Richard Feynman, the late Caltech physicist and Nobel Laureate, perhaps best known for his work on quantum electrodynamics, was also a thoughtful explainer of science. Already a physics rock star, his 1961-1963 Caltech undergraduate lectures, designed to reinvigorate the undergraduate educational experience, arguably became his most famous work. Compiled as The Feynman Lectures on Physics, they have sold over 1.5 million paper copies and are now available online as well. Anyone reading the compiled lectures or viewing the recordings will immediately recognize the contents as brilliant, complex, and subtle, pitched perhaps even above the high intellectual level of Caltech undergraduates, where being “just an average genius” could well mark you as an underperforming student.
Alas, I never met Feynman, though I had hoped I would. As a young whippersnapper assistant professor at the University of Illinois in the 1980s, I was pursuing parallel computing projects related to the Caltech Cosmic Cube and ongoing work at the Jet Propulsion Laboratory (JPL). (My Ph.D. dissertation was on the then crazy idea that we might build supercomputers using large numbers of microprocessors.) I agreed to serve on a panel at JPL simply because Feynman had agreed to serve as well. I wanted to discover for myself if even a portion of the oft-repeated stories were true. Unfortunately, by then, Feynman was too sick to participate, and he died soon thereafter from the effects of cancer.
Just a few years before this, my friend and later Microsoft colleague, Tony Hey, had worked with Feynman to convert a second lecture series, on computation, into another book, the Feynman Lectures on Computation. However, this essay is about neither Feynman’s physics or computation insights, but about how to first learn and understand deeply, then explain simply and clearly.
Feynman was unparalleled in identifying the irreducible core of any scientific topic and elucidating it with clear and simple language. If you doubt me, remember his iconic ice water demonstration of O-ring failures during the Rogers Commission investigation of the space shuttle Challenger explosion. As he later opined on the dangers of go fever, “The first principle is that you must not fool yourself, and you are the easiest person to fool." (See Nature Cannot Be Fooled.)
Feynman’s simple, yet powerful four step approach to understanding a topic and sharing it with others has been codified in the now eponymously named, Feynman Technique:
- Choose a topic, study it and the interrelations among its components
- Explain what you have learned, simply and clearly, to a child
- Identify and fill the knowledge gaps exposed by your explanation
- Refine and simplify your explanation and repeat as necessary
It seems simple, and it is, but as Leonardo da Vinci reputedly said, “Simplicity is the ultimate sophistication.” Let’s deconstruct each of these four ideas, with a few personal detours along the way.
Choosing and Learning a Topic
Entire forests have been decimated by pundits and experts, all pontificating on the art of learning. Yes, you learn faster and more efficiently if you have had a good night’s sleep, have eaten breakfast, and (hear me, college students) are not hungover. Nor is a yellow highlighter required, though it can help. Learning is not a black art, it simply requires patience, diligence, and some paper and pencils.
Pick a topic you want to understand, something not so broad as to be an abstraction. The Theory of Everything is not the place to start, unless you are a theologian or cosmologist. Instead, choose something clear and specific (e.g., Why is grass green?) that can be understood in terms of simpler concepts, then write down everything you know about the topic.
The act of writing will undoubtedly raise some questions; find the answers, and write them down too. Finally, organize and reorganize what you now know into a coherent story. Throughout, look for missing elements and contradictions. Ask yourself questions and see if you can derive the answers from what you now know.
I wasn’t joking about the pencils. Writing (or typing) is a powerful way to force oneself to think about ideas and to internalize their relationships as a coherent narrative. For these reasons, good teachers, whether in secondary schools or universities, always tell students to take their own notes, even if the textbook or course materials contain the same information.
Learning is not a passive process; it is an active one that requires questioning how and why the jigsaw puzzle pieces fit together, and if what you have been told is internally consistent. If you exhaust the pile of known pieces, and the puzzle is still incomplete, congratulations, you have identified the need for original research.
In his biography of Feynman, James Gleick relates a story about Feynman studying for his qualifying examinations, one of those life altering transition points for every putative PhD student. In Gleick’s telling, Feynman created a book of study notes:
On the title page he wrote: Notebook Of Things I Don’t Know About. For the first but not the last time he reorganized his knowledge. He worked for weeks at disassembling each branch of physics, oiling the parts, and putting them back together, looking all the while for the raw edges and inconsistencies. He tried to find the essential kernels of each subject.
As Feynman knew well, even as a graduate student, rather than rote memorization or blind acceptance of textbook statements, you must assemble the pieces yourself. Only by peering behind the wizard’s magic curtain, studying the theme park ride’s engineering, repeatedly asking yourself how and why, then reproducing what you have seen, can you truly be confident you understand.
If you cannot recreate an idea from its elementary components, you do not really understand it -- knowing something is not the same as knowing the name of something. It is why teachers always tell students not to memorize formulas, but to understand the principles. From that, one can derive the formulas. I agree, but it is best to do both.
Now about that green grass; it is a scientific and biological marvel. Understanding how it functions in the biological ecosystem and why it is green requires internalizing several key topics, among them the electromagnetic spectrum, differential absorption, photosynthesis, chlorophyll (itself worthy of a deep dive), quantum efficiency, ATP, optics, visual perception, and cognition. (For extra credit, consider whether grass would be green if the sun were not a G-type main-sequence star.)
There’s a lot to assemble and connect before one can thoughtfully and clearly answer a child’s question, “Mommy, why is the grass green?” Doing so while not hiding behind jargon is even harder.
Explain What You Have Learned To A Child
Feynman himself said that the best way to know if you have well and truly understood a concept is to explain it to someone else. There is no better litmus test of one’s own understanding than explaining something to someone young. A child has a shorter attention span, a smaller vocabulary, and far fewer emotional filters than most adults. Moreover, a child will ask excited, impertinent, and repeated questions in ways that the social conditioning of adults would prevent.
Nothing can humble an adult more quickly than a child’s persistent questions. Therein lies the beauty of explaining ideas to children. They have neither the social filters to prevent themselves from asking uncomfortable questions, nor the shame in admitting ignorance. They expect clear, simple answers, all consistent with their own experience. Using unnecessarily complex technical jargon is also a sign of, at best, intellectual laziness, and at worse, one’s own shallow understanding.
Let me be clear. I believe every child is born a scientist, innately inquisitive and curious how the world works. They embody the essence of science, doggedly asking questions, being unsatisfied with answers that will not withstand scrutiny, and being utterly unimpressed by intellectual stature or pedigree. A resigned and frustrated appeal to authority – “because I said so” – is an indicator of elucidative failure. Though the incessant, “But why?” may seem like an infinite regress, fear not. It’s not turtles all the way down, and the Münchhausen trilemma lives to fight another day.
The classic xkcd Up Goer Five cartoon about the Saturn V rocket, which uses only the ten one hundred most common words (thousand not being among them), illustrates how challenging it can be to explain complexity via only simple words. If you doubt me, try explaining why the grass is green using a text editor that limits you to just those one thousand (uh, ten one hundred) most common words. (Grass is not among them; you’d best start with “green sticks that grow toward the sky” instead. This might also be a good time to think about explaining phototropism and the rabbit hole of multicellular biology.)
In a televised lecture, Feynman himself talked about the egalitarian nature of scientific exploration, noting, “It doesn't make any difference how beautiful your guess is, it doesn't matter how smart you are, who made the guess, or what his name is… If it disagrees with experiment, it's wrong. That's all there is to it.” (See The Epistemology of Science.)
Quantum Confusion and Uncertainty
Years ago, when I was a corporate vice-president at Microsoft, the company’s quantum computing project, Station Q, which was then located at UC Santa Barbara, reported to me as part of the eXtreme Computing Group. Station Q was headed by Michael Freedman, himself a Fields Medal winner, in recognition of his work on the generalized Poincaré conjecture.
As part of our computing research, we regularly brought leading experimentalists and theoreticians together for a multiday workshop, all of whom were working on topological approaches to quantum computing. The intellectual throw-weight of the invitees was a highly skewed sample of the smart kids club; everyone in the room had won their school’s fifth grade spelling bee.
Although I can impress unsuspecting undergraduates with a whiteboard discussion of quantum computing, superposition, Hilbert spaces, and Bloch spheres, I am by no means a quantum computing expert. Hence, I fully anticipated to become intellectually lost at some point during the workshop presentations, though I expected to understand the gist of each. As the first theoretician began speaking, I was dismayed, however, at just how quickly I was overwhelmed. After just a few minutes, as complex and subtle mathematics danced and whirled, juxtaposed with “as you can clearly see” phrasings, I realized I had no idea what the speaker was discussing, or even the point he was trying to make.
Just as I was about to sigh with resignation, open my laptop, and begin responding to my denumerable but enervating steam of backlogged email, an equally accomplished experimentalist spoke up, saying, “Excuse me, but I have no idea what you are trying to say! Can we go back to the beginning, please? I have some basic questions.” As I looked around the room, gratified that I was not the only lost soul, the puzzled but relieved expressions revealed everyone – theoreticians and experimentalists alike – felt the same way.
All of the very smart, highly educated people in the room were confused, and not in the way Niels Bohr meant when, in a mashup of a Zen koan, a physics superposition joke, and Dadaist wordplay, he had commented, ““If you are not confused by quantum mechanics, you do not understand it.” Rather, we were confused due to inadequate and opaque explanation.
The speaker responded quickly and with good humor, asking where people had become lost. What then followed was a lively give-and-take of questions and answers that led to mutual understanding, a pattern that continued throughout the day. None of that would have happened had one person not evinced the intellectual courage to profess total confusion and an utter lack of understanding.
Although I was just a bit player in this quantum play, regrettably, I had starred in my own production. As a senior graduate student, I had given a colloquium on my research, where I had excitedly derived all the queueing theory formulas underlying my work. It was a disaster, leaving everyone else confused and me flustered and disheartened. Afterward, my advisor pulled me aside and offered some sage advice, reminding me that the goal of a colloquium is to tell the audience what you have done, why it matters, and why they should care. As he put it, “If you excite people with clear rationales and explanations, they will want to read the paper later to understand the details.” Wisdom that.
Linguistic castles of idiosyncratic academic buzzwords frequently isolate individuals and disciplines, preventing collaboration and shared understanding. It is an unfortunate academic disease, and too few seek the Strunk and White treatment. (See Renaissance Teams: Reifying the School at Athens.) As anyone who has read (or tried to read) research papers or academic books knows all too well, we in academia often hide behind turgid, meandering prose. In the name of intellectual precision, we seek to impress and sometimes to obfuscate, rather than elucidate and explain. Perhaps driven by intellectual insecurity, we fear clear explanation might imply our ideas are simple and obvious – and sometimes they are. I have been guilty of this myself.
Remember, the primary purpose of communicating is not to impress others with one’s intellectual prowess and academic stature, it is to share ideas and invite discourse. A research colloquium, paper, or poster is a not a denouement, but a prelude to conversation, one where inevitable knowledge gaps are identified and rectified, the third step in the Feynman technique.
Identify and Fill Knowledge Gaps
If you have ever spoken to a grade school class, whether as a practicing scientist or as a part of a “take a parent to school” day, you know the questions can be far more challenging than those experienced during either a venture capital startup pitch or a research colloquium. You need to know your stuff, because you will be asked, and you may discover that you are, in fact, not smarter than a fifth grader.
Humbled by such experiences, any teacher will readily confess that when teaching a class for the first time, even one in an intellectual area where they are an acknowledged expert, perhaps even the world’s leading authority, the teacher learns far more than any of the students. Whether from the unexpected questions that reveal poor explanations, or in an advanced graduate class, questions with no currently known answers, the act of explaining is a test of one’s own understanding. Explaining anything shows others what you truly know and do not know, exposing the gaps in your own knowledge, and it makes you ask yourself questions.
Occasionally during lectures, most often during a graduate class, I have had a student ask me a question that truly made me pause and think, “Why is that really so?” only to realize I was not sure myself. At point, honesty is the only approach, “I do not know, but I will answer your question in detail at the start of the next class.” At that point, it is time for some faculty homework, or maybe some original research.
Why is that so? How does this relate to that? I was told this, but why is it true? Is it actually true? Such questions are one of the purposes of PhD qualifying examinations, to assess a student’s knowledge base and readiness to conduct independent research. Do the student understand – at a deep level – or is the student merely parroting words, phrases, and concepts?
They may be using a CRISPR to edit genes and polymerase chain reactions (PCR) to amplify DNA, or deep neural networks to classify Seyfert galaxies, but can they explain mitosis, stellar evolution, and the convergence properties of stochastic gradient descent? Mastery of the known is a prerequisite to exploration of the unknown. (See Research: When There Are No Answers in the Back of the Book.)
Refine and Simplify
Sadly, not all initial attempts at explanation succeed, as anyone who has taught or attempted to explain something to others will ruefully acknowledge. During their educational journey, each student develops a finely tuned sense of teacher quality and explanatory skill. Within minutes, seasoned students can separate experienced and effective explainers from those less adept. However, recognizing is not the same as doing, as more than one inexperienced teacher has learned to their chagrin. Explaining something clearly and accurately takes both skill and practice, though there are best practices.
Good teachers watch their students while speaking, seeking non-verbal cues for explanatory clarity. Confused faces trigger alternative explanations, additional decompositions, and new analogies. Recognizing that it takes courage to admit ignorance, good teachers encourage and welcome questions, for they provide additional educational opportunities. If one student is confused, others almost always are as well.
A teacher who is dismissive of questions is rarely an expert, but more often fears having their inadequacies exposed. Conversely, true experts have a deep reservoir of background knowledge on tap for interactions and clarifications. A willingness, even an eagerness, to entertain questions is a hallmark of someone who truly understands their subject and takes joy in sharing that understanding with others. Indeed, the joy of explaining something well is its own reward, reflected in enlightened faces.
Coda
There you have it – the Feynman technique for learning:
- Choose a topic, study it and the interrelations among its components
- Explain what you have learned, simply and clearly, to a child
- Identify and fill the knowledge gaps exposed by your explanation
- Refine and simplify your explanation and repeat as necessary
The next time a child asks why the sky is blue, do not send them to the encyclopedia. Embrace the curiosity and wide-eyed wonder, sit down and begin explaining, using words they understand. Share the passion and the joy! Few things in this world are more fun and exciting than science, if explained well and correctly. (See Science: It’s About the Wide-Eyed Wonder.) Under no circumstances should you consider saying – Rayleigh scattering. Though true, it is an obfuscation, not a clarification. Hiding behind big words and technical phrases is a “baffle them with B.S.” parlor trick to hid one’s own lack of understanding and intellectual depth.
Study the camber of the wings, twist the ailerons, move the rudder, work the pistons, spin the propeller, oil and assemble the parts. Build a model yourself. Then, when the intellectual airplane takes flight, you will understand how it flies, and you will not need fancy phrases like laminar flow or Bernoulli principle to explain how and why to others. (And for the record, that grade school demonstration, where the teacher blows over the paper, watches it rise, and exclaims, “This is how airplanes fly!” is not quite the correct explanation of lift.)
Finally, remember Feynman’s admonition, “Nearly everything is really interesting if you go into it deeply enough.” Go, learn, explore, explain, celebrate!
Thanks Dan for the post. There is also a humorous and human side to Feynman that is shown in publications like: Surely you are joking Mr. Feynman and what do you care what other people think, etc. I still breakout in laughter whenever I re-read any of those books. Ahmed
Posted by: Ahmed Elmagarmid | March 03, 2022 at 10:33 PM