Showcase Brainstorm

Symposium Brainstorm (Nov. 17)

On November 17, our class will present at the Senior Symposium. Visitors will be students, faculty, and community members who may know very little about how AI works. Nothing to submit. Come to class ready to discuss what you would want to explore. A half-formed idea is fine. We will combine and refine ideas together.

Choose something you care about. The best ideas usually start with a system you have used, a question you keep arguing about, or a place where AI has already shown up in your life.

Think about:

1. Topic: What AI system, controversy, or question interests you? Why does it matter to you?
2. Goal: What should visitors understand, question, or experience?
3. Interaction: What could visitors actually do – not just read?
4. Connection: Is there an older technology, controversy, or social issue this reminds you of? What is similar, and what is genuinely new?
5. Visitor knowledge: What would someone need to understand about AI to make an informed judgment about this system?

Topics

Here are some possibilities. You are not limited to these. Consider mixing two.

• AI in education
• Recommendation systems and social media
• Generative AI and creative work
• Copyright and training data
• The future of work: hiring and workplace AI
• Facial recognition and surveillance
• Deepfakes and synthetic media
• AI companions and relationships
• Healthcare and medical AI
• Predictive policing and criminal justice
• Autonomous vehicles and robotics
• Data centers, energy, water, and minerals
• AI labor: data labeling, moderation, and hidden human work
• Bias, classification, and algorithmic decision-making
• AI safety, regulation, and governance
• Neuromorphic computing and alternative approaches to AI
• Technological solutionism

Which of these interest you most? What is missing?

What Makes a Good Showcase Piece?

Whatever topic you choose, your piece should help visitors see what is happening beneath the surface. It should engage with these questions:

1. Representation: What does the system receive, and how is the world turned into data?
2. Procedure: What does the system actually do with that information?
3. Priorities: What is it trying to get right, and who decided what counts as success?
4. Impacts: What changes when the system is used – and for whom?
5. History: How is this similar to technologies, systems, or controversies that came before? What is genuinely new?

Across all five, keep asking: How are we deciding what should happen?

The goal is not just to explain these questions in text. Think about how a visitor could see, experience, manipulate, compare, or question them.

Also think about format. What would make an exhibit, poster, demo, or activity interesting enough that someone would stop and engage with it? What theme or question could tie all of our work together so the showcase feels like one project rather than unrelated pieces?

Should We Ask the Campus Community?

We could ask people what they want to know about AI before choosing our topics. Each of you could ask two or three people you know (a roommate, a parent, a coworker, a professor) what they wonder or worry about. Bring one thing you heard, if you try it. This is optional.

Interesting Projects to Take a Look At

Public Education & Advocacy

• https://www.survivalofthebestfit.com/game/
• https://www.hownormalami.eu/
• https://www.theglassroom.org/
• https://datanutrition.org/label/
• https://incidentdatabase.ai/
• https://aiblindspot.media.mit.edu/index.html
• https://airesistlist.org/
• https://ainowinstitute.org/
• https://www.ajl.org/
• https://www.media.mit.edu/projects/ai-ethics-for-middle-school/overview/
• https://studio.code.org/courses/oceans/units/1/lessons/1/levels/2
• https://nellwatson.itch.io/ai-guardians
• https://betterimagesofai.org/

Benefits

Remember that there are also benefits to these systems that are important to engage with, while also being critical of many AI systems. AI isn’t just one thing!:

• Accessibility: captioning, speech-to-text, image descriptions, translation, assistive communication
• Healthcare: image analysis, clinical decision support, drug discovery, administrative burden reduction
• Science: protein structure, climate modeling, astronomy, materials discovery
• Education: tutoring, feedback, language support, practice generation
• Creative work: brainstorming, prototyping, editing, coding assistance
• Safety / maintenance: anomaly detection, fraud detection, predictive maintenance
• Everyday convenience: navigation, spam filtering, search, recommendations