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 10 looks at how enhanced prediction helps both humans and machines handle more situations, resulting in better outcomes. Examples with navigation are given. The concept of satisficing is also discussed; satisficing is when a decision is made that's "good enough" based on the information available. Prediction machines can reduce the need to satisfice-which is currently very common in businesses and people's social lives-and provide better ways to manage risk.