Название: Prediction Machines, Updated and Expanded: The Simple Economics of Artificial IntelligenceАвтор: Ajay Agrawal, Joshua Gans, Avi Goldfarb
Издательство: Harvard Business Review Press
Год: 2022
Страниц: 293
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
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.
AI is everywhere. It’s in our phones, cars, shopping experiences, romantic matchmaking, hospitals, banks, and all over the media. No wonder corporate directors, CEOs, vice presidents, managers, team leaders, entrepreneurs, investors, coaches, and policymakers are anxiously racing to learn about AI: they all realize it is about to fundamentally change their businesses.
Today, AI tools predict the intention of speech (Amazon’s Echo), predict command context (Apple’s Siri), predict what you want to buy (Amazon’s recommendations), predict which links will connect you to the information you want to find (Google search), predict when to apply the brakes to avoid danger (Tesla’s Autopilot), and predict the news you will want to read (Facebook’s newsfeed). None of these AI tools are performing an entire workflow. Instead, each delivers a predictive component to make it easier for someone to make a decision. AI empowers. But how should you decide whether you should use an AI tool for a particular task in your business? Every task has a group of decisions at its heart, and those decisions have some predictive element.
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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