Joshua Gans – författare

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system.

In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI.

The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

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.

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.

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 TheTerminator.

A guide to the pandemic economy: essential reading about the long-term implications of our current crisis.

The COVID-19 pandemic has unleashed a firehose of information (much of it wrong) and an avalanche of opinions (many of them ill-founded). Most of us are so distracted by the everyday awfulness that we don''t see the broader issues in play. In this book, economist Joshua Gans steps back from the short-term chaos to take a clear and systematic look at how economic choices are being made in response to COVID-19. He shows that containing the virus and pausing the economy—without letting businesses fail and people lose their jobs—are the necessary first steps.

Gans outlines the phases of the pandemic economy, from containment to reset to recovery and enhancement. Warning against thinking in terms of a “tradeoff” between public health and economic health, Gans explains that containment gives us the opportunity to develop effective testing that will make it safe for people to interact. Once the virus is contained, we will need to pivot toward innovating, and, finally, we will come together to plan how to protect ourselves from future pandemics. He looks at policy tools that might aid an economic recovery, distinguishing between economic losses during a pandemic and a recession.

Gans lays out the economic choices accessibly but with urgency, leaving politics out of it. Economics in the Age of COVID-19 is essential reading for anyone interested in the long-term implications of our current crisis.

Covid-19 is a global pandemic inflicting large health and economic costs. In his previous book, The Pandemic Information Gap: The Brutal Economics of COVID-19 (MIT Press, 2020), economist Joshua Gans explains that those costs have been so large because governments and others have lacked the information needed to control the pandemic. Unless we know who is infectious, we can''t break the chains of transmission, which results in the escalation of our problems. Pandemics, he writes, are information problems.

Now, in this follow-up book, Gans outlines the solution to the information gap. By engaging in rapid, frequent screening, we can control the pandemic and restore normality. We can lower the number of cases, break chains of transmission, and make it safe for people to interact again. This will require changing our mindset about testing, gathering the right information, and matching that information to the right decisions. We have the ingredients to do all these things. We just need to put them together in a scalable and sustainable system. This book is a guide to the issues and trade-offs that policymakers and other key decision-makers need to grapple with and follow.

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:

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.

Blockchain technologies have been rapidly adopted for the creation of cryptocurrencies and have been explored for a myriad of applications. While this is of important economic interest, the computer science behind how blockchains operate to provide security and provenance has been largely inaccessible to economists. This book is a bridge between the computer science and the economics of blockchains.

The focus is on the value and the achievement of blockchain consensus; that is, how distributed and independent nodes are able to reach an agreement on what the current state of digital ledgers, that are the product of blockchains, are. The book shows that the goals of computer scientists in designing blockchains place very high weight on security beyond what an economist trained in game theory and mechanism design would require. It shows how blockchains can be redesigned to account for key economic trade-offs, and will be of interest to researchers and students of economics, financial technology and computer science, alongside policymakers.