Table of Contents
If you’re looking for a few AI books to add to your summer reading list, here’s what I recommend—and what I’m reading right now.
What I Just Finished
The Coming Wave—Mustafa Suleyman
Worth reading. Strong framing around containment and acceleration. But I was left wanting more from the DeepMind section. For a book by its cofounder, there’s surprisingly little detail on how it worked—or didn’t.
But Read These First
If you haven’t read Tegmark, Fei-Fei Li, or Kai-Fu Lee—start there. These three gave me the footing to make sense of everything else.
Life 3.0—Max Tegmark
He says you can skip the first chapter. Don’t. It’s unsettling in the best way—and sets up the rest of the book with clarity and weight. From my review:
Using a fictional scenario that’s too real for comfort, he shares why the fears of AI achieving consciousness are overblown and do a huge disservice to the real issues that need to be addressed.
The Worlds I See—Fei-Fei Li
A remarkable memoir from the godmother of AI. You’ll notice right away how distinct her voice is from her research writing. From my review:
This book is about entrepreneurship at the edge of the wave and the emotional and intellectual fortitude it takes when you’re the only one working in the lab for years on end.
AI Superpowers—Kai-Fu Lee
When DeepSeek made headlines earlier this year, Kai-Fu wasn’t surprised. Thanks to this book, neither was I. A clear, pragmatic look at China’s AI ambitions—and why they shouldn’t be underestimated. From my review:
Kai-Fu says that “unencumbered by lofty mission statements,” Chinese startups have no problem following trends in user activity wherever it takes them. Layer on that the latest AI improvements have made it very easy to think and build big.
What I’m Reading Now
Artificial Intelligence—Melanie Mitchell
It starts slow—more textbook than narrative—but picks up once the author starts challenging Kurzweil. That part’s worth the wait.
Not About AI But Helps You Understand It
The Scientist in the Crib—Alison Gopnik, Andrew Meltzoff, Patricia Kuhl
Not an AI book, but it reframes how I think about learning systems. And it’s a good check against the intellectually smug Valley speak of “We’ve figured out how the brain works.” From my review:
If algorithms constantly need data to fine-tune their models, babies do the same—always building new neural connections and pruning old ones. In fact, by age two, a child’s brain is the largest it will ever be as a percentage of body mass. To understand how neural networks work, it’s essential to first understand how humans learn. They say our days begin and end as stories, and this book reveals how our brains create those stories.
Finally
There’s a lot of noise in the AI book space right now. From faux trendspotting to inflated certainty. These five books cut through that. They either gave me language I still use or challenged assumptions I didn’t realize I had.
If you’ve already read these, I’d love to hear what stuck with you—or what you think should be next.