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Summary:

"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 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 new business 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"-- [Provided by publisher]

Table of Contents:

• Machine generated contents note: 1. Introduction: Machine Intelligence
• 2. Cheap Changes Everything
• pt. One Prediction
• 3. Prediction Machine Magic
• 4. Job of Prediction
• 5. Why It's Called Intelligence
• 6. Data Is the New Oil
• 7. New Division of Labor
• pt. Two Decision-Making
• 8. Unpacking Decisions
• 9. Value of Judgment
• 10. Predicting Judgment
• 11. Tanning Complexity
• 12. Fully Automated Decision-Making
• 13. What's at Stake?
• pt. Three Tools
• 14. Deconstructing Workflows
• 15. Decomposing Decisions
• 16. Job Redesign
• pt. Four Strategy

• 17. AI in the C-Suite
• 18. When AI Transforms Your Business
• 19. Your Learning Strategy
• 20. Managing AI Risk
• pt. Five Society
• 21. Beyond Business.

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Author/Creator:

Agrawal, Ajay , author

Contributors:

Gans, Joshua, 1968- , author

Goldfarb, Avi , author

Languages:

English

Language Notes:

Item content: English

Main Work:

Prediction machines: the simple economics of artificial intelligence [by Agrawal, A.]

Other Related Resources:

Revision of: Prediction machines [by Agrawal, A.] (Boston, Massachusetts : Harvard Business Review Press, [2018] — ISBN 9781633695672; LCCN 2017049211; OCLC Number 1007083496)

Print version: Prediction machines [by Agrawal, A.] (Updated and expanded edition; Boston, Massachusetts : Harvard Business Review Press, [2022] — ISBN 9781647824679; LCCN 2022020640)

Subjects:

Artificial intelligence — Economic aspects

Decision making — Statistical methods

Forecasting — Statistical methods

General Notes:

Includes bibliographical references and index.
Description based on online resource; title from digital title page (viewed on January 03, 2023).

Physical Description:

1 online resource

Call Numbers:

TA347.A78 A385 2022eb

ISBNs:

9781647824686 (electronic book)
1647824680 (electronic book)
9781647824679 (hardcover) [Invalid]

Library of Congress Control Numbers:

2022020641

OCLC Numbers:

1340411821

Other Control Numbers:

EBC6846950 (source: MiAaPQ)
[Unknown Type]: ybp303123930