Resources and References
Essential Reading List
Books on AI and Design
- “The Design of Everyday AI” by Google PAIR Team
- “Human + Machine” by Paul Daugherty and H. James Wilson
- “Weapons of Math Destruction” by Cathy O’Neil
- “Race After Technology” by Ruha Benjamin
- “Algorithms of Oppression” by Safiya Noble
- “The Alignment Problem” by Brian Christian
- “The Creativity Code” by Marcus du Sautoy
- “Design Justice” by Sasha Costanza-Chock
Foundational AI Understanding
- “The Hundred-Page Machine Learning Book” by Andriy Burkov
- “Deep Learning” by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
- “Artificial Intelligence: A Guide for Thinking Humans” by Melanie Mitchell
- “The Master Algorithm” by Pedro Domingos
Ethics and Philosophy
- “Weapons of Math Destruction” by Cathy O’Neil
- “Automating Inequality” by Virginia Eubanks
- “Artificial Intelligence: A Very Short Introduction” by Margaret A. Boden
- “Human Compatible” by Stuart Russell
Online Courses and Resources
Free Courses
- Google’s Machine Learning Crash Course: Basic ML concepts for beginners
- Fast.ai’s Practical Deep Learning: Hands-on approach to deep learning
- Andrew Ng’s Machine Learning Course (Coursera): Comprehensive introduction
- Elements of AI (University of Helsinki): Non-technical AI introduction
- MIT’s Introduction to Deep Learning: Video lectures and materials
Design-Specific Resources
- Microsoft HAX Toolkit: Guidelines for human-AI interaction
- Google PAIR: People + AI Research resources
- IBM Design for AI: Principles and practices
- Apple’s Human Interface Guidelines for Machine Learning: iOS-specific but broadly applicable
Communities and Forums
- Designer Hangout AI Channel: Slack community for designers
- AI for Designers Facebook Group: Active community with 50k+ members
- r/artificial and r/userexperience: Reddit communities
- Designer News AI Section: Curated AI news for designers
- Product Hunt AI: Daily AI tool discoveries
Tool Directory
Ideation and Research
- ChatGPT/Claude: General purpose AI assistance ($20/month)
- Perplexity: AI-powered research assistant ($20/month)
- Dovetail: Qualitative research analysis ($29/user/month)
- Notably: AI-powered research synthesis ($20/user/month)
Visual Design
- Midjourney: Artistic image generation ($10-120/month)
- DALL-E 3: OpenAI’s image generator (via ChatGPT Plus)
- Adobe Firefly: Adobe-integrated AI (Creative Cloud included)
- Stable Diffusion: Open-source image generation (Free/self-hosted)
UI/UX Design
- Figma AI: Native Figma features (Beta/Free)
- Uizard: Sketch to design ($12-49/month)
- Galileo AI: Text to UI design ($19-99/month)
- Framer AI: Website generation ($10-30/month)
Content and Copy
- Copy.ai: Marketing copy generation ($36-49/month)
- Jasper: Long-form content creation ($39-59/month)
- Writesonic: AI writing assistant ($19-99/month)
Development and Prototyping
- GitHub Copilot: AI pair programming ($10/month)
- Cursor: AI-first code editor ($20/month)
- Vercel v0: UI component generation ($20/month)
- Replit AI: Collaborative AI coding (Free-$20/month)
Testing and Analytics
- Maze: Usability testing with AI insights ($99+/month)
- Attention Insight: AI eye-tracking prediction ($19-199/month)
- UserTesting AI: Automated insight generation (Enterprise pricing)
Key Organizations and Research Centers
Research Institutions
- Stanford Human-Centered AI Institute: Leading research on human-AI interaction
- MIT Computer Science and AI Laboratory: Cutting-edge AI research
- Carnegie Mellon Human-Computer Interaction Institute: HCI and AI integration
- Oxford Internet Institute: AI’s societal impact
Industry Groups
- Partnership on AI: Industry consortium for responsible AI
- AI Now Institute: Research on social implications
- Future of Life Institute: AI safety and ethics
- IEEE Standards Association: AI standards development
Company Research Labs
- Google AI: Research papers and tools
- Microsoft Research: Human-AI interaction studies
- Meta AI Research: Open-source models and research
- Adobe Research: Creative AI applications
Staying Current
Newsletters
- The Batch by Andrew Ng: Weekly AI news
- Import AI by Jack Clark: Technical AI developments
- AI Weekly: Broad AI coverage
- Design + AI Newsletter: Intersection of design and AI
- The Algorithm by MIT Tech Review: In-depth AI analysis
Podcasts
- Design Better (episodes on AI): Practical design applications
- What’s NEXT: AI product implications
- The TWIML AI Podcast: Technical but accessible
- Radical AI: Critical perspectives on AI
- Wireframe: Adobe’s podcast on design and creativity
Annual Conferences
- CHI Conference: Human-Computer Interaction (May)
- Google I/O: AI product announcements (May)
- NeurIPS: Neural Information Processing Systems (December)
- Config by Figma: Design tools and AI (June)
- Adobe MAX: Creative AI tools (October)
Practical Exercises
Week 1: Foundation
- Generate 10 variations of your current project with AI
- Use ChatGPT to analyze your portfolio
- Create a mood board with Midjourney
Week 2: Integration
- Redesign a flow using AI suggestions
- Generate and test 20 copy variations
- Use AI to synthesize user feedback
Week 3: Innovation
- Create something impossible without AI
- Design an AI-powered feature
- Build a functional prototype with Copilot
Week 4: Reflection
- Document your AI workflow
- Teach someone else an AI tool
- Write about AI’s impact on your process
Templates and Frameworks
AI Project Canvas
- Problem Definition
- Data Requirements
- Success Metrics
- Ethical Considerations
- User Impact
- Technical Constraints
- Feedback Mechanisms
Prompt Engineering Template
Role: [Who the AI should act as]
Context: [Background information]
Task: [Specific request]
Constraints: [Limitations and requirements]
Format: [Output structure]
Examples: [If applicable]
AI Tool Evaluation Scorecard
- Capability Match (1-10)
- Integration Ease (1-10)
- Learning Curve (1-10)
- Cost/Value Ratio (1-10)
- Security/Privacy (1-10)
- Vendor Stability (1-10)
- Exit Strategy (1-10)
Ethical AI Checklist
☐ Who benefits from this AI? ☐ Who might be harmed? ☐ What biases might exist? ☐ How transparent is the system? ☐ Can users control their data? ☐ Is human oversight maintained? ☐ Are we solving the right problem? ☐ What are the long-term implications?
Getting Started Roadmap
Month 1: Exploration
- Try 5 different AI tools
- Complete one project with AI assistance
- Join one AI design community
- Read one foundational book
Month 2: Integration
- Integrate AI into daily workflow
- Create AI-augmented portfolio piece
- Share learnings with team
- Develop prompt library
Month 3: Advancement
- Lead AI initiative at work
- Publish article on AI design
- Mentor someone in AI tools
- Define personal AI ethics stance
Month 6: Leadership
- Become team’s AI expert
- Create organizational guidelines
- Speak at local meetup
- Build thought leadership
Year 1: Transformation
- Transform team’s workflow
- Create new methodologies
- Influence company AI strategy
- Shape industry conversations