Prediction Machines: The Simple Economics of Artificial Intelligence
暫譯: 預測機器：人工智慧的簡單經濟學

Agrawal, Ajay, Gans, Joshua, Goldfarb, Avi

Prediction Machines: The Simple Economics of Artificial Intelligence
  • 出版商: Harvard Business Review Press
  • 出版日期: 2018-04-17
  • 售價: $1,280
  • 貴賓價: 9.5 折 $1,216
  • 語言: 英文
  • 頁數: 272
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1633695670
  • ISBN-13: 9781633695672
  • 相關分類: 人工智慧、經濟學 Economy

    • 海外代購書籍(需單獨結帳)

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商品描述

"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google

Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring 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 analysts 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 CEOs, managers, policy makers, investors, and entrepreneurs.

When AI is framed as cheap prediction, its extraordinary potential becomes clear:

  • Prediction is at the heart of making decisions under 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 structures and strategies to compete.

Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

商品描述(中文翻譯)

「人工智慧對您的業務意味著什麼？閱讀本書以了解更多。」-- Hal Varian，Google 首席經濟學家

人工智慧似乎能做不可能的事情，神奇地讓機器活過來——駕駛汽車、交易股票和教導孩子。然而，面對人工智慧將帶來的巨大變化，可能會讓人感到不知所措。企業應該如何制定策略，政府應該如何設計政策，人們又應該如何規劃他們的生活，以適應這個與我們所知截然不同的世界？在這樣的不確定性面前，許多分析師要麼因恐懼而退縮，要麼預測一個不切實際的美好未來。

但在《預測機器》中，三位傑出的經濟學家將人工智慧的興起重新詮釋為預測成本的下降。透過這一單一而高明的觀點，他們揭開了人工智慧魔法般的炒作，並展示了經濟學的基本工具如何為人工智慧革命提供清晰的視角，並為首席執行官、經理、政策制定者、投資者和企業家提供行動的基礎。

當人工智慧被框架為廉價預測時，其非凡的潛力變得清晰可見：


  • 預測是面對不確定性時做出決策的核心。我們的商業和個人生活中充滿了這樣的決策。

  • 預測工具提高了生產力——操作機器、處理文件、與客戶溝通。

  • 不確定性限制了策略。更好的預測為新的商業結構和競爭策略創造了機會。

《預測機器》深入淺出、有趣且總是充滿洞察力和實用性，遵循其不可避免的邏輯來解釋如何應對即將到來的變化。人工智慧的影響將是深遠的，但理解它的經濟框架卻出奇地簡單。

作者簡介

Ajay Agrawal is Professor of Strategic Management and Peter Munk Professor of Entrepreneurship at the University of Toronto's Rotman School of Management. He is also cofounder of The Next 36 and Next AI, cofounder of the AI/robotics company Kindred, and founder of the Creative Destruction Lab. Ajay conducts research on technology strategy, science policy, entrepreneurial finance, and the geography of innovation.

Joshua Gans is Professor of Strategic Management and the holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at Toronto's Rotman School of Management. Gans is a frequent contributor to outlets like the New York Times, Harvard Business Review, Forbes, Slate, and the Financial Times. Joshua also writes regularly at several blogs including Digitopoly.

Avi Goldfarb is the Ellison Professor of Marketing at Toronto's Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab, Senior Editor at Marketing Science, a Fellow at Behavioral Economics in Action at Rotman, and a Research Associate at the National Bureau of Economic Research. His research has been widely covered in the popular press.

作者簡介(中文翻譯)

Ajay Agrawal 是多倫多大學羅特曼管理學院的戰略管理教授及彼得·蒙克創業教授。他也是 The Next 36 和 Next AI 的共同創辦人、AI/機器人公司 Kindred 的共同創辦人，以及創意破壞實驗室的創辦人。Ajay 的研究領域包括技術策略、科學政策、創業金融及創新地理。

Joshua Gans 是多倫多大學羅特曼管理學院的戰略管理教授及傑佛瑞·S·斯科爾技術創新與創業講座的持有者。Gans 經常為《紐約時報》、《哈佛商業評論》、《福布斯》、《Slate》和《金融時報》等媒體撰稿。Joshua 也定期在多個部落格上撰寫文章，包括 Digitopoly。

Avi Goldfarb 是多倫多大學羅特曼管理學院的艾利森市場營銷教授。Avi 同時也是創意破壞實驗室的首席數據科學家、《市場科學》的高級編輯、羅特曼行為經濟學行動的研究員，以及全國經濟研究局的研究助理。他的研究在大眾媒體上得到了廣泛報導。

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