Scott Adams has this really memorable term for how to think about people: moist robots. Moist because — well, we’re wet and squishy. Robots because there are certain predictable behaviors that we repeat. In situations like A, most people do f(A). In situation; in situations like B, most people will do f(B). Sounds very robot-like to me.
Now I’m sure you can remember a time where this rings true, everyone has that friend who thinks their going to win big at the casino despite what hundreds of years of math suggest. This is great example of irrational behavior that has been programmed (in one way or another) into many of us moist robots. Most of the time our squishy brains are great at detecting these problems but only when it’s not about us. It’s easy to see your friend has no idea about probability, but much harder to see why you’re such a sucker for Instagram.
As you read this sentence, you can imagine how this story can play out in any number of ways. Here’s a very common story, you see someone who is super successful, perhaps someone famous you saw on the interweb. Naturally, you wonder how you can become super successful. Your parents will tell you that all you need is hard work. You’re not so sure since they also told you that the Easter Bunny was real, so you also read Ms. Super Successful’s biography. The book tells you it was her passion that drove her to eventually become CEO of company X. You’re mostly convinced but to be sure you listen to her commencement speech and any interviews you can get a hold of, and they tell you the same thing: hard work and passion got Ms. Super Successful to where she is, and so can you!
But let’s not forget about one very important thing: we’re all still moist robots. A very common pattern (or cognitive bias as the psychologists call it) with moist robots is that of self-serving bias: we have the tendency to perceive oneself in an overly favorable manner. So when Mrs. Super Successful is attributing her success to something, she overemphasizes the aspects that she has control over, namely: hard work and passion. Never mind the fact that her parents were in the 99th percentile of wealth, had connections with the trustees at an Ivy League school, and had an abundance of opportunities to learn the skills she needed to be successful — all she really needed was hard work and passion. Which leads to another pattern called survivorship bias where us moist robots mistakenly draw conclusions about what worked based on who survived (e.g. successful people) instead of the entire population (e.g. all people, successes and failures). If you looked at the people who worked hard and have passion, you would see a surprising number of moist robots who weren’t successful.
And so a successful moist robot tells another young moist robot, how to be successful and we see a predictable pattern of behavior again (you’re a young moist robot in this situation). You have multiple authority figures (parents, teachers, successful people) telling you to one thing (authority bias), these people are generally very likable (liking bias), and you see that all successful people have worked hard and followed their passion (suvivorship bias and bias from mere association), it’s no wonder we’re programmed to think that hard work and passion alone are enough to be successful. We’re just moist robots after all.
Having said all of that, I’m still a big fan of working hard and following your passion. It’s a pretty good program as far as us moist robots go. I would add another crucial subroutine though: luck (or more aptly randomness). Everything that happens is so dependent on our surrounding environment, which we rarely have control over, hence luck. If you’re not factoring in luck then you’re not factoring in reality. The trick is that your program should seek out and maximize the situations where luck is on your side and correspondingly move out of positions where it isn’t. After all, what good is a (moist) robot if you can’t program it?
Atul Gawande, the surgeon, writer, and public health expert (and author of a couple of my favorite books: The Checklist Manifesto and Better), delivered a commencement speech to CalTech recently, here’s an excerpt:
“The scientific orientation has proved immensely powerful… But even where the knowledge provided by science is overwhelming, people often resist it—sometimes outright deny it. Many people continue to believe, for instance, despite massive evidence to the contrary, that childhood vaccines cause autism (they do not); that people are safer owning a gun (they are not); that genetically modified crops are harmful (on balance, they have been beneficial); that climate change is not happening (it is).”
He goes on to describe how pseudoscience “experts” propagate these types of common sense misinformation while simultaneously dismissing scientifically established facts. If you haven’t read the speech, I highly recommend it.
Beyond what the speech has to say, I want to emphasize two important points about good science and good explanations. Science does not equal truth; it is incomplete, sometimes out right wrong, but that’s a feature not a bug. The big reason science works is because you can show that these hypotheses are wrong. Once you do, you can learn from it, and form a new hypothesis or model that describes the world a bit more accurately. The established scientific knowledge that we take as “facts” have withstood every attempt we throw at it to prove it wrong; the ones that show cracks have either been discarded or corrected, what could be more rational? On the whole, science moves forward by explaining the world with increasingly more accurate approximations — never complete but always self-correcting. Contrast this to common sense and pseudoscience which never seem to move until contradictory scientific knowledge becomes so pervasive that it is forced to change.
The complementary point to this is about good explanations. It’s natural for people to cling to their seemingly plausible pseudo-scientific beliefs even when faced with overwhelming evidence to the contrary (e.g. vaccines). Despite this overwhelming evidence that science provides, it is hard for someone to change their world view and part with their intuitive beliefs — it’s not natural. The scientific community has recently been doing a poor job of explaining science to the masses. This is probably because many “intellectuals” find it necessary to attack the bad science instead of focusing on the good science. What these “intellectuals” forget is that attacking bad science is the same thing as attacking a person’s world view — a very personal thing! It’s no wonder that people don’t respond well to it. Instead of rebutting bad science, a better approach is to explain the good science. For example, instead of berating someone for thinking vaccines cause autism, explain how they can save their child’s life and the lives of many other children (who doesn’t want to save children?). It’s not enough to tell them their wrong (besides being ineffective), instead it’s important to help them understand how the evidence is right. This is how things change, not with scientific discoveries but with people.
It’s important for all of us to realize that rational thinking and cold hard facts aren’t the end of an argument but rather its beginning. What comes after is what we scientists and intellectuals often forget: the human component. Ironically, it’s all too human to think like this. So next time you’re trying to educate someone on good science, don’t forget that the most important part: good (human) explanations.
Here’s another old joke:
Two friends, John and Mark, are camping when a bear pops out of the bushes.
John starts to put on his tennis shoes.
Mark says, “What are you doing? You can’t outrun a bear!”
John says, “I don’t have to outrun a bear — I just have to outrun you!”
This joke has two important lessons: (1) you really can’t outrun a bear, and (2) skill is relative. The latter point is something Charlie Munger often emphasizes in a different way:
“You don’t have to be brilliant, only a little bit wiser than the other guys, on average, for a long, long time.”
I like this sentiment. Just like John outrunning Mark, you just need to be a bit — even a tiny bit — better than the other guys with the big caveat that it’s for a long time (on average). So less of a sprint and more of a marathon kind of idea. It just takes a little discipline and an hour a day.
In any case, if there’s one thing I’ve learned in my short time here it’s this: always wear running shoes when camping.
Sometimes it pays to keep things simple (even though people insist on making things complex). Take for example this old joke about NASA:
In the early days of the space program, NASA discovered that using ballpoint pens would not work in zero gravity. NASA scientists — some of the best and brightest people at the time — spent a decade and a billion dollars developing a pen that wrote not only in zero gravity but on almost any surface, at very low temperatures, and in any position the astronaut happened to be in.
The Russians, not to be bested, did something a lot smarter: they used a pencil.
This story illustrates a couple of things: (a) keep it simple and (b) solve the right problem! It’s also a good story because it’s a memorable way to learn vicariously through the mistakes of others. Two quick thoughts:
- People naturally like to make things more complex than they need to be. Maybe it’s an ego thing, complexity is sometimes related to importance, and who doesn’t like to work on important stuff? This is especially true of intelligent people (or at least people who think they are intelligent). The truly wise ones are the ones who can see how to make things simple, not complex.
- Engineers and technical people usually get carried away in their craft. Architecting an elegant solution, digging deep into the details, and handling all the corner cases is second nature (and fun!) to them. This, however, does not lend itself well to an on-time and on-budget project. The most creative solutions are usually time and budget constrained (not the opposite!).
I think it’s fun learning vicariously through others (less so when it’s my own mistake). One of my favourite people, Charlie Munger, has one liner about that:
“If people weren’t wrong so often, we wouldn’t be so rich.”
Some wisdom from Charlie in time for the holiday season:
“Do the best that you can do. Never tell a lie. If you say you’re going to get it done, get it done. Nobody gives a shit about an excuse. Leave early for the meeting. Don’t be late, but if you are late, don’t bother giving people excuses. Just apologize… Return your calls quickly. The other thing is the five-second no. You’ve got to make up your mind. You don’t leave people hanging.”
— Charlie Munger
Some additional commentary from me:
- “Do the best that you can do.”
What could be more obvious? But sometimes I get the feeling that many people don’t follow the same set of values that I do. Instead they eschew this virtue and instead “do the least to get by”. Obviously not something we should be striving for.
- “Never tell a lie.”
I’ve always found lying difficult, too many “versions” of the truth to keep straight. Chalk it up to my like for keeping things simple.
- “If you say you’re going to get it done, get it done. Nobody gives a shit about an excuse.”
This is another obvious one but somehow not everyone has internalized it. There’s something to be said about someone with a lot of assiduity (as Charlie puts it, “Sitting on your ass until it gets done”).
- “Leave early for the meeting. Don’t be late, but if you are late, don’t bother giving people excuses. Just apologize…”
Punctuality is just another form of respect, definitely a virtue to strive for.
- “The other thing is the five-second no. You’ve got to make up your mind. You don’t leave people hanging.”
This is another great one. If someone asks you to go out, just make up your mind. Don’t wait and see if something better comes along, just decide. Don’t be “that” guy.