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 2, covering chapters 7 through 11, focuses on decision making. The components of decision making are outlined, including judgment. The value and complexity of judgment and predicting judgment are thoroughly discussed. Levels of automation in decision making are also explored, from minor machine involvement to fully automated decision making. Chapter 8 looks at the idea of judgment in decision making. Because prediction machines don't offer judgments, they raise the value of human judgment. But judgment can be costly as it can take a good amount of time, effort, and experimentation. Many decisions also occur under conditions of uncertainty, which then increase the cost of judging potential payoffs. The conditions for automating decisions are also discussed.