In "Prediction Machines," economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explore the advancement and growing use of artificial intelligence (AI). The key to AI is not actually intelligence but prediction. This text looks at the value of prediction and data, the importance of trade-offs, and the impact of AI in the workplace. Beneficial to business leaders, financial analysts, policy makers, and students, "Prediction Machines" offers insights, tools, and strategies on how to adapt businesses to the world's ever-growing use of AI. Part 1-consisting of chapters 3 through 6-discusses prediction itself, including how prediction machines work, why many call prediction machines artificial intelligence, the need for data with prediction, and how prediction machines affect the division of labor within organizations. Chapter 3 discusses prediction more in depth. Prediction is the process of taking known information and using it to generate information you don't have. This applies to knowledge about the past, present, and future. Recent advances and innovations in prediction machines are described, including translation systems. This chapter also warns against being deceived by the impact of small improvements.