43 pages • 1 hour read
Steven D. Levitt, Stephen J. DubnerA modern alternative to SparkNotes and CliffsNotes, SuperSummary offers high-quality Study Guides with detailed chapter summaries and analysis of major themes, characters, and more.
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This first chapter explains what the book is about and how it differs from the authors’ first two books, Freakonomics and SuperFreakonomics. After those books, Levitt and Dubner received many requests from readers looking for answers to questions both mundane and profound. Rather than looking at specific questions, they thought it best to examine their approach to thinking and seeking answers, believing “it might be better to write a book that can teach anyone to think like a Freak” (2).
This kind of thinking, they explain, relies on an approach that may not seem obvious. An example is a penalty kick in soccer. A single player kicks at close range toward the goal, which is guarded only by the goalkeeper. Because the goal is so large, the goalkeeper can only really guess which direction the kick will go and make a split-second decision to dive that way. The very corners are completely out of their reach, but if the kicker is not perfectly accurate, the kick might go wide or ricochet off the post. Data show that goalkeepers move right 41% of the time and left 57% of the time. In only 2% of shots do they stay in the middle; thus, the best odds are for the kicker to aim dead center.
However, this rarely happens. It seems illogical to kick the ball directly at the goalkeeper—even if you know they will almost certainly move when the kick is made. More important is the fear of shame. If the kick goes in, one basks in the glory; if it doesn’t, one feels foolish from appearing to do so little to fake out the goalkeeper. This selfish incentive is what causes players to so infrequently aim for the center. Because the data show that it brings the best odds, doing so requires a communal incentive (the good of the team).
These are the kinds of scenarios the authors set out to examine in the book: when the answer to a problem goes against conventional wisdom. We all need to look past the obvious, think creatively, and take an economic approach. That last point simply means relying on data, not hunches or assumptions.
This chapter reviews the process of learning, starting with the relatively rare occurrence of admitting one doesn’t know something. As the authors write, “It has long been said that the three hardest words to say in the English language are I love you. We heartily disagree! For most people, it is much harder to say I don’t know” (20). Instead, people constantly make predictions about things that turn out to be wrong. When researcher Philip Tetlock studied the predictions of more than 300 experts in myriad fields for more than 20 years, he found the experts to be no better than a computer programmed to make extrapolations. Predictions to complicated issues are so difficult because there are often several influential factors, not just one cause.
Despite people being so bad at making predictions, they continue to do so. The authors give three reasons for this. First, people get short-term benefits from predicting future events. If they’ve built up a reputation as an expert, it’s a way of feeding the myth. And if they happen to be right, they gain much personal acclaim, not to mention the ability to cash in on their expert status. Second, there are rarely any consequences when they’re wrong. If people even remember (most people will move on), no one follows up to hold them accountable, so they lose nothing. However, the most important reason is dogmatism, “an unshakable belief they know something to be true even when they don’t” (24). When people hold to a belief or system of values, it prevents any evidence from altering their viewpoint.
The best way to learn about something to make better predictions is through feedback. Getting feedback is a matter of making observations, either in real life or through experiments. The former is often better because controlled experiments can involve unnatural conditions that cause people to alter their behavior. The authors describe a retail chain they consulted for, which always bought ads in the Sunday newspapers of major markets. When this came up, they learned the company had no information about how effective this strategy was. The only bit of feedback came by mistake: One year, an intern forgot to set up the ads in Pittsburgh so none ran there during the summer months. When Levitt and Dubner looked at the numbers, it turned out that sales in that city did not dip at all. Yet the company continued to buy ads because it had always been done.
Experimenting to gather feedback is actually quite rare, due in part to companies maintaining old ways and not rocking the boat. It can also be difficult or daunting to set up experiments, so people avoid it. Most importantly, though, is that “it requires someone to say ‘I don’t know’” (39). People who think they know the answers (as many people do) never look into other possibilities. Sometimes the only way to get to the bottom of something is to admit you don’t know the answer and investigate it with a fresh pair of eyes.
The first two chapters set up the book’s premise: what it means to think like a Freak. Levitt and Dubner explain what the book is about and their reason for writing it, as well as how it differs from their first two books. The writing style is introduced here and continues in a similar pattern throughout the book, with Levitt and Dubner mostly alternating research and stories that are organized by topic.
For example, immediately after stating that they want to teach readers to think like a Freak, the authors begin their explanation of that with the story of penalty kicks in soccer. As they later detail in Chapter 8, stories include data but hold people’s attention better to get the point across. Thus, the soccer story depicts how data and incentives interact in determining what part of the goal a penalty kicker aims for, and the authors explain how to view this story with their way of thinking. They assert that thinking like a Freak is not hard—anyone can do it, so they want to teach it.
Chapter 2 examines how people come to learn things and why there is such variation in what people think they know to be true. Before getting into the specifics of how to think like a Freak (in the chapters to follow), the authors essentially state here how not to. That is, they review what prevents people from thinking like a Freak. One issue is that people pretend to know everything; they’re seemingly allergic to the words “I don’t know.” A true Freak is never afraid to say those words. Another barrier is what the authors call one’s “moral compass.” Focusing too much on right and wrong causes people to lose focus on the problem itself, preventing them from seeing it clearly. Conversely, the key to learning is feedback. This provides data from either experiments or real-world situations that allow people to discern what is actually happening.