What do you think?
Rate this book
The Means of Prediction: How AI Really Works
Not yet published
Expected 4 Nov 25An eye-opening examination of how power—not technology—will define life with AI.
AI is inescapable, from its mundane uses online to its increasingly consequential decision-making in courtrooms, job interviews, and wars. The ubiquity of AI is so great that it might produce public resignation—a sense that the technology is our shared fate.
As economist Maximilian Kasy shows in The Means of Prediction, artificial intelligence, far from being an unstoppable force, is irrevocably shaped by human decisions—choices made to date by the ownership class that steers its development and deployment. Kasy shows that the technology of AI is ultimately not that complex. It is insidious, however, in its capacity to steer results to its owners’ wants and ends. Kasy clearly and accessibly explains the fundamental principles on which AI works, and, in doing so, reveals that the real conflict isn’t between humans and machines, but between those who control the machines and the rest of us.
The Means of Prediction offers a powerful vision of the future of a future not shaped by technology, but by the technology’s owners. Amid a deluge of debates about technical details, new possibilities, and social problems, Kasy cuts to the core Who controls AI’s objectives, and how is this control maintained? The answer lies in what he calls “the means of prediction,” or the essential resources required for building AI data, computing power, expertise, and energy. As Kasy shows, in a world already defined by inequality, one of humanity’s most consequential technologies has been and will be steered by those already in power.
Against those stakes, Kasy offers an elegant framework both for understanding AI’s capabilities and for designing its public control. He makes a compelling case for democratic control over AI objectives as the answer to mounting concerns about AI's risks and harms. The Means of Prediction is a revelation, both an expert undressing of a technology that has masqueraded as more complicated and a compelling call for public oversight of this transformative technology.
AI is inescapable, from its mundane uses online to its increasingly consequential decision-making in courtrooms, job interviews, and wars. The ubiquity of AI is so great that it might produce public resignation—a sense that the technology is our shared fate.
As economist Maximilian Kasy shows in The Means of Prediction, artificial intelligence, far from being an unstoppable force, is irrevocably shaped by human decisions—choices made to date by the ownership class that steers its development and deployment. Kasy shows that the technology of AI is ultimately not that complex. It is insidious, however, in its capacity to steer results to its owners’ wants and ends. Kasy clearly and accessibly explains the fundamental principles on which AI works, and, in doing so, reveals that the real conflict isn’t between humans and machines, but between those who control the machines and the rest of us.
The Means of Prediction offers a powerful vision of the future of a future not shaped by technology, but by the technology’s owners. Amid a deluge of debates about technical details, new possibilities, and social problems, Kasy cuts to the core Who controls AI’s objectives, and how is this control maintained? The answer lies in what he calls “the means of prediction,” or the essential resources required for building AI data, computing power, expertise, and energy. As Kasy shows, in a world already defined by inequality, one of humanity’s most consequential technologies has been and will be steered by those already in power.
Against those stakes, Kasy offers an elegant framework both for understanding AI’s capabilities and for designing its public control. He makes a compelling case for democratic control over AI objectives as the answer to mounting concerns about AI's risks and harms. The Means of Prediction is a revelation, both an expert undressing of a technology that has masqueraded as more complicated and a compelling call for public oversight of this transformative technology.
224 pages, Hardcover
Expected publication November 4, 2025
45 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 of 1 review
July 12, 2025
Book Review: The Means of Prediction: How AI Really Works (and Who Benefits) by Maximilian Kasy
Rating: 4.7/5
Maximilian Kasy’s The Means of Prediction is a bracing, brilliantly clear-eyed dismantling of AI’s mythos—one that left me equal parts enlightened and unsettled. Stripping away the veneer of technological inevitability, Kasy reframes AI not as an autonomous force but as a tool of power, meticulously designed to serve its owners’ interests. As someone who’s oscillated between AI optimism and dystopian anxiety, I found his focus on control rather than capability revelatory.
Kasy’s greatest strength is his ability to demystify complexity without oversimplifying. His chapters on supervised learning and deep learning (Part II) are masterclasses in accessibility, using crisp analogies to explain how AI “fits” patterns to data—and why that process inherently reproduces existing inequalities. The concept of the means of prediction (data, compute, expertise, energy) crystallizes the book’s central thesis: AI’s dangers aren’t technical glitches but structural choices. When Kasy details how algorithmic “fairness” often masks corporate self-interest (Chapter 17), I found myself audibly groaning in recognition.
Yet the book’s real power lies in its vision for democratic resistance. Kasy’s proposal for public oversight (Chapter 20) is pragmatic yet radical, grounded in historical precedents like utility regulation. I wished for more concrete examples of grassroots movements challenging AI power—stories to balance the abstract institutional solutions—but his critique of ideological obfuscation (Chapter 13) is worth the price alone.
By the end, I felt both urgency and agency. This isn’t just another AI ethics primer; it’s a call to reclaim technology as a collective good.
Summary Takeaways:
-The Das Kapital of AI: Kasy exposes how prediction algorithms entrench power—and how to fight back.
-Forget rogue robots—the real AI threat is shareholder profit. Kasy’s book is the wake-up call we need.
-A revelation: Turns out AI isn’t magic—it’s math, money, and monopoly. Read this before the next ‘AI revolution’ headline.
-If you’ve ever felt AI was ‘out of control,’ Kasy proves it’s precisely under control—just not yours.
-The most important book on AI since Weapons of Math Destruction—with a roadmap for democratic hope.
Thank you to the University of Chicago Press and Edelweiss for the advance copy. The Means of Prediction is essential reading for fans of [Atlas of AI] or [Race After Technology]—a rare blend of scholarly rigor and polemical fire.
Rating: 4.7/5
Maximilian Kasy’s The Means of Prediction is a bracing, brilliantly clear-eyed dismantling of AI’s mythos—one that left me equal parts enlightened and unsettled. Stripping away the veneer of technological inevitability, Kasy reframes AI not as an autonomous force but as a tool of power, meticulously designed to serve its owners’ interests. As someone who’s oscillated between AI optimism and dystopian anxiety, I found his focus on control rather than capability revelatory.
Kasy’s greatest strength is his ability to demystify complexity without oversimplifying. His chapters on supervised learning and deep learning (Part II) are masterclasses in accessibility, using crisp analogies to explain how AI “fits” patterns to data—and why that process inherently reproduces existing inequalities. The concept of the means of prediction (data, compute, expertise, energy) crystallizes the book’s central thesis: AI’s dangers aren’t technical glitches but structural choices. When Kasy details how algorithmic “fairness” often masks corporate self-interest (Chapter 17), I found myself audibly groaning in recognition.
Yet the book’s real power lies in its vision for democratic resistance. Kasy’s proposal for public oversight (Chapter 20) is pragmatic yet radical, grounded in historical precedents like utility regulation. I wished for more concrete examples of grassroots movements challenging AI power—stories to balance the abstract institutional solutions—but his critique of ideological obfuscation (Chapter 13) is worth the price alone.
By the end, I felt both urgency and agency. This isn’t just another AI ethics primer; it’s a call to reclaim technology as a collective good.
Summary Takeaways:
-The Das Kapital of AI: Kasy exposes how prediction algorithms entrench power—and how to fight back.
-Forget rogue robots—the real AI threat is shareholder profit. Kasy’s book is the wake-up call we need.
-A revelation: Turns out AI isn’t magic—it’s math, money, and monopoly. Read this before the next ‘AI revolution’ headline.
-If you’ve ever felt AI was ‘out of control,’ Kasy proves it’s precisely under control—just not yours.
-The most important book on AI since Weapons of Math Destruction—with a roadmap for democratic hope.
Thank you to the University of Chicago Press and Edelweiss for the advance copy. The Means of Prediction is essential reading for fans of [Atlas of AI] or [Race After Technology]—a rare blend of scholarly rigor and polemical fire.
Displaying 1 of 1 review