AI Image Debate exercise
Version 1.1
👨🏫 Introduction
This exercise prepares students for a debate about AI-generated images.
- In teams, brainstorm a handful of questions about the technology, ethics, and impact of text-to-image generators and the like.
- As an individual, choose a question you would be interested in and willing to ask the class and post it to the appropriate channel (eg, #ai-image-questions).
- The entire class votes on the questions that seem most interesting and meaningful by adding three (3) thumbs-up emoji 👍.
💬 Sample questions
- Can text-to-image generators do X?
- Can you explain how diffusion models are able to do X?
- How do you see the field of AI image generation evolving in X years?
- How will AI-generated images impact industry X?
- Which creative industries will be most immune, and which most vulnerable, to AI-generated images?
- I'm interested in career X. How might I use text-to-image generators for a future job in that industry?
- Who stands to benefit/lose the most from the proliferation of AI images?
- Is it legal to use text-to-image generators for X?
- Researchers have found evidence of AI companies secretly modifying prompts behind the scenes. Do you think text-to-image generators are doing other secret things we're not aware of?
- Which deserves more attention, "AI ethics" (bias/disinformation/plagiarism) or "AI safety" (robots will destroy/enslave us)?
- How has being a New Media alumnus affected how you see these issues?
- Are you worried that your own career could be compromised by AI?
- Can you show us some of your work made with AI?
- Where would you personally draw the line in using text-to-image generators in your work?
🧭 Tool or Shield? A four-corners debate
You've heard artists call AI image generation theft. Here's the strongest argument on the other side — and then the argument against that. This works best standing up.
- Read this claim, adapted from a viral post: “Generative AI brings down barriers for disabled people who want to make art.”
- Pick your corner of the room: AGREE • DISAGREE • IT'S COMPLICATED. Commit before you see the evidence.
- Open each reveal below, one at a time. After each one, anyone may change corners — and the moving is the point. Watch where the room goes.
🟦 Reveal 1: The democratizing case
Advocates point to voice-to-image tools for artists with mobility impairments, AI-generated tactile art for blind creators, and sign-language–integrated installations — concrete ways the technology opens doors that brushes and keyboards keep shut (Pixel Gallery, 2025). As Dazed put it: “By changing who can be an artist, artificial intelligence is changing art itself.”
🟥 Reveal 2: The shield rebuttal
Many disabled artists reject this argument — and resent being used to make it. When defenders of AI invoke accessibility, they argue, the disabled identity becomes a shield against criticism, deployed mostly by people who never asked disabled artists what they think. Writer and artist Daniella Ryan: “generative AI is basically the worst thing to ever happen to art.”
🟨 Reveal 3: What disabled artists say access really means
A wheelchair-using student artist notes that calling AI images “accessible” implies disabled people can't make art, when in her experience disability “just leads to creative solutions” (NC State Technician, 2025). A disabled multimedia artist, citing creators from Frida Kahlo to Stevie Wonder: “We don't need AI to succeed; we need accessibility, education, awareness, and acceptance” (Channel Kindness, 2026).
🏁 Close: Notice the disagreement isn't really about AI — it's about who gets to speak for whom. Post one sentence to the class channel: “The quote that moved me was ___.” Add 🤯 to the reply that most changed your mind.
⛑️ Recommendations
- Changing corners is not losing the debate — it's what evidence is for.
- Quote people accurately. Every reveal above links its source; check before you cite.
- Notice who is present in each argument, and who is being argued about.