • Spiritual and cultural understanding
  • Community wisdom and collective experience
  • Integration of practical and sacred knowledge
How is knowledge validated?
  • Testing against real-world outcomes
  • Elder approval and cultural protocols
  • Consistency with whakapapa and cultural values
  • Community consensus and intergenerational transmission
How is knowledge shared?
  • Oral tradition, storytelling, whakataukī
  • Ceremonial and cultural practices
  • Mentorship and relationship-based learning
  • Contextual application in specific situations
Machine Learning (AI Knowledge Creation)
How is knowledge created?
  • Pattern recognition in large datasets
  • Statistical analysis and correlation finding
  • Repetitive training on examples
  • Mathematical optimization processes
How is knowledge validated?
  • Testing against reserved data sets
  • Performance metrics and accuracy scores
  • Peer review of technical methods
  • Real-world deployment testing
How is knowledge shared?
  • Code repositories and technical papers
  • APIs and software interfaces
  • Commercial products and services
  • Automated application without human interpretation

Strengths & Limitations Analysis (8 minutes):

Groups complete analysis matrix:

Aspect Mātauranga Māori Strengths Machine Learning Strengths
Speed Slow, deliberate, generational Extremely fast processing
Wisdom Deep understanding of meaning and context Pattern recognition without understanding
Values Integration Inherently value-laden and culturally grounded Claims objectivity but reflects training bias
Scale Community and relationship-based Can process massive amounts of information

Integration Possibilities Discussion (7 minutes):

Whole class explores: "How might these knowledge systems complement each other rather than compete?"

Discussion Prompts:
  • Could AI help preserve and share mātauranga Māori more effectively?
  • Could mātauranga Māori provide ethical guidance for AI development?
  • What would "Indigenous AI" look like?
  • How might AI support rather than replace traditional knowledge?

Phase 3: Cultural AI Ethics Framework Development (25 minutes)

Te Ao Māori AI Ethics Design Workshop

Values-Based AI Assessment Framework (15 minutes):

Groups work to create ethical framework for evaluating AI using Te Ao Māori values:

Whakapapa (Relationships & Connections)

Applied to AI: How does this AI system affect relationships between people, communities, and the environment?

  • Does it strengthen or weaken human connections?
  • How does it handle personal and cultural information?
  • Does it respect the interconnectedness of all things?
Manaakitanga (Care & Hospitality)

Applied to AI: Does this AI system care for and protect the wellbeing of all users?

  • Is it designed with user welfare as the priority?
  • Does it protect vulnerable users from harm?
  • How does it handle consent and user agency?
Kaitiakitanga (Guardianship & Stewardship)

Applied to AI: How does this AI system protect and preserve what is valuable for future generations?

  • What is its environmental impact?
  • How does it handle cultural knowledge and intellectual property?
  • Does it contribute to or detract from long-term wellbeing?
Tino Rangatiratanga (Self-Determination)

Applied to AI: Does this AI system support or undermine people's ability to make their own decisions?

  • Who controls the AI system and its decisions?
  • Can users understand how it works and what it's doing?
  • Does it empower or disempower communities?

AI System Evaluation Practice (10 minutes):

Groups use their framework to evaluate a real AI system:

Scenario Options (each group chooses one):
  • Social Media Algorithm: How Facebook/Instagram decides what content to show users
  • Job Application Screening: AI that filters job applications before humans see them
  • Medical Diagnosis AI: AI that helps doctors identify diseases from symptoms or images
  • Predictive Policing: AI that predicts where crimes are likely to occur
  • Educational AI Tutor: AI that provides personalized learning support to students
Evaluation Process:
  1. System Understanding (3 mins): What does this AI system do? How does it work?
  2. Values Assessment (5 mins): Apply each Te Ao Māori value to evaluate the system
  3. Recommendations (2 mins): What changes would make this system more aligned with Māori values?

🌅 Whakamutunga - Reflection & Closing

AI Ethics Commitment & Cultural Grounding (5 minutes)

Personal AI Ethics Reflection:

Students complete individual reflection:

  1. What is one thing about AI that you understand differently now?
  2. Which Te Ao Māori value is most important for guiding AI development? Why?
  3. How might you approach AI tools differently after this lesson?
  4. What questions about AI and ethics do you want to explore further?

Closing Circle - Tech Wisdom Sharing:

Students share one insight about balancing technology with cultural values, followed by teacher reflection:

"He aha te mea nui o te ao? He tangata, he tangata, he tangata"

As we explore AI and digital technologies, we remember that people remain the most important thing in the world. Technology should serve humanity, respect our values, and strengthen our connections to each other and our culture. Your cultural grounding gives you wisdom to navigate the digital future.

📊 Assessment & Next Steps

Formative Assessment - Today's Evidence:

  • Conceptual Understanding: Accuracy in AI myth-busting and system exploration
  • Comparative Analysis: Quality of knowledge systems comparison
  • Values Application: Depth of Te Ao Māori values integration in ethics framework
  • Critical Thinking: Sophistication of AI system evaluation

Preparation for Lesson 2:

  • AI Observation: Notice and document 3 examples of AI in your daily life
  • Bias Investigation: Find one example of AI bias or error in news/social media
  • Cultural Reflection: Think about how AI might impact Māori communities specifically

🛠️ Teacher Resources & Adaptations

AI Tools for Classroom Exploration:

  • ChatGPT/Claude: Free language AI for testing responses
  • Google Lens: Image recognition for cultural object testing
  • Teachable Machine: Simple tool for students to train their own AI
  • AI Safety Resources: Partnership on AI educational materials

Cultural Consultation Support:

  • Local Kaumātua: Invite cultural advisors to validate mātauranga discussion
  • Te Reo Integration: Incorporate relevant Māori tech vocabulary
  • Iwi Tech Leaders: Connect with Māori professionals in tech industry
  • Cultural Protocols: Ensure respectful handling of cultural knowledge

Differentiation Strategies:

  • Tech Experience Levels: Pair tech-savvy with less experienced students
  • Cultural Knowledge: Welcome diverse cultural backgrounds while centering Māori perspectives
  • Learning Preferences: Offer visual, kinesthetic, and discussion-based options
  • Extension Activities: Advanced students can research specific AI applications