Welcome to The Knowledge Project.
I'm your host, Shane Parrish.
I'm the author of The Furnham Street Blog, a website dedicated to mastering the best of what other people have already figured out.
The Knowledge Project is an experiment in which I will host interesting guests from a wide range of disciplines to better expand our minds.
Before we get started with the first episode, I just wanted to take a minute to comment on the premise of the show and our guest.
Michael Movison is one of the better thinkers about thinking out there.
I thought Michael would be the perfect person to start the series.
Not only is he a managing director at Credit Suisse, but he's also a teacher and a writer.
He's done a ton of research on decision -making, and he's written two books I absolutely love, Think Twice and The Success Equation.
I'm not aiming to have these conversations long and drawn out.
Rather, I want to pick the brain of the person on the other side.
There won't be filler, so some episodes will be shorter and some will be longer.
I may mean to walk away with increased understanding, to master the best of what other people have already figured out, if you will.
Topics will focus on things like innovation, leadership, and making better decisions.
But perhaps more importantly, I want to also explore philosophy, the questions of life and what it means to live a good life.
You can leave comments online at Farnham Street for Twitter, Facebook .com, slash Farnham Street, or you can send me an email.
I'd love to hear from you.
I was wondering if maybe we could start with your daily routine.
What's that like? Well, you know, every day is a little bit different for me, but there are probably a couple key elements and you know, for me, one of the key starting points is always sleep.
So I'm one of those guys that actually needs to sleep and doesn't function as well without sleep.
And I went too long in my life without figuring that out.
So for me at least, eight hours is really important for me to be functioning effectively.
A lot of time is usually, you know, normal days is usually doing research and reading things.
So I actually am one of those guys who spends very little time watching TV.
I do watch things like sports from time to time, but most of the time is spent reading and trying to do some research.
So a typical workday, that is.
And the other thing I'll say that's really super important to me is, is physical activity.
So I try to try to work out a number of times a week.
I'm actually you appreciate this as a Canadian, I'm a hockey player.
So like to go out a week or two, a night or two a week and try to play skate with a skate with the fellows and so forth.
So I think that those those balances between sleeping well, trying to eat well, exercising and then spending a lot of time reading is a typical and productive day for me.
That's awesome. Do you chunk your time like when you're reading, do you do that in increments of like, what would be your kind of this time that you set aside for that?
Some days are better than others.
I'll tell you, it's interesting, mostly when I may be even more indicative when I go away on vacation, for instance, I will almost always be very methodical about chunking large blocks for reading specifically.
And work, it's a little bit more haphazard, of course, because things are coming going calls and meetings and so forth.
But whenever possible, I'm obviously much more effective at writing and reading and chunks.
And I'll mention one little side story in this, the first book I wrote, I co authored, this is now, you know, a dozen years ago, or none, more, more than that actually, 17 or 18 years ago.
And I thought that I could do it a bit on the fly, you know, a little bit here, a little bit there.
And what I realized is for my sustained effort and attention, I really do need to block out and chunk.
So for me, it's actually a very important thing to do.
Yeah, I find that if I don't chunk out time, and at least kind of 30 to 45 minute increments, it tends to be consumed by technology.
And, you know, you, I don't know about you, but I end up picking up a device or doing something else.
What role does kind of technology play and how you go about your time?
And do you read on a Kindle?
Are you reading books, physical books, or?
Yeah, well, the technology I actually, I try to, I'm the same, I can get fidgety.
And then if I'm easily distracted by, by technology, that said, I find it to be very useful.
So I do, you know, it's actually now probably the first thing I check in the morning is Twitter versus papers, although I do try to go through the papers fairly methodically.
So, but I do try to turn that stuff or tune that stuff out as much as possible and just come to it from time to time.
As for reading, and I, and I don't know if this is a generational thing, but I still prefer physical books to reading on the Kindle.
So I might read on the Kindle on a, on a plane or something, but usually I'll do shorter reads versus long reads.
But mostly I like physical books, probably it's because of habit, but I also like to, to write in them from time to time.
But the most important thing for me, is I feel like I can remember, I actually don't have that kind of memory when I read, but I do tend to remember where things are in books physically.
So I sort of know, like, this is something that's interesting.
It was a passage on the left page about in the middle, you know, so I can go back and find it that way.
So for some reason, my own mental recall tends to do much better with physical assets than it does with electronic.
Even though I know I could search for it electronically, I feel more comfortable with it in the, in the physical form.
So I don't know if, I know, I think there probably is some research showing that there might be differences in how people can absorb and recall information based on physical versus electronic.
But I'm still a bit of an old school guy.
Now the problem is I have all these books everywhere.
I don't know what's gonna happen to them.
But but that's okay.
So you're a bit of a pro prolific reader.
I mean, how do you go about taking notes and synthesizing books?
And what is your process to kind of integrate that into your, your day to day life when you read something that's meaningful to you or something you want to remember?
So I'm probably not as methodical about it as I should be.
That said, a lot of what I read does relate to my day job.
Because a lot of my day job, I'm working with mostly concepts around business and investing, many of the concepts crossover quite well.
So I find myself often using things in my own research.
And that is actually incredibly useful.
Because when I write about it, or I have to speak about it, it typically means I need to understand the material reasonably well.
But there are still a lot of there are a lot of little side topics.
I don't really I just try to remember them.
I try to bring them up in conversation.
I try to weave them into my own mental models.
There are some books, not many, but probably one and 10, where I will write in them quite, you know, underline a lot and write notes and so forth.
But most of the books, you know, the great book how to read a book, you know, is what I would recommend most people do and talking about different levels of attention that you would Mortimer Adler different levels of attention you might pay to different things you read.
And I don't I'm not sure again, I do it systematically, but that's roughly a structure that I tend to follow.
Do you go back and organize that through Evernote or something or I don't, I should.
That said, a lot of it's a bit I mean, I'm sure I should probably more systematic and this is well in terms of my library.
But my library, I can find almost everything I you know, I have a few 1000 books probably, but I can find almost everything pretty quickly because I have a mentally catalog.
So certain sections, I often put authors together, but certain sections, I sort of know where things are.
So for the most part, I can do that reasonably well, it's probably I'm sure there are many things I'm missing.
And I probably should be more systematic.
But yeah, so far so good.
I I'm comfortable with this approach.
You've done a lot of thinking on decision making.
And as it pertains to not only I mean, specifically to the investment industry, but outside of that, in terms of how we can go about making better decisions.
One thing I don't recall a lot in reading your research is the role of intuition in decisions and how that can be helpful or harmful.
Is that something you can speak to?
Yeah, absolutely. I've thought and thought a fair bit about this.
And I actually wrote a bit about it in one of my books.
The let me first say that I think there is a role for intuition.
That said, I think that it's broadly over overestimated.
And the way I like to think about this, and by the way, there's a great book by David Myers on this called intuition.
And it's a book I really would recommend.
It's one of the better treatments of this and more thoughtful treatments of this.
The way I think about this is, is intuition is very domain specific.
And specifically, I would use the language of Andy Kahneman, you know, system one system two, so system one is our experiential system.
It's fast, it's automatic, but it's not very malleable.
It's difficult to train our system to, of course, our Atlanta analytical system, slower, more purposeful, more deliberate, but more trainable.
And I think that intuition applies when you participate in particular activity to a sufficient amount that you effectively train your system one, so that things become go from your slow system to your fast system.
So where would this work for instance, it would work in things like obviously with things like chess, you know, chess masters, we know they chunk, they can see the board very quickly know who's an advantage, who's not an advantage.
But it's not going to work.
So the key characteristic is going to work in what I would call stable linear environments, stable linear environments.
Athletics would be another example for history for long parts of history was in warfare, certain elements of warfare would work.
But if you get into unstable nonlinear environments, all bets are going to be off.
And there's a great, there's a great quote from Greg Northcraft, which I love when he says, you have to differentiate between experience and expertise.
And I think intuition releases and he said expertise, an expert is someone who has a predictive model that works.
Right. And so just because you've been doing something for a long time, doesn't mean that you have a predictive model that works.
So so I would say intuition should be used with a lot of caution, some realms really great other realms, it doesn't work so well.
Now, one of the things I'll end on this point is that, you know, the first time I met Danny Conman was probably a decade ago.
And so I took very copious notes in that session.
And one of the concepts he talked about was what he called disciplined intuition.
So he said, you know, you're going to have sort of these base rates, or statistical ways of thinking about things.
And how do you use those two things?
And in what order? And the argument he made was you should always start with the base rate, sort of the statistical approach, and then layer in your intuition.
So he called it disciplined intuition.
And otherwise, if you go with your intuition first, you're going to you're going to seek out right, you're going to seek out things that support your point of view.
So I've always, I always think about it that way.
I know that a lot of people make decisions using their gut or their intuition.
But I just don't know that that's the best way to do it in most settings, some settings, yes, but most settings no.
So let's say we're in a fairly stable kind of environment where intuition can play, you know, a predictive role.
How do we go about honing that?
And I guess more importantly, in the context of an organization, how do you go about learning to hone your intuition based on other people's expertise?
Yep. That's a great question.
I think that's the simple there, this is where you would fall back on the Andrew's Ericks and stuff on, you know, deliberate practice, right?
So this would be I think that the key here is really the notion of feedback, right, where you make a decision, or you see something and you get, you get feedback as to whether that's correct or not, and then you correct course and so forth.
So in those stable linear environments, you can practice deliberate practice, and you can get feedback that allow you to correct course and get better and better.
And then you start to internalize a lot of those lessons.
So, you know, there's even a, you know, an even more trivial example of where intuition might work, and that is low level driving, right?
So you learn to drive a car the first day, you're using your system to, but as you progress, you get better so that you're, you know, you're capable, right, you're, you're okay, and you're not a hazard to society.
Now, the fact is, most of us as drivers can't go on some race course or drive some stunt, right, because we don't really have that level of expertise.
But for good, you know, for, for many things in life, good enough is good enough.
But to really train your system one to be really, really good, I think it requires, you know, that structure deliberate practice.
And I think the essential element there is, is feedback.
That's an awesome point.
When you're working in a large organization, and you're making decisions, you may be part of the cog, I guess, in the wheel, so to speak, how do you as an employee learn from the process by which other people are making the decisions?
Like, how do you try to tease out the variables that you should be paying attention to that you may not be an expert in this industry?
How do you go about how would you orchestrate that kind of process to maximize the learning between people, and not necessarily just reaching the most rational or I guess best decision you can?
Yeah, it's a great question.
I think that the way I would probably think about this is to emphasize the process rather than the individuals, right?
And you think about quality decision making, and even things like the wisdom of crowds, and so forth.
I mean, the key is, first of all, settle on what you're trying to figure out to begin with, which is important, and not always crystal clear.
And then the next thing is really to surface alternatives or surface various ideas.
And I think this, when you think about where a lot of organizations go wrong, it's actually in this process, is people either winningly or unwittingly suppress their views or opinions about various things, and hence not all the possible solutions are considered, and then you go from there to figure
out what is the best solution.
So when I look at organizations and say, are things working well?
Are things not working well?
I really tend to focus on the process and saying, are the processes here in place sensible?
Now, there are a couple of things I'll just mention.
When you talk to people, for example, on committees, there are common things you hear from people.
One is, my committee is too large, right?
There is an optimal size for a team, and it's not 10, right?
It's not 15. So people will complain, we have too many people, and that's dilutive to what we're trying to do.
You'll hear people talk about someone in the room, the senior leader, for example, might express his or her view very strongly, and that immediately suppresses alternative points of view.
So, yeah, I think that those are common things.
So to me, the essential thing to try to learn from is, at its core, a thoughtful process.
And I'll tell you that I think a lot of organizations of all stripes emphasize the virtues of diversity, which certainly is of some value, but they're not necessarily clear on how to manage diversity, right?
So it's not just to have it, it's how do you take advantage of it, and I think that's something that's lacking in a lot of places, and that's a potentially very large area for broad improvement, not just in business, but in almost every walk of life.
So I love the idea of evaluating your decision making process.
It's kind of like, you know, the check and balance for the knowledge worker, so to speak, if you're making decisions all day, and that's how you're going about it.
One question is, you know, I guess we can kind of come up with the construct that a thoughtful decision process will look different depending on the environment and depending on the type of decision, but how do you go about evaluating a decision process if you're operating in a constantly changing environment?
Is it different in terms of how you look at that, do you think?
I think it's inherently different and really, really difficult to do.
And you know, this is things, you know, and by the way, just as a general statement, I think this is right that, you know, often in, for example, companies or large organizations, when you're relatively low level, right, so you're starting out, or you're doing a lower level job, often a lot of what you're
doing is very skilled based, very prescribed.
And it's, it's can be quite clear whether you're doing your job effectively or not.
As you move up in the organization, interestingly, you're probably making fewer decisions on average.
So a CEO is making fewer decisions.
And for example, a line employee, they're obviously more consequential decisions, but they also also tend to be much more probabilistic, right?
And so it becomes really difficult, I think, to try to assess that.
So things like setting a strategy for a company is an inherently probabilistic exercise, you don't really know if what you're doing is the right thing to do or not, or you really can anticipate all the possible contingencies.
So yeah, it does kind of go back still to the process, but we need to acknowledge even societally that certain types of jobs or certain types of roles have an inherent lack of predictability that make them very difficult to assess, right?
The natural thing we all do then, of course, is after the fact, is say successes should be equated with good decisions and failures equated with bad decisions.
And that's a really big mistake in a lot of a lot of circumstances.
So yeah, I mean, I don't know, maybe even those complex environments, we could talk about subcomponents.
And you know, are you getting the subcomponents right?
I'll tell you, Shane, that I've always I've been thinking about this, and I don't really know of a good answer for this.
But for example, the market stock markets are a great example of what you're talking about as sort of this nonlinear, dynamic environment where, you know, correlations are constantly changing, and so forth.
But the question is, are there are there ways that we can train people to think in such a way that allows them to just have an edge over other people, right?
And so there are some investment organizations, for instance, that teach their employees how to play poker, right, to think about probabilities to think about pod odds, right?
So how much I should bet given the probabilities in front of me.
And the question is, are those little small scale lessons, lessons where we can give feedback, scalable to a larger stage?
And that's a really, I mean, I don't know the answer to that.
But that's a really interesting question.
But I do think, you know, sort of getting into that mindset of how to think about the world properly, probably probably confer some advantage for folks as they get into the more complex environments.
If you're like a low level employee in an organization, how would you go about nudging kind of the process when you don't control it?
Because I always thought, you know, intuitively, that the people at the top who tend to, you know, like for generalizing here, but make decisions based on their gut also have the most to lose by implementing a decision decision process, because what they're losing is not, is their ability to use their
opinion to guide the course of the conversation versus a process, which may, you know, run contrary to that, which would be an incredibly humbling act.
And I haven't run into a lot of people at those levels who are humble.
Yeah, I mean, I don't know, I think a lot of that is probably a communique.
Well, first of all, it is, are you in the right organization, but second is can be a communication challenge.
In other words, if you're a lower level employee, and you see a better way of doing something, you certainly would hope that if you articulated that to your more senior people, and you explain the benefits to the organization as well, you know, that they would see that and make those changes.
And I think for the most part, I think most firms and most managers do want to improve for the better.
So I mean, I would be optimistic about that.
But if something's so set in stone, it's very rigid.
And as you said, maybe there are even incentives for more senior people to leave things, the status quo, for example, to emphasize the status quo that, you know, that's a really fundamental challenge.
And I would I would rethink whether, you know, you're in the right place for what you want to do.
So, you know, maybe it is a community rather than saying, I can't believe we're doing it this way.
This is really dumb.
You might say something like, here's another way to do it.
I think this is much more constructive.
It'll give us better business results.
Let's try, let's try it.
And that's another thing I'll say is that another another card to play in that is experimentation.
So let's try it this way for, you know, this subset or for this period of time.
And if it works out great, and if it doesn't work out, we'll revert to what we were doing before.
So just if that's if that's not too costly to do an experiment like that, that's really also another very useful way to try to approach that challenge.
That's interesting.
How do you see the role of technology affecting decisions, and not only decisions, but the decision making process, I guess?
Well, I think it's, I mean, it's potentially very, very huge, right?
And I think for the most part, very positive.
And, you know, I think that there's been this almost a tension between, you might call them fundamental or the intuitive or sort of the gut feel group, and more of the quantitative group, you know, the quants and so forth.
And I think that tension been brewing for 60 or 70 years.
But now it's really spilling over, right, big time.
And the question is, can we use, to what degree can we use algorithms and computers to make a lot of the decisions?
And, you know, by the way, one of the chapters in one of my books, I talked about called it the expert squeeze, which is to say that it is, I think, factual to say that we're using algorithms to do many of the tasks that used to be the domain of humans, right?
And that's so that's interesting.
So but the question would be something like, how might I use technology more effectively?
And, you know, part of it is that what are computers good at, right?
They're good at looking at lots of data, they're good at establishing and understanding base rates.
So, for example, if you're thinking about an appropriate reference class for a particular decision, your technology will allow you to access that reference class, I think, much more effectively than you could otherwise.
And they're not emotional is the other big thing, right, which is if you say, you set out some thoughtful decision rules, or algorithms, when you become stressed for whatever reason, well, I shouldn't even say just stress, it could be it could be emotionally aroused either favorably or unfavorably.
The algorithm may see you through that middle ground, which allow you to make quality decisions over time.
So I think it's going to be tremendous.
I think it comes to head with certain, you know, these ongoing debates about, you know, will we live in a world with no drivers of automobiles?
We have driverless cars, we live in a world where airplanes, the airplane you get on will be flown by effectively, it'll be basically a big drone, it'll be flown by somebody in a station, you know, these are interesting questions.
And whether we whether as a society to what degree we'll accept those kinds of things, how fast it will happen and so forth, really, very rich.
I mean, I tend to be more optimistic than pessimistic on this, but it's going to be there are going to be some arm wrestles as we move down this path for sure.
I read that you use the I think it's called the Colonel Blotto game with your kids to help you maybe explain that.
Yeah, yeah, exactly.
This is why why it's weird to be one of my kids.
Um, you know, so Colonel Blotto is an interesting formulation from game theory.
So if you ask people about game theory, almost everybody at some point learned about the prisoners dilemma, and which is a which is useful because it has real world applications and even things in you know, military strategy or or, or bidding wars and so forth.
The Colonel Blotto game was developed in the 1920s originally and was actually kicked around a bit at the Rand, Rand Corporation in the 1950s, but sort of went into the backwater in part because it didn't have that many logical solutions.
So so here, but but it's been resurrected in the last 10 or 15 years.
And so it has some very interesting applications.
So Shane, here, I'll give you the most simple version of the Colonel Blotto game is that you and I are competing with one another, and we're each allocated 100 soldiers.
So you have 100 soldiers, I have 100 soldiers, and we have three battlefields.
So your task is to allocate your soldiers, your 100 soldiers behind the three battlefields 123 in any way you want, I'll do the same thing.
And then we sort of, we do it without communicating, of course, then we lift the doors, and we basically do battle whoever has the most soldiers in, you know, battle one, battle two, battle three, wins that war, then, probably wins that battle, then whoever wins the most battles wins the world.
Okay, so that's the basic idea.
Now, the formulation I just laid out with 100 103, is basically rock, paper, scissors, I mean, there are some really dumb strategies, but for the most part, most strategies are fairly random.
So that's not that interesting.
So what Blotto becomes really interesting is when you start to introduce asymmetric resources and expanding battlefields.
So for example, rather than we both have 100 soldiers, now I give you 120 soldiers, and I only have 120 soldiers, 100 soldiers.
So now you have more soldiers to deal with.
Now, there are still scenarios under which I can win, but you can start to see how that would tilt the advantages for you.
And then we might say, well, instead of three battlefields, let's have five or seven or nine or 11 or what have you.
So what's interesting is it starts to shed some light on how you might want to compete in various contexts.
And the simple rules, by the way, is if you're the stronger player, what you want to do in a head -to -head competition, what you want to do is simplify the game, in other words, have as few battlefields as possible.
So you're almost assured that your skill will overwhelm that of your competitor, your resources, right?
If you are the weaker player, what you want to do is add battlefields, you want to dilute, you want to play across as many domains as possible to dilute the strength of the stronger player.
So the application of that underdog strategy might be, instead of going toe -to -toe in welfare, it's a guerrilla tactic.
Instead of in sports, instead of trying to sort of go play head -to -head, you might try trick plays or different formations that are unfamiliar to the stronger player.
In business, it would be disruptive innovation.
So trying to go after the incumbent, again, head -on, you try to kind of circumvent.
So there are some practical applications of the Bellotto game that can be really, really, I think very rich and very interesting.
Once you sort of explain it to people, they get it, but what's beautiful about Bellotto is it's all been mathemetized now and leads to some very interesting and beautiful, I think some beautiful conclusions.
It's a good behavior in your head, is it gets you more soldiers?
No, actually, this is most like squabbling about dumb things.
So instead of doing rock -paper -scissors, which is what I would usually have them do, we just do Bellotto because it's a little bit more interesting.
We keep it very simple.
What other tools do you use to help your kids learn how to think?
I mean, that's a subject that I think people are really interested in because it goes to the broader question of how do we teach people how to think.
Yeah. Well, I think the first thing is to say, I'm a big believer in the Carol Dweck work on mindset.
And so the first thing is to, in our household, we never emphasize outcomes.
We only emphasize effort.
So for young people, in particular, is to dwell on their effort.
And whether that effort yields good results or bad results, the effort's the point of emphasis.
And that can be confusing for kids, right?
Because they think, for example, grades or, you know, particular tests or assessment is really giving them feedback about whether they're doing well or not.
But when you say, you know, you've done well on an assessment, but your effort was lacking, that's a hard lesson to hear from the kid.
But likewise, and more encouragingly, if you see your kid work really hard, and do quite poorly, you can give them a pat on the back and say, I know that you worked hard on this.
And that's what I really want to see.
So that's the first thing.
The second thing is just is, well, another aspect is just to make people aware of thinking about the world in a broader sense, right?
So opening up different points of view.
So typically, if a kid of mine will express a particular point of view on something, what I'd like to do is to get them to think about alternative points of view, and maybe have some ways to think about that.
And, you know, so that's, you know, I think constantly always thinking about that.
And then the third thing is, you know, I've had particular situations where we would do, you know, fun bets, and to try to teach a lesson.
And I'll give you one example.
That's a funny one.
It's, it's, it's a few years old, but my oldest son, this is a 2007 World Series.
And I think it was the Boston Red Sox against the Colorado Rockies.
And, you know, he comes to me, and he's in his mid teens or something.
He comes to me and says, you know, I'm feeling it.
I'm feeling it. I think the Red Sox are going to sweep.
So I'm like, okay, you know, you have any money for that?
And he said, yeah. So I said, all right, here's the bet I propose to you is if they sweep, I'll pay you $20.
And if they don't sweep, you pay me five.
Right? So that's, that's, that's inherent in that bet that I've offered him is the probability of them sweeping.
Right? So by the way, this is, this is one of those bad outcomes for me.
And by the way, so the way it works, I mean, if you work out the math, but it's the probability of a sweep is probably somewhere between, I mean, if you're super generous to 18%, you know, more likely to 12 or 15%, something like that.
So I definitely had the better of that bet.
But of course, they did sweep, right?
So of course, I'm handing over my $20 and honoring my bet.
But I said, this is a teaching moment, right?
Because you realize that you won this bet and you're feeling good about that money in your pocket.
But if you make these kinds of bet over time, you're going to lose and here's why it doesn't work.
Right? So that's, that's an example of how, you know, to explain the math of it.
And, you know, and I think he got that.
And the last thing I'll say, this is I'll mention this quickly, this kind of stuff we talked about from time to time around the dinner table.
But my youngest son who was in seventh grade had a tutor working with him on some math work.
And the tutor came out to me afterwards said, Mr.
Mobison, I have to mention that it's really quite unusual that I gave your son the Monty Hall problem.
And he knew the answer to it.
He's like, most 13 12 year olds don't really know the answer to the Monty Hall problem.
Right. So this is one of these little math problems.
And, you know, the reason he knew the answer is because we had talked about it just a few weeks before.
And, you know, the answer to the problem is very counterintuitive.
But we walked through why the answer was what it was.
And we actually pulled up a simulation on the on the computer.
So so so it was beyond just understanding that you what you should do, but really understanding the concepts.
So so all those things probably spill.
That's a long answer.
But what part of it is just and by the way, also trying to model it.
So just saying, if I'm making a decision, let me let me explain how I might think about this problem.
I'm also one of those people actually, I never tell my kids what to do.
I do tell them things what to do like around the house.
But when they're making decisions, I mostly try to stick to recommendations versus telling them what to do.
So I want them to think for themselves, but I say I'm going to give you some things to think about that may, you know, so these are some ideas or recommendations that may be helpful in your in your process.
Right. So they probably know where I'm coming out on things.
But rather than saying I'm going to decide on your behalf, I'm going to let them think about it and try to give them some some some guides for their thinking.
I like that a lot. You mentioned open mindedness.
How do we go about you know, fostering that in adults, not necessarily children, but you're you're in an organization.
And you know, I think we've determined through the Good Judgment Project, that part of what makes a good predictor is being open minded and being willing to change your mind.
How do we go about fostering that type of behavior?
You know, it's really hard.
And I think that I do think this obviously, this is part of an element of personality.
So there's I don't want to say it's immutable, but there's an element of this, it's going to be more natural for some people than others.
So that's the first thing is to say if you find someone who's naturally not open minded, it's going to be a struggle to try to change their behaviors.
But that said, I mean, it is it's it's it's this constantly this constant point of view, you know, by the way, Ted lock, you mentioned Ted lock, the Good Judgment Project, I mean, they've done really beautiful work.
And part of it is even things like if I want to be a man is this fancy language, right?
But if I want to be a Bayesian updater, in other words, what the base view is, I have, I have a point of view on some prior and new information comes in, you know, I should update my my probabilities based on the new information.
How good are we at doing that?
It's extremely difficult.
And even if I get you to move in the right direction, I often can't get you to move the appropriate amount, so on, so forth.
So yeah, part of it is, is I think revealing alternative points of view and trying to be open about them describing those and suggesting how those things might be either solutions or things that should be considered carefully.
I don't know what else to say.
I do think that and I think, Shane, you and I share this, you know, enthusiasm, and I do think that the willingness or encouraging people to read across disciplines also, by definition, almost always opens people up to different points of view that can be helpful.
So you have to make a concerted effort to expose yourself to different different ways of thinking.
So part of it is going to be hardwired, probably, but part of it is putting people in an environment where they're going to be exposed to various ideas.
And, and those are not only welcome, but they're also encouraged, right?
Excellent. Thank you.
Let's wind up with three questions that I'm going to try to ask everybody, at least for the start.
So we'll see how this goes.
But what book influenced you the most in your life and why?
Wow, that's hard. It's too hard to answer one, but I can mention probably a handful of them that were very influential.
I mean, from a business point of view, certainly the book written by my mentor, Al Rappaport, called Creating Sheralder Value, was enormously influential.
He's a dear, dear friend.
We are collaborating on a project now, so that would that would be one.
In terms of thinking, probably three books for me.
One is Dan Dennett's book, Darwin's Dangerous Idea.
And I'm just a huge Charles Darwin fan, but this is this idea of how evolutionary thinking should permeate basically, almost almost everything you think about.
So Dennett, I think it did.
It's a fascinating book.
Another one I would mention is E .O.
Wilson's book, Consilience.
Consilience really means the unification of knowledge, but the plea that Wilson makes in this book, to which I'm deeply sympathetic, is that many of the problems that we face as individuals and societally are problems that are going to be at the intersections of disciplines.
And it's simply not enough now for us to use one discipline to try to solve problems.
We need to bring people together to think across those intellectual barriers.
And the third one, which has also been a very big part of my life, is Mitch Waldrop's book, Complexity.
And this really documents the birth of the Santa Fe Institute, but is intertwined with a lot of stories about complex adaptive systems and that whole way of thinking.
And for me, that was a huge revelation.
It actually clicked into place as I was trying to contemplate, think about things like markets or economies, but just as a mental model, extremely fertile to get you to think about all sorts of systems out there, be they organizations, businesses, markets, what have you.
And things like the wisdom of crowds, all those ideas, they naturally flow from looking at the world through the lens of complex adaptive systems.
That's awesome. What book is on your nightstand right now?
Right now I'm reading a Laszlo Bock's book called Work Rules, which I love.
So Bock is the, I don't know exactly what his title is, but he's basically runs the human resources effort at Google and has been extremely innovative.
I think Google itself has been extremely innovative, but Bocks were leading some of that charge to think about the policies around managing people much more effectively than most organizations.
And what I like about it in particular is it's very analytically driven.
And it's also been, you talk about open -mindedness, very much of a learning process.
So not only does he share many things they do very well, he also talks about the bumps along the road and some of the mistakes they made and how they corrected those.
So that's a topic in general I'm very interested in is how do we think about finding the right people?
How much time do we spend hiring?
How much time do we spend evaluating people and so forth?
So that's what I'm reading right now.
That's a fascinating subject.
One of the ways that I find new books to read is always in the back, kind of the bibliography and recommendations from the author in terms of where he or she got the sources for what they're doing.
So I was thinking one of the parts of the Knowledge Project would be asking guests who I should interview next in their opinion to be on the Knowledge Project.
So that you're asking me, yeah.
So wow, I mean there's so many people, but a couple of people come to mind.
Look, I think that one of the books I really enjoyed the most in the last couple of years was Ed Catmull's book, Creativity, Inc.
So how I just have enormous respect for what they've done at Pixar.
And if you read that book, Catmull talks about how it is you generate diversity in an organization but also have a common mission.
And he also talks about a couple of restarts.
So situations where he somehow had a sense that they were drifting away from their mission and then he was able to make some changes to try to bring that back into focus.
So that's one. The other one I'll just mention, it's a book I just recently read is Michael Gazzaniga's book, A Tales from Both Sides of the Brain.
I used to find this to be, so Gazzaniga is a neuroscientist at UC Santa Barbara and is known for, I mean over 50 years for his absolutely extraordinary, I think fascinating research on split -brain patients.
So people where there's a section of the corpus callosum.
And so the allowing for the analysis of what modules work in your right and left hemisphere.
So that to me is another very, very fascinating area and in particular this module on our left hemisphere which he's dubbed the interpreter.
This module that attempts to close all cause and effect loops.
And for heaven's sakes we're all about narratives in our lives, we're all as humans we're all about causality.
By the way that's one of the reasons we struggle so much with understanding statistical thinking.
And that book is absolutely, it's a fascinating read.
The research is to me extraordinarily interesting and also very revealing of who we are and how we think.
That's awesome, thank you.
Michael this was fascinating, I appreciate having you on the show.
