Joshua Gans

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.

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines can help you prepare. Artificial intelligence (AI) has impacted many industries around the world—banking and finance, pharmaceuticals, automotive, medical technology, manufacturing, and retail. But it has only just begun its odyssey toward cheaper, better, and faster predictions that drive strategic business decisions. When prediction is taken to the max, industries transform, and with such transformation comes disruption. What is at the root of this?

In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it. The rise of AI is shifting prediction from humans to machines, relieving people from this cognitive load while increasing the speed and accuracy of decisions. This sets the stage for a flourishing of new decisions and has profound implications for system-level innovation. Redesigning systems of interdependent decisions takes time—many industries are in the quiet before the storm—but when these new systems emerge, they can be disruptive on a global scale. Decision-making confers power. In industry, power confers profits; in society, power confers control. This process will have winners and losers, and the authors show how businesses can leverage opportunities, as well as protect their positions. Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policymaker on how to make the coming AI disruptions work for you rather than against you.

Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted.

It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions. Contributors:. Daron Acemoglu, Massachusetts Institute of Technology. Philippe Aghion, Collège de France. Ajay Agrawal, University of Toronto. Susan Athey, Stanford University. James Bessen, Boston University School of Law. Erik Brynjolfsson, MIT Sloan School of Management. Colin F. Camerer, California Institute of Technology. Judith Chevalier, Yale School of Management. Iain M. Cockburn, Boston University. Tyler Cowen, George Mason University. Jason Furman, Harvard Kennedy School. Patrick Francois, University of British Columbia. Alberto Galasso, University of Toronto. Joshua Gans, University of Toronto. Avi Goldfarb, University of Toronto. Austan Goolsbee, University of Chicago Booth School of Business. Rebecca Henderson, Harvard Business School. Ginger Zhe Jin, University of Maryland. Benjamin F. Jones, Northwestern University. Charles I. Jones, Stanford University. Daniel Kahneman, Princeton University. Anton Korinek, Johns Hopkins University. Mara Lederman, University of Toronto. Hong Luo, Harvard Business School. John McHale, National University of Ireland. Paul R. Milgrom, Stanford University. Matthew Mitchell, University of Toronto. Alexander Oettl, Georgia Institute of Technology. Andrea Prat, Columbia Business School. Manav Raj, New York University. Pascual Restrepo, Boston University. Daniel Rock, MIT Sloan School of Management. Jeffrey D. Sachs, Columbia University. Robert Seamans, New York University. Scott Stern, MIT Sloan School of Management. Betsey Stevenson, University of Michigan. Joseph E. Stiglitz. Columbia University. Chad Syverson, University of Chicago Booth School of Business. Matt Taddy, University of Chicago Booth School of Business. Steven Tadelis, University of California, Berkeley. Manuel Trajtenberg, Tel Aviv University. Daniel Trefler, University of Toronto. Catherine Tucker, MIT Sloan School of Management. Hal Varian, University of California, Berkeley.

How to get more innovation and more equality.Is economic inequality the price we pay for innovation? The amazing technological advances of the last two decades—in such areas as artificial intelligence, genetics, and materials—have benefited society collectively and rewarded innovators handsomely: we get cool smartphones and technology moguls become billionaires. This contributes to a growing wealth gap; in the United States; the wealth controlled by the top 0.1 percent of households equals that of the bottom ninety percent. Is this the inevitable cost of an innovation-driven economy?

Economist Joshua Gans and policy maker Andrew Leigh make the case that pursuing innovation does not mean giving up on equality—precisely the opposite. In this book, they outline ways that society can become both more entrepreneurial and more egalitarian. All innovation entails uncertainty; there's no way to predict which new technologies will catch on. Therefore, Gans and Leigh argue, rather than betting on the future of particular professions, we should consider policies that embrace uncertainty and protect people from unfavorable outcomes. To this end, they suggest policies that promote both innovation and equality. If we encourage innovation in the right way, our future can look more like the cheerful techno-utopia of Star Trek than the dark techno-dystopia of The Terminator.

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Survive and Thrive: Winning Against Strategic Threats to Your Business, edited by Joshua Gans and Sarah Kaplan. Whether big or small, companies incessantly face challenges that can threaten their bottom line and even their survival. These threats keep corporate leaders up at night. What can companies do to stay alive? Survive and Thrive: Winning Against Strategic Threats to Your Business features a collection of essays by strategy professors at the University of Toronto's Rotman School of Management, Canada's #1 business school.

The essays take the reader on a tour through some of the most vexing threats to business today, threats that put the very existence of organizations into question. From disruptive innovation, to social media disasters, to mistaken technical investments, to gender discrimination, to misunderstood competition, companies need to be able to anticipate crises and prepare to deal with them head on. Across this collection of essays, readers will get warnings about four mistakes that companies commonly make - failing to appreciate interactions within systems, getting stuck in existing ways of doing business, falling victim to cognitive biases, and getting derailed by short-term incentives. But, Survive and Thrive isn't just about mistakes. Its primary goal is to provide step-by-step actions to help companies stay alive. Executives will find principles and practices for anticipating potential threats and creating responses that permit their businesses to not only survive but thrive. Editor Joshua S. Gans is a professor of Strategic Management and holds the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management. He is also chief economist of the University of Toronto's Creative Destruction Lab. Gans wrote The Disruption Dilemma, Information Wants to be Shared, and several other books. Editor Sarah Kaplan, Director of the Institute for Gender and the Economy at the Rotman School of Management, is also Distinguished Professor of Gender and the Economy and a professor of Strategic Management at Rotman. She co-wrote the business bestseller Creative Destruction.