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Prediction Machines, Updated and Expanded: The Simple Economics of Artificial Intelligence

by Ajay Agrawal

Understanding AI through the economics of prediction

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Awards & Recognition

  • Editorial selection

    Named one of The Economist’s five best books to understand AI

    Selected as one of The Economist’s five best books to understand AI.

AlbakiReads Editorial

Understanding AI through the economics of prediction

Ajay Agrawal frames artificial intelligence in economic terms: as a reduction in the cost of prediction. That lens connects AI’s technical capabilities to the decisions made by businesses and individuals under uncertainty, and to the productivity gains that prediction tools can enable. The revised edition revisits how the book’s argument has played out in practice, adds an account of prediction’s place in decision-making, and considers how technologies such as quantum computing may affect business choices. Together, these topics make the book a framework for thinking about AI’s implications for strategy and policy, rather than treating the technology as magic.

Good fit for readers who enjoy

  • Business leaders and strategists considering AI’s effects on productivity and competition
  • Readers interested in the economics of artificial intelligence and decision-making
  • Policy makers, investors, and entrepreneurs exploring AI’s broader implications

Themes

Artificial intelligence and economicsPrediction and decision-making under uncertaintyBusiness strategy and productivityTechnology policy

Based on publisher information and book metadata.

Book overview

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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