AI Ethics Discussion Sheet — WeTeach

As AI tools enter our classrooms, educators must actively guide students in becoming ethical AI users not just consumers. This sheet is designed to spark honest, practical conversations about how we integrate AI responsibly in student programs, especially when building real-world skills like entrepreneurship. Use these prompts individually, in pairs, or as a full-group discussion.

Six Pillars of Ethical AI Use

Fairness & Equity

AI systems reflect the data they are trained on. Biased data produces biased outcomes. Every student deserves AI tools that work equally well for them.

Transparency

Students and teachers should understand how an AI makes decisions or generates content. Black-box tools require critical evaluation before trust.

Privacy & Data Rights

Student data is sensitive. Knowing what is collected, stored, and shared is a right, not a privilege, especially for minors under FERPA and COPPA.

Autonomy & Agency

AI should scaffold student thinking, not replace it. The goal is to amplify student brilliance, not outsource it. Students must remain the author of their ideas.

Societal Impact

AI-powered student ventures will affect real communities. Teaching students to anticipate harm, unintended consequences, and opportunity gaps is critical.

Accountability

When AI-generated content causes harm or spreads misinformation, who is responsible? Students, educators, and platforms all share accountability.

Discussion Questions

For Educators

How do you currently communicate AI use expectations to students? What does academic integrity look like when AI is involved in a business pitch or project?

If an AI tool recommends a business idea to a student, and that student uses it for a competition, who owns the idea? How should attribution work?

Which of your current students might be disadvantaged by AI tools (e.g., English language learners, students with limited devices, neurodiverse learners)? How do we mitigate that?

For Student-Facing Conversations

Imagine an AI suggests your business idea. You develop it further and win a competition. Is this your work? What would you tell your investors?

An AI chatbot tells your student their startup idea is "great" but it is similar to a venture that already failed. What does critical thinking about AI feedback look like?

If an AI model consistently suggests business ideas that work better in urban settings, what does this tell us about bias in training data? What should students do?

Real-World Scenarios — What Would You Do?

Scenario A · The Pitch Problem

A student submits an AI-generated pitch deck to a startup competition. The judges ask follow-up questions the student cannot answer. The student wins second place.

As an educator, how do you address this? What policy would prevent it?

Scenario B · The Data Concern

A free AI tool your district wants to adopt collects student conversation logs to "improve the model." No opt-out exists. The privacy policy is 12 pages long.

What questions do you ask before approving it? Who do you involve?

Scenario C · The Feedback Loop

An AI platform gives positive feedback to a student's harmful business idea (e.g., a surveillance app for parents to track teenagers). The student is excited.

How do you guide this student using both ethical and entrepreneurial lenses?

Scenario D · The Equity Gap

In a class of 30, 22 students have reliable home internet access. AI tools require constant connectivity. Eight students consistently fall behind in AI-assisted tasks.

What accommodations do you put in place? How do you design for all learners?

My AI Ethics Commitments — Take One Action This Week

I will TEACH students to...

I will REVIEW in my classroom...

I will SHARE with my team...

AI Ethics in the Classroom