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.
Yossi Beilin was a seminal figure during the Israeli-Palestinian peace process. As deputy foreign minister in the second Rabin government, he was responsible for leading the Oslo process, which was the most important attempt to end the conflict between Israel and the Palestinians. This book is the first to tell the story of the left wing and the peace process based on the private archive of Beilin himself. The thousands of documents – shared exclusively with the author - reveal a far more complete picture of Israel's political-diplomatic history in the late 20th century, and provide new information on key events. Avi Shilon offers a critiques of the 'liberal peace-building' project and analyses the connections between the Labour party's economic policy and foreign policy since the 1970s. This book is both a political biography of Beilin and a new history which recounts the diplomatic processes and social-political changes that occurred in Israel in the past four decades.
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.
Cheap changes everything -- The magic of prediction -- Why it's called intelligence -- Data is the new oil -- The new division of labor -- Unpacking decisions -- The value of judgment -- Taming complexity -- What machines can learn -- Fully automated decision-making -- Deconstructing workflows -- Decomposing decisions -- Job redesign -- AI in the C-suite -- When AI transforms your business -- Managing AI risk -- Beyond business
A foundational new collection examining the mechanics of privacy in the digital age. The falling costs of collecting, storing, and processing data have allowed firms and governments to improve their products and services, but have also created databases with detailed individual-level data that raise privacy concerns. This volume summarizes the research on the economics of privacy and identifies open questions on the value of privacy, the roles of property rights and markets for privacy and data, the relationship between privacy and inequality, and the political economy of privacy regulation. Several themes emerge across the chapters. One is that it may not be possible to solve privacy concerns by creating a market for the right to privacy, even if property rights are well-defined and transaction costs are low. Another is that it is difficult to measure and value the benefits of privacy, particularly when individuals have an intrinsic preference for privacy. Most previous attempts at valuation have focused only on quantifiable economic outcomes, such as innovation. Finally, defining privacy through an economic lens is challenging. The broader academic and legal literature includes many distinct definitions of privacy, and different definitions may be appropriate in different contexts. The chapters explore a variety of frameworks for examining these questions and provide a range of new perspectives on the role of economics research in understanding the benefits and costs of privacy and of data flows. As the digital economy continues to expand the scope of economic theory and research, The Economics of Privacy provides the most comprehensive survey to date of this field and its next steps.
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