Prediction Machines: The Simple Economics of Artificial Intelligence
预测机器：人工智能的简单经济学
Authors: Ajay Agrawal（阿杰·阿格拉瓦尔），Joshua Gans（约书亚·甘斯），Avi Goldfarb（阿维·戈德法布）
Publisher: Harvard Business Press
Publication Year: 2018
Pages: 272
About Book:
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.
关于书籍
人工智能完成了看似不可能的任务，神奇地赋予了机器生命——驾驶汽车、交易股票以及教导儿童。然而，面对人工智能即将带来的剧变，人们往往会感到无所适从。在这样一个与我们所知截然不同的世界里，公司应如何制定策略？政府应如何设计政策？个人又该如何规划生活？面对这种不确定性，许多分析师要么畏缩恐惧，要么预言一个不可能实现的灿烂未来。
但在《预测机器》一书中，三位杰出的经济学家将人工智能的崛起重新定义为“预测成本的降低”。通过这一精妙的视角，他们揭开了“人工智能即魔法”的虚假宣传，并展示了经济学的基本工具如何为这场人工智能革命提供清晰的见解，并为首席执行官、经理、政策制定者、投资者和企业家提供行动指南。
当人工智能被界定为“廉价的预测”时，其非凡的潜力便清晰可见：·预测是在不确定条件下做出决策的核心。我们的商业和个人生活中充满了这类决策。·预测工具能够提高生产力——包括操作机器、处理文件以及与客户沟通。·不确定性制约着战略。更精准的预测为新的业务结构和竞争战略创造了机会。
《预测机器》深入浅出、妙趣横生且始终保持洞察力与实用性，它遵循其必然的逻辑，解释了如何应对即将到来的变革。人工智能的影响将是深远的，但理解它的经济学框架却出奇地简单。
About Author：
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.
关于作者
阿杰·阿格拉瓦尔（Ajay Agrawal）是多伦多大学罗特曼管理学院的战略管理教授及彼得·芒克创业学教授。他还是 The Next 36 和 Next AI 的联合创始人，人工智能/机器人公司 Kindred 的联合创始人，以及创造性破坏实验室（Creative Destruction Lab）的创始人。阿杰的研究方向包括技术战略、科学政策、创业金融以及创新的地理学。
约书亚·甘斯（Joshua Gans）是多伦多大学罗特曼管理学院的战略管理教授，并持有杰弗里·斯科尔技术创新与创业讲席。甘斯经常为《纽约时报》、《哈佛商业评论》、《福布斯》、《Slate》和《金融时报》等媒体撰稿。约书亚还定期在包括 Digitopoly 在内的多个博客上撰文。
阿维·戈德法布（Avi Goldfarb）是多伦多大学罗特曼管理学院的埃里森营销学教授。阿维还担任创造性破坏实验室的首席数据科学家、《营销科学》高级编辑、罗特曼“行为经济学行动”研究员，以及美国国家经济研究局的研究员。他的研究受到了大众媒体的广泛报道。
编译：任艳林、刘鑫
