#28 Michael Mauboussin: A Decision Making Jedi

Michael Mauboussin returns for a fascinating encore interview on the Knowledge Project. We geek out on decision making, luck vs. skill, work life balance, and so much more. *** Michael Mauboussin is back as a returning guest on the Knowledge Project! He was actually the very first guest on the podcast when it was still very much an experiment. I enjoyed it so much, I decided to continue with the show. (If you missed his last interview, you can listen to it here, or if you’re a member of The Learning Community, you can download a transcript.) Michael is one of my very favorite people to talk to, and I couldn’t wait to pick up right where we left off. In this interview, Michael and I dive deep into some of the topics we care most about here at Farnam Street, including: The concept of “base rates” and how they can help us make far better decisions and avoid the pain and consequences of making poor choices. How to know where you land on the luck/skill continuum and why it matters Michael’s advice on creating a systematic decision-making process in your organization to improve outcomes. The two most important elements of any decision-making process How to train your intuition to be one of your most powerful assets instead of a dangerous liability The three tests Michael uses in his company to determine the health and financial stability of his environment Why “algorithm aversion” is creating such headaches in many organizations and how to help your teams overcome it, so you can make more rapid progress The most impactful books that he’s read since we last spoke, is reading habits, and the strategies he uses to get the most of every book The importance of sleep in Michael's’ life to make sure his body and mind are running at peak efficiency His greatest failures and what he learned from them How Michael and his wife raised their kids and the unique parenting style they adopted How Michael defines happiness and the decisions he makes to maximize the joy in his life Any one of those insights alone is worth a listen, so I think you’re really going to enjoy this interview. Go Premium: Members get early access, ad-free episodes, hand-edited transcripts, searchable transcripts, member-only episodes, and more. Sign up at: https://fs.blog/membership/ Every Sunday our newsletter shares timeless insights and ideas that you can use at work and home. Add it to your inbox: https://fs.blog/newsletter/ Follow Shane on Twitter at: https://twitter.com/ShaneAParrish Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:08Shane Parrish?

  Hello listeners, welcome to the Farnam Street Podcast called The Knowledge Project. I'm your host Shane Parrish, the curator behind the Farnam Street blog, which is an online community focused on mastering the best of what other people have already figured out. The Knowledge Project is where we talk with interesting people to uncover the frameworks that you can use to learn more in less time, make better decisions, and live a happier, more meaningful life. On this episode, I have Michael Musaben. Michael is one of my favorite people to talk with. This dude is a true polymath. He's the Director of Research at Blue Mountain Capital Management. Prior to that, he was the Head of Global Financial Strategies at Credit Suisse and the Chief Investment Strategist at Legg Mason Capital Management.

• 0:52Shane Parrish?

  He's also the author of three books, including one of my favorite multidisciplinary reads, More Than You Know: Finding Financial Wisdom in Unconventional Places. As you'll see, when the two of us get together, we geek out over decision-making. This conversation will not disappoint.

• 1:17Shane Parrish?

  You were the first podcast guest we ever had on The Knowledge Project, which was almost two and a half years ago. Bring me up to date, what have you been working on in the last few years since we chat a lot?

• 1:28Speaker 01

  Well Shane, I think it's a lot of the same stuff. And really, what I've been trying to do is deepen some of the themes that we've been working on. So, just a couple of examples. One, I think we talked briefly about some economists' work on the inside versus the outside view, and really the application of base rates to improve the quality of forecasts and decision-making. And in that regard, we've really tried to do some deep dives, especially in corporate performance, to understand a large sweep of history in terms of corporate performance for sales growth, and gross profitability, earnings growth, and so forth. Some of the more recent stuff I've been working on that's fun, I've been doing a lot of research

• 2:12Speaker 01

  on the concept of comparing things. And it turns out, right, comparison is actually something that comes quite naturally to us as humans. And it's been a deep study of cognitive psychology for decades. But not surprising that we're not very good at it. So that's another, that's another area where I've been doing a really big deep dive. But more of the same, a lot of work on decision making. But again, thinking about the sweep of things from how are markets efficient or inefficient? Thinking a lot about still issues around valuation and thinking a lot about what makes for a good business and sustainable competitive advantage.

• 2:52Shane Parrish?

  Where have you landed on with base rates? And talk to me about a little bit of the nuances that you've come up with in terms of how you apply them to make more effective decisions.

• 3:02Speaker 01

  Yeah, it's really super. So just to take one step back, the concept here relates to a notion that Danny Kahneman popularized, but it's been around for a while. And he calls it the inside versus the outside view. So the inside view basically says if I present a problem to you, the way we all tend to cope with it is to gather lots of information, to combine it with our own experience and inputs, and then we project it to the future. And almost all problems, you know, we deal with in that fashion. And what psychologists have come along and said is, you know, what you should probably do is start with something called a base rate. And basically asking the question, what happened when other people were in this situation before? And I, and I should mention, it's not a natural way to think, right?

• 3:45Speaker 01

  Because you have to find the base rate and defer to it. And you have to sort of leave aside your own experience and inputs. And we all are sort of slow to discount our own views of the world. So that's the basic idea. And I think there are a couple of things that come out of this that are extremely rich. The first is how you should weight the inside versus the outside view. And the basic heuristic on this is that if there's a lot of luck, a lot of randomness, you should rely exclusively or almost exclusively on the base rate. If there's a lot of skill, you should rely almost exclusively on the inside view, right, on your own experience.

• 4:29Speaker 01

  And actually, most activities in life are between those two extremes, and so you should blend the two in some appropriate measure. Now, what this introduces immediately, if you think about it for a moment, is a framework for not only understanding regression toward the mean, but also quantifying regression toward the mean. You know, you go talk to the investment community, even like in athletics, everybody understands the notion, at least at a high level, of regression toward the mean, but very few people know how to operationalize it, and this actually lays out a very specific framework for operationalizing it. Let me just give you one kind of example to try to make it slightly more concrete. In corporate performance, two measures that are very common for people to look at are

• 5:13Speaker 01

  sales growth rates and earnings growth rates. And it turns out that sales growth rates are a lot more persistent, so you might say more indicative of some sort of underlying skill, perhaps related to the industry and so forth, and hence they're much more predictable. So you don't have to regress growth rates as much as earnings, which themselves are actually not quite random, but quite close to random, where regression happens really, really quickly. So, to me, it's first trying to get your arms around the idea of base rates, identifying the data, but then understanding how to intelligently integrate the inside and the outside view, and again, with this eye to really understanding, not just qualitatively, but quantitative.

• 5:56Shane Parrish?

  How do I find out where I am on this luck, randomness, skill continuum? I mean, as a knowledge worker, I would think that I'm prone to believe, maybe overexaggerate the skill that I'm bringing to the table, and thus I would discount the base rate in favor of my own skill.

• 6:14Speaker 01

  Right, exactly. So, there's a whole range of approaches to doing this. I'll mention that there is a statistical method, so I'll start with something that makes my life easy to explain, but a statistical method to do that. And it's based on a something, a formulation in statistics that can be very useful. And this formulation that says that independent, actually, independent, the standard deviation of independent distribution A squared.

• 6:43Speaker 01

  Plus the standard deviation of independent distribution b squared equals the standard deviation squared of a plus b. So, so basically, it's called like the Pythagorean theorem of statistics. You say, all right, what the heck do I do with that? And the answer is you can apply this, for example, to professional sports leagues. So let's take in this example, say, the NBA, National Basketball Association. You say, all right, well, how would I apply this formula? Well, you actually know what the standard deviation or the variance is of the win-loss records of all the teams in the NBA. So that isn't known. And then you also can estimate through binomial distribution what the league would look like if it were totally dictated

• 7:25Speaker 01

  by luck, right? So instead of the teams actually playing, they just flipped a coin, right? So by inference, you can then back into the variance of skill and see how much skill contributes to the outcomes. And, you know, by the way, you can rank professional sports leagues on this. And not surprisingly, probably, the NBA is the most, let me say it more carefully, the NBA is the sport that's furthest from randomness, furthest from pure luck configuration. And sports like actually ice hockey and baseball are actually quite much closer to, to being random. So that's one thing. Now, you might say, hey, as a knowledge worker, I can't, you know, I'm not getting win-loss records and so forth. There are some other things you

• 8:08Speaker 01

  can do as well. Now, you know, one example is, you know, how predictable is your field? How good are experts at anticipating particular outcomes? How much do experts agree? Because usually, if there's a lot of skill or a lot of, you know, very little luck or randomness, experts will come to the same conclusion about similar topics. So there's some other more qualitative ways to do that, but that would be, those would be some of the things to think about. And I'll also say one more thing that's really interesting that, about organizations. This is my observation. I don't know that I can prove this, but my observation would be usually when you're a lower level worker. Your job actually tends to have a higher skill component, right?

• 8:52Speaker 01

  So you're doing something, you're an accounts receivable clerk and you're collecting accounts receivables, right? We can measure what we're doing is pretty much skill-based. But as you move up through the organization, it's not uncommon for the frequency, the types of decisions you make to go down, but the importances of the decisions to go up and also the luck of the outcomes related to those decisions to go up. What's also ironic, of course, is the remuneration tends to be higher, the higher you are in the organization. So CEOs are often making fewer sort of big consequential decisions than people below them. They are paid more, but also those decisions tend to be more luck-laden, which is really interesting.

• 9:36Speaker 01

  So sort of a funny, funny thought about how, how organizations can work.

• 9:43Shane Parrish?

  Is there also a bigger variance in the types of decisions that you're making?

• 9:47Speaker 01

  At the high end?

• 9:48Shane Parrish?

  Yeah.

• 9:49Speaker 01

  Yeah, I suspect that's the case, right? Because in conceptually, at least someone who is a CEO is making decisions really about resource allocation. And that would be, you know, financial resources, human resources and so forth. So yeah, I suspect there is a lot more variance as you move up. Yeah, which is all really super interesting. And the question is, are the, are the, what you learn at lower levels or as you, as you grow up in an organization, are those things applicable as you get to that senior job? So it's really, it's, these are all super interesting questions.

• 10:23Shane Parrish?

  So when you're thinking about organizations making decisions or maybe senior managers or CEOs, do you find that there's often a process involved in those decisions?

• 10:34Speaker 01

  I think it runs the gamut. And, you know, one of the things that I've always found to be fascinating and actually somewhat disconcerting is that many executives will Say that they and by the way, majority of executives will say that they rely or lean on their intuitions for making their decisions, right? And you know, the definition of an intuition is sort of a sense of what you should do or view of things without really tapping your conscious thinking. And if that's the case, that to me would suggest that there's much more that we can do to improve. That said, you know, in other fields, for example, money management, the business that I've been associated with, you know,

• 11:14Speaker 01

  you you sort of learn to, over time, think about, you know, distributions of outcomes and probabilities attached to those distributions and really trying to think sort of more of an expected value type of framework. So I think it runs the gamut. But, you know, clearly, I think that with a lot of the work by, you know, Kahneman, Traversky, and of course, Dick Thaler winning the Nobel Prize a few weeks ago, has put into sharper focus some of the virtues of thinking about decisions more systematically and, you know, trying to to address or remove some of the biases.

• 11:48Shane Parrish?

  So how would you advise me hypothetically if I was, I had a company, we, you know, we're a Fortune 500 company, we don't really have a decision making process. How do we put one in place? What does that look like? And how do we, how do we use that to get better over time?

• 12:07Speaker 01

  Right, exactly. So, you know, there's, I mean, the overarching theme here would be whether there, and by the way, we should acknowledge at the outset that there's probably a continuum of decision types, some of which are very simple, cut and dried, and there are probably right or close to right answers and there are wrong answers. And other decisions that are inherently probabilistic and, you know, harder to write. I will say that, so I think the broad concept would be, are there ways that we can be systematic in evaluating the goodness? Particular decision, right? So by goodness, you need to really think about two things. One is what are the inputs and what are the measures by which we judge this, right? So in certain applications, that's pretty straightforward.

• 12:51Speaker 01

  For a company, it might be, you know, creating value. It might be for a portfolio manager in investing, it would be creating a more attractive portfolio. But you need sort of good inputs and some measure of goodness. Now, one of the things, so, so, and, and the key is to try to be as systematic about that as possible and, you know, in a sense, write down. So one of the things that's really captured my imagination since we have spoken last was this article published about a year ago by Danny Kahneman and some of his colleagues on noise in the Harvard Business Review. Did you see that article? Do you know that article?

• 13:26Shane Parrish?

  No, I don't think so.

• 13:28Speaker 01

  So here's the basic idea. You know, Kahneman obviously is renowned for, and so, right, renowned for his work on heuristics and biases. This idea that it goes to life with rules of thumb that are incredibly time-saving and by and large, pretty accurate, come with inherent biases that lead to suboptimal decisions. So that's fine, and hopefully everyone's got the memo on that. This newer work actually is a somewhat different, of a somewhat different ilk. And he says, you know, it's, so, so I should probably give an example of it. So they, so they went to a large insurance company and, you know, and these guys, these firms typically have, for example, insurance adjusters, people who will settle your claim if you make a claim. And, you know, they're used, you know, they're trained the same way, they have the same

• 14:13Speaker 01

  software, you know, basically you should have expected, maybe not perfectly interchangeable, but these, these, these folks should be basically doing similar jobs, similar tasks, and should have similar outcomes. And so what they did is they gave these people a claim, a set of facts. And they first went to their managers and they said, hey, you know, how much variance do you expect in these outcomes, right? Again, playing the same way, same software and so forth. And the manager said, you know, a priori, you know, five to 10% variance. Some people have good days, some people have bad days, right? But there'll be a little bit of variance, but pretty tight, right, for the most part. When they got the numbers back, they found

• 14:52Speaker 01

  the variance between 40 and 60%. So people were just completely inconsistent in applying the basic rules and the basic algorithms. So economists come to call this noise, and it's this basic idea that even when there are systematic ways to do things, as humans, we often don't stick to the script and there's a huge amount of variation. So that would be something I would really want to examine in organization, and that's from top to bottom, is if there are systematic processes that make sense, or different levels of decision making, can we identify those, can we articulate those, and now perhaps most importantly, can

• 15:33Speaker 01

  we make sure that our employees queue to those? And you know, there is a series of papers that came out of Wharton that I thought were awesome about algorithm aversion. You may have seen these. And the basic idea was that as human beings, we tend to be quite adverse to sticking to a simple algorithm. And in fact, the algorithm goes wrong, we get very upset and very dismissive. And it turns out, they said, there's a way to overcome this, which I think makes enormous amounts of sense. And they said, the way you overcome this is you say to people, your first answer is going to be what the algorithm tells you, right? Just apply the algorithm. And then we'll allow you to introduce a little bit

• 16:18Speaker 01

  of judgment. You can tweak the response. They said, it doesn't matter how much you let them tweak it. They can tweak it just a tiny amount. But you could tweak the response. So then there's a sense of volition that humans involved in some way, shape, or form. But you do stick closer to what is ultimately a better solution. So this idea of algorithm aversion and, you know, being systematic, I think that's, that would be the approach that I would try to take if I were starting with a clean sheet of paper in any organization.

• 16:45Shane Parrish?

  What sort of things would you incorporate into that process? Would you have a checklist sort of?

• 16:53Shane Parrish?

  That level of formulaic systematic process where like what are the base rates? Or would you have more intuition based where people are feeling but the process is generalized but outlined, but you kind of feel your way through it?

• 17:09Speaker 01

  Yeah, I think that, well, you probably know where I'm gonna come down on this, but it depends a little bit on the activity. But I think checklists are really powerful and checklists are mostly, I mean, I think that most people don't like checklists because they feel strained to some degree. But what a checklist does is compels you to make sure that you, you know, you've covered all your bases. And certainly the lessons we've learned in medicine for checklists have been extremely powerful. I think that the applications should go beyond that. Now, you know, intuition, I think we've talked about intuition before, but I mean, the key to intuition is that it exists, it can be very powerful, but we have to be very careful about where it applies.

• 17:51Speaker 01

  And I think the general rule is intuition can be developed in realms that are stable and linear. So if there's a repeated pattern and things don't change that much, you can train your intuition, you have to train it, but you can train your intuition, it can be very powerful. So, you know, the canonical examples, obviously chess players and, you know, grandmasters are amazing, their ability to chum, their ability to see what's going on quite rapidly. But, you know, it should be noted that it's not some sort of superpower force of these grandmasters. If you change the rules of chess or change the size of the board, all bets would be off and they'd be back to square one.

• 18:32Speaker 01

  So, yeah, as you know, I probably, I probably tend toward the more structured. Now, all that said, right, you need, there are many things in life that do change over time, so they evolve over time. So you gotta be careful about getting too rigid. And having a mismatch between your decision processes in the environment. So there is that that blend as well.

• 18:56Shane Parrish?

  Let's talk about intuition for one second there. How do we develop intuition? I mean, I'm thinking about myself in the context of working for an organization. And I have all of these people around me who might be domain experts and they have really good intuition in their particular domain. How do I acquire a better knowledge of that domain? So one like, how do I improve my intuition in other people's domains?

• 19:18Speaker 01

  Yeah, I think that's a really interesting question. Once again, I think that, you know, there's, there's a, you know, there's just some great quotes on this that, you know, just because you've been doing something for a long time doesn't mean you're an expert, right? So, so I think we should first be very, um, I don't know if skeptical is the right word, but we should just be careful about, you know, suggesting people have domain or don't have domain expertise. That said, um, you know, to me, again, there are sort of two conditions. By the way, there was a great paper written by Danny Kahneman and Gary Klein in 2009. You know, and, and the history was really interesting because Kahneman was obviously of the belief that people are subs can be suboptimal in their decision making or they

• 20:02Speaker 01

  have these biases and Klein was, you know, sort of celebrated the notion of intuition and how intuition could work. And, you know, they're both very thoughtful, respectful guys and they said, you know, maybe we should try to work together on something and see if we could find some common ground. And I think the common ground that they came to, which I think makes sense, is that expertise intuition applies or expertise applies when you have this sort of stable regularity in the, in the, in the domain itself and where you're trained with really quality feedback and accurate feedback. So I think it's those two dimensions is A, it's going to be to some degree domain specific and B, it requires training. And that goes back to, you know, the Anders Ericsson work on.

• 20:46Speaker 01

  You know, I don't want to say 10,000 hours, but basically deliberate practice, right? So deliberate practice being, being at the boundary of your capabilities with quality feedback to improve. So, you know, can you sort of look over somebody else's shoulder and acquire their domain expertise? I think the answer is actually probably not, unless you are willing to dedicate some amount of time to, to getting trained and, and through deliberate practice, which is a non-trivial, which is a non-trivial thing. So, um, yeah, no, it's interesting. And then, and again, the, the degree to which you should rely on others also is a degree to which, again, those two characteristics have been satisfied, right? That it's a fairly stable domain and, and they've been trained effectively.

• 21:32Shane Parrish?

  I want to dive into that for one second. I mean, we improve through deliberate practice. Someone can't run a, you know, someone who can't run a few miles can work at it and get a little bit better. There's this feedback loop going on, but I want to talk about knowledge workers. Say I'm a manager, maybe a portfolio manager, maybe a people manager in an organization. Let's also say I'm above average in my performance, but I, I hit a rut and all of a sudden my performance is worse than normal. I'm underperforming. This is normal. It's natural. I mean, it happens, but at the same time I feel smarter and better because I'm always learning. But history is replete with people like me being stubborn or lacking humility and missing a big change.

• 22:15Shane Parrish?

  Uh, how do I know I'm not one of these people? Like, how do you measure whether you're in a typical trend or you've lost the skill advantage? In his book, Ed Thorp talked about card playing and how he hit a rut, but as long as there was, he was consistent with the odds, he knew he was fine because cards are a physical system, but managing people is more of a biological system. So this type of analysis isn't as relevant. How would you kind of advise me?

• 22:43Speaker 01

  Yeah, you know, so Shane is such an, I mean, I, you know, I don't know really what the answer to that is, but it is an interesting, um, and I think a little, a little bit of what Thorpe was saying, you know, would apply or some of those lessons might apply. And, um, you know, I think one of the observations we can make is if you are operating in this completely skill dominated domain, outcomes are all you really Need to know about, right? And so to your point, if you're performing well or performing poorly, that's almost a pure reflection of your skill. And in those domains, uh, it's easy. But as you get into things that are more, uh, as you mentioned, you know, maybe luck laden or, uh, biological, so they're going to be much messier.

• 23:25Speaker 01

  You do have to go back and default to understanding the process. And, you know, with some sort of faith, a good process will ultimately lead to good outcomes. So the simpler case in that realm would be the Thorpe story, right? Where you know that, um, there's, there's a, you're making bets with a probability and there can be stretches where, uh, you just have bad luck, even though you're making the right decisions in your process. Um, but when you talk about managing people, it becomes altogether, uh, that much more difficult, right? Because we don't really, don't really know exactly how the system is, and it's certainly not a physical system. So, I mean, part of that would be to me, um, is, is to, is to think about or revisit your process, um, periodically.

• 24:08Speaker 01

  And again, one of the important ingredients to improving process over time is trying to get feedback. And the challenge is, I think, that the, the thing you're trying to manage, the thing you're trying to, uh, game your plan, let's say it that way, the rules can be changed, can change. And, and as a consequence, you probably have to, you have to probably evolve. And, you know, the, the, a great example of that is in markets where markets, as a market practitioner, you have to be very process oriented. But, um, you know, and like there's, and so that means that there are some elements of markets that are, uh, immutable, some principles that probably carry throughout any environment. But there are a lot of ideas that are mutable, that change and evolve.

• 24:52Speaker 01

  I mean, our economy evolves, the characters evolve, um... Relationships between nations evolve and those are things you just have to take into consideration. So I don't know if there's an easy answer to that at all, but I do think you have to be very process oriented and I do think you have to think about the domain, whether that's changing. You have to think about trying to gather and implement whatever feedback you get to make sure that you're aligned with what will lead to success in your domain.

• 25:22Shane Parrish?

  I'm curious about your take on the concept of invariant strategies or invariant ideas, something that never steers you wrong, no matter the environmental changes, sort of a go-to, always on by default. Do you have any of these in your head, whether it's life or business?

• 25:40Speaker 01

  Yeah, I mean, I think that when I think about, you know, I would just step back and just think about evolution and what is evolution trying to do? And really, it goes back to Dawkins, right? I mean, it's propagation of genes to some degree. So it's basically living to see another day and living, basically, right? So strategies to propagate certainly would be a big one for that. And yeah, and you know, in money management, there probably would be a few things that are really important. One is, and then I would say, close to immutable, if not immutable, one is that the value of usually a business, but really a financial asset is the present value of the cash that it generates. And, you know, it's hard to

• 26:21Speaker 01

  get away from that ultimately being case. And that has always been true and I think it will always be true going forward. Second is while it's extremely difficult to characterize, there should be a general relationship. Is the sure something is, the less you get paid to bet on it and the less sure it is, the more you get paid to bet on it. And, you know, the very simple metaphor is the horse race, the track, you know, so the favorite should get paid less if you bet on the favorite than the long shot. And that's probably pretty close to immutable. So there are some of those principles like that. So again, evolution

• 27:01Speaker 01

  is a big one. But again, the cast of characters tends to change, the circumstances tend to change. So how you would evaluate those things might change quite a bit. And you think about from an evolutionary point of view, right? There are some ecosystems that are extremely stable that encourage a certain kind of ecosystem development and then there are other ecosystems. Systems that change really rapidly will allow for success and propagation. That environment could be quite different, right? And this all ties back to things like how much, how much as an organization or even as a species, you should trade off between exploitation, which is basically doing the same thing you've always done and taking advantage of it, and exploration, which is seeking new domains, new ideas and so forth.

• 27:47Speaker 01

  And those trade offs, again, probably conditional on the rate of change in the environment. But, but that, that idea of how much you need to explore, how much you need to spend on R and D, that's also probably something that you can see almost everywhere you look.

• 28:00Shane Parrish?

  How do you determine the rate of change in your environment?

• 28:04Speaker 01

  Yeah, I mean, I think that, um, I'm sure there's an ecological answer to that. That's, uh, much more rigorous than anything I could come up with. But, yeah, I mean, I think that, uh, for example, in the world of business, you know, so, so, you know, in the world of business, I think there are some things that we can do to try to measure that. Um, I'll, I'll mention some of the tests that we use, um, that may be useful. One is a straight up entry and exit, um, data. So, you know, you're looking at a particular industry and the question you want to pose is how many companies come into it? How many companies leave? And all things being equal, higher entry and exit would be a less stable, uh, more changing. We look at a measure called, uh, market share change.

• 28:45Speaker 01

  So we look at all the participants over some period of time, say three years or five years. And then we look at the absolute average market share change, right? So whether you've lost or gained becomes a positive number, but at that average. And all things being equal, if that number's higher, that means there's a lot of market share moving around. If that number's low, uh, that means it's relatively stable. So that's another, uh, rough proxy for it. The third thing we do is we look at something called profit pools, which is, you know, basically a breakdown of how much each company makes. And we see how that changes over time. So those, at least in the world of business, those might be some high level proxies for people that rate change.

• 29:25Speaker 01

  That can be pretty helpful heuristics. And again, you don't want to pay for a, you know, huge amount of competitive advantage. In an industry where there's a ton of entry and exit, where market shares are very volatile. And by contrast, you might be much more willing to pay for franchise value. For an industry where market shares are very stable, where, you know, entrance and exits are very scarce and so forth, right? So that that will be from an environment, from a corporate point of view, might be one way to think about that.

• 29:55Shane Parrish?

  How have your your thoughts on algorithmic kind of decision making progressed over time? Last time we talked, I think we talked a little bit about AI and I think you called it the expert squeeze. Where are you on that these days? Do you think AI is going to take over ground more quickly or perhaps less quickly than most people think?

• 30:14Speaker 01

  Um, yeah, well, I think it's incredible. It's incredibly wide open. Um, I think that we can continue as societies to continue to apply more of these kinds of concepts. So there's there's applicability. But, you know, all this also gives me a little bit of a little bit of pause. And I guess the thing that concerns me the most, if you can imagine, almost like a little three by three grid. And in the various columns, you would put, you know, business, government and academia. And then in the rows, you might put something like, you know,

• 30:55Speaker 01

  access to resources, access to data, and then maybe incentives, right? Those three rows. And then just fill them out in a way that you think would make sense. And I think if you do that, what you probably would find is the access to resources and the access to data is probably greatest among a certain handful of businesses, companies, actually.

• 31:22Speaker 01

  And those are companies you could probably name right off the top of your head. And then the question is, what are the incentives? And whereas in academia, the incentive might be, you know, to write some really cool paper and to get citations and so forth. In government, it might be to obviously try to govern effectively and do the best for the most people. For business, the incentives might be sell more ads, get more people to click on my page, right? Something like that. And those might not be, um, there's a question as to whether those are ultimately great societal goods. So, so that to me is something that gives me a little bit of pause in all this.

• 32:03Speaker 01

  The second thing I'll just say in general, because I come at the world from the point of view of markets and, and, uh, you know, there are, there are areas where applications of algorithms are incredibly effective. Again, goes back to these sort of more stable environments or predictive environments. But you have to be very, very careful about, um, systems that are changing. You know, the fancy term for it's non-stationarity. So the statistical properties and underlying systems change over time. And that's another concern I might have, and we see it a little bit up in finance, it's this concept of overfitting, right? So you have these data, you can match history beautifully, uh, but you fail to anticipate that the world itself is dynamic and so the rules that worked in the past may not work

• 32:47Speaker 01

  in the future. So, um, yeah, I mean, overall, I would say probably I'm a technology enthusiast. I tend to be an optimist, rightly or wrongly. Um, but there are some aspects of all this that give me pause and, you know, this sort of this idea of the incentives, who's got the resources, data, and what are their incentives? I guess is the thing that gives me the most, uh, most concern.

• 33:09Shane Parrish?

  Do you think we ever end up in a situation where, um, the data just becomes this insurmountable advantage?

• 33:16Speaker 01

  Yeah, I mean, maybe there already, I don't know. Um, you just think about, you think about the amount of data that some of these large technology companies have, you know, the ones that come right to mind, of course, would be Google and Facebook and amazon.com. It's staggering and, and it doesn't seem to be a lot of, um, slowdown in the momentum of a lot of those businesses. Now broadly, those things generate Huge amounts of value, right, for a consumer. For Google, it gives you a huge amount of value. I don't know that I could go through a day without deferring to my Google searches, which I use all the time. You know, Amazon, great value, Facebook, you know, societal value.

• 33:56Speaker 01

  So there are a lot of good things with this, but again, the amount of data they can capture, and because all those companies have substantial resources, they can put a lot of resources against not only capturing but analyzing data. Yeah, it's an interesting flywheel, right?

• 34:11Shane Parrish?

  Do you think that that should be a public good? Like, maybe hypothetically, these companies should be forced to release data that's anything over six months old, so we can encourage people to compete?

• 34:25Speaker 01

  I've never thought about that. I don't know. Yeah, I mean, I probably would be inclined to think that's not a bad idea, but I just haven't thought about that. I don't know.

• 34:34Shane Parrish?

  Let's go back to your work on the, you're on the Santa Fe Institute, you're the head of the board of trustees. How did you originally get involved with complexity research?

• 34:44Speaker 01

  So in the mid 1990s, I went to a Baltimore Orioles baseball game, and my host was Bill Miller, who preceded me as chair of the board. And, you know, Bill is a very interesting guy, very eclectic reader, and he had read a bunch of articles and had been out to the Santa Fe Institute and said, you know, this might be a place that would have an appeal for you. I ended up working with Bill a few years after that. And at the time, I was reading a lot, you know, I was just reading a lot, but I was reading in particular a lot of science and biology and evolution, and I was very keen to understand the intersection between economics and biology.

• 35:26Speaker 01

  I was also doing a lot of work on, you know, competitive advantage. And in particular, the theory that got me sort of first roped in was work done by Brian Arthur, who sort of ran the first economics program at SFI. And Brian has this idea of something called increasing returns. So we're taught in economics, microeconomics, and by the way, still largely true, that returns on incremental capital tend to migrate toward the cost of capital, and typically the reason for that is competition, right? If you're generating, Shane, massive excess returns, I'm going to come in and compete with you and compete those, whittle those away eventually over time. Brian laid out a situation, a set of circumstances where returns actually may not

• 36:11Speaker 01

  regress toward the mean, they may actually be repulsed from the mean, increasing returns. And it was a sort of a heretical thought in the world of economics, right? He was sort of shunned a little bit for this point of view. But it was based on a lot of this, what now seems to be more mainstream, but at the time very nascent work on networks and network effects and those kinds of concepts. So I went out there and probably a little more than 20 years ago, and from the very first meeting there was, in all, the whole thing. And as you probably know, SFI was founded in the mid 1980s by a slew of very prominent scientists, many of which had Nobel prizes, who felt that much of academia had become siloed.

• 36:52Speaker 01

  And so people were speaking to one another within disciplines, but that many of the most important investing issues that are scientific and really our world face were at the intersections of disciplines. So it was set up as an institute that was meant to break down disciplinary orders and have people of different disciplines speak with one another about problems that are common. And the unifying theme, if there is one, is the study of complex systems. And complex systems, I think we can articulate fairly simply, which is, you know, independent agents, which could be neurons in your brain, or people in the city of New York, or ants

• 37:32Speaker 01

  in an ant colony, allowing those to interact with one another and observing and understanding the systems that emerge from that interaction. And so absolutely fascinating stuff, and I've learned so many important lessons that apply both to science and also the world of business. But perhaps most importantly, for me at least, it's an extraordinary community in the sense of massive self-selection for People who are intellectually voracious, willing to go across intellectual boundaries, just wide minds wide open, which is really fantastic. So, we actually have our board meeting coming up this weekend.

• 38:16Speaker 01

  It's the beginning of November and I'm really always excited to go out there. And we're going to be talking actually about intelligence and the application of intelligence. It's one of our themes. So, yeah, very, very influential, continues to be very influential. And in my 20 years of involvement, it's been a really important contributor to my intellectual development.

• 38:38Shane Parrish?

  You do so much. So, you're on the board, you have a full-time career in finance, you're a prolific kind of author and researcher. How do you, how do you balance all of these different demands?

• 38:51Speaker 01

  It doesn't feel like I do very much, actually. No, I, I, there's no, there's nothing magical about it. I think that is, is the nature of the work that I've been able to do over the years, I've been, I've been blessed with the opportunity to allocate a fair bit of time doing research and, and being able to write. And, you know, it's, it's really fun for me. I like to think about it as input and output. And that's, by the way, really the essence, I think, of teaching or quality teaching. So, I, I've been able to have this balance between learning about things and inputting and, you know, especially being able to follow a little bit of, of what I find to be interesting. And then output, which is communicating it, you know, certainly within our organization

• 39:35Speaker 01

  first, but also and more broadly. And, you know, I'm a big believer that the notion of synthesis and being able to write and speak reasonably intelligently on something is actually an indication of understanding or first step toward understanding, let's say it that way. And I just had this sort of lucky, a lucky ability to, or life that I've been able to pursue some of these things. I also, I think Shane, we may have talked about this before, but I think it's also important to, to always recognize, and I think this is true for you as well, so I can't speak on your behalf, but I think I'll speak on your behalf, which is, you know, a lot of this time allocation.

• 40:09Shane Parrish?

  Yeah.

• 40:10Speaker 01

  Whereas I, I really enjoy reading books, I get a lot from it, I spend a lot of time doing it, that's, I'm not watching TV much, right? I don't, if you talk to me about popular TV show series or something, I don't know what's going on. And that's not great. I mean, you know, there are Game of Thrones, I've never seen an episode of Game of Thrones. About it, so uh not that I'm proud of that, but that's a trade off that I've decided to make. So when you focus on sort of the output results, uh it's important that I acknowledge that there are some things that I there are many deficiencies that

• 40:44Shane Parrish?

  Yeah.

• 40:45Speaker 01

  should be underscored.

• 40:47Shane Parrish?

  I've never seen an episode of Game of Thrones either.

• 40:49Speaker 01

  Yeah.

• 40:50Shane Parrish?

  I think we're in the same boat there. Do you think in the all the opportunities that you get, do you think about them from an opportunity cost lens? How how do you how do you think about that?

• 41:01Speaker 01

  Yeah, I do a little bit. I mean, I think that, as you know, time is really our most scarce resource, so trying to be thoughtful about allocation of time is always useful. But um to some degree, um and again, it's part of it's just I've been very lucky in my career and who I've been able to work with. In some degree, there's been a remarkable overlap between the kinds of things that I'm interesting interested in and the kinds of things that um I can actually do from a professional point of view, like festival to generally, right? So that's been, to me, that's really been a lifesaver. So there's not, it's not like um uh I'll even, by the way, even all the stuff that I read outside of work, um I I can't

• 41:43Speaker 01

  I I can't ever view that as separate from my work, right? So basically, everything that goes into this mix um is part of the part of the overall uh thinking and partly overall output. So, yeah, I mean, um uh so, yeah, and we say opportunity cost, right? So like not not watching Game of Thrones is probably an opportunity cost. That's a trade off I'd be willing to make. But um I also think it's not, these are, you know, I I it's not for everybody and as the way I live my life is not for everybody, should just always want to be clear about that. There's no uh claim of superiority or anything like.

• 42:19Shane Parrish?

  I think we might be the only two people on the planet who've never uh watched Game of Thrones and we're talking to each other right now. You're a prolific reader. I have a lot of reading questions for you. I mean, I have to ask, of course, what are a few of the best books you've read since we've chatted last? Are there any that have changed, you've changed your mind on significantly?

• 42:41Speaker 01

  Yeah, I mean, I think that even this year has been, I've really found a few books to be really terrific. Over the summer, and by the way, I think it's, and I always forewarn people on this, I think it's a very big commitment. But over the summer, I spent a lot of time reading Robert Sapolsky's new book, Behave. And did you read that, by the way?

• 43:01Shane Parrish?

  Uh, I haven't read it yet. I did a skim of it already, but...

• 43:04Speaker 01

  Yeah. So I think Behave is, I don't want to be too hyperbolic about it, but I think it's probably the best book I've ever written on, read on human behavior. And, you know, Sapolsky himself is a, is obviously a really terrific scholar, but he's a brilliant communicator as well. It's a slog, though. It's 700 pages and it's a lot of work and it requires some commitment. But it starts really with neuroscience and goes everywhere from, you know, neuroscience up to culture. And basically everything in between. And I think when you read a book like that, when you put that down and really contemplate it, it makes you really circumspect about a lot of things, about, you know, people's behaviors, by your own behaviors, how we fit into societies and so forth.

• 43:49Speaker 01

  So Sapolsky's book, Behave, I thought was epic. And again, it's not, it's not something you can just dip in and dip out of. What I'd recommend if someone goes away on holiday or whatever, is to allocate a couple hours a day for a week or so and really get into it. Earlier this year, one of my Santa Fe Institute colleagues, Jeffrey West, published a book called Scale. I find this work to be among the most wondrous research I've ever seen. The principle of scale is, there's a, there's a relationship that's been well understood in biology for a long time, which is if you plot the mass and metabolic rates, basically mass and energy usage of, let's just use something simple, say mammals,

• 44:32Speaker 01

  and you do it on a logarithmic scale. So that's, the key is not 1, 2, 3, 4, 5, but rather logarithmic means that each tick mark is the same percentage difference. So 1, 10, 100, 1,000, and so forth. So you plot it on a logarithmic scale. And then you plot where each mammal is. It follows a perfect line. On a logarithmic scale with a three quarters exponent. Amazing, right? So you tell me the mass of a mammal, I can tell you that mammal's metabolic rate. Um, precisely. And I can tell you a bunch of other stuff as well. So that's been known empirically for a long time, but, but it turns out that Jeffrey West and some of the other colleagues at Santa Fe Institute, Brian Anquist and, and Brown, came along with a theory to explain that, Jim Brown. So a theory to explain that.

• 45:17Speaker 01

  And it's actually really cool. And basically the simple version, I think, is energy dissipation in a network. They really figured out the math and so forth. Jeffrey then extends that work from biological systems to social systems. And we see very similar, uh, there are different mechanisms, but similar patterns for social systems. For example, cities follow these scaling laws. Uh, corporations follow these scaling laws. Uh, not exactly the same mathematical relationship, but also scaling laws. And there's some really, really fascinating sort of, uh, research on this and some conjectures as to what those things mean. So, uh, Scale by Jeffrey West. By the way, uh, here's my little cocktail party statistic on, uh, on that, which I

• 45:59Speaker 01

  find, I find this really, um, both fascinating and also frightening. Um, if you plot humans on that mass metabolic rate scale, um, humans should use about a hundred watts a day. So, you know, what it takes to sustain your basic metabolic rate, what it takes to sustain you is about, uh, what it takes to power a light bulb, right? Um, but it turns out that, uh, in, in, in the United States, I think it's probably true for North America, but the United States, our average, uh, energy usage is 11,000 watts per day. And around the world, it's 3,000 watts per day. So why, why is it so much higher? Because we've harnessed technology to allow us to deploy much more energy than each of

• 46:43Speaker 01

  our bodies require. So saying that differently is our energetic footprint is 30x our mass. And, uh, so that would be saying instead of having seven Billion people, we have two hundred ten billion people in the world, right?

• 46:59Shane Parrish?

  Right.

• 47:00Speaker 01

  And so it's a question that's really interesting is, um, does, uh, how long will Mother Nature put up with that, right? And will Mother Nature, uh, put a stop on that? That's really interesting. And then, um, a third book on, by the way, I mean, I, I liked, I really liked the F four book. I like the first part better than the second part. I really enjoyed, uh, Andrew Lowe's book, Adaptive Markets. But maybe the next book I would mention that I thought was interesting was, um, Peter Godfrey Smith's book called Other Minds. And the book is actually, um, and he's a philosopher by training. It's really about consciousness, but he does that through the lens of, um, octopus, the octopus intelligence. So it's a really, really fun read.

• 47:42Speaker 01

  You learn a lot about, uh, octopuses, um, but also about the notion of consciousness and, uh, sentience and so on and so forth. So that, I thought was a really fun book, but I think, um, I don't read as much as you do, but I think I'm around, had around twenty-five or thirty books for two thousand and seventeen. Those are some of the ones that I found. I mean, there are lots of other ones that I really enjoy, but those are ones that come to, come bubble to the surface.

• 48:05Shane Parrish?

  Talk to me a little bit about the Jeffrey West book, uh, in terms of taking linear and nonlinear thinking. How, how can we apply that to day-to-day life?

• 48:16Speaker 01

  Yeah. So one of the things that Jeffrey and his colleagues found that, um, is really interesting is that for, for example, cities, that when they broke down some of these relationships, they found sub and super linear scaling. So what does that mean in plain language? Um, so sublinear scaling basically is an indication of economies of scale. So for example, if you look at cities of different sizes, as they get larger, they tend to use the physical infrastructure more efficiently. So you need fewer, you know, miles per road per person or, uh, you know, distance of pipes and electric wires and so forth, right? So cities like larger beings tend to be more efficient, um, as they get larger. So that's the sublinear scaling, economies of scale.

• 49:02Speaker 01

  What they also found was super linear scaling, which is some things grow faster than linear. And those are things that are good, for example, patents. So larger cities tend to be more productive from an intellectual capital point of view than smaller cities. But it also applies to things that are negative, for example, crime and things like that. So I think that these guys are starting to make some headway in understanding these various properties of, and in this case, cities. Corporations, by the way, you know, we're early on in that, but above, both, by the way, for animals, for biological systems as well as social systems. This idea of economies of scale seems to pop up in both, well, both particular instances.

• 49:46Speaker 01

  So, so the, you know, the cell of an elephant or a whale is working substantially less hard than the cell of a mouse or a shrew, something like that, which is really, they're the same mammalian cell, of course, but they're, they're, they have different, they work very differently. So that, those are interesting ideas. And then Jeffrey, you know, I think that this, all this work ties back ultimately to things like innovation. And, and we, how, how do we, how, how have we been able to harness so much energy as humans, right? Mostly via technology. But in a sense, we have to get better and better at innovation in order to sustain the growth that we've been able to achieve over the last few hundred years.

• 50:29Speaker 01

  And, and, you know, I think there's, like I said, you know, will Mother Nature put up with this? We'll see, but there might be a limit to how much we can continue to grow through innovation. And, you know, that, that would be, you know, I don't think it'll be within our lifetimes we have to worry about anything, but over the next couple hundred years, there might be some, some challenges. And one of the ways that may manifest, for example, might be something like just a population reset. In other words, there may be some tragic event, whether it's war, disease, propagation, or something that resets the human population to, to a more manageable level. It's a cheery thought.

• 51:04Shane Parrish?

  My next question, what book do you give away the most to other people?

• 51:14Speaker 01

  You know, usually the books that I give away are, it's usually a little trio. See Pinker's book, How the Mind Works.

• 51:25Speaker 01

  Bill Wilson's book, Consilience.

• 51:27Shane Parrish?

  Hmm.

• 51:28Speaker 01

  And the third book is The Metaphysical Club. So those tend to be the three books that if you said to me, and I usually give those to younger people. They're a twenty year old kid, those are the three.

• 51:40Shane Parrish?

  How do you go about reading? Like, when you pick up a book, do you read cover to cover? Is there a process? I know you, there's probably a process well thought out behind this. Like, how do you do this?

• 51:52Speaker 01

  I say, go to the Farnam Street blog and read the section about how to read a book. No, I think that the Adler, the Adler stuff is really how you should do it. And I do some of that.

• 52:03Speaker 01

  I don't do it as systematically as I should. I usually do read things from cover to cover. I will periodically read part of a book and put it down. But for the most part, I try to pick stuff that I like and I usually will try to get through it from cover to cover. And I don't know if you find this as well. I do find that there tend to be ebbs and flow in my reading pace. So there'll be episodes, weeks where I'll read, I'll really read a lot. Part of that might be the content that I'm going through. Part of it might just be how my schedule works and so forth. And other weeks where it tends to be much slower. I try to be consistent about doing something all the time, but it does speed up and slow down.

• 52:44Speaker 01

  And I do, there are certain books where I will just do a sort of a heavy skim to make sure that I have some sense of the content and hopefully can remember if there's something in there that I should refer back to. So I won't read the whole thing. But for the most part, I do read things cover to cover. And yeah, sometimes I regret that. But for the most part, I don't mind doing that.

• 53:07Shane Parrish?

  Do you keep all the books after you read them?

• 53:10Speaker 01

  I do. It's becoming a sore spot because I don't have any place to put them anymore. So I'm going to probably have to some point get rid of some of them. But, and I have books primarily in two places. One is my home office and one is an office that's outside of my home, a work office. And they both probably have now, I don't know, fifteen hundred or two thousand books. So I don't, it's not like a crazy book collection, but probably three or four thousand altogether. And I always feel very, very comforted about sitting in the middle of that pile, those piles, those shelves, right? Because I always feel like I have access to just a lot of, it's almost like they're friends, but a lot of. Knowledge and resources and I always feel great being in the middle of all that so um.

• 53:55Speaker 01

  And and there will be days where if I'm between meetings or I have a few minutes. Um I just might walk over to a shelf and pull a book off I haven't seen in a while and just flip through it and say is there any you know. Re- make myself an old friend and say is there anything in here that I I should probably be paying attention to because as you know. Especially very good books when you go back to them. Uh you know with with new with new a a new point of view and new knowledge. They're they they they're gifts that continue to give right there you can always take something new from them which is which is awesome.

• 54:25Shane Parrish?

  How much time do you spend reading new ver- books versus rereading uh older classics?

• 54:31Speaker 01

  Mostly new probably ninety ten ninety percent ten percent but I but um I that I I can. One caveat to that is that when I am researching so when I'm writing. Almost always that will encompass going back to things that I and that that actually may not just be books might be academic articles. But that does require circling back around so so maybe it's higher if you did it that way but but pure like. Books off the shelf what am I you know uh what am I actually reading what's on my nightstand it's gonna be ninety.

• 55:02Shane Parrish?

  Is there a spot where you read or time of day that you're most comfortable in?

• 55:06Speaker 01

  No the no I I usually evenings uh at home uh we'll do that anywhere basically in the house um. And then a lot on the weekends and usually weekends are a fairly simple routine part of that um. You know we my wife and I have five kids um almost all of them out of the house the one that's at home is now in high school so. That creates a lot more flexibility than I know with people with younger kids and so forth but. Uh on weekends that's a you know very typical thing for me is to get up on the earlier side of things come come downstairs it's quiet. Uh make a make some coffee and just go at it for a few hours in the morning and that's great so it's you know it's quiet it's comfortable. It's the morning I I tend to be more of a morning person than an evening person personally so.

• 55:50Speaker 01

  That's that's where I can get a lot of the best reading done so weekends big big on the weekends a lot of weekends.

• 55:55Shane Parrish?

  Are you the type of person who goes to bed early or just the type of person who rises early?

• 56:03Speaker 01

  Uh you know and and I think we may have talked about this before um one of the things that I have become quite religious about is. Sleeping and um it it I find it helps me on so many different levels. So um I you know, I I I probably go to bed at a big normal time and get up at a big normal time. But I try to be very religious about eight hours. For me, eight hours of sleep a night is really, really good. And you know, there's some nights where I'll sneak by with seven, seven and a half hours. But I really try to be really religious about sleeping and that that just just washes over so many other aspects of my life. It affects my exercise, it affects my diet, it affects my productivity. And I just find if I if I sleep, I can do those things much better than if I don't. So and and I think that's how many people under I still think, I know there's been a ton written about this.

• 56:49Speaker 01

  But I still think people don't understand how important it is to sleep. And it's often the case that, you know, one, one less hour doing something else and one more hour of sleep. You're gonna be much more productive in your in your other activities.

• 57:00Shane Parrish?

  What have you learned about what contributes to your sleep quality?

• 57:05Speaker 01

  It's usually um probably very common ingredients, right? Which is um I also am a big believer in exercise and moving, so exercise helps a lot. So um I I will always sleep better, almost always sleep better on nights where I've exercised and the nights where I don't. So the more night, more days I exercise, the better I'll have to be. Diet's very important too, so try not to eat too much, try to eat qual- quality stuff. I um I I don't not drink alcohol, but I drink very little alcohol. That also probably helps. So I very rarely will I have more than one drink in a day, something like that. So those are probably the things that contribute it. And I've never had a problem sleeping. Um so uh but those probably are contributing uh factors.

• 57:47Shane Parrish?

  Yeah, I would say you've got a firm grasp of what derails most people. Why don't you describe a time that you failed? Um and I I'm interested in the situation in which you you failed through a personal mistake. And then not only how you recovered and got out of that failure. But how did you go about learning from that failure?

• 58:11Speaker 01

  Yeah, well, probably my uh, you know, the episode that I think of as the greatest failure was right when I got out of college. Um I was in a training. Program for investment bank, which was terrific, by the way, and I learned a lot. And it was a year and a half long. And then that put us into our first jobs. And these were, we're now called financial advisors, but basically stockbrokers. And so I was given a job as a stockbroker. And this, by the way, was early 1988. The firm I was with, Drexel Burnham, had gone through a bunch of legal issues. It was obviously in the heels of the stock market crash. So the environment may not have been ideal, but I was so ill-suited for that work.

• 58:56Speaker 01

  And so I, you know, I gave it a try, but I was miserable and I was certainly a big failure in doing that job. And, you know, essentially, I mean, I don't think I formally got fired, but basically got fired, right? Basically, there was a parting of the ways between the firm and me. And that made sense, by the way, on many levels. And so, you know, maybe the silver lining and all that, maybe there are two things that came out of that for me that were really important. The first was that having gone through the training program, and this is why I'm forever grateful for that training program, we were exposed in our program to lots of different parts of the bank. And that allowed anyone who was there to understand sort of where they felt most comfortable, where they felt they could add the most value.

• 59:39Speaker 01

  So we were on the trading desks and we were in investment banking and we were in research and in operations. So, you know, it was a great opportunity to see where you fit, see where your skills and interests would align with what the organization was trying to do. And by the way, from that, I realized the kinds of things that I thought I could be more effective at. And then the second lesson was learning precisely what I'm bad at. And, you know, part of it was, I'm a natural introvert. That job, I think, was much better suited for an extrovert. I was in sense, selling products that I had nothing to do with creating, so I had no real competence in the underlying products and so forth.

• 1:00:21Speaker 01

  So I just learned a lot about what made me uncomfortable, what made me ineffective. And those were lessons that I, uh, by the way, there were some positive things because they taught you a lot about sales and, and, and how to sell things and some of those lessons I've been able to carry through in my life. But, um, yeah, so that was, that was a big one. And, and so then from then I just resolved to find a job or a set of jobs that I thought would suit the kinds of things that I tended to be better at and work toward my strengths. And so usually the advice, you know, I often get called by, by young people, college students and so forth, and they're saying, you know, what should I do? And so, you know, my first bit of advice is to agree with you can do this even when you're young is to take an inventory of what you're, what you think you're good at, what

• 1:01:06Speaker 01

  you think you're not as good at, what kinds of environments you're comfortable in, where you think you can be productive and what you're not good at, and try to find, um, a career path that sort of gets you on the right trajectory to, to help, help you build off your strengths versus build off your weaknesses. So, so to me, that's, that was my big failure. And, you know, last thing I'll say on that is I used to take the train to go to work and, um, I remember telling my, my then girlfriend, now wife, you know, I'd rather ride on this train back and forth from the stations all day than go to work. And I was like, okay, that's probably a good sign that I should not be doing this anymore. So, I was a painful period, but a great learning experience.

• 1:01:47Shane Parrish?

  Yeah, on the, the notion of advice and kind of following your, your skills, um, one of the things that I tell people is, um, to identify what they're really good at, um, that other people are typically really bad at.

• 1:02:02Speaker 01

  Yeah, I mean, I love that. I love that. That's great. I mean, and that's, that's a little bit of like, uh, Peter Thiel's, like how to build a great company, right? Kind of thing. It's the same, yeah, right. Like what, what problems can you solve that other people can't solve and you're going to be good at? Yeah, no, it's, it's a great way to think about things. Now, you know, when you're young, you often don't have, you know, there's not that much, you don't, you really don't. ...skills you can bring to the world, but you can start to think about, um, you know, do I want to deal with people, do I want to deal by myself, or am I more project oriented, or am I want to continue slow, I mean, there's just, there are certain, uh, am I a nine to fiver, or am I something that needs to be out and about, I mean, there are certain sort of dimensions that you can probably think about, and at least place yourself somewhere in those dimensions that can be helped.

• 1:02:44Shane Parrish?

  Hey, on the, the notion of Peter Thiel, to steal one of his questions, I mean, like, what is something that you believe that other people don't?

• 1:02:51Speaker 01

  You know, uh, I always find those to be tricky questions, but, um, the, the one thing that, um, I think that has really changed, one, one view of mine that's really changed, um, and was very much inspired by this work, work by Judith Rich Harris, is the work on, um, parenting. And as a parent of five kids, this obviously is not a tru- non-trivial thing for me. And, you know, I think the argument, I, I think as parents, um, we all tend to think that we're really, really pivotal in the lives of our kids, and on some levels, of course, uh, we can be very influential, but I think the argument that Harris makes that's quite compelling is that parents aren't quite as important as they think they are.

• 1:03:35Speaker 01

  And there are a lot of studies that I think would contribute to that. Um, you know, some of these fascinating studies, by the way, in twin, of twins, especially identical twins, um, would suggest that they turn out a lot more similar than different, notwithstanding they're very different environments, and that's quite compelling stuff. But, um, I also think the other point that she makes that, that I've really tried to take to heart and think a lot about in the context of my own kids was the importance of your peer group, especially when you're sort of, uh, early teen through, kind of high school, it's called that way, so through middle school and high school. And, um, that your peer group's a really important influence on your life in terms of everything, academic achievement, so on and so forth. So, um, that's, you know, I, I think I would have placed much greater

• 1:04:18Speaker 01

  emphasis on the role of parents, uh, 20 years ago, 15 years ago, and after reading that, that was something that really did, really, I, I really did change my mind on that a lot, um, from that.

• 1:04:29Shane Parrish?

  What, what other sort of, I mean, possibly counterintuitive strategies do you use as a parent with your kids? Do you either encourage them to think, or?

• 1:04:38Speaker 01

  So, so one of the things that I, I always try to do, especially when the kids get to a certain age, I mean, look, some things for Young kids, you're you're telling them what to do, just, you know, basic things like go to bed. Bathe yourself or whatever it is. And and so that's you're not gonna get around that. But when the kids get a little bit older, um, for me, I try to be very mindful uh to give them ideas and ways of thinking, and I call them recommendations. So I say, here's a here's a way you might, here's a recommendation for you. Here's a way you might think about this. Rather than saying, here's what I think, or here's what it's to. And um it's been rare that uh the kids have come have done something different than what that recommendation is,

• 1:05:22Speaker 01

  because obviously I'm trying to illuminate it in a certain way that would make it uh sensible. But in a sense, it allows them to take ownership of these ideas, right? So so I think that's one thing is I say, you know, here's a recommendation for you. Here's something, here's what the way I might think about that problem. See how that fits you and that suits you and that's if that's helpful in your decision making process. So uh and I think there's a lot of, you know, there's a there's a book that was also very influential for me. Um my kids are much younger called um. Parent Effectiveness Training, P P T. And their basic argument was, as as adults, um, you probably see the answer or a solution faster than your kid does. Or you can solve the problem more effectively than your kid does.

• 1:06:08Speaker 01

  And especially in this uh our society today, the temptation then is to solve the problem for your kid. Um and that, of course, um leaves the kids without the tools of problem solving on their own. So in that book, they like to distinguish which is which is prob- your problems that are not the kid's problem, in which case you need the kids to help you get uh solve the problem. And then problems that are the kid's problems, not your problems, which case you should have them solve them and you need a facilitator, right? helpful, right? And that's I thought that was a very useful distinction between whose problem. My facing and as a parent sort of holding back on this idea that I can solve this problem faster than you let me deal with it and you don't have to deal with it.

• 1:06:51Speaker 01

  Right. So essentially teaching the kids how to solve problems, you as an advisor or a guider or a facilitator rather than doing it on their behalf. So that that to me was another thing that I thought was really helpful as a as a mental model.

• 1:07:07Shane Parrish?

  I like that a lot. One of the members of our learning community wrote in with a question for you asking whether you have a recent example of updating your views. Maybe cryptocurrency, what to eat, something along those lines.

• 1:07:23Speaker 01

  Oh, updating my views?

• 1:07:24Shane Parrish?

  Yeah, yeah.

• 1:07:26Speaker 01

  Well, you know, I gotta say that I don't know if this counts as updating my views, but there's a book and I don't know if we talked about this, but there's a book I read last year that I thought was really awesome. And it was Ed Yong's book called I Contain Multitudes. Do you know that book?

• 1:07:42Shane Parrish?

  Yeah, I think we talked about that at the the retreat last year.

• 1:07:46Speaker 01

  You did? Awesome. So, right, so the work on the microbiome. And so I think that's another area that, you know, I, well, I don't know that much about it. I think there's a lot to learn about that. But I have a I have a suspicion that that's probably much more important than most of us probably believe. So I have changed a couple habits as a result of reading that and thinking about that a little bit. The main thing, which I should have done a long, long time ago, but the main thing is I've sworn off any type of soda in any way, shape or form. No soft drinks, no Diet Coke, no anything like that. And I don't know that this is causal. I should be really clear about that.

• 1:08:31Speaker 01

  But from the moment I did that, I found it much easier to maintain a lower weight. I found, you know, I just feel better. So again, that might be all psychosomatic, but it may not be as well. So that may have had an effect on me that I wasn't fully appreciating. So that's a big one. By the way, the stuff on cryptocurrencies, I don't know. I mean, I've studied a little bit about this and I suspect many people have, but I'm only watching this mostly out of the corner of my eye. But it's really fascinating. And certainly something like the blockchain, I would imagine, will be a technology that will continue to develop. But whether things like, you know, these basic cryptocurrencies, what those mean and so forth. Yeah, I don't have a, I don't have a strong view one way or another.

• 1:09:16Speaker 01

  It is amazing to watch what's happened right the last four or five years.

• 1:09:21Shane Parrish?

  Oh, yeah.

• 1:09:22Speaker 01

  No strong views on that one.

• 1:09:27Shane Parrish?

  One of the questions that I wanted to ask you that I've never had a chance to ask you, which is, what is happiness to you? What does that mean? What does that word mean? Can you unpack it for me?

• 1:09:37Speaker 01

  Yeah, a lot for me is, you know, ultimately, I thought a little bit about this and really for me, it's a sense of, I don't know, like independence, actually. It's probably the word that comes to my mind, which is that I feel like I can do a little bit of what I want. And don't have to worry about too many, to be able to do that. What brings me happiness, though, as I get older, certainly come to realize it is about people. And I think everybody emphasizes this, but it's really true. So, you know, I can say that I look forward to nothing greater than having, being with all my family. Because now we have, you know, with all these kids and many, a couple of them out of college and so forth. It's difficult to bring everybody together.

• 1:10:21Speaker 01

  I look forward to nothing and I'm no happier than when we have everybody together as a group. And so family, I think, is ultimately the top thing, being with those people. But the sense of independence is society, they don't have to worry about, I guess, goes ties back to this work on scarcity. They don't have to worry about, you know, where my, where I think it's going to come from. And having a little bit of financial stability and so forth would be related to that as well. And then I think a lot about, you know, I think this is this idea, it's funny.

• 1:10:54Speaker 01

  You know, one of the things I do is play in a sort of beer league hockey group, right? So, you know, so skating, you know, try to skate, get out there and skate once or twice a week. And skating with the guys, obviously itself is fun and that's exercise. But, you know, I've always also come to realize that part of what makes like hockey, this beer league hockey, so interesting is that you're spending essentially, you know, twenty or thirty minutes before the game and twenty or thirty minutes after the game, hanging out with these guys, right?

• 1:11:23Shane Parrish?

  Yeah.

• 1:11:23Speaker 01

  People from all different walks of life and very different day experiences, very different experiences in general, different ages, and there's just a lot to that. By the way, a lot of people saying a lot of zany things, but a lot, there's a lot to that, right? In terms of the social processes and so forth that I really value. So, yeah, to me, it's being able to do what you want, having that independence. And ultimately, it's being around people that, yeah, that you want to be around. And then the other thing is, I'll say that from an intellectual point of view too, that's the affiliation with SFI has been incredibly valuable in that regard. So I'm usually very happy when I'm there, hanging out with those scientists and talking to people. Again, learning, growing, it's a lot of fun.

• 1:12:08Shane Parrish?

  I can imagine. I mean, I would love geeking out like that too.

• 1:12:13Shane Parrish?

  What's next for you? Are you working on a new book these days?

• 1:12:17Speaker 01

  No, so nothing, nothing formal. There are a couple of things that are percolating, and so we'll see if something comes to pass. One of the things that has come up over and over is about a little over a year ago, I wrote a piece, I think it was called Thirty Years. But basically, I started on Wall Street just a little, now it's thirty-one years, but thirty, a little over thirty years ago. And I tried to write down my reflections on what made for a great investor. So the top ten attributes of a great investor. And that was, that then ended up being, you know, very popular. I think for someone like you, Shane, it would be, you know, mom and apple pie, because a lot of the ideas were about decision making and mental models and reading and so forth, and, you know, sort of intellectual growth.

• 1:13:01Speaker 01

  But that is something that I've been approached numerous times, whether that could be something that... Be reasonable to develop into a little book and it wouldn't be, you know, it wouldn't be a one piece, it could be a relatively short book. And there's some other things, I mean, I, I, the other thing I've always been drawn to is this idea of, and it's really at the outset of your question about the Santa Fe Institute is really, might we be able to, and this would be something probably more of like an edited volume, might we be able to draw on, you know, a handful of really great thinkers to talk about the role of complex systems and how, how it permeates into the world of markets and into the world of business. And that, I might be in a decent position to be able to tap those people, to write

• 1:13:45Speaker 01

  a little introduction, something like that would be a project too that I would be, I would be inclined to entertain. So, so nothing, nothing in the immediate offing, but a couple of ideas that are percolating, hopefully something at some point in the next couple of years will, will materialize.

• 1:14:00Shane Parrish?

  Oh, that's awesome, Eve. I'm already waiting with anticipation. This has been great. Where can people find out more about you?

• 1:14:07Speaker 01

  Well, a couple of areas. One is, if you follow, you know, if you don't follow me on Twitter, I'm certainly on Twitter at MJ Mobison is my handle and MichaelMobison.com is another website. We don't update it a ton, but there's references to all the books, there are free chapters, there are a couple of fun things in there as well. But if you really, you know, and I'm not a hugely active person on Twitter, but I do post stuff from time to time, a few times a week probably. That's probably the best way to keep up a little bit on what I'm working on, what I'm thinking about.

• 1:14:38Shane Parrish?

  Thank you so much, Michael. It's been phenomenal.

• 1:14:41Speaker 01

  My pleasure, Shane. Thank you.

• 1:14:47Shane Parrish?

  Hey, guys. This is Shane again. Just a few more things before we wrap up. You can find show notes from today's show at fs.blog/podcast.

• 1:14:56Shane Parrish?

  You can also find out information on how to get a transcript there. And if you'd like to receive a weekly email from me filled with all sorts of brain food, go to fs.blog/newsletter. This newsletter is all the good stuff I found on the web that week, and I've read and shared with close friends, the books I'm reading, and so much more. Last, if you enjoyed this or any other episode of The Knowledge Project, please consider subscribing and leaving a review. Every review helps make the show even better. Expand our reach and share our message with more people, and it only takes a minute. Thank you for listening and being part of the Farnam Street community.