52 pages • 1 hour read
Richard FeynmanSurely You're Joking, Mr. Feynman!: Adventures of a Curious Character
Nonfiction | Autobiography / Memoir | Adult | Published in 1985A modern alternative to SparkNotes and CliffsNotes, SuperSummary offers high-quality Study Guides with detailed chapter summaries and analysis of major themes, characters, and more.
Themes
Luck, Play, and Serendipity in Science
In scientific fields, luck is often described as occurring where chance and wisdom intersect. For example, Wilhelm Roentgen noticed that an experiment he was conducting on cathode ray tubes produced a glow in a nearby piece of equipment. This was an unintentional consequence of his experiment, but he was curious enough to investigate it and thereby discovered X-rays. Alexander Fleming returned to his lab from vacation and noticed that some of the bacteria he was growing appeared to be dying in the presence of mold that had accidentally entered a window; he pursued his observation and discovered penicillin. Richard Feynman noticed how plates in a college cafeteria moved at certain rates of spin and wobble. He pursued that insight and made a major contribution to quantum physics.
A fortunate happenstance can often be predicted. The chance of drawing a specific card from a deck has a mathematical likelihood that anyone can know. The possibility does not guarantee what the next card will be, but it makes the draw predictable. In contrast, superstition is an irrational belief, based not on empirical evidence, that the next card will be “lucky.” Feynman gives an example of the distinction when he talks with a professional gambler who tells him that he, the gambler, knows “the odds for all the numbers inside out” and knows that the odds are always, in the long run, in favor of the casino. Instead of playing against the casino, however, the gambler plays against the other players who, he says, “have prejudices – superstitious ideas about lucky numbers” (262). He bends luck in his favor because he understands that seemingly random events are statistically predictable.
For Feynman, the point of science is to have fun. It is not simply the pursuit of knowledge but the structuring of natural curiosity in a way that makes it pleasurable. The fun in science is what one can’t resist questioning. Math is not just something that is learned for a test but a game or puzzle to be solved, an intellectual challenge that causes pleasure when the beautiful answer is discovered. Mathematicians call certain proofs “elegant”; they embody not just knowledge but what Feynman calls “the mathematical beauty of nature” (299). Puzzles, jokes, and competition play a large role in Surely You’re Joking because Feynman becomes burned out and depressed without them.
Genius and the Perception of Intellectual Ability and Authority
Feynman uses the term “genius” several times, but he always disclaims it as a label that applies to him. When he solves a math problem for high school classmates, they think he is a “super-genius” for solving it so quickly, but they don’t know that he worked on the problem before (28). He may, indeed, have been good at solving a problem that others found difficult, but he had to work hard to do it. His authority as someone who can help with homework is earned, but not in the ways that his school friends think. Genius is a misperception that others place upon him because their knowledge and assumptions are faulty. The same applies later in Feynman’s life to military officers who label him a “genius” based on a single observation, while Feynman admits that what they saw was an educated, but very lucky, guess.
Feynman stands in awe of highly intelligent people. He does not hesitate to call people “monster minds” or “great men,” but he never describes them as geniuses. He perceives several traits in them, including intellectual generosity (not demeaning the ideas of others but carefully considering), the ability to see both the general concept at stake and the small details at the same time, the ability to predict outcomes based on experience and knowledge, the ability to think efficiently and express themselves clearly, and the willingness to make mistakes. The last might seem odd. After all, what good is a mistaken theory? Isaac Newton’s ideas dominated physics for more than 200 years until Albert Einstein suggest a better understanding of gravity. Einstein understood that another thinker may show that his ideas are not exactly correct. Genius is not a label to be coveted. But great thinkers are real and willingly stand to be corrected by thinkers of the future.
Learning and Knowledge; The Genuine and the Fake
Feynman expresses frustration that so many people possess knowledge that is “fragile” (44). That is, people can repeat an idea but cannot explain or properly use it. This distinction ties closely to another: the genuine and the fake. Feynman often calls himself a faker or relates how other people believe him to be a faker. What he generally means is that he feels he does not have a fundamental understanding of what he’s doing. He hasn’t mastered a concept, though he mastered a trick to make it appear that he’s competent. In an interesting twist of perception, when people call Feynman a faker, they often mean that they believe him to be playing a trick, but in those cases, he often does understand what he’s doing.
Many educational outlets practice what is now termed the “Feynman Learning Technique,” which comprises several apparently small steps. First, a student identifies a topic that interests them and studies it. Second, they try to explain it to a sixth grader. Third, they identify, revise, and refine the places where there were gaps in their knowledge or where they failed to get the idea across to their audience. In light of those mistakes, they re-study the subject and revise and simply their ideas until they can communicate them with clarity and authority. The path to non-fragile knowledge reflects Feynman’s beliefs in studying what interests you, being able to teach it both to yourself and someone else, and communicating that information as directly as possible, which will likely involve concrete examples. The method distinguishes genuine from fake knowledge.
