Unit 7: Digital Technologies & AI Ethics

Navigating the Future of Artificial Intelligence

This senior-level unit provides a critical and practical introduction to Large Language Models (LLMs) and Artificial Intelligence through integrated collaboration, combining technological literacy with Māori Data Sovereignty, ethical reasoning, and community-centered innovation.

Peer edition · Critical AI Ethics Seminar

Deliberate, reason, reflect, and act

This edition foregrounds explicit ethics teaching, structured kōrero, evidence-based deliberation, and personal reflection. Ākonga build a defensible ethical position before committing to community action.

Approach: Critical literacy seminar
Duration: Five 75-minute lessons
Scaffolding: Discussion protocols, ethics frameworks, and reflection prompts
Outcome: A personal ethics framework and community action commitment

Prefer project inquiry and design? Open the Inquiry & Design Studio edition →

Whakatūwhera - Unit Opening

As we stand at the dawn of the AI age, we must approach these powerful technologies with both wisdom and caution. This unit grounds AI learning in mātauranga Māori principles, ensuring that technology serves our communities while protecting what is sacred.

"Mā te huruhuru ka rere ai te manu" - It is the feathers that allow the bird to fly. Knowledge and ethics are our feathers in the digital realm.

📋 Kaiako Planning Snapshot

Ngā Whāinga Akoranga — Learning Intentions

Ākonga will understand how AI systems work at a conceptual level — including data, algorithms, training, and bias.
Ākonga will critically analyse the ethical implications of AI, including surveillance, privacy, algorithmic bias, and tino rangatiratanga.
Ākonga will apply mātauranga Māori values — kaitiakitanga, manaakitanga, and whanaungatanga — to evaluate and design responsible digital technologies.
Ākonga will take an informed position on a real AI ethics issue and communicate it persuasively.

Paearu Angitu — Success Criteria

I can explain how AI learns from data and why bias in training data matters.
I can identify at least two real-world AI ethics dilemmas and explain the harms and benefits.
I can connect a Māori value (e.g., kaitiakitanga) to a specific AI design decision.
I can argue a position on an AI ethics issue using evidence and ethical reasoning.

Entry / On-Level / Extension

Entry: Guided case study with structured questions; visual explainers of AI concepts; ethics frameworks provided as scaffolds.
On-level: Independent case study analysis; structured debate or persuasive essay; AI design challenge with ethical constraints.
Extension: Research a real AI system and write a policy recommendation; create an AI ethics charter for your school community.

Inclusion Guidance

ESOL / ELL learners: Glossaries for AI and ethics terminology. Use real-world examples close to students' experience. Oral discussion before written output.
Neurodiverse learners / ADHD: Break the ethics case study into clear steps. UDL principle: visual flowcharts for AI processes; choice between written, oral, or multimedia presentation.
Dyslexia: Audio-text versions of readings; annotated diagrams instead of dense text; voice recording accepted for analysis tasks.

Ngā Akoranga - Lesson Sequence

AI Foundations

Introduction to Large Language Models and foundational understanding of AI systems.

Ethics & Bias

Critical analysis of AI bias and ethical frameworks for responsible technology use.

Data Sovereignty

Exploring data ownership from a Te Ao Māori perspective and Indigenous knowledge protection.