up: index
“Ethics before capabilities, partnership over replacement” - How to use AI as a creative collaborator while maintaining your agency and creativity.
Key Principle: AI amplifies human creativity rather than replacing it.
Ethics First: The “Explain the Whole Process” Test
“A test of whether you’ve used AI unethically is whether you can explain the whole process - it’s almost like someone recorded a video of everything you did.”
Day 20: Before introducing any AI tools, we established this fundamental principle.
✅ Green Light Scenarios (Good AI Use)
- Learning reinforcement: Using AI to explain concepts you’re studying
- Ideation partner: Brainstorming with AI while maintaining creative ownership
- Technical support: AI explaining how tools and processes work
- Screenshot useful suggestions: Capture AI ideas, then make them your own
❌ Red Light Scenarios (Problematic AI Use)
- Replacing thinking: Having AI do work you should be learning to do yourself
- Hiding AI use: Not being transparent about AI assistance when required
- Uncritical acceptance: Not evaluating AI suggestions for accuracy or appropriateness
The Tools We Used
Magic School AI: Laser Cutting Specialist
What it is: AI assistant custom-trained with laser cutting knowledge for our projects.
Day 20 - How we used it:
- Project feedback: “State an idea to Magic School and ask for feedback”
- Learning support: “Ask for understanding about something you’re not sure about”
- Problem-solving: “Hey, this is where I am stuck. I don’t get it; it’s messy”
- Technical guidance: Laser cutting-specific advice and troubleshooting
Best Practice: Screenshot useful suggestions into your group journals for team reference.
Key Applications:
- Material selection and workflow guidance
- Safety protocol integration
- Design consultation for manufacturability
- Quality standard development
Google Gemini: Visual AI
What it is: Multi-modal AI that can analyze images, generate visuals, and help with creative development.
Day 20 - Breakthrough moment:
“I put the context of our laser-cutting project into Google Gemini… Gemini annotated how the laser-cut piece could be modified to hold the robot and did a decent job.”
Key Applications:
- Image analysis: Prototype assessment and design feedback
- “Vibe coding”: Rapid app development assistance
- Creative generation: Image creation and concept visualization
- Visual documentation: Enhancing project presentations
Understanding AI Limitations
Context Rot (Day 21)
What is it: AI “forgetting” earlier conversation elements or providing lower-quality suggestions over time.
Common AI Challenges:
- Context degradation: AI loses track of earlier conversation
- Overconfidence: AI providing inaccurate information with high confidence
- Bias amplification: AI reflecting biases in training data
- Creative stagnation: Over-relying on AI suggestions instead of human insight
How to Handle It:
- Start fresh conversations for new projects or when context becomes muddy
- Verify suggestions through research, testing, or expert consultation
- Maintain creative ownership - AI suggests, humans decide
- Balance AI and human input throughout the creative process
AI Across the Design Process
Empathize: Understanding Users
- User research: AI helps analyze and document user needs
- Stakeholder mapping: Understanding different perspectives
- Visual documentation: Recording observations and insights
Define: Framing Problems
- Problem reframing: AI helps generate “How might we…” questions
- Constraint identification: Understanding project limitations
- Requirement clarification: Articulating challenges clearly
Ideate: Generating Possibilities
- Brainstorming partner: AI expands creative possibilities
- Visual concepts: Image generation for early exploration
- Cross-pollination: Connecting ideas from different domains
Prototype: Making Ideas Tangible
- Rapid prototyping: “Vibe coding” for quick app development
- CAD guidance: Technical modeling assistance
- Fabrication workflow: Process optimization suggestions
- Design iteration: Quick visualization of alternatives
Test: Learning from Reality
- Visual feedback analysis: AI assessment of prototypes
- Improvement visualization: Clear representation of suggested changes
- Documentation support: Recording design decisions and rationale
In Practice
Calendar: Key Learning Days
-
Day 20 - AI Ethics Foundation: “Ethics before tools” - Establishing responsible AI partnership before exploring capabilities. Introduction of Magic School AI and breakthrough Gemini annotation of robot storage prototype.
-
Day 21 - Understanding Limitations: Discussion of “context rot” and AI challenges - learning to recognize when AI suggestions degrade in quality.
-
Day 28 - Vibe Coding: AI-assisted rapid app development demonstrating creative partnership and natural language programming. Also: student AI conference experience connecting classroom learning to real-world AI applications.
-
Day 30 - Creative Applications: Advanced Gemini capabilities for image generation and creative exploration.
Efforts: Projects Using AI Partnership
-
Robot Storage: Comprehensive AI integration - Magic School brainstorming, Gemini visual annotation, ethics-first approach to design feedback.
-
Individual Explorations: Student-driven AI applications including voice-to-text transcription, chord diagram generation, and creative assistance.
-
Family Coasters: AI-assisted design for rapid prototyping and concept exploration.
See AI Ethics Before Tools milestone for breakthrough moment analysis.
Best Practices: Capture and Make It Your Own
The Three-Step Approach
- Find/Generate: Use AI to explore ideas, get suggestions, find resources
- Capture: Screenshot or copy-paste anything useful (just like finding things on the internet)
- Make It Your Own: Adapt, modify, and integrate AI suggestions into your creative vision
Maintaining Human Agency
- You drive the creative direction: AI responds to and amplifies your ideas
- You evaluate quality: Assess AI suggestions for appropriateness and accuracy
- You make final decisions: Creative ownership remains yours
- You focus on learning: AI supports your learning process, doesn’t bypass it
Transparency and Documentation
- Clear attribution: Document when and how AI contributed to projects
- Process explanation: Be able to explain both AI contributions and your decisions
- Learning emphasis: Focus on what you learned, not just what AI produced
- Showcase collaboration: Demonstrate effective human-AI partnership
Professional Skills for the Future
AI Literacy Development
- Understanding capabilities and limitations: What AI can and can’t do well
- Prompt engineering: Effective communication with AI systems
- Critical evaluation: Assessing AI output quality and appropriateness
- Ethical reasoning: Making responsible decisions about AI use
Career Preparation
- Industry integration: How these skills apply in various career paths
- Lifelong learning: Staying current with rapidly evolving AI capabilities
- Innovation mindset: Using AI to enhance rather than replace human capabilities
- Professional collaboration: Understanding AI’s role in team workflows
Integration with Core Frameworks
Design Thinking Enhancement
All five phases benefit from AI partnership while keeping human creativity central:
- Empathize: AI for user research and insight synthesis
- Define: AI for problem reframing and question generation
- Ideate: AI as brainstorming partner and possibility expander
- Prototype: AI for rapid concept visualization and development
- Test: AI for feedback analysis and improvement suggestions
4Ms Framework Application
- Maker: Developing AI literacy as essential maker skill
- Machine: AI as another tool with capabilities and constraints
- Method: Incorporating AI workflows into design processes
- Materials: Using AI for material research and selection
- Margin: Planning for AI unpredictability and learning curves
Assessment and Reflection
Evaluating Your AI Partnership
- Learning enhancement: Is AI helping you learn more effectively?
- Creative growth: Are you generating more and better ideas with AI assistance?
- Skill development: Are you developing both AI collaboration skills AND independent capabilities?
- Ethical consistency: Are you using AI in ways that align with your values?
Portfolio Documentation
- Process transparency: Clear documentation of when and how AI was used
- Learning reflection: What did you learn through AI collaboration?
- Creative ownership: How did you direct and evaluate AI contributions?
- Future applications: How will you apply AI partnership skills going forward?
See Assessment Portfolio for documentation strategies.
Reflection Questions
- How has AI changed your approach to creative problem-solving?
- Where do you draw the line between AI assistance and AI dependence?
- What strategies help you maintain creative ownership while using AI tools?
- How do you balance exploring AI capabilities with developing independent skills?
- What ethical considerations guide your AI use decisions?
Navigate: ← Tools & Techniques | Laser Cutting | CAD