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.

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.

The path to success as an academic economist is littered with obstacles. Even with excellent research material, one faces issues of running the seminar and conference gauntlet, tempestuous relationships with co-authors, the selection of an appropriate journal outlet, a detailed peer review process and, with it, the ever-present spectre of rejection. This collection tackles the issues confronting the up-and-coming economist. The authors include some of the subject's finest luminaries who offer friendly and invaluable advice as well as providing a more light-hearted look at the publication process. Some articles have become classics in their own right. They vary from an examination of seminal (and originally rejected) articles by leading economists to an analysis of why referees are not adequately paid. The tools of both economic theory and econometrics are applied to uncover some home truths and, as a result, these papers provide new insights into the nature of economic discourse.

The path to success as an academic economist is littered with obstacles. Even with excellent research material, one faces issues of running the seminar and conference gauntlet, tempestuous relationships with co-authors, the selection of an appropriate journal outlet, a detailed peer review process and, with it, the ever-present spectre of rejection. This collection tackles the issues confronting the up-and-coming economist. The authors include some of the subject's finest luminaries who offer friendly and invaluable advice as well as providing a more light-hearted look at the publication process. Some articles have become classics in their own right. They vary from an examination of seminal (and originally rejected) articles by leading economists to an analysis of why referees are not adequately paid. The tools of both economic theory and econometrics are applied to uncover some home truths and, as a result, these papers provide new insights into the nature of economic discourse.

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, College 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

An expert in management takes on the conventional wisdom about disruption, looking at companies that proved resilient and offering managers tools for survival. "Disruption" is a business buzzword that has gotten out of control. Today everything and everyone seem to be characterized as disruptive-or, if they aren't disruptive yet, it's only a matter of time before they become so. In this book, Joshua Gans cuts through the chatter to focus on disruption in its initial use as a business term, identifying new ways to understand it and suggesting new tools to manage it. Almost twenty years ago Clayton Christensen popularized the term in his book The Innovator's Dilemma, writing of disruption as a set of risks that established firms face. Since then, few have closely examined his account. Gans does so in this book. He looks at companies that have proven resilient and those that have fallen, and explains why some companies have successfully managed disruption-Fujifilm and Canon, for example-and why some like Blockbuster and Encyclopedia Britannica have not. Departing from the conventional wisdom, Gans identifies two kinds of disruption: demand-side, when successful firms focus on their main customers and underestimate market entrants with innovations that target niche demands; and supply-side, when firms focused on developing existing competencies become incapable of developing new ones. Gans describes the full range of actions business leaders can take to deal with each type of disruption, from "self-disrupting" independent internal units to tightly integrated product development. But therein lies the disruption dilemma: A firm cannot practice both independence and integration at once. Gans shows business leaders how to choose their strategy so their firms can deal with disruption while continuing to innovate.

Why solving the information problem should be at the core of our pandemic response: essential reading about the long-term implications of our current crisis. COVID-19 is caused by a virus. The COVID-19 pandemic is caused by a lack of good information. A pandemic is essentially an information problem: this is the enlightening and provocative idea at the heart of this book. If we solve the information problem, argues economist Joshua Gans, we can defeat the virus. For example, when we don't know who is infected, we have to act as if everyone is infected. If we actively manage the information problem--if we know who is infected and with whom they had contact--we can suppress the virus or buy time for vaccine development. This is an expanded version of an eBook originally published as Economics in the Age of COVID-19.

What every parent needs to know about negotiating, incentives, outsourcing, and other strategies to solve the economic management problem that is parenting. Like any new parent, Joshua Gans felt joy mixed with anxiety upon the birth of his first child. Who was this blanket-swaddled small person and what did she want? Unlike most parents, however, Gans is an economist, and he began to apply the tools of his trade to raising his children. He saw his new life as one big economic management problem-and if economics helped him think about parenting, parenting illuminated certain economic principles. Parentonomics is the entertaining, enlightening, and often hilarious fruit of his "research." Incentives, Gans shows us, are as risky in parenting as in business. An older sister who is recruited to help toilet train her younger brother for a share in the reward given for each successful visit to the bathroom, for example, could give the trainee drinks of water to make the rewards more frequent. (Economics later offered another, better toilet training solution: outsourcing. For their third child, Gans and his wife put it in the hands of professionals-the day care providers.) Gans gives us the parentonomic view of delivery (if the mother shares her pain by yelling at the father, doesn't it really create more aggregate pain?), sleep (the screams of a baby are like an offer: "I'll stop screaming if you give me attention"), food (a question of marketing), travel ("the best thing you can say about traveling with children is that they are worse than baggage"), punishment (and threat credibility), birthday party time management, and more. Parents: if you're reading Parentonomics in the presence of other people, you'll be unable to keep yourself from reading the funny parts out loud. And if you're reading it late at night and wake a child with your laughter-well, you'll have some guidelines for negotiating a return to bed.

In this engaging text Joshua Gans turns economic teaching on its head. Specifically aimed at the management or MBA student, Core Economics for Managers covers the essentials but does so in ways that build on and reinforce the student's work experiences Beginning with the tools of decision-making, this book does not shy away from the complexities of managerial decisions but embraces them to consider both uncertainty and strategic interaction in a readily accessible way. This allows the student to move with ease to considering the principles of negotiated exchange and how prices are formed when parties interact face to face rather than anonymously in markets. This provides a natural way of talking about competition and the gains from cooperation. The traditional topics of economics and competitive strategy can then be introduced by considering pricing; that is, how a firm chooses its price, how a firm can innovate in pricing, how prices are constrained by competition and how prices can act as signals for investment. Finally, with all of these tools in hand, the student can seamlessly move on to topics of contracting, outsourcing, the provision of incentives and the building of relationships. No other single book covers this multitude of topics in such an accessible way. Gone are unnecessary jargon from economics and strategy. All that remains is the core. And that core can be taken with the student back into their studies and commercial life.