Best for
Lesson 2 and 3 discussion, ethics circles, think-pair-share, debate preparation, and paragraph responses where students must justify a judgement.
Unit 7 AI Ethics • Years 9–10 • Discussion and writing • Print-ready
AI Ethics Scenarios
Critical decision-making scenarios and ethical frameworks to help ākonga evaluate the impact of artificial intelligence in Aotearoa.
Kōwhiringa Aromatawai · AI Ethics Scenarios
Ingoa / Name
Akomanga / Class
Read the following AI scenarios. Think about who benefits, who is harmed, and how tikanga values should guide your decision.
🧭 Ethical Questions to Ask
- Who Benefits? Who Is Harmed? Does this technology help everyone equally, or does it advantage some while disadvantaging others?
- Is There Bias? Does the AI treat different groups fairly? Does it reflect existing inequalities?
- Privacy & Data Rights? Who owns the data? Is consent freely given? Is privacy protected?
- Accountability? If something goes wrong, who is responsible? Can decisions be explained and challenged?
- Tikanga Alignment? Does this honour manaakitanga (care), kaitiakitanga (guardianship), and tino rangatiratanga (self-determination)?
Scenario 1: Facial Recognition in Schools
Your school wants to install facial recognition cameras at all entrances to "improve security." The AI would track who enters/exits, flag "suspicious behaviour," and create a database of student movements. The principal says it will reduce bullying and theft. Some students feel safer; others feel surveilled and uncomfortable.
🤔 Consider:
- How might this system be biased? (Research shows facial recognition is less accurate for Māori and Pasifika faces)
- What privacy rights do students have?
- Who has access to this data? For how long?
- Could this normalize constant surveillance?
Your Decision: Should the school install this system? Why/why not?
Alternative Solution:
Scenario 2: AI Hiring Tool
A major NZ company uses AI to screen job applications. The AI was trained on 10 years of past hiring data to identify "successful employees." After 6 months, a study finds the AI systematically rejects applications from people with Māori names, women with children, and people from low-income areas - even when their qualifications are identical to accepted candidates.
🤔 Consider:
- Why did the AI learn these biases? (Hint: Past hiring was biased!)
- Is this discrimination legal? Ethical?
- Who is responsible - the company, the AI developers, or both?
- How could this perpetuate inequality?
Your Decision: What should the company do?
How could AI hiring be made fair?
Scenario 3: Deepfake Technology
You discover a free AI tool that can create incredibly realistic fake videos (deepfakes) of anyone saying anything. Some students use it to create funny memes. Others use it to create fake videos of classmates doing embarrassing things or saying offensive statements. The fakes are so good, people can't tell they're not real.
🤔 Consider:
- What harm could this cause? (Reputation, bullying, trust in information)
- Should this technology be freely available?
- How does this relate to manaakitanga (caring for others)?
- What if it's used on public figures? Is that different?
Your Decision: Would YOU use this tool? Under what conditions (if any)?
How should deepfakes be regulated?
💭 Final Reflection
1. What ethical principles should guide AI development in Aotearoa?
2. How can tikanga values help us make ethical choices about technology?
3. What's ONE action YOU can take to use technology more ethically?
🌟 Extension Challenge
Create Your Own Scenario: Write a new AI ethics dilemma based on current technology. Share with classmates and discuss possible responses!
Your Scenario:
Dignity check: "He aha te mea nui o te ao? He tāngata, he tāngata, he tāngata." Technology should serve people, not replace human judgment and care. Keep this principle in mind as you work.
Ngā kōrero kaiako · Teacher notes — everything below supports the handout; it is not part of the printed worksheet.
Mō te kaiako · At a glance
Adapt this handout · Te Wānanga
Free ethics dilemmas, premium local adaptation
Run these scenarios as written, then use Te Wānanga if you want school-specific, iwi-specific, or younger-reader versions built around your context.
- Swap in local school, sports-club, workplace, or marae situations.
- Generate junior and senior versions of the same dilemma.
- Turn the discussion into an assessed speech, article, or recommendation memo.
Kaiako planning
Kaiako planning snapshot
- Use length: 20-30 minutes for one scenario, or 45-60 minutes for a full rotation and report-back.
- Grouping: Small groups work best because students have to test and defend their judgement aloud.
- Prep: Decide whether you want one shared scenario, rotating stations, or a written response task.
- Differentiation: Support learners can focus on one scenario deeply; extension learners can compare two responses and propose a policy.
- Teaching move: Keep pulling students back to who is affected, who decides, and what a better next step would actually be.
Resources already provided
- Four AI ethics scenarios grounded in school and public life
- Decision questions and te ao Māori values prompts
- Recommendation writing scaffold
- Teacher-only curriculum companion
What to print: one sheet per student or group. If you want a written output, add lined paper or have students use the recommendation box as a planner first.
Ngā whāinga me ngā paearu · Learning intentions & success criteria
Ngā Whāinga Akoranga / Learning Intentions
- We are learning how to judge AI dilemmas using fairness, evidence, and responsibility.
- We are learning how to identify who benefits, who may be harmed, and who should be consulted.
- We are learning how te ao Māori values can guide technology decisions in Aotearoa.
Paearu Angitu / Success Criteria
- I can explain the main issue in a scenario clearly.
- I can identify at least one harm, one benefit, and one missing perspective.
- I can justify a next step that is safer, fairer, or more culturally responsible.
Why this matters in Aotearoa
AI ethics is not only about whether a tool works. It is about whether the decision is fair, who holds authority, what data is used, and whether the people most affected have been treated with care and respect.
Good ethics discussion asks better questions. By grounding these conversations in Aotearoa scenarios, students learn to apply critical thinking to the digital systems shaping their own communities.
Dignity and safety note
Take care to ensure discussions about AI harms, particularly those affecting Māori and Pasifika, are handled respectfully and safely in the classroom. Avoid positioning Indigenous students as the class "expert" on bias.
Hononga Marautanga · Curriculum Alignment
Digital Technologies — Hangarau Matihiko
Level 4–5: Apply ethical reasoning to real-world digital scenarios; evaluate trade-offs in AI design and deployment; recognise how values and culture shape what counts as a fair or unfair outcome.
Social Sciences — Tikanga ā-Iwi
Level 3–4: Understand how technology shapes relationships, power, and identity within communities; evaluate the impacts of digital innovation on society and culture.
Aronga Mātauranga Māori
In tikanga Māori, utu (reciprocity) and manaakitanga (care for others) provide ethical principles that predate and outlast any algorithm. When students work through AI ethics scenarios, they can ask: Does this AI system uphold manaakitanga — does it genuinely serve the people it touches? Does it honour utu — does it return something of value without taking more than it gives? These are not abstract questions: they are tools for evaluating AI systems in real Aotearoa contexts.
Ngā Rauemi Tautoko · Support Materials
- AI Ethics and Bias — conceptual reading to prepare for these scenarios
- AI Bias Lab Activity — hands-on testing that grounds these scenarios
- Teacher Discussion Guide — kaiako facilitation support