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Full Description
An 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 AI: 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 issue: 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 systems: 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.
Contents
Preface
Part I. Introduction
1. The Story of Humans Versus Machines
2. What the Old Story Misses
3. What This Book Does
Part II. How AI Works
4. What Is Artificial Intelligence?
5. Supervised Learning
6. Overfitting and Underfitting
7. Deep Learning
8. The Exploration/Exploitation Trade-Off
9. Key Ideas to Remember
Part III. Machine Power
10. Social Welfare
11. The Means of Prediction
12. Agents of Change
13. Ideological Obfuscation
Part IV. Regulating Algorithms
14. Value Alignment
15. Privacy
16. Automation
17. Fairness
18. Explainability
Part V. Old Problems, New Challenges
19. The Ancient Questions Behind AI
20. Toward Democratic Control of the Means of Prediction
References
Index
