"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 ofAI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by executives, policy makers,investors, and entrepreneurs. In this newly revised and expanded 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; and uncertainty constrains strategy. Better prediction creates opportunities for newbusiness strategies to compete. Reflecting on the book's reception, 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 impact of AI will be profound, but the economic framework for understanding it is surprisingly simple"--
The authors describe how to identify the key trade-offs in using artificial intelligence for making decisions amid uncertainty in organizations and how to evaluate their pros and cons through the framework of economics. They explain how machine learning makes prediction better, the role of data in making predictions, how prediction machines can perform better than humans, and how to work with them for better accuracy; the role of prediction in decision making and judgment; artificial intelligence tools for prediction; artificial intelligence as part of an organization’s strategy; and its impact on jobs, inequality, and other areas of society. Updated and expanded, this edition includes new material that explains how prediction fits into decision-making processes and how technologies like quantum computing impact business choices. It includes two new chapters on how prediction is a substitute for other ways of managing risk and how the stakes associated with decisions matter when thinking about relying on prediction machines that are not perfect. Annotation ©2022 Ringgold, Inc., Portland, OR (protoview.com)
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.
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