Prediction Machines: The Simple Economics of Artificial Intelligence

Description

The idea of artificial intelligence - job-killing robots, self-driving cars, and self-managing organisations - captures the imagination, evoking a combination of wonder and dread for those of us who will have to deal with the consequences. But what if it's not quite so complicated? The real job of artificial intelligence, argue these three eminent economists, is to lower the cost of prediction. And once you start talking about costs, you can use some well-established economics to cut through the hype. The constant challenge for all managers is to make decisions under uncertainty. And AI contributes by making knowing what's coming in the future cheaper and more certain. But decision making has another component: judgment, which is firmly in the realm of humans, not machines. Making prediction cheaper means that we can make more predictions more accurately and assess them with our better (human) judgment. Once managers can separate tasks into components of prediction and judgment, we can begin to understand how to optimize the interface between humans and machines. More than just an account of AI's powerful capabilities, Prediction Machines shows managers how they can most effectively leverage AI, disrupting business as usual only where required, and provides businesses with a toolkit to navigate the coming wave of challenges and opportunities.

Ajay Agrawal is Professor of Strategic Management and Peter Munk Professor of Entrepreneurship at the University of Toronto's Rotman School of Management. He is also cofounder of The Next 36 and Next AI, cofounder of the AI/robotics company Kindred, and founder of the Creative Destruction Lab. Ajay conducts research on technology strategy, science policy, entrepreneurial finance, and the geography of innovation. Joshua Gans is Professor of Strategic Management and the holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at Toronto's Rotman School of Management. Gans is a frequent contributor to outlets like the New York Times, Harvard Business Review, Forbes, Slate, and the Financial Times. Joshua also writes regularly at several blogs including Digitopoly. Avi Goldfarb is the Ellison Professor of Marketing at Toronto's Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab, Senior Editor at Marketing Science, a Fellow at Behavioral Economics in Action at Rotman, and a Research Associate at the National Bureau of Economic Research. His research has been widely covered in the popular press.

"This is a timely book, well written, and accessible putting forward their insights, and is well worth reading." -- Irish Tech News Advance Praise for Prediction Machines Lawrence H. Summers, Charles W. Eliot Professor, former president, Harvard University; former secretary, US Treasury; and former chief economist, World Bank-- "AI may transform your life. And Prediction Machines will transform your understanding of AI. This is the best book yet on what may be the best technology that has come along." Susan Athey, Economics of Technology Professor, Stanford University; former consulting researcher, Microsoft Research New England-- "Prediction Machines is a path-breaking book that focuses on what strategists and managers really need to know about the AI revolution. Taking a grounded, realistic perspective on the technology, the book uses principles of economics and strategy to understand how firms, industries, and management will be transformed by AI." Dominic Barton, Global Managing Partner, McKinsey & Company-- "Prediction Machines achieves a feat as welcome as it is unique: a crisp, readable survey of where artificial intelligence is taking us separates hype from reality, while delivering a steady stream of fresh insights. It speaks in a language that top executives and policy makers will understand. Every leader needs to read this book." Kevin Kelly, founding executive editor, Wired; author, What Technology Wants and The Inevitable-- "This book makes artificial intelligence easier to understand by recasting it as a new, cheap commodity--predictions. It's a brilliant move. I found the book incredibly useful." Advance Praise for Prediction Machines Lawrence H. Summers, Charles W. Eliot Professor, former president, Harvard University; former secretary, US Treasury; and former chief economist, World Bank-- "AI may transform your life. And Prediction Machines will transform your understanding of AI. This is the best book yet on what may be the best technology that has come along." Susan Athey, Economics of Technology Professor, Stanford University; former consulting researcher, Microsoft Research New England-- "Prediction Machines is a path-breaking book that focuses on what strategists and managers really need to know about the AI revolution. Taking a grounded, realistic perspective on the technology, the book uses principles of economics and strategy to understand how firms, industries, and management will be transformed by AI." Dominic Barton, Global Managing Partner, McKinsey & Company-- "Prediction Machines achieves a feat as welcome as it is unique: a crisp, readable survey of where artificial intelligence is taking us separates hype from reality, while delivering a steady stream of fresh insights. It speaks in a language that top executives and policy makers will understand. Every leader needs to read this book." Kevin Kelly, founding executive editor, Wired; author, What Technology Wants and The Inevitable-- "This book makes artificial intelligence easier to understand by recasting it as a new, cheap commodity--predictions. It's a brilliant move. I found the book incredibly useful."