Prediction Machines, Updated and Expanded: The Simple Economics of Artificial Intelligence (Revised) Spiral-Bound | November 15, 2022

Ajay Agrawal, Joshua Gans, Avi Goldfarb

★★★☆☆+ from 1,001 to 10,000 ratings

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Named one of "The five best books to understand AI" by The Economist

The impact AI will have is profound, but the economic framework for understanding it is surprisingly simple.

Artificial intelligence seems to do the impossible, magically bringing machines to life—driving cars, trading stocks, and teaching children. But facing the sea change that AI brings can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many either cower in fear or predict an impossibly sunny future.

But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this masterful stroke, they lift the curtain on the AI-is-magic hype and provide economic clarity about the AI revolution as well as a basis for action by executives, policy makers, investors, and entrepreneurs.

In this new, updated edition, the authors illustrate how, when AI is framed as cheap prediction, its extraordinary potential becomes clear:

  • Prediction is at the heart of making decisions amid uncertainty. Our businesses and personal lives are riddled with such decisions.
  • Prediction tools increase productivity—operating machines, handling documents, communicating with customers.
  • Uncertainty constrains strategy. Better prediction creates opportunities for new business strategies to compete.

The authors reset the context, describing the striking impact the book has had and how its argument and its implications are playing out in the real world. And in new material, they explain how prediction fits into decision-making processes and how foundational technologies such as quantum computing will impact business choices.

Penetrating, insightful, and practical, Prediction Machines will help you navigate the changes on the horizon.

Publisher: Harvard Business Review Press
Original Binding: Hardcover
Pages: 304 pages
ISBN-10: 1647824672
Item Weight: 1.49 lbs
Dimensions: 6.1 x 0.91 x 9.3 inches
Customer Reviews: 3 out of 5 stars 1,001 to 10,000 ratings

"It's a must read for economists; it forces us to think more deeply about the essence of AI and its connection to prediction. And it's a must read for the public who need to know the enormous dangers the old/new AI poses to our own and our children's economic futures and freedoms." — Journal of Economic Literature

Advance Praise for Prediction Machines:

"What does AI mean for your business? Read this book to find out." — Hal Varian, Chief Economist, Google

". . . framing AI in terms of its predictive capabilities is not only a realistic portrayal of its capabilities today, but also one that business leaders can both understand and act upon. For that alone the book is worth reading." — Forbes

"This book, written by three brilliant minds from the University of Toronto, is invaluable for business leaders looking for a primer on how AI might impact them." — Business Insider

"A must-read for business leaders who need to know where AI is heading and how best to harness the new technology." — Journal of Economic Literature

"Prediction Machines does a good job of showing where computers work best and where humans still have an edge." — the New York Times

". . . a useful way to look at the fast-changing world of machine learning . . ." — the Financial Times

"Consider it a CEO guide to parsing and prioritizing AI opportunities." — McKinsey Quarterly

"Prediction Machines provides a very accessible and high-level overview of machine learning and the power and limits of the predictions provided by AI algorithms. The book is a must-read for business leaders and executives." — TechTalks

"The authors . . .offer a compelling framework for mapping out the likely impact of AI on economies in the decades ahead." — BlackRock Investment Management

Ajay Agrawal is Professor of Strategic Management and the Geoffrey Taber Chair in Entrepreneurship and Innovation at the University of Toronto's Rotman School of Management. He is founder of the Creative Destruction Lab and the Metaverse Mind Lab and cofounder of NEXT Canada and Sanctuary.

Joshua Gans is the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship and Professor of Strategic Management at Toronto's Rotman School of Management. He is Chief Economist of the Creative Destruction Lab, department editor (Strategy) at Management Science, and cofounder and managing director of Core Economic Research.

Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and Professor of Marketing at Toronto's Rotman School of Management. He is also Chief Data Scientist at the Creative Destruction Lab, a fellow at Behavioral Economics in Action at Rotman, and a faculty affiliate at the Vector Institute for Artificial Intelligence.