The Ethics of Artificial Intelligence

Active learning works well for this topic because ethical debates about AI require students to wrestle with complex, real-world dilemmas where facts and values intersect. Students need opportunities to practice applying ethical frameworks, testing their own assumptions, and collaborating to find balanced solutions.

• Grade 12
• Canadian & World Studies
• 3 activities
• 25 min–60 min

Learning Objectives

1. Critique the ethical frameworks proposed for AI development and deployment.
2. Analyze the potential for algorithmic bias to exacerbate existing social and economic disparities.
3. Design a policy proposal for an international body to govern AI, considering human rights implications.
4. Evaluate the impact of AI on democratic processes, identifying both risks and opportunities.
5. Synthesize arguments for and against international AI regulation through treaties.

Simulation Game

⏱ 60 min·Small Groups

Simulation Game: The AI Ethics Board

In small groups, students act as an ethics board for a tech company or a government agency. They are given a proposal for a new AI tool (e.g., facial recognition for policing or an algorithm for hiring) and must decide whether to approve, modify, or reject it based on ethical criteria.

Prepare & details

Evaluate whether there should be an international treaty to regulate AI development and use.

Facilitation Tip: During the AI Ethics Board simulation, assign roles deliberately to ensure conflicting viewpoints are represented, even if students disagree with them.

Setup: Flexible space for group stations

Materials: Role cards with goals/resources, Game currency or tokens, Round tracker

• Apply
• Analyze
• Evaluate
• Create
• Social Awareness
• Decision-Making

Inquiry Circle

⏱ 50 min·Small Groups

Inquiry Circle: AI and the Future of Work

Small groups research which job sectors in Canada are most likely to be impacted by AI and automation. They create a 'Risk and Opportunity' report and propose a policy (like retraining programs or a basic income) to support workers.

Prepare & details

Analyze how algorithmic bias can reinforce existing societal inequalities.

Facilitation Tip: For the AI and the Future of Work investigation, provide students with a mix of quantitative data and human-centered stories to help them see both the scale and the individual impact of labor displacement.

Setup: Groups at tables with access to source materials

Materials: Source material collection, Inquiry cycle worksheet, Question generation protocol, Findings presentation template

• Analyze
• Evaluate
• Create
• Self-Management
• Self-Awareness

Think-Pair-Share

⏱ 25 min·Pairs

Think-Pair-Share: Should We Regulate AI?

Students read two perspectives: one arguing for strict government regulation of AI to protect rights, and another arguing that regulation will stifle innovation and put the country at a disadvantage. They discuss with a partner which approach is better.

Prepare & details

Design ways AI can be used to strengthen rather than undermine democracy.

Facilitation Tip: When facilitating the Think-Pair-Share on AI regulation, have students first write down their thoughts privately to ensure quieter students contribute before group discussion.

Setup: Standard classroom seating; students turn to a neighbor

Materials: Discussion prompt (projected or printed), Optional: recording sheet for pairs

• Understand
• Apply
• Analyze
• Self-Awareness
• Relationship Skills

Teaching This Topic

Experienced teachers approach this topic by grounding abstract concepts in concrete examples students can relate to, such as social media feeds or hiring algorithms. They avoid presenting AI ethics as a purely philosophical exercise, instead framing it as a design challenge where technical decisions have ethical consequences. Research suggests that students retain ethical reasoning better when they must defend their positions in low-stakes, iterative discussions rather than one-time debates.

What to Expect

Successful learning looks like students recognizing the tensions between innovation and regulation, articulating thoughtful positions supported by evidence, and demonstrating empathy for diverse perspectives. They should move beyond abstract ideas to connect AI ethics to tangible impacts on people's lives.

Watch Out for These Misconceptions

Common Misconception

During the AI Ethics Board simulation, watch for students assuming AI systems are neutral because they are 'based on math and data.'

What to Teach Instead

Use the AI Ethics Board's deliberation time to prompt students to examine the data sources, the values embedded in the algorithm's design, and whose interests are prioritized or excluded in the system's deployment.

Common Misconception

During the AI Audit of their digital lives, watch for students claiming AI is a 'future' technology that does not yet affect them.

What to Teach Instead

Have students trace their daily interactions with AI tools (e.g., recommendation algorithms, predictive text, automated customer service) and identify at least one immediate impact on their rights or opportunities.

Assessment Ideas

Discussion Prompt

After the AI Ethics Board simulation, facilitate a debrief where students must justify their group's recommendation using evidence from the simulation's scenarios and counterarguments raised during the debate.

Quick Check

During the Collaborative Investigation on AI and the Future of Work, ask students to identify one ethical concern and one potential benefit of an AI application in their assigned industry, then explain how algorithmic bias could emerge in that specific context.

Peer Assessment

After students draft policy recommendations for regulating AI, pair them to exchange drafts and provide feedback focused on whether the recommendation addresses employment impacts and human rights, along with one specific improvement.

Extensions & Scaffolding

• Challenge students to draft a counter-policy that addresses the shortcomings of their group's AI Ethics Board recommendation.
• Scaffolding: Provide sentence starters like, 'One concern about this AI system is...' for students who struggle to articulate ethical objections.
• Deeper exploration: Ask students to research a recent AI policy proposal from a country outside their own and compare it to their group's recommendation.

Key Vocabulary

Algorithmic Bias	Systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others.
AI Governance	The set of rules, practices, and processes by which artificial intelligence is directed and controlled at a global or national level.
Deepfakes	Synthetic media in which a person in an existing image or video is replaced with someone else's likeness, often used to spread misinformation.
Human Rights	Fundamental rights inherent to all human beings, regardless of race, sex, nationality, ethnicity, language, religion, or any other status, which AI development must consider.
Algorithmic Transparency	The principle that the decision-making processes of algorithms should be understandable and explainable to humans.