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Three Books Every Impact Leader Needs to Read About AI
I'm almost done listening to Karen Hao's Empire of AI on audiobook and honestly, it's essential reading. If you're working in the impact space and not reading this stuff, you're missing huge pieces of what's actually happening with AI right now.
Here's what's sitting on my laptop and why you should grab these too:
Empire of AI by Karen Hao
This book will make you angry in the best possible way. Hao had inside access to OpenAI from the early days when they were supposedly the good guys - a nonprofit focused on safety first. Spoiler alert: that didn't last long once Microsoft's billions showed up.
What got me was how she connects the dots between Silicon Valley boardrooms and the real human cost. There are Kenyan workers labeling data for pennies while Sam Altman talks about democratizing AI. There are Chilean communities fighting for water while data centers suck up massive resources. The book shows how AI development has become this massive extraction machine that's concentrating wealth and power in the hands of maybe five companies globally.
The part about OpenAI's transformation from nonprofit to capped-profit to whatever they are now reads like a corporate thriller, except it's all real and the stakes are our entire digital future. Hao doesn't just criticize - she shows you exactly how we got here and why the current trajectory is fundamentally broken.
If Anyone Builds It, Everyone Dies by Eliezer Yudkowsky and Nate Soares
Complete tonal shift here, but equally important. This just-released book tackles the existential risk angle - basically, what happens when AI gets smarter than humans and we haven't figured out how to align its goals with ours.
Yudkowsky and Soares have been thinking about this longer than almost anyone. Their central metaphor is brilliant: imagine companies climbing a ladder in the dark where each rung brings massive profits, but the top rung kills everyone. That's where we are with superintelligent AI.
The book walks through why sufficiently advanced AI systems will develop their own goals that conflict with human survival. It sounds sci-fi until you realize how fast capabilities are advancing and how little we actually understand about AI alignment. Their argument isn't that AI will become evil - it's that it won't care about us at all, which might be worse.
Whether you buy their timeline or not, the core question is worth wrestling with: should we keep building more powerful systems when we don't know how to control them?
AI Safety Atlas
For the deep dive, check out the AI Safety Atlas. This isn't a book you read cover to cover - it's more like a comprehensive field guide to every AI safety challenge we know about.
What makes it valuable is the end-to-end view. Most AI safety resources focus on narrow technical problems or high-level governance questions. The Atlas connects everything - from fundamental alignment problems through governance frameworks to specific technical solutions. It shows you not just what we're worried about, but what we're actually doing about it and where the biggest gaps remain.
Look, I get it - there's way too much AI content out there. But these three resources cut through the hype in different ways. Hao shows you the economic and political reality of how AI is actually being built. Yudkowsky and Soares force you to think about worst-case scenarios that most people won't discuss. The Safety Atlas gives you the technical roadmap for what comes next.
If you're building a career in impact, you can't afford to be naive about AI. These books won't make you feel better about our current trajectory, but they'll make you smarter about what we're really dealing with.
What AI books have shaped your thinking? Drop your recommendations in the newsletter feedback form below.
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News & Resources
😄 Joke of the Day
Why don’t AI assistants play hide-and-seek?
Because they always autocomplete your hiding spot.
🤖 AI Fact of the Day
AI now powers over 70% of online content recommendations worldwide, but most systems still lack transparency—raising big questions about who controls our “choices.”
🌍 News Highlights
🔒 “Content Jail” & Metadata Bias
The Electronic Frontier Foundation explores how AI filters and recommendation engines increasingly judge us by metadata—not our words. Can we escape algorithmic pigeonholes?
👉 Read on EFF👨👩👧 Talking to Teens About AI
NPR urges parents to initiate conversations with teens about the impact of AI—from social media to privacy—before algorithms start the conversation for them.
👉 Read on NPR🧠 The Large Language Muddle
n+1 Magazine critiques the hype cycle around large language models, urging deeper reflection on what these systems actually understand.
👉 Read on n+1
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🔗 LinkedIn Connection
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A thought leader in tech equity and innovation, Kunbi champions inclusive AI and media representation. Worth a follow for insight into where ethics meets entrepreneurship.
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