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 7 discusses the value of prediction machines in decision making. Predictions are only one aspect of a decision; other components include judgment, action, outcome, and data. By looking at these different decision-making elements, how prediction machines affect the value of humans and other assets can be explored. As prediction machines improve, the value of human judgment will also increase.