Afford Anything - When Career Zigzagging is Smarter - with David Epstein

Episode Date: July 29, 2019

#206: We live in a society that values career specialization. You’re not a “doctor” -- you’re a pediatrician, an anesthesiologist, an oncologist. You’re not a “lawyer” -- you practice family law, or bankruptcy, or criminal law. You’re not an “engineer” -- you’re an electrical engineer who specializes in solar technologies, or a civil engineer who specializes in the application of artificial intelligence in highway traffic design. Specialization is beneficial and necessary, but specializing too early in life or too narrowly can also have drawbacks. According to today’s podcast guest, New York Times bestselling author David Epstein, overspecialization can stifle innovation if we’re all digging in parallel trenches. Sampling a broad range of subjects prior to specializing (e.g. at the undergraduate level, or as a hobby) allows people to make connections between far-flung domains and ideas. If you’re an athlete, spend your childhood playing a variety of sports before you commit to the one you’d like to develop. If you’re a musician, try learning different instruments before you pick your primary focus. If you’re bound for a graduate degree in a STEM field, consider a multidisciplinary undergraduate that pulls from chemistry, physics, biology and perhaps even art. Specialization can come later. We hear stories of people who specialized early in life. Tiger Woods won his first golf competition at age two, beating everyone in the age-10-and-under category. Many world chess champions started training in early childhood. The notion is that early specialization provides a headstart; if you haven’t started training at chess or golf by age 12, it might be too late. But chess and golf are limited in their scope. They’re contained games with fixed, predictable rules. In the wider world, in which challenges and assumptions fluctuate and problems are ill-defined, being a generalist is a lifehack. For more information, visit the show notes at https://affordanything.com/episode206 Learn more about your ad choices. Visit podcastchoices.com/adchoices

You can afford anything but not everything. Every decision that you make is a trade-off against something else. And that doesn't just apply to your money. It applies to your time, focus, energy, attention. It applies to anything in your life that is a scarce or a limited resource. And that leads to two questions. Number one, what's most important to you? Not what does society say ought to be most important to you,

but what is truly a priority in your own life? And number two, how do you align your daily decisions in a way that reflects that even when that means that those daily decisions need to be conventional or weird. Answering these two questions is a lifetime practice, and that is what this podcast is here to explore. My name is Paula Pan. I'm the host of the Afford Anything podcast.

And today's guest, David Epstein, is a New York Times bestselling author who has an interesting thesis. He states that in a world in which specialization is encouraged, it's actually the generalists who triumph. In almost every knowledge-based field, specialization. is encouraged. And while there are many advantages to this type of specialization, it also may have the effect of stifling innovation.

Overspecialization has the potential to stifle innovation if all of us are digging in parallel trenches. By contrast, having a wide range of experiences allows us to make connections between far-flung domains and ideas. And David shows in his book, which is called range, that high-level broad, conceptual and transferable thinking is more useful than specialization, at least in many fields. And when specialization must happen, it is often enhanced if there is a previous sampling period. A sampling period in which athletes can try multiple sports, musicians can try multiple instruments,

and students can learn from multiple disciplines. Those sampling periods, while they come at the risk of an early head start, are effective in allowing us to progress further later and to practice analogical reasoning. And so I sat down with David to ask him how these ideas apply in the context of an early retirement or a midlife career change. If we are becoming generalists or developing second acts in life, what can these ideas teach us in how we find the best match for our personalities and our skills and our talents? even when we pivot in our 30s and 40s and 50s and do something drastically different than what we have been doing, when we do something different than our 9 to 5.

So David and I discuss all of this in this coming interview. Here he is, David Epstein, discussing why not siloing yourself, why thinking broadly is the most effective path to success in any domain. Hi, David. Hi, thanks for having me. Let's talk about the premise that your book range debunks, the premise being that specialization and early heads start in a narrow field is what you need in order to succeed. My interest in that really started in the sports world, honestly, where I was the science writer at Sports Illustrated. And I was after sort of writing a book about athleticism, I was invited to debate Malcolm Gladwell about the 10,000 hours rule at this. conference that was particularly about the way to develop the best athletes. And of course,

he's very clever and I didn't want to get embarrassed on stage. So I went and did some homework and kind of anticipated what I thought he would argue. And I knew he'd have to argue for this early start in narrowly focused practice or deliberate practice. So I just looked at what the scientific literature said. And it said that in fact, athletes who go on to become elite typically have what's called a sampling period where they try a variety of things. They learn these broad skills that scaffold later knowledge. They learn about their interests. They learn about their abilities. they systematically delay specializing until later than their peers. Now, there were some exceptions to that. I think golf might be an exception to that. We don't really know. There's a dearth of

science on it, but because of the structure of the domain, which skill acquisition scientists consider almost like an industrial task, try to do the same thing over and over and over with as little deviation as possible. And I sort of discussed that in range, but that's not really the good analogy for the working world that most of us are living in now, where we can count on, you know, perfect information, repeating patterns and people taking turns and just being able to do the same thing yesterday as we'll be doing tomorrow. And so I think one of the things I was reacting to was a lot of the books, the bestsellers that have used the so-called Tiger Woods model to say, this is what you should do in whatever you're doing, when so much of the science shows the opposite. And sports

was just an analogy, but it turned out to be the case in a lot of other domains I looked at. You make the point that these narrow domains such as golf and chess are rigid areas with a fixed set of rules that are extremely predictable. And in those narrow circumstances, you may be able to achieve mastery by starting early. But the rest of the world is not like that. That's right. So those are domains that the ones you highlighted, what the psychologist Robin Hogarth calls kind learning environments. And in fact, not only might narrow specialization work in lots of kind learning environments, it's extremely helpful. or maybe even essential. So in chess, for example, if you haven't started studying patterns,

so Grandmaster's advantage over other players is essentially pattern recognition. And if you haven't started studying patterns by the age of 12, your chances of reaching international master status, which is one down from Grandmaster, drops from like one in four to like one in 55. So you need specialization and early technical practice there. But again, it's a kind learning environment, which means that all the information is available. There's a huge store of previous data tomorrow will look like yesterday patterns repeat it's heavily based on patterns every time you do something there's automatic feedback which is immediate and fully accurate and that is also the reason why it's so easy to automate because when you have a huge store of previous data and something is

based on patterns that you know can repeat um that's like the perfect uh scenario for computers so the things that are the most amenable to early specialization in the work world are also the most easily automatable. So that might not be the areas you actually want to be in. What we've seen so far with automation and with AI is that that tactical learning, using chess as an example, tactical learning is what computers are great at, but strategic thinking hasn't yet been achieved. Yeah. And so tactical, we can think of in chess as tactical learning is basically the patterns that you recognize and say, well, what's the best move to make in this scenario when you've seen it before? And humans can get quite good at that, but, but

computers are quite a bit better because they can analyze so many past patterns. But when Gary Kasparov lost to Deep Blue in the late 90s, it was sort of deemed, I mean, I remember the Newsweek cover was the brain's last stand, right? So chess was often used as the embodiment of human intellect. Like sometimes if we want to compliment someone, we say he or she is playing chess. But Kasparov recognized what's called Moravex paradox in the game, which was that humans and computers often have opposites strengths and weaknesses. And he realized that the computer was not as good at strategy, which is the bigger picture thinking of how you manage the little battles to win the war in chess. And for the most part, tactics, like 99% of chess's tactics and strategy is sort of often in afterthought,

but still important once you get people who are already good at tactics. So Kasparov decided to start new kinds of chess tournaments and help promote what's called freestyle chess, where humans could play and computers could play, but also humans and computer teams combined could play, like any arrangement of anything. And surprisingly, the winners of the freestyle chess tournament were two amateur players with three laptops. They knew something about chess, but they were not nearly grandmasters. They beat grandmasters, they beat supercomputers, and they beat grandmasters with supercomputers. So once the tactical skill, the pattern recognition, that grandmasters take years of study to learn was outsourced to the computers, suddenly the activity was totally

different, and the humans who could best focus on strategy and taking these streaming information coming from multiple computers and what Kasparov said, coach those computers where to look and then make decisions. So that was really a great partnership where you see computers doing what they do best and liberating humans to focus on that bigger picture thinking that they do best, which is not something that is amenable to the kind of early specialization in 10,000 hours thinking. You mentioned kind learning environments. Can you elaborate a little bit on the difference between kind learning and wicked learning environments? Yeah, so again, kind learning environments are these areas where next steps are clear, all information is available.

In some cases, people take turns. The goals are clear. Patterns are very repetitive. And whenever you do something, you get automatic feedback that is comes very quickly and is perfectly accurate. On the complete other end of the spectrum are what Hogarth called wicked learning environments. Now, here, people may not take turns, wait for each other. Human behavior is often involved. A lot of information is not clear.

Patterns don't repeat. Feedback may or may not be automatic. It may be delayed. It may be only partially accurate. It may, in rare cases, even reinforce the exact wrong lesson. So one of the scenarios that Hogarth liked to mention involved a New York City physician who became wealthy and famous because using only his hands to feel around patients' tongues or palpate their tongues, he could predict again and again that patients who hadn't shown a single symptom would develop typhoid. And he got, he became

renowned for doing this. And as one of his colleagues later observed, using only his hands, he was a more productive carrier of typhoid than even typhoid Mary. What was actually happening was he was spreading the typhoid. And therefore, the feedback he was getting was reinforcing the exact wrong lesson. And that turns out in more wicked learning environments, most learning environments aren't quite that wicked, but it turns out that in a lot of more complex domains where the rules change, what Hogarth called Martian tennis, where you see people playing, but nobody's told you the rules and they're subject to change, narrow experience often makes people more confident, but actually know better. And that's a dangerous combination. So would it be accurate to say that

examples of wicked learning environments could include bootstrapped entrepreneurship or even managing relationships of all kinds? Those are both arenas in which the rules are abstract and subject to change. Definitely. I mean, entrepreneurship in some ways I would think is almost a definition, right? Like exactly what you're going to do. I'm not sure, I've met a lot of entrepreneurs and I'm not sure I've ever met one where all of the steps that they thought from day one turned out to be the steps that they needed to take going forward. So those next steps are not so clear. You can't just count on stability or on the world being the way it was tomorrow, the way to today. And this also shows up in what's difficult for computers. So for example,

Take Google flu. So Google decided to bring its formidable power to try to predict the spread of flu based on search queries. And there was a kind of a famous scientific paper where they announced that they had predicted the spread of flu as accurately and more quickly than the CDC. So great. I think it was in either journal science or nature, one of the two big ones. But, you know, those kinds of behavior, what people search in relation to the flu doesn't change this. Doesn't stay the same every year. And so it changed. And Google flu got a little worse and a little worse until a couple years after the big paper, it missed by 100% in predicting the prevalence of flu and during a flu season. And at that point, if you go and look at Google Flu Trends now, you just see a holding page that says, well, it's early days for this kind of prediction. So we're not really doing it right now. I think they learned a hard lesson that when you're not in a chest-like domain, things don't work that way.

It's not as easy. So as one of the researchers I talked to for Range said, the reason IBM's Watson destroyed at Jeopardy and has been a disaster in medical research is because we know the answers to jeopardy and we don't in medical research. And I think entrepreneurs are in these areas where they have exciting ideas, but they don't always know the answers. And they have to be flexible and adaptable and they have to bring their knowledge to bear on problems that they haven't seen before necessarily. And when that happens, I think a classic research finding is an important one to keep in mind. And it goes like this. Breath of training predicts breadth of transfer. That is,

whatever it is you're trying to do, transfer is the term psychologists used for applying your skills and knowledge to problems and situations you've never quite seen before. So if you're in an area where you can't just count on repetitive patterns. And what predicts the ability of people to do that well is how broad their base of training was and how much it forced them to build these broader conceptual models of the world as opposed to just learning how to execute procedures and patterns like you would in golf or chess. And so breadth of training would lead to analogical thinking? Absolutely. Absolutely. So analogical thinking is using domains that are not the one you're currently looking at to help you solve problems. And this dovetails with one of Conneman and Tversky's famous finding. So Daniel Kahneman, the author of Thinking Fast and Slow, won the Nobel Prize for illuminating cognitive bias. One type of bias that he and Tversky studied was called the inside view. And this means, let's put it in context for, say, investors. So when investors, are trying to predict the return on the investment of a certain project, what they'll do is

they focus on all the internal details of whatever project it is they're looking at. And that makes a ton of sense. That's very intuitive. But it also turns out to lead them wildly astray because what happens is as you investigate any particular scenario, turns out that human cognition is such that you will deem that particular scenario to be increasingly common as you learn more details of it, whether or not that is actually true. And a better thing to do is to take.

take what kind of interversky called the outside view, where you don't delve too much into the specific details at hand, but instead you consider the deeper structure of the problem. Let's say, you know, investing some of the areas I talk about in range where this is actually studied is the revenue for a new movie or situations like a startup founder looking to sell or something like that and not focus too much on the internal details. and instead look in other disciplines at analogous situations and create what's called a reference class of those, a bunch of analogies, and then you look at what usually happens and you use that to make your predictions. And even like really experienced venture capitalists in one of the studies I cite, when they were made to do this, over the course of one day, they altered their return on investment projections by 50% once they were forced to think about the deep structure of the problem and make analogies to other projects they need. knew about as opposed to just focusing on the internal details of their project.

And so interdisciplinary thinking and looking at the conceptual framework behind a question rather than the narrow application of overly specific knowledge leads to ultimately better or more accurate assessments of your own subject matter. Yeah, and more creative problem solving. So something that dovetails with that analogical thinking was and breadth of training predicts breadth of transfer. So I think we can cover those in one example I'll share where when I visited Diedrich Gintner in Northwestern University, she's probably the world's expert in using analogies for problem solving, so-called analogical thinking. So she created this task called the

ambiguous sorting task where you're presented with different problems from economics, from biology, all these sorts of things. One of the things that people who are taking this sort of test are asked to do is to identify the deep structure of types of problems and group them by that deeper structure. Like, for example, some are positive feedback loops and some are negative and some are causal chains. And you're supposed to group them by identifying that deep structure. And she tested this on students at Northwestern because she's there. And it turned out that students were pretty good at problem solving and identifying problems in their domain, like in their major, basically. But when they were asked to do things outside of their major, they were not so good at identifying deep structure

or at solving problems. But the students who were good were the ones that were in this program called the Integrated Science Program, where they didn't have a major. They were just made to take a few classes in a whole bunch of different domains. And so even when they were faced with things totally outside of any of the areas they had studied, they were much better at identifying the structure of a problem and using analogies from all these other domains they had dabbled in for problem solving. And so instead of when you're too narrowly focused, whether it's a sports skill or learning math, you learn what's called using procedures knowledge, where you learn how to execute specific

types of procedures. When you have much broader training, you're instead learning where you're not seeing the same type of problem over and over. You learn what's called making connections knowledge, where you're building these conceptual models that allow you to grapple with problems that you've never seen before. One of the disappointments to me, of course, was when I was at Northwestern, and I went around to faculty members and asked about the Integrated Science Program. A lot of them said, well, those students will, we don't really like it because those students are getting behind because they don't have a major. And I'm like, here you have your own. colleague is the world's expert in this very important type of problem solving. She's saying,

here's the students who were making the best at it. And then most of the faculty members are saying, well, they're falling behind. So that kind of gave me a headache. And with the Integrated Science Program, the students learned from a wide variety of scientific disciplines, right? Chemistry, physics, biology. And so they were able to then draw from all of those disciplines while they were creatively and laterally thinking about problems. To what extent would it be beneficial to learn not just adjacent subject matters, like going from biology to physics, but widely disparate subject matters, such as biology, music, art, the German language. Yeah, I think there's a lot of potential value to it. And that isn't just to say, like, go roll yourself into anything,

you know, but I think to testing, there's a lot of value. So if we look at, say, Abby Griffin, Professor Abby Griffin's work on serial innovators, these are people who make repeated creative contributions wherever they are. The terms that come up over and over again as she describes them almost sound like they're flaky or like we should. It's like they seem to flit among ideas. They read more and more widely than colleagues. They have a need to learn from domains that aren't their own. They have a need to communicate with people in disciplines that aren't their own. They use analogies from other domains for problem solving, all these sorts of things. They tend to have lots of hobbies outside of work. And this looks like, so to quote Santiago Ramonica Hall, the Spanish

Nobel laureate and father of modern neuroscience, where he was writing about people who have the best judgment and make the most creative contributions. And he noticed this too long before Abby Griffin was studying it and said, to him who observes them from afar, they look as though they are dissipating their energies when in fact they're strengthening and channeling them. That sort of theme kept coming up. Howard Gruber, a psychologist I write about who studied creative contributions, called it the network of enterprise. And basically the theme is everyone who studies people who find a way to think differently and problem solve creatively finds that they have that, whether they think that it's a distraction or not. You know, Nobel laureates are 22 times

more likely than normal scientists to have hobbies outside of work. These things actually start to feed into each other. What seem like totally unrelated disciplines start to help build these more conceptual models for judgment and general problem solving. And that's sort of one of the underlying themes of the book. And eventually, you know, for people who are investors, Chapter 10 about judgment about political and economic trends is probably one of the interesting ones, where it turns out that the people who develop the ability to make the best predictions are not the people who have access to the most information, but the people who have the broadest range of interests and do what they call perspective aggregating. They go to people in different

discipline. They're not tied to any particular approach or any particular discipline. They do what the researcher who studies them called they have dragonfly eyes. So dragonflies, their eyes have many like thousands of lenses that each take a different picture of a perspective and they integrate it in the dragonfly's brain. And that's kind of the analogy of what these people who develop good judgment are able to make good predictions about the world do. They roam across disciplines. They have these incredibly wide interests. They're often self-conscious about not being an expert in any particular area, and they outpredict even people with top secret security clearance who have access to classified data when it comes to geopolitical and economic trends.

As I hear about analogical reasoning, the immediate question that strikes me is, if a person is geared towards reasoning by analogy, does that interrupt their ability to take the alternate approach of reasoning by first principles? That's a really interesting question. I don't think so. And I'll say that because I think the most relevant work to that was done by Kevin Dunbar, who was examining creativity and problem solving in the context of scientific labs, particularly in like the 1990s when he was at genetics and molecular biology labs

because they were making huge breakthroughs. That was like where that's where the action was at the time. And he went to watch how labs worked in real time. So he was in a different lab every day over years in several different countries. And what he found was that the breakthroughs tended to happen when somebody found something unexpected in the lab. And they would first think that it was an error of equipment calibration or something like that. And they would test it. And eventually, if they couldn't get it to go away like that, then at the weekly lab meeting, it would basically be brainstorming time.

And what helped predict whether a lab would make the breakthrough was the, the, the, diversity and number of analogies that they used. And so that also corresponded to the diversity of the backgrounds of the people in the lab. And in those labs, they had to do, they very much had to do reasoning from first principles and analogical problem solving. And I think those things lived side by side. And analogies sort of often got them off a plateau and helped them consider what to try and novel approaches to problems. But I think they were also in a situation where you could not abandon working from first principles and that they were able to merge both. So I don't think those are in zero-sum competition. So would it be fair to say that analogical reasoning can provide that brainstorming first step? And then once you've come upon a novel idea, you can then use reasoning from first principles in order to further flesh it out. Absolutely. And in fact, I'd say that's partly the conclusion in some of the work in range by Dan Lavallo, who actually worked with Connemon, which is you want to use really wide or what's called distant analogies in the idea generation stage. and you want lots of them, but eventually you want to work down more narrowly, basically,

and you can work from first principles. Certainly one way to do that. So I think you actually articulated it, the conclusion of his work pretty succinctly there. We'll come back to this episode after this word from our sponsors. I'm a bookworm. I love reading books, but the list of books that I want to read is significantly longer than the list of books I realistically could read based on time constraints. That's why I recommend this app called Blinkist.

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Just go to freshbooks.com slash paula. And when they ask, how did you hear about us? Type in, afford anything. Again, that's freshbooks.com slash paula. One of the points that you make in your book is that three quarters of U.S. college graduates go into a career unrelated to their major, including graduates in the state. STEM fields. And so even though we have a cultural appreciation of early specialization, we also simultaneously see lots of career changing happening, not just among millennials, but also among

Gen Xers and baby boomers. Yeah, that's, in fact, I was surprised when I was looking at Bureau of Labor Statistics data to find that this idea of the professionally itinerant millennial was really very much just a continuation of a trend that started with like the very last baby boomers. I won't the very end of that generation, starting with the very last baby boomers, between 18 and 48, they've averaged about 12 different jobs. And that's become even more. But that was already, I think, I think the trend is a little bit older than we give it credit for. And I think there are a number of reasons for that. But if I can, I hope this won't be too much of a tangent, but I think a good place to think about it. And this is why I wrote about it in this context is in the

US Army, where the Army, with the dawn of the knowledge economy, basically. So in the U.S. Military Academy, you know, we spend a lot of taxpayer money trying to produce future top officers in the military. And since about 1990 or so, the retention rates of those officers who go through the U.S. Military Academy on full scholarships have been plummeting to the point where by like the mid-1990s, about half of West Point graduates would leave the Army basically on the day that they were allowed after their first commitment of service, which is not what the Army wants, because they want those, you know, they've spent the most money on those people, they want them to stay for 20 years. This reached such proportions that a high-ranking officer suggested we defund West Point because

he called it, quote, an institution that taught its cadets to get out of the Army. And, you know, it probably didn't do that. And so at first the Army tried throwing money at these high potential officers to keep them in retention bonuses. And the people who were going to stay and took the money and people were going to leave left anyway. And so that was a half billion dollars of taxpayer money that didn't do anything. And then research was done through the Army Strategic Studies Institute. And what this research found was that it wasn't a money problem. It was a problem of how the Army had not changed while the economy had changed. So the Army was still in what the researchers called the company man era, where it did make

sense to be specialized because more tasks were sort of of the industrial variety where and work wasn't changing quite as fast, where you could do the same thing. You could more so expect. tomorrow to be the same as yesterday. And so being specialized made a lot of sense. And that also meant there was a lot less lateral movement because if specialization works than getting someone, you really just want someone to build up that narrow experience. But as the knowledge economy exploded, these broader conceptual skills, in some cases, these softer skills became much more easily laterally transferable between companies.

And the army continued with the up and out ladder, while their highest potential employees started saying like, hey, I'm learning stuff that can transfer. I'm getting new interests. I'm going to go out and apply these things in the wider work world because I don't have much mobility inside the Army. So after they failed with retention bonuses, they started something they called talent-based branching. Where instead of saying, here's your career track, get up or out. They say, here's a bunch of career tracks. We're going to pair you with a coach.

Dabble in some of these career tracks. The coach will help you reflect on how they fit your industry. interests or abilities, search for so-called match quality, the degree of fit between your interests abilities and the work that you do, and then we'll zigzag until we triangulate a better fit for you. And it was that that started retaining these high potential, highly invested in future officers in a way that money bonuses hadn't. And I think that's kind of a good model for approach for the wider world, where we can transfer skills laterly and match quality is incredibly important in this kind of economy.

So match quality, again, that degree of fit between your interest abilities and the work that you do turns out to be incredibly important for people's motivation, their sense of fulfillment, their performance level. So, you know, we like to think of grit, this sort of psychological construct of stick-to-itiveness. It turns out when you get people with a good fit,

it looks like grit because they work a lot harder. And so we should think about going through the world in search of match quality instead of just in search of a head start, basically. And so how do you determine your match quality for a career or for a second act, particularly if you're already in your 30s or 40s or 50s? Yeah. Well, you have to do some experimenting. And so Hermione Eibara, a professor of London Business School, who studies how people, you know, essentially triangulate their match quality, has this phrase that I love, which says, we learn who we are in practice, not in theory.

What she means is that psychological research shows that we actually don't have all that much insight in. into our talents and interests a priori. We actually have to try things and reflect on them, and that's how we learn about our talents and interests. So instead of in theory, having a theory about ourselves, we actually have to do stuff. She says, act and then think. Don't think and then act.

The problem is, you know, we don't like to think that we might be experimenting and losing some time, but it's well worth it if you get better match quality. So an economist who studied specialization timing in England and Scotland in higher ed, for example, where the school systems are very similar, except for specialization timing, the Scottish students can experiment longer, found that the English students who had to specialize earlier did jump out to an income lead

because they had more specific skills because they specialized earlier. But the Scots got to experiment a little bit, or the Scottish students, they weren't necessarily Scots, but got to experiment a little bit, and they picked better fits. So they had higher growth rates, and by year six, they caught and passed the English students. And then the English former students started quitting their career tracks in much higher numbers. Basically, they had been made to pick earlier, so they made worse choices. And I think that's another good model to keep in mind. Your insight into yourself and into the world is constrained by your roster of previous experiences. And so if you're not experimenting, you're not working on your match quality. And you don't have to do that in a wasteful way,

but keep this in mind to. This principle, psychological principle called the end of history illusion. This is the finding that everyone recognizes that they have changed a lot in the past, but then underestimates how much they will change in the future at every time point in life. Every time point in life. This leads to really funny results. Like if you ask people how much they'd pay today for a ticket to see their favorite ban 10 years from now, the average answer is $129. And if you ask how much they'd pay to see today their favorite ban from 10 years ago,

the average answer is $80. because we severely underestimate how much our taste will change. And that's just a funny example. But it turns out to be true for every personality trait. So in fact, we should be changing throughout life. If you're not, you know, in your 20s or 30s, all through life, looking too far down the line, trying to set a goal that should be unchanging, what the investor Paul Graham calls premature optimization to use computer scientist terms, is essentially trying to make a choice for a person you don't yet know in a world you can't,

yet conceive. So instead of being committed to a long-term goal, we should be committed to a process. The process that is kind of embodied by the subjects in research and range called the Dark Horse Project, where this is again about how people find match quality, how they find fulfilling work. These were two researchers at Harvard who were studying these people and found that they would all say, oh, you know, don't tell people to do what I do because I started in this one thing and then that wasn't right. And so I did something else. And like, just I'm not a good model. Don't tell people to do what I do. And they found that almost everybody said that. And so they called it the Dark Horse Project because all these fulfilled people saw themselves as having come out of nowhere,

like a dark horse. And their common trait was short-term planning. So instead of sticking to a long-term goal and saying, here's what I'm going to be in 10 or 20 years and marching confidently toward that, their approach was, here's who I am today, here are my skills and interests, here are the things I want to learn or try, here are the options in front of me. I'm going to try this one. And maybe a year from now I'll change because I will have learned something about myself. And they just do that over and over and over and over. And some of them find a great fit at 30 and some of them find a great fit at 50, but they all end up really fulfilled. And for most of them, that also ends up, you know, that they are successful in much more objective ways, too.

But they didn't have to be to be in that study. Fulfillment was the dependent variable. But many of them turned out to be very financially successful also. So instead of working backwards from a goal, work forwards from a promising situation. Exactly, exactly. And I think that's, I may have also quoted Paul Graham on that. because, yeah, so, and I think that's a great take. How do you then balance experimentation with commitment since both are needed?

Yeah, that's a great question. And in fact, the dark horses, they do sometimes formulate long-term goals. Sometimes they go to med school or something like that, which, of course, is a goal that you have to set for some time in the future. But they only do it after a period of experimentation. And so I think the conceptual model to take is that talent is like that talent-based branching that the Army uses. You know, you're not going to get assigned that coach that the Army is assigning where they're sort of helping you reflect. And reflection is a key component of so-called self-regulatory learners. So people who learn more about their interests and they evaluate their own strengths and weaknesses more the way that their managers do.

So they're kind of more objective about themselves. They spend a lot of time in reflection. might sound facile, but actually most of us don't do that so we don't get the maximum learning out of our experiences. And so I think we should make sure to kind of be ourselves, that coach that the Army uses in talent-based branching where we do things and then make sure to reflect on them. So I started, it's a little bit embarrassing maybe, but I started what I call a book of experiments. So the way, I used to be a science grad student and, you know, you had a book where you put hypotheses in and then you would test them and then you would record what you learned.

And so I've sort of started a book like that for myself that I call my book of experiments where there's something I want to learn or an interest I want to test. I make a hypothesis for how I'll feel about it or what I'll learn and I do it. And then the reason I have the book is solely to prompt myself to reflect in a deep way that I might not do intuitively. And I've found it to be really valuable. And so when I find something I want to stick with, like when I find a project like my two books, which are, you know, I was super goal directed when I was a teenager. and I've gotten like linearly less so as I've gotten older and I realize that all the projects that have been important to me were never anything I planned from far out. But instead I just reacted to opportunities and interest that came up. And so when those projects come up, there's no difficulty in saying like, oh, this is something that's grabbing my attention.

Again, it's that when you get fit, it looks like grit. So when I find a project that fits me well, like it's not even a question. I'm not going to deviate from it, you know. And then I'll and then when I'm done with that like I am now, I'm going to go back into experimentation mode. But I'm going to continue that dark horse approach, I think, for my entire life, because I don't think there's a, because first of all, the world changes and I change. And so I think knowing the end of history illusion and knowing the way the world changes, there is no sort of cap on your match quality because things will always be changing. One of the experiments that you talk about in your book is when people were considering whether or not to switch jobs, the Freakonomics authors did a study in which they had people flip a coin. And based on the coin toss, those who flipped heads switched their jobs and ended up having to be.

Can you explain that? Because on the surface, that sounds quite counterintuitive. Yeah. So this was Steve Levitt, yeah, the so-called Freakonomics economist, who leveraged his rather large following to get people, people who are considering any sort of life change. You know, it could be from having a kid to like going on a diet or getting a tattoo, and they would flip a digital coin and were supposed to follow the results. I think it was if they got heads, they sweat. They do the change. And the most common question people asked was if they should quit their job. And I won't go in the details of the analysis here, but the paper is cited in the book if people want to do that. But there was an actual causal effect of the coin toss on the choice

people made. So if they got heads, they were in fact more likely to change their job. And those people ended up happier when he followed up with them down the line. And so the basic conclusion of the study was that if you're thinking about changing your job, you probably should. And he went about it a counterintuitive way, but maybe that's not such a counterintuitive conclusion. the end. In the context of if you're thinking about quitting your job, you probably should, or if you're thinking about moving to a new city, you probably should, or any of those. How do you discern a fleeting thought from your intuition guiding you? That's a great question. My approach to that is again, sort of from the Herminia Ibarra school. I mean, her work, you know, I was like living in a

tent in the Arctic when I decided I was going to try to become a writer. So her work about career changing deeply resonated with me. One of the things she talks about is your work identity, basically, and that, like, the reason, one of the reasons that changes feel so psychologically unsettling is because it isn't like this sort of trope of, oh, you just take a flying leap all the time. Identity changes slowly and one piece at a time, and you're going to have to have a foot sort of straddling the chasm in two worlds at some point, because we just don't change our identity that fast. And so the way that the most... successful career changers she studied worked was they would start with these smaller experiments.

In many cases, their new interests developed as, oh, they met someone in a dinner party, or they attended some event and ignited some new interest they had no insight into. And then they would just a little by little start to, you know, get a little more interested. Maybe they would take a class or maybe they would meet a few more people. And then they would become a full-fledged hobby. And then it would get to the point where they were like, okay, I think I really want to do something else and make this a career. And their associates and friends would tell them, no, no, just keep it as a hobby. You don't want to get behind. But eventually they would get to the point where they felt like they had to. And so this wasn't usually a flying leap. So my suspicion,

and this isn't recorded in that Freakonomics study, but my suspicion is that those people had already been taking a lot of steps toward those career changes, that they weren't just like flipping the coin and taking a flying leap, or they probably wouldn't have been submitting for that question anyway. So I think the way to do it is to start with these sort of little, little experiments that you can test with your own book of small experiments, and you start forming that new identity piece by piece. And so I think in most cases when people are ready to take that leap and to do it well, they've done these little experiments and started shifting their identity. In terms of the total flying leap, I mean, I think people do that when they're kind of miserable in what they're

currently doing. And that's a whole other situation, I think. One thing you also talk about is how people's personality is quite context dependent. Yeah, so there's this great, and by great, I mean, large, not necessarily awesome, but also kind of cool. Debate in psychology called the person situation debate. And the essence of this debate is whether personality traits that people display are innate to them, you know, essentially genetic or if not genetic, then for whatever reason. immutable, or are they the product of the situation that they happen to be in at the moment or the past experiences they've had in that? So it's sort of a nature-nurture debate of personality. And some of the work I decided to highlight is work that is building a bridge between the extreme

ends of the person situation debate. And it's specifically work that's finding what's called, well, one of the researchers called if-then signatures. And what that means is, For example, if David is at a giant party, he's an introvert, and if David is with his team at work, then he's an extrovert. Those things are true about me. And they are consistently so. And that's what these researchers are finding that people do have these consistent signatures in some cases, at least over shorter spans of time, but that the situation, the context, can completely change them. So it's sort of a bridge in the person's situation debate. We say, okay, yes, David shows very different behaviors in different situations, and yet those

differences are pretty stable within him. And so I think it's important to acknowledge that because along with the end of history illusion, where our personality overall changes quite a bit, we tend to overestimate some of our insight into ourselves where really you can get in different situations that make you behave like a different person. And one of the places I saw this, and again, I think about grit a lot just because I was writing about that psychological construct. But like, I was a college athlete. And some of the people that I ran track with in college were the grittest people I've ever seen on the track and the biggest chickens I've ever seen in the classroom.

And vice versa. So I think it's demonstrably true that very important traits like grit are context dependent and that they are not just stable. They are states, not traits. That's the terminology psychologists used to say something is a state that might not follow you in. every context you go in, as opposed to a trait where you behave with the same personality traits in every situation. And people probably understand this intuitively because, you know, is someone confident or not? Well, you can probably put them in context where they feel competent and they are and then in others where they're totally, you know, fearful and not so confident. So I think we should

be mindful of these if-then signatures because when you're exploring, you're partly exploring your own, you know, your own personality. And again, some of this research actually looks at entrepreneurs and that some people who are very kind of risk averse socially are incredibly risk tolerant when it comes to their work life. They might not know that unless they give it a try. I mean, this is something I've learned about myself from self-regulatory learning is when I realized when I first had like some disposable income that I wanted to invest after my first book, you know, I engage some financial advisors and I start to realize, okay, they're giving me these quizzes. And basically what these quizzes are getting at, I can tell, is they're trying to figure out, like, will I freak out or not

if I invest something in the market goes down? And to what degree will I freak out? And over what span of time will I freak out? And so I started to say, okay, well, I can test this more directly than filling out their quiz, like, I'll invest something, and then I'll watch how I feel when something happens. And I basically learned that I'm a lot more risk tolerant than I expected I would be. And so now, and that's like what I build into my own strategy. So, for example, I don't buy, this is maybe more than anyone wants to know, but I don't buy like bonds because if I'm investing money, then I'm willing to risk it. And if I'm willing to risk it, I want a risk premium, so I'm willing to risk it.

And I've learned that about myself. And that's not something I ever would have guessed a priori. I learned that through very conscious experimentation and saying, oh, you know, this is how I am, so I'm going to take advantage of that. But I just don't think you learn that stuff without trying it because I wouldn't have assumed based on, I mean, I guess I've made lots of career leaps. So maybe I'm sort of risk-tolerant in that sense. But I'd say there are other areas where I'm not so very risk-tolerant at all. And somewhere I really am risk-tolerant. I think that's an important thing

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more risk tolerant, can they move that benchmark through deliberate practice or thought or desire? Yeah, that's a great question. I think there is definitely, there are definitely things you can do, and there are a couple things to discuss in that sense. So first is what's called free traits. This is another aspect of personality psychology that is part of the bridge in the person's situation debate. And what free traits means are essentially you can assume certain personality traits when something is really important to you. And someone who wrote really eloquently about this is Susan Cain in her book, Quiet, where she goes through some of the science of this and I'm with a scientist named Brian Little and who shows that if certain work or certain situations are important to you,

like, you know, in the context of her book is introverts can easily assume extroverted personalities when they need to, even if it's not their natural state. So yes, they can. And in other cases, So I write in range about the famous marshmallow test that everyone, you know, if you've heard of the marshmallow test, you know, bottom line is kids are given a marshmallow and an experimenter says if you don't eat it, you can eat it now, but if you don't, when I come back, I'll give you two. And it's a test, they're delayed gratification. And it's famous because like parents are all over YouTube doing it on their kids. And everyone thinks of it as predicting the future of these kids, you know, how well their outcomes will be in school and in income and all these other things. And it turns out that actually it's not very good at doing that. And the more interesting finding of that study was how easily you could get the kids to change their behavior by changing their mental models of what they were doing. So, for example, instead of thinking of the marshmallow as a marshmallow, helping them think about the marshmallow as a fluffy cloud or something like that where they could divert their attention. And it was not very hard to do that. And so, you know, I think there's a lot that's unknown about exactly how stable certain personality characteristics are. I think Angela Duckworth, I think, is now studying, you know, in what context can you, in what ways can you alter grits?

There's a lot we still have to learn about that. But I think there's also a lot of suggestive work that shows that if we sort of change our mental models, we can assume characteristics that might not come to us totally naturally. Now, that may mean that some people need to work more to have those, whereas they come more naturally for other people. But, you know, that's okay. It doesn't mean you can't do those things. And in what ways you said a person might need to work more, in what ways would they do that work? Yeah. So for example, again, when I'm in larger situations, you know, I tend to be more introverted, but I also like meeting people. So I don't think of introverted as being just overall shy. It's almost like, you know, I need to recharge on my own, basically.

But I actually, much to my amazement, I must say, I enjoy networking. I thought that was going to be like my downfall when I, when I switched out of science to get into writing. But it turns out I really like meeting people and hearing their stories and brainstorming and all those things. But I can also find it exhausting at a certain point. And so for me, I have to like build in deliberate times to do those things and then sort of rest periods between them. And that's just something I learned from doing those things. And I think you learn how to make those sorts of things work for you. But if it's if it's more about delayed, if you're thinking about delayed gratification specifically,

that's a large can of worms that ranges from everything to how you change your context. So to use a really dramatic example, there's a famous finding that, like, in Vietnam, a lot of soldiers were addicted to heroin. They got addicted when they were overseas. People who are addicted generally relapse or stay addicted. It's very addictive drug. And yet when those soldiers came back, they defied. all of the expectations for their ability to kick that addiction. And it turns out that has a lot to do with changing the context.

So they made a move, a contextual move that most people don't make, right? Like they came back home. They left the context that was associated with their addiction. And that, again, is a very extreme example. But it turns out that a lot of habits are very sort of context cue dependent. And so that if you can change the context or change your environment or change the setting, you can alter those habits or form other good ones. And so I think that's, those are good things to keep in mind that if you want to make a major change,

you probably want to also change things about your environment as opposed to just sort of trying to will it with your mind. Right. Both James Clear and Charles Duhigg talk about that, the trigger that leads to the action that leads to then the outcome or the reward. Yeah, and Adam Alter in the book Irresistible, which I love. He's a psychologist at the business school at NYU, and he gets into that as well. in very interesting ways. Going back to the end of history illusion, given that we do not know what our future selves will want, how do we make any type of long-term plan? How do we plan for retirement?

That's a good question. And I think you probably, even if you don't know exactly what you're doing, you probably know that you would like to be comfortable in retirement. And so I'm not sure that requires as much specific planning. And also, I think if you think of the opportunity cost of if you are set to be comfortable in retirement, you can always blow through that money once you get there if you decide that wasn't the right choice for you or even sooner if you want to. And so I think most of the opportunity cost comes on one side there. And also, some of the predictable personality changes that occur over time are, you know, more desire to spend time with family. As people age, they get lower, they score lower on openness to experience.

They become less neurotic. They become more capable of forming stable relationships, all those things that to me would suggest that, you know, having a good nest egg is a really good thing to do. But also I just think there's an issue of opportunity costs there where you can adjust if you're going in the right direction, you can adjust as you want to. But if you're not, then you really limit your options. So one of my overall kind of advice for whether this is people managing their own life or or sports. development programs or companies is to diversify the pipelines by which they include and develop people because it turns out that if you make it too narrow, first of all, you screen out a lot of people you want, but you also limit people's ability to have insight into their own self-development if you require everyone to go down a certain path. And I think since you don't know exactly who you'll be in the future, having appropriately saved your retirement is essentially a form of freedom that will allow you to explore that. And since I feel that we should stay as open as possible, I think that appropriately saving for retirement is one of the ways that you keep your options as open as

possible. And I know it's easier said than done. It's not necessarily such an easy thing for everybody, but that's one thing that I gear myself toward is trying to keep my, and first of all, the things I like to do, I have to say, are cheap. Like, I like reading a lot and I like running a lot. So I moved next to a national park and a bookstore, which is another thing that makes me more risk tolerant on that front because the things I like to do are not that expensive. But I'm very geared toward keeping my options open because when I look back at the history of my life and my career, zigzagging has been the norm. And when I was a teenager, I was sure I was going to go to the Air Force Academy and be an astronaut. And I didn't do those things.

And all of the projects that have been the most important to me have been unexpected. And so I'm very oriented toward keeping my options open. And I think financial security, to the extent you can have it, is an extraordinary facilitator of being able to keep your options open. open. So what I'm hearing is increase freedom and then let your current self make decisions in that in the current context. You know, and I don't want to be prescriptive for other people, but I think that's what I've taken away from my own development from some of the research that went into range. Sometimes when people retire, and many people who are listening to this podcast are particularly interested in an aggressively early retirement, meaning that they might retire

at the age of 35 or 40, which means that functionally they would be starting second careers or maybe moving into entrepreneurship. What can they expect in that second part of their life? Yeah, that's perfect because one of the themes of my book is also about our obsession with precocity and how not reflective of reality it often is. And so I was just invited to a motley fool event. Before the panel I was on, they kind of took something from the introduction of my book and made it into an audience poll where they put up on a screen, they asked the audience to guess what is the average age of a founder of a blockbuster startup, not when it became a blockbuster, but on the day of founding. And the options were 25, 35, 45, 45, 55, and 25 was the overwhelming

favorite. I think it was 60 some percent. And then it was descending from 35 to 45, and then 55 was like three percent or something like that. And I think that's telling. You know, we just like we remember the Tiger Woods story, even though it's the exception. We remember when Mark Zuckerberg said, you know, at age 22, young people are just smarter. Well, in fact, brand new research from MIT and Northwestern and the U.S. Census Bureau found that the average age of a founder of a blockbuster startup on the day of founding is 45 and a half. And with considerable spread, and a 50-year-old was much more likely than a 30-year-old to be a blockbuster startup founder. And the 30-year-old was more likely than the 20-year-old. But we never hear those stories. We fall prey to the

the so-called availability heuristic, where it's just a few dramatic stories of younger founders that stick in our head. And so I think that's an important thing to keep in mind, because it is these people, these entrepreneurs, they've typically had to zigzag a bit, and that's how they find the ground on which they can uniquely compete, because they are really facing a wicked problem, right? They're trying to do something that nobody has quite done before. And that often requires learning about yourself and learning about the world, so you can find out where that should even be. You know, Mark Zuckerberg, pronouncements aside, the people who have done a little zigzagging and have some experience and are coming into middle age are proving themselves to be uniquely valuable,

even despite our obsession with Prakassi and all the forces that tell people to specialize when they're really young and not change directions. And so if we could systematically build for that, I think we'd be even better off. But I think people should just acknowledge that. And that's why I highlighted some of the people in my book like Francis Heselyne, who took her first professional job, the age of 54 and when saved the Girl Scouts basically and Peter Drucker, the famous management guru, pronounced her the greatest CEO in America. I just saw her the other day. She's still running an organization in Manhattan and teaching at the U.S. Military Academy at the mere age of 103 and a half. And she didn't really find her calling until she was in her mid-50s. And that's not as abnormal as we

think. And so I just think we should embrace that. It doesn't mean it's easy to find those things. It's not easy to be an entrepreneur, startup founder, but it's worthwhile. And the zigzagging could actually be beneficial in the long run in that it provides that better match. It not only provides a better match, but then there are other benefits of it. We talked about analogical problem solving, but from research in comic books that I looked at where the people who make the breakthrough creations are the ones, not the ones with the most experience necessarily or the most resources, but the ones who have worked across the largest number of genres over to looking at technological. patent research where since the explosion of the knowledge economy, the biggest contributions are coming not from specialists with the deepest technical expertise, but the people who have spread their work across the largest number of technological classes, as deemed by the U.S.

Patent and Technology Office. And those things, you know, those sound different. Or LinkedIn just did research on a half million members that found one of the best predictors of who would go on to become an executive was the number of different job functions that an individual had worked across in an industry. And all of those things sound like very counter to the sort of pick and stick safe strategy, but that's what the research shows. Well, thank you, David. Where can people find you if they would like to know more about you and your work? David Epstein.com. And I'm at David Epstein on Twitter.

Excellent. Thank you so much. It's my pleasure. I'm just talking to. Thank you so much, David. What are some of the key takeaways from this conversation? Here are five. Number one, knowledge about how to think analogically by a nice. and how to make connections between a wide variety of disparate disciplines is more effective than knowledge that is simply limited to knowing how to follow procedures. When you're too narrowly focused, whether it's a sports skill or learning math, you learn what's called using procedures knowledge, where you learn how to execute specific

types of procedures. When you have much broader training, you're instead learning where you're not seeing the same type of problem over and over. You learn what's called making connections knowledge, where you're building these conceptual models that allow you to grapple with problems that you have never seen before. And so when you are trying to learn any skill set, whether that skill set is rental property investing or deciding how to manage your money or retirement planning or index fund investing or career management or entrepreneurship or side hustling or growing an online business,

regardless of what skill set you're trying to learn, resist the temptation to ask for a step-by-step plug-in-play formula. That is an example of using procedures knowledge, and that's not the knowledge that's ultimately going to serve you in the long run. Learning how to think is more important than learning what to do. And so to the greatest extent possible, as you're learning a new skill set, as you're learning about rental property investing, don't ask simply what, ask why. If you're a long-time listener, I think you know that the secret mission of this podcast is to teach you and to teach myself how to become a better critical thinker, how to become better at making decisions, and how to sharpen the skill set of sharpening skill sets. This is a podcast about critical thinking,

disguised as a money podcast. And that's why so much of our content is about cognitive biases and mental models and articulating the frameworks that we use as we think through a problem. And so all of that ties back to key takeaway number one, which is that knowledge that allows you to make connections between multiple disciplines is far more beneficial to your life and to society than knowledge that is narrowly focused around following procedures. So that's key takeaway number one. Key takeaway number two. Fit is grit.

When you find the right fit in terms of matching your skills, interests, talents with the type of work that you do, that often looks like grit because it motivates you to work harder. That's another way of saying that you will work the hardest in the thing that you are most passionate about. And therefore, the cliche of follow your passion is not some trite rainbows and unicorns feel-good cultural trope. It is a strategic guideline that improves your probability of success because you are more likely to be successful at the thing at which you work the hardest. and you are more likely to work the hardest at the thing that is the best match. We can transfer skills laterally, and match quality is incredibly important in this kind of

economy. So match quality, again, that degree of fit between your interest abilities and the work that you do turns out to be incredibly important for people's motivation, their sense of fulfillment, their performance level. So, you know, we like to think of grit, this sort of psychological construct of stick-to-itiveness. It turns out when you get people with a good fit, it looks like grit because they work a lot harder. And so we should think about going through the world in search of match quality instead of just in search of a head start. And so don't worry about getting a head start at something. Don't worry about early specialization. Explore and sample so that you have a higher likelihood of coming across the career, the industry, the project

that is genuinely a best fit. So that's key takeaway number two. Key takeaway number two. Key Number three, act first, think second. Humans are terrible at predicting who their future selves will be. We do not know how we will feel about a situation, how we will respond to a situation until we are in it or until we are through it and can look back on it in hindsight. And so there is wisdom to not overthinking something in advance. Hermione Ibarra, a professor of the London Business School, who studies how people, you know, essentially triangulate their match quality, has this phrase

that I love, which says, we learn who we are in practice, not in theory. What she means is that psychological research shows that we actually don't have all that much insight into our talents and interests a priori. We actually have to try things and reflect on them, and that's how we learn about our talents and interests. So instead of, in theory, you know, having a theory about ourselves, we actually have to do stuff. She says, act and then think. Don't think and then act. And so key takeaway number three is to act first, think second. Many of our sharpest insights occur only in hindsight. You know, they say hindsight is 2020, but prospective hindsight, which is trying to have hindsight

in advance of something, prospective hindsight is 50-50. You just never know if you're going to get it right or not. And so that's key takeaway number three. Key takeaway number four, remember the end of history illusion. In this quote, David will explain what that is. Your insight into yourself and into the world is constrained by your roster of previous experiences. And so if you're not experimenting, you're not working on your match quality. And you don't have to do that in a wasteful way, but keep this in mind to.

This principle, psychological principle called the end of history illusion. This is the finding that everyone recognizes that they have changed a lot in the past, but then underestimates how much they will change in the future. Our future self is unlikely to be similar to our current self, just as our current self is in many ways dissimilar to our previous selves. Look no further than your 1990s haircut to know how much you've changed. And so the fourth key takeaway is not to assume that future you will want the same things or value the same things as current you,

but rather to build options, freedom, and flexibility into your life. so that future you has options, freedom, and flexibility that they can use as tools to build the life that they want at that time. And so that is key takeaway number four. Finally, key takeaway number five, and this is an actionable takeaway, start a book of experiments, a book in which you track your hypotheses and how well they worked out. And so I've sort of started a book like that for myself that I call my book of experiments where there's something I want to learn or an interest I want to test.

I make a hypothesis for how I'll feel about it or what I'll learn, and I do it. And then the reason I have the book is solely to prompt myself to reflect in a deep way that I might not do intuitively. And so key takeaway number five, and this is an action item, is to have a notebook or a document on your computer or on your phone in which you write down, hey, my hypothesis is blank. And then you write down all of your notes as to how it worked out and whether or not, it worked out in the way in which you thought it would. So, for example, if you're trying to pick a side hustle, you might write down, hey, hypothesis, I'm going to enjoy renting out my guest room on Airbnb. And then in the notes, it turns out that's not the case because the thing that you didn't

think about is that turnover in an Airbnb happens every few days. And so being around for such frequent guest turnover, you know, Sunday somebody checks in, Wednesday they're out, Thursday somebody new is in, Saturday they're out. it ends up being more of a time commitment than you expect. And so then you move on to the next thing. And you track what you like and what you don't like and how you feel about things. What is it that you expected? What is it that surprised you?

What did you observe about yourself in the process? And then this becomes a more structured way of noting down observations about yourself. This becomes a structured way of developing self-knowledge. Those are five key takeaways with this conversation with David Epstein. I would love to know what you thought of today's episode. Go to Instagram. Follow me at Paula Pant. That's P-A-U-L-A, P-A-A-P-A-N-T.

And let me know what you thought about today's episode. We have a free e-book. It's called Seven Expensive Rental Property Mistakes to Avoid. You can download it for free at Afford-A-A-Nthing.com slash real estate. So if you're interested in learning about rental properties, download the free e-book, seven expensive rental property mistakes to avoid. you can download that at Affordanithingthing.com slash real estate. If you enjoyed today's episode, please do me a favor.

Go to iTunes or Apple Podcasts, as it's now known, and please rate us and leave us a review. If you go to Affordanithing.com slash iTunes, that will take you to the page on the Apple Podcast website, where you can leave us a rating and a review. These are very helpful in allowing us to book awesome guests. People like New York Times bestselling author David Epstein. When we reach out to them, we can say, hey, check out. out these ratings that we have, check out these reviews that we have. Would you please come on the show? So if you could please leave us a review in Apple Podcasts, either you can do it directly in your app or you can go to Afford Anything.com slash iTunes.

That would be super awesome. I really appreciate it. Thank you so much. Three more notes and then we're done. Okay, first of all, we have a Facebook group. If you want to hang out with other people in the Afford Anything community, you can join our Facebook group. Just go to Afford Anything.com slash Facebook. Number two, as a reminder, I am taking a September sabbatical. So in September 2019, during that month, we will not be releasing new episodes. We will still be releasing new stuff on this channel, but they won't be brand new episodes. We will be releasing some rewind content from the archives, a collection of some of my favorite interviews, and we'll be releasing a couple of interviews that other podcasters have done with me. So that is coming up in September 2019.

I will be spending five weeks traveling. I'll be going to Croatia, Slovenia, Washington, D.C., and Japan. So four countries in five weeks. You can follow the adventure on Instagram at Paula Pant. And then finally, last but not least, our course on rental property investing is going to reopen for enrollment at the end of September. So September 23rd through September 27th, for that one week only, the course will re-reported. reopen for enrollment. It's called Your First Rental Property, and it is a course aimed at beginner rental property investors. If you have always been interested in learning about how to

buy a rental property, how to invest in rental properties, then you will enjoy this course. Again, September 23rd through September 27th is when we open for enrollment. And the course is online. It's 10 weeks long. You have the option of moving through it at your own pace, but you can also move through it with a cohort of students so that everyone is able to, talk about the lessons in the forums and take quizzes together and have accountability groups. You can chat with me live during the office hours or submit questions on the FAQ portal. So if you'd like that closer attention and a structured curated lesson plan that guides you from the A to Z of learning how to buy your first rental property, then this course is for you.

Again, we open for enrollment from September 23rd through 27th. And if you download our free ebook at Affordanything.com slash real estate, then you will receive all of our emails about this course. Those are all of our announcements. Thank you so much for tuning. And my name is Paula Pan. I am the host of the Afford Anything podcast. I'll catch you next week.