Ethical Considerations of AIActivities & Teaching Strategies
Active learning helps Year 6 students grasp abstract ethical concepts by making them concrete and personal. When students debate, role-play, and design guidelines, they move beyond passive listening to active reasoning and empathy. These approaches align with how children learn best—by doing, discussing, and collaborating—especially on topics that blend logic with moral reflection.
Learning Objectives
- 1Critique the potential for algorithmic bias in AI decision-making systems used in healthcare or public safety.
- 2Analyze the ethical implications of AI accountability when errors occur in automated systems.
- 3Design a set of ethical guidelines for the responsible use of AI in a school environment.
- 4Compare different perspectives on AI's role in making life-altering decisions.
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Debate Carousel: AI in Health Decisions
Prepare four scenario cards on AI health uses, like automated diagnosis. Divide class into small groups to prepare pro and con arguments for 10 minutes. Groups rotate to debate each scenario with another group, noting new points on worksheets.
Prepare & details
Critique the idea of AI making decisions about human health or safety.
Facilitation Tip: During the Debate Carousel, assign clear roles (e.g., moderator, data scientist, patient advocate) to ensure every student contributes and stays engaged in the conversation.
Setup: Chairs arranged in two concentric circles
Materials: Discussion question/prompt (projected), Observation rubric for outer circle
Dilemma Role-Play: Safety Scenarios
Assign pairs roles like doctor, patient, or AI developer in safety dilemmas, such as AI controlling emergency vehicles. Pairs act out 3-minute skits, then switch roles. Whole class votes on best resolutions and discusses outcomes.
Prepare & details
Predict potential ethical dilemmas that could arise from advanced AI.
Facilitation Tip: In the Dilemma Role-Play, provide a brief ‘script starter’ for each scenario to help students begin their responses without scripting their emotions or values.
Setup: Chairs arranged in two concentric circles
Materials: Discussion question/prompt (projected), Observation rubric for outer circle
Guideline Workshop: School AI Rules
In small groups, students brainstorm and draft five ethical guidelines for school AI tools, like chatbots. Groups present to class for feedback. Class votes and refines into a shared poster.
Prepare & details
Design a set of ethical guidelines for the use of AI in schools.
Facilitation Tip: During the Bias Hunt, give students a simple three-column table to record their findings, keeping the task structured and focused on observable patterns.
Setup: Chairs arranged in two concentric circles
Materials: Discussion question/prompt (projected), Observation rubric for outer circle
Bias Hunt: Dataset Analysis
Provide printed datasets with biases. Individuals or pairs identify unfair patterns, then share in whole class discussion to propose fixes.
Prepare & details
Critique the idea of AI making decisions about human health or safety.
Setup: Chairs arranged in two concentric circles
Materials: Discussion question/prompt (projected), Observation rubric for outer circle
Teaching This Topic
Experienced teachers approach this topic by grounding abstract ethical questions in relatable, real-world contexts that students can explore through structured interaction. They avoid letting debates turn into opinion-based arguments by requiring students to cite evidence from datasets or scenarios. Teachers also model ethical humility, showing students that responsible AI use includes recognizing limitations and seeking human oversight. Research suggests that guided role-plays and collaborative guideline writing help students internalize ethical standards more deeply than lectures alone.
What to Expect
By the end of these activities, students will confidently identify ethical dilemmas in AI, justify their positions with evidence, and propose thoughtful guidelines. Success looks like students asking critical questions, recognizing bias, and supporting their ideas with examples from the activities. They should also show respect for diverse viewpoints during discussions and debates.
These activities are a starting point. A full mission is the experience.
- Complete facilitation script with teacher dialogue
- Printable student materials, ready for class
- Differentiation strategies for every learner
Watch Out for These Misconceptions
Common MisconceptionDuring the Debate Carousel, watch for students assuming AI decisions are always neutral and fair.
What to Teach Instead
During the Debate Carousel, pause the discussion and ask groups to examine sample diagnostic or traffic datasets. Have them highlight any patterns or missing groups that might lead to unfair outcomes, then revisit their debate points with this evidence in mind.
Common MisconceptionDuring the Dilemma Role-Play, watch for students believing AI can fully replace human judgment in ethics.
What to Teach Instead
During the Dilemma Role-Play, design scenarios where the AI’s recommendation leads to a negative outcome. After the role-play, facilitate a reflection where students identify what human qualities (empathy, context) were missing, and propose how humans should oversee AI in such cases.
Common MisconceptionDuring the Guideline Workshop, watch for students assuming privacy concerns disappear with advanced AI.
What to Teach Instead
During the Guideline Workshop, ask students to draft one rule about data collection and one about consent. Provide a short case study (e.g., a student’s medical data shared without permission) and have students revise their guidelines to directly address the risks in the scenario.
Assessment Ideas
After the Debate Carousel, present students with a scenario: An AI recommends denying a student access to a specialized school program based on predicted future academic performance. Ask: Who is responsible if the AI is wrong? What information should the AI have access to? What information should it NOT have access to? Listen for students connecting their debate points to accountability and data limitations.
After the Bias Hunt, provide students with a short paragraph describing an AI application (e.g., AI assisting doctors with diagnoses). Ask them to identify one potential ethical concern and one potential benefit, writing answers on a sticky note. Collect notes to assess if students can distinguish between bias risks and technical benefits.
During the Guideline Workshop, after groups draft one ethical guideline for AI use in schools, have groups swap their guideline with another group. Each group provides feedback on clarity and feasibility, suggesting one improvement. Collect the revised guidelines to assess whether students can articulate ethical principles in accessible language and refine them based on feedback.
Extensions & Scaffolding
- Challenge students who finish early to create a short comic strip illustrating a dilemma from the role-play or debate, showing both the AI’s decision and a human’s alternative response.
- For students who struggle, provide sentence starters for the guideline activity, such as, “AI should never ____ without ____ because ____.”
- Deeper exploration: Invite a guest speaker (e.g., a local tech ethicist or librarian discussing data privacy) to discuss how real-world organizations address these dilemmas.
Key Vocabulary
| Algorithmic Bias | Unfair outcomes produced by an AI system, often due to skewed or incomplete data used during its training. |
| Accountability Gap | The difficulty in assigning responsibility when an AI system makes a mistake or causes harm. |
| Ethical Guidelines | A set of principles or rules designed to ensure that AI is developed and used in a morally sound and fair way. |
| Transparency | The principle that the decision-making process of an AI system should be understandable and explainable. |
Suggested Methodologies
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