See the files in this repository for various materials related to the conference Life on a Star in August of 2025.

• Day One: Introduction
  • I Teach Creative Writing. This Is What A.I. Is Doing to Students. by Meghan O’Rourke
  • The Psychology of Life Stories By Dan McAdams
  • Dutch Pink and Italian Blue by John Moore
• Day Two: What is Generative AI?
  • Neural Networks By Grant Sanderson / 3 Blue 1 Brown
  • Chat Log: Brainstorming for CS Extensions
  • Chat Log: Diamonds are Compressed Coal
  • Chat Log: Librarian of the Coloring Castle
  • Claude and ChatGPT for ad-hoc sidequests by Simon Willison
• Day Three: The Attention Mechanism
  • Attention Is All You Need by the Google Brain team
  • Co-Intelligence by Ethan Mollick
• Day Four: Slow AI
  • No new resources!
• Day Five: How to Prompt, and other Guidance
  • A guide to prompting AI (for what it is worth) by Ethan Mollick
  • On the Necessity of a Sin by Ethan Mollick
  • The AI Co-Lab and the corresponding NAIS article, A Teacher-Led Collaborative Approach to AI Professional Development (If you're an educator, Ask Nick for an invite!)
• Day Six: Purpose
  • Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. by Bjork and Bjork
  • Learning in the brain by Efrat Furst
  • Chat Log: AI and Purpose
  • Chat Log: True Dimensional Complexity
  • Rampant AI Cheating Is Ruining Education Alarmingly Fast by James Walsh
  • An Ethic of Excellence by Ron Berger
  • The Writing Life by Annie Dillard
• All Days: Purpose in the age of AI — this version has all the slides, with repeats (e.g., daily review) removed. It might be easier for your searching purposes to have this version.

There are many links on the slides themselves (click on the PDFs above, then click through to the various links), but here are a few other items that I wanted to share as well with you as they come up in conversation.

• Confessions of a Virtual Writer and the corresponding Ghosts by Vauhini Vara
• Reading and Writing by Dan Cohen
• Similar to above: An Open Letter to My Students about AI by Jon Bergmann
• I’m a Therapist. ChatGPT Is Eerily Effective. by Harvey Lieberman
• The Future of AI in Education: 13 Things We Can Do to Minimize the Damage by Arran Hamilton, Dylan Wiliam, and John Hattie
• How ChatGPT Could Embed a ‘Watermark’ in the Text It Generates by Keith Collins
• How ChatGPT Is Fast Becoming The Teacher’s Pet by Emma Whitford
• AI 2027
• The Scaling Era: An Oral History of AI, 2019–2025 by Dwarkesh Patel and Gavin Leech

I've tried to be as thorough and accurate as possible above, but some of these resources are likely less useful than others. In this list, I pull what I think might be the most useful from among the above, and list use cases as relevant.

• Co-Intelligence by Ethan Mollick. This book is for laypeople to understand generative AI, with an eye toward how to extract the most value from your interactions with AI. It's where useful advice like "Invite AI to the Table" comes from. I think it's definitely worth a read, but just keep a critical eye out using Nick's "Slow AI" approach.
• Learning in the brain by Efrat Furst. This is a wonderful resource to learn more about the human brain and how it learns. If you are someone who learns, and wants that to be a significant part of your identity, then this is worth a read.
• Confessions of a Virtual Writer and the corresponding Ghosts by Vauhini Vara. These together tell a story about how the author couldn't create the narrative surrounding the loss of her sister, and how AI helped her do so. It's a fascinating lens through which to view the provocation, "Don't let AI steal your voice."
• Reading and Writing by Dan Cohen. This is a short read, but it motivates a lot of how I view the "Slow AI" approach.
• Neural Networks By Grant Sanderson / 3 Blue 1 Brown. Use this resource to go way deeper on what is a neural network, and in particular, what is generative AI. Lots of math here, but also lots of beautiful visuals.