Artificiality Book Awards 2024

Information, not just physical matter, may be the true foundation of intelligence and life. This perspective, which we call The Artificiality, suggests that the human experience will be transformed as the boundaries of organic and synthetic blur. The books we read sit at this juncture—writing at the frontier of complexity science and emerging theories of reality, biology and evolution, technology and artificial intelligence, the nature of experience, and the social sciences and philosophy.

2024 was a banger year for books in our space and I have selected ten books for the Artificiality Book Awards 2024:

• First, I include a handful of books which hit The Artificiality head on. Every one of them tackles how our most fundamental assumptions about reality are being rewritten. The notion that everything can be reduced to its smallest parts is giving way to a more nuanced understanding—one where complexity gives rise to genuine novelty, where consciousness and observation shape reality itself, and where purposeful agency is placed at the center.
• Second, among the obvious inclusions are those books that have most powerfully shaped people's understanding of AI and its implications for human thought.
• Third, exemplary works of popular science that blend scholarly rigor with engaging narratives. I think these books will expand both your knowledge and intellectual horizons while remaining a genuine pleasure to read.

Without further ado, the winners are...

Life As No One Knows It: The Physics of Life's Emergence,
by Sara Imari Walker

This is, hands down, my favorite book from 2024. Sara's scientific style is refreshing—informal, personal yet respectful. Her book tackles deep questions about life’s origins and potential future forms, offering a transformed perspective on what life is and why its emergence matters—especially if we’re serious about understanding how AI might become AL (artificial life). She moves beyond her work on assembly theory, which rethinks life’s origins in terms of the complexity of informational systems, unpacking a range of frontier ideas on the relationship between matter and consciousness, that consciousness organizes matter over time.

You will come away with a deeper grasp of how life—and possibly intelligence—emerges, not as a quirk of biology but as a universal property of information flow and self-organization. This is essential reading for anyone curious about how concepts of life and consciousness might extend into artificial systems.

Read this if you want to understand not just where life might come from, but where it could be going. This book reorients how we think about intelligence and life, and what kinds of forms they might take in the future.

And, if you like this book, be sure to check out Caleb Scharf's The Ascent of Information: How Data Rules the World and Stuart Kauffman's A World Beyond Physics: The Emergence of Evolution and Life.

The Blind Spot: Why Science Cannot Ignore Human Experience,
by Adam Frank, Marcelo Gleiser and Evan Thompson

In 2024, this book shook things up by challenging a core assumption baked into science from the start: that objectivity means removing the observer. The argument is that this move—while useful—left us unable to address some of the biggest problems in science today. Physics can’t reconcile its key theories, biology is under-theorized, and consciousness remains a mystery. So, what now?

The book’s ideas center on the importance of measurement—specifically, that measurement matters in ways we’ve barely begun to understand. Quantum mechanics already hints at this, but we don’t yet know how to fully grapple with it. Enter the agent: the measurer, the experiencer. There aren’t concrete answers or new theories here, but there’s a fascinating tour of ideas like quantum Bayesianism that push us to rethink how science works.

The book's perspective fits with The Artificiality concept because it backs up our conjecture that as artificial entities become more sophisticated, they will fundamentally reshape human experience—changing how we work, relate, create, and understand ourselves. Machines will help us move beyond the presumption of absolute knowledge, reshaping our understanding of reality through the experience of experience. Side note: It takes a moment to adjust to the way their thesis loops back on itself—feeling both obvious and deeply counterintuitive at the same time.

This is for readers who want to get a handle on the core challenges facing science and philosophy today. It’s one of the best primers on why a fundamental shift might be coming—and why AI and information theory will play a central role in shaping the next phase of human discovery.

And if you like this book, check out George Musser's Putting Ourselves Back in the Equation: Why Physicists Are Studying Human Consciousness and AI to Unravel the Mysteries of the Universe.

The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking, by Shannon Vallor

In this book, Shannon invites us to rethink AI as being a reflection of our past, capturing both our triumphs and flaws in ways that shape our present reality.

Shannon uses the metaphor of a mirror to illustrate the nature of AI. She argues that AI doesn’t represent a new intelligence. Actually it reflects human cognition in all its complexity, limitations, and distortions. Like a mirror, AI is backward-looking, constrained by the data we’ve already provided it. It amplifies our biases and misunderstandings, giving us back a shallow, albeit impressive, reflection of our intelligence.

This book is one of my top AI-centric reads from 2024. I was pleasantly surprised by how much she was able to integrate multiple ideas about AI and present them in a fresh manor. There have been many books on similar ideas but hers is the best. By casting AI as a reflection rather than an independent force, she validates how AI may be an impressive tool, but it’s still just that—a mirror of our past. Humanity, Shannon suggests, remains something separate, capable of innovation and growth beyond the confines of what these systems can reflect. Hurrah! You can listen to our interview with her here.

If you enjoyed this book, there are a host of books that go deeper into the technical issues of the "mirror" and how AI can lock us into past patterns. The canonical text is perhaps Algorithms of Oppression by Safiya Umoja Noble. Different angle but if you haven't read it, you should.

Tech Agnostic: How Technology Became the World’s Most Powerful Religion, and Why It Desperately Needs a Reformation,
by Greg M. Epstein

Oh. My. God. This is SUCH a great book. Greg goes well beyond the obvious parallels and shows his scholarly chops in this examination of how the tech industry has created a religion. It's vivid and visceral. And he says something about what we should actually do about this!

Epstein doesn't just point out the eerie similarities between Silicon Valley's culture and organized religion—like AI gods and tech-driven rapture fantasies—he peels back the layers to show how these beliefs shape everything from corporate ethics (or lack thereof) to our everyday interactions. And he doesn't leave us hanging. With the wit and wisdom you'd expect from a humanist chaplain, he argues for a "Tech Reformation," complete with modern-day heretics, skeptics, and reformers who are already challenging the faith.

Tech Agnostic is 2024's best call to action. If you've ever felt uneasy about worshipping at the altar of optimization or wondered if there's room for humanity in the tech world's relentless march forward, this book is your guide to finding answers. I even found a little salvation.

We'll be posting our interview with Greg soon—keep a watch out, it's a fun and enlightening conversation.

AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference, by Arvind Narayanan and Sayash Kapoor

For those who follow the AI world, Arvind Narayanan and Sayash Kapoor are reliable sages, so their book has been both long awaited and acclaimed. It doesn't disappoint—covering the new hype in AI as well as the older, more traditional issues we associate with it.

This book slices right through the AI industry's biggest myths with sharp, precise clarity. Arvind and Sayash dismantle the overblown promises we hear every day, from miracle cures for bias to claims of unbeatable predictions, all while reminding us what AI actually can do. It’s so refreshing to read their work, especially when so much AI discourse is clouded by buzzwords and vague optimism.

What makes this book so compelling is how they handle the bigger questions, too. They take a hard look at the societal structures we’re building around it. They unpack why “just add data” isn’t a fix for complex problems and how blind faith in AI often does more harm than good. Every page is a reality check. My favorite section: why AI can't fix social media. Buy it for this chapter alone!

If you’re tired of AI hype but still hopeful for its potential, this book is exactly what you need. It’s not here to tear down technology for the sake of it—it’s here to push for a better, smarter, more human approach to how we use it.

Why Machines Learn: The Elegant Math Behind Modern AI
by Anil Ananthaswamy

First off, massive respect to Anil for having the guts to write a book about AI when it evolves faster than you can say “gradient descent” is no small feat. Add that doing it in a way that makes math not just understandable but fascinating is next-level.

This book is the ultimate explainer for anyone who's ever asked, “WTF even is AI?” Anil wraps equations in stories that make the math feel alive. For example, he dives into how linear regression—yes, the thing you learned in stats—forms the backbone of AI’s ability to make predictions. He connects that to how machines were first trained to recognize patterns, from simple lines on a graph to complex decision-making.

What I love most is how he threads history into the equations. You get why these methods matter, how they were discovered, and why they’ve stuck around. I felt like I was part of the journey, not just staring at some abstract formula.

If you’re curious about how machines learn but feel like math is a wall you can’t climb, this book is your ladder. Highly recommended.

If you liked this, I'd also recommend The Ethical Algorithm: The Science of Socially Aware Algorithm Design by Michael Kearns and Aaron Roth. Less math but no less of an explainer.

Uncertain: The Wisdom and Wonder of Being Unsure,
by Maggie Jackson

So technically this book was published in 2023 but I'm making an exception. Maggie Jackson has done it again. Just like she woke us all up to attention with Distracted, she’s here to shake things up with this book. This book is everything we need right now—a deep, thoughtful exploration of why uncertainty isn’t just something to tolerate but something we should embrace, even celebrate.

Jackson doesn’t just tell us to “sit with the unknown” like it’s something to be solved by meditating on the unknown. She explains how uncertainty fuels creativity, drives better decisions, and helps us navigate the chaos of modern life. She breaks down why our obsession with certainty and control is holding us back and shows, through vivid stories and phenomenal research, how opening up to the unknown can actually make us more resilient, more innovative, and more alive.

This is personal for me. Reconceptualizing uncertainty is one of my soapbox issues, and Maggie gets it. She gives us a new way to think about and live with the unknown. You'll start seeing it as a tool for growth and discovery, and get evidence-based insights on how to change your own practices.

My hope with this book is that it sparks a societal shift in how we collectively reconceptualize uncertainty, much like Distracted did for attention activism and awareness.

Keep an eye out for our interview with Maggie and come join us and her at the 2025 Artificiality Summit in Bend, OR in October. And be sure to check out the updated edition of Distracted.

Fluke: Chance, Chaos, and Why Everything We Do Matters,
by Brian Klaas

Building on Maggie Jackson’s Uncertain, Fluke goes into the messiness of complexity—increasingly the only lens by which to view the world IMO.

A lot of our work involves leveraging complexity science so I was curious to read Brian's perspective. And I learned a new thing to watch out for: "critical slowing down." This is where systems, right before a tipping point, start dragging their feet in response to change. It’s subtle, but it’s a warning sign—a signal that things are about to shift in big, irreversible ways. If you’re thinking about AI’s hockey-stick growth, this is the kind of nuance that easily gets lost.

Brian weaves history, science, and storytelling into a powerful argument—one we bang on about ourselves: we can’t afford to ignore complexity. Especially in a world where AI is being designed for agency, inevitably amplifying chaos and unpredictability. 

Fluke is sharp, it’s thoughtful, and honestly humbling—a reminder that so much of what shapes our lives hinges on events that are, quite literally, flukes.

If you’re as captivated by complexity as we are and eager to explore its many dimensions through the lens of creativity, we highly recommend The Nexus by Julio Mario Ottino with Bruce Mau. This stunning book is not just an insightful exploration—it’s a fabulous read.

Making Sense of Chaos: A Better Economics for a Better World,
by J. Doyne Farmer

For a more academic yet accessible take—with a focus on economics—Doyne’s book stands out as one of the most important books of the year.

Doyne’s work spans an incredible range of topics, from agent-based modeling of financial markets to understanding how innovation drives the long arc of human progress. This book is about prediction—not in the sense of guessing next quarter’s market trends, but in uncovering the generative forces that shape economies and societies over time.

What sets Making Sense of Chaos apart is its challenge to the overly simplistic assumptions of traditional economics. Doyne uses the tools of complexity science to reveal the messy, adaptive, and unpredictable realities of real-world economies—showing us why treating markets as rational or efficient is both outdated and dangerous. His ideas are practical and forward-looking, offering new ways to think about systemic risk, innovation policy, and how AI is reshaping economic systems.

Listen to our interview with Doyne here.

Living on Earth: Forests, Corals, Consciousness, and the Making of the World, by Peter Godfrey-Smith

Peter Godfrey-Smith’s Living on Earth is one of those rare books that feels both profound and personal. It's a meditation on what it means to be part of the natural world and is utterly beautiful. If you've read any of his other books you'll know that he has this uncanny ability to make the abstract tangible, bringing together philosophy, biology, and wonder into something that sits with you long after you’ve put the book down.

It is about connection. He reminds us that we’re not separate from nature and how this matters in our current age. He shows how living organisms shape and are shaped by their environments, messy, unpredictable, awe-inspiring. This alone would make it worth reading, but then he touches on AI in ways that left me wishing for an entire chapter—no, an entire book—on the subject.

He raises subtle but vital questions about AI: what does it mean for intelligence to emerge in a synthetic system? How do these systems fit—or fail to fit—into the evolutionary story of life? Now that AI is advancing at a pace that feels almost out of control, these questions feel urgent. What would he say about the ways AI is reshaping our understanding of agency, of decision-making, of life itself? I wish I could ask him.

Living on Earth is a gift, and if you care about nature, about AI, or simply about what it means to be alive, you should absolutely read it. As well as his previous books: Other Minds and Metazoa.