#486： How to Get Better at Making Life-Changing Decisions
Episode Stats
Summary
In this episode of the Art of Manliness podcast, Brett McKay sits down with Steven Johnson, the author of Farsighted: How We Make the Decisions That Matter the Most, to discuss how to make decisions that matter the most.
Transcript
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Brett McKay here and welcome to another edition of the Art of Manliness podcast.
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How do you make the biggest decisions you face?
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The ones that have significant consequences and can change your life.
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Choices like whether to get married, move, attend a certain college, take a particular
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If you're like most people, you just kind of wing it and maybe draw up a basic pros and
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My guest today has studied the latest research in decision-making theory and has formulated
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His name is Steven Johnson and his latest book is Farsighted, How to Make the Decisions That
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And today on the show, he walks us through how to move beyond listing pros and cons to
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using a more effective three-step decision-making process.
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We begin our conversation discussing how most people make decisions and how it hasn't changed
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Steven then walks us through the phases of a better decision-making mythology, including
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developing a more creative map of the possibilities before you, accurately predicting the outcomes
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of those options, and questioning the narratives you have about your choices.
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Steven then makes the case that reading novels and watching quality television shows can be
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a great way to train our brains in the skill of decision-making.
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And we end our conversation discussing what the raid on Osama bin Laden can teach us about
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After the show's over, check out our show notes at aom.is slash Farsighted.
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So you got a new book out, Farsighted, How We Make the Decisions That Matter the Most.
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Curious, how did you get started thinking about decision-making or the philosophy and science
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Because you've written all about where ideas come from, this idea of emergence.
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You know, how we, innovations that got us to where we are now.
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You know, this project I have been working on for a really long time.
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It's actually the longest kind of incubation period of any of my books, which is maybe appropriate
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for a book that in some ways is about long-term thinking and decision-making.
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But I started actually working on it originally right after my book, Where Good Ideas Come From,
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I think I started taking notes on it in 2011 or something like that.
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One, a story from history and one, a story from my own personal life.
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The story from history is this, in Where Good Ideas Come From, I had a whole long riff about
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And, you know, there are these incredible personal notebooks that Darwin maintained, particularly
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during the 1830s, late 1830s, as he was developing the theory of evolution.
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And it's a beautiful case study and watching a mind kind of come up with a radical new idea.
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But I knew from that research that there's a kind of a comical moment in those notebooks
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where Darwin takes up two facing pages of his notebooks, kind of interrupts his scientific
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musings and starts wrestling with another question, which is a little bit more intimate,
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And he basically creates this pros and cons list of, you know, pro-marriage and anti-marriage.
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And it's funny to read it now because some of them are kind of like, well, if I get married,
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But on the other hand, he says, I might have to give up the clever conversation of men in
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It was like, you know, the pros and cons list is the one technique that most of us actually
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learn in adjudicating a complicated choice in our lives.
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And so here we are, you know, 150 years later, and we're still using the same technique.
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And so I was like, surely there must be, you know, some interesting science and research
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And maybe they're better tools than just making a pros and cons list.
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And the personal story was right at that point in my life, I was wrestling with my wife with
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this equally complex choice, which is we were, I had, as my kind of version of a midlife crisis,
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I had gotten obsessed with the idea that we should move to the West Coast.
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And I was getting sick of winter and needed more nature in my life.
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And so I really wanted to move to, you know, the Bay Area.
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And I tried to persuade my wife that we should make this big momentous choice for us and for
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And I started thinking about, like, you know, how do we make these kinds of, that's a choice
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that the consequences of which will, you know, reverberate for decades, you know, in both
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What's the best approach when the stakes are so high?
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And then I figured there would be a really good book to write about that.
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And then I kept getting distracted with other projects.
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And I kept taking notes in the background for it and finally, finally put it kind of
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As you said in the book, this is an important topic because every day we're making decisions,
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like small ones, but even really big ones that will affect the rest of our lives.
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And no one really tells you how to go about making these decisions.
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You just sort of, you sort of wing it oftentimes.
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Sometimes I think you don't even actually make a decision where there should be a decision
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I mean, for instance, where do you live, right?
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I mean, in our case, we had a period of time where we actually put that front and center
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and said, you know, let's decide what city, what part of the country, you know, suburbs
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versus city, countryside, you know, all that kind of stuff.
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But I think actually most people don't have a kind of crossroads moment in their life
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where they really decide where they want to live.
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It just is something that happens to them, you know, that they stay at home where they
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were born or they, you know, stay where they, if they go to college, they stay near their
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college or they move somewhere kind of accidentally when they're 22 and they get stuck there.
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And so some of the most important choices in life, we don't even make, which is, which
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So, so trying to recognize and also trying to differentiate between the choices, as you
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say, that we do make day in and day out that actually aren't that significant, that don't
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require the kind of deliberation that I'm talking about in the book and the techniques that I
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Like, it's fine to make, you know, what you're having for dinner or even, you know, 99% of
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the decisions you make at work don't require this much thought.
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But when you do confront a choice that really does have significant long-term consequences,
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to take time out to do some of the exercises that I talk about in the book, I think is a
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And you give this great example to start the book off of decisions being made that have
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had lasting consequences, but people weren't really making decisions.
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They were just doing whatever they thought was the next best thing.
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And this is the story of Collect Pawn in Manhattan.
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So I should say the book is both about personal intimate decisions, like should I get married
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And also group decisions, collective decisions, business decisions, but also planning.
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There's a lot of urban planning in the book, for instance.
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And that's why I started with this story about Collect Pawn.
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So there was for many, many years, for centuries, for millennia, there was a freshwater pond in
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lower Manhattan, what became Manhattan, which was actually really the only major source of
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drinkable water in lower Manhattan because the East River and the Hudson River are tidal
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And the Native Americans who lived there and then the early Dutch settlers, you know, relied
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There was a kind of a rocky hillside next to it and people would skate on it in the winter.
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And it was a kind of lovely part of early New York life.
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But, you know, New York being what it was and continues to be, people started, you know,
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dumping their garbage there and old dead, you know, barnyard animals and the occasional
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And some tanneries opened up that started polluting it with chemicals and all that stuff.
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And so by the 1770s, 1780s, it was just, you know, a stinking hole, basically, as it was
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And so basically the city tried to decide whether, like, maybe we should turn it into a park.
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But they were like, oh, no one will ever, it's too far north.
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No one will ever live around that place, which was ridiculous because this is like, if you know
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Manhattan, this is, you know, below Canal Street, basically.
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And so they kind of trashed their plans to build a park.
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And then they basically just decided to fill it in and get rid of the pond.
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And they built some houses over it, but they'd done a poor job at the landfill and the houses
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started to kind of decay and all these noxious smells came out and people fled from the neighborhood.
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And that neighborhood became the legendary Five Points neighborhood, the first kind of
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famous slum in New York City where Gangs of New York was set and all these things.
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And it was all because they just kind of didn't know what to do with this beautiful natural
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And if they had built that park, that would be today one of the great urban parks in the
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And it probably would have survived for 500 years or longer, this beautiful lake in the
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So you can think of it almost as like a 500 year mistake that they made that they failed
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to capitalize on this wonderful natural resource.
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And part of what I'm trying to argue in the book is actually as pessimistic as we can sometimes
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be, we wouldn't make that same mistake as cavalierly as we did back in the 1790s, early 1800s.
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You know, we are actually better at kind of planning decisions like that and looking at natural
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And we've advanced the art of making those kinds of choices in many ways.
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And all of us can learn from the way in which we've advanced that art and that science.
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Well, before we get to some of the advances we've made in decision making theory, let's
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So you mentioned for most of human history, probably we've been using the pros and cons
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But you also highlight cases of individuals who were getting a little more sophisticated
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For example, Benjamin Franklin sort of developed a decision calculus when he was a young man.
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Yeah, he called it moral algebra, which is actually the title of the first chapter, which
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But he basically proposed a pros and cons-like list.
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But he had one correction to it, which is really important, which is he had a kind of a
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rudimentary scheme for what we now call weighting, i.e. giving a weight to each of the values that
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Because the problem with the pros and cons list, if you're just like write up a list
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of pros and write up a list of cons, you know, and whichever one is longer, that gives you
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That doesn't really work because presumably some of the things on the list are more meaningful
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to you or more consequential than other things on the list.
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Having children, presumably, was more important to him than clever conversation of men in clubs,
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I mean, maybe he really liked this conversation, but I think knowing what we know about Darwin,
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And so when we kind of list the different kind of assets, we can't have them all have
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Franklin proposed this system where you create your list and then you kind of cross out ones
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But that actually doesn't, that helps a little bit, but it doesn't really get to the issue.
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So they're now much more advanced versions in a sense where you give a score to each
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And you say, okay, this one is like, you know, on a scale of one to 10, this one's a nine,
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And the other problem with the pros and cons list is it really only works well when you're
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But what if you're looking at a choice where there are five options?
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The pros and cons list effectively doesn't scale up to handle a choice with multiple variables,
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There's a technique that I talk about at the end of the book that's sometimes called a
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values model or linear values model that is actually used in environmental planning,
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And it's the kind of thing you actually really build in a spreadsheet.
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You know, sometimes there's some choices in life, like, should I get married?
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Where maybe you don't want to create a spreadsheet and sit there.
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Sit your perspective spouse down and say, look, darling, I've run the numbers here and it
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And so what you do is like, you create, you know, a list of all the different places you
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And then you create a list of the values that are important to you in your life.
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And then you kind of score each of those values in terms of how important that value is.
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Like, you know, happiness for, you know, access to nature is more or less important than good
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And then for each of the options you're looking at, you give it a score for each of those values.
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You say, hey, I think, you know, if we move to the country, we'll have more access to nature
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And then you basically multiply, you know, the weight or magnitude of each value by the
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score for each option and add it all up and you get an answer.
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It's not always the, for some people, I think that kind of approach is maybe too mathematical
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And it's maybe not the last stage of the process, but it's a way of visualizing all the things
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And in the book, I call them these kinds of choices, I call them full spectrum choices
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because they involve so many facets of what it is to be alive, right?
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That involves, you know, the future education of your kids.
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That involves things like nature and your friends and your politics.
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Like, do you want to live in a sidewalk culture or a car-centric culture?
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I mean, just all these different elements and it's just really hard to keep all that
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And so creating a kind of matrix or grid like this and in a sense kind of running the
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numbers on it, I think is a really good tool for helping you see it all in one place.
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And there's also like with complex, well, with these complex decisions, there are second
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order and third order consequences that you don't think about, right?
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With like the collect ponds, like, well, if we throw in the dead animal carcass, they don't
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think, well, the water's not going to be drinkable and then they don't think, well, the water's
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And then if we had to cover it up, then we build houses, but then the houses are going
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You know, this is one of the things that I didn't fully wrestle with when I first came
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up with the idea for this book that became increasingly important to me as I researched
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it and wrote it, which is that really when you're making a complex long-term decision,
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whether it's, you know, a civic decision or a personal decision or a business decision,
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a huge part of it is about predicting the future, right?
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It's, you know, this book is like a third of it is about prediction because anytime you're
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making a choice like that, you're making a prediction.
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I think if I choose this, that in five years, things will turn out this way.
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And so I got, it sent me down this whole rabbit hole of like, okay, well, what do we know about
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What are the places where people have gotten better at predicting?
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And there's a lot of great, I mean, if you could write, many books have been written,
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in fact, about how we predict and how bad in general we are at predicting the future.
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But as you say, a lot of that prediction process is trying to imagine consequences that don't
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There's a great quote, one of my favorite quotes in the book from Thomas Schelling, the Nobel
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Laureate, who, among other things, kind of half invented game theory and other things.
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He has this great quote that more or less is, the one thing a person cannot do, however
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brilliant they are, is write up a list of things that would never occur to them.
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And I love that because that is, in a sense, what you're trying to do when you're making
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It's like, okay, I know there's a blind spot here.
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There's something in the future that I'm not anticipating, that I'm going to choose this
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path and I'm going to get blindsided by this development down the line.
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And so part of it is just going through these exercises to try and see around those blind
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And to get better, you can't, no one has a perfect crystal ball, but there are techniques
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that make people more aware of the alternatives and potential consequences than they would just
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So you said that we're getting better at decision making.
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We'll talk about some of the ways we've gotten better in some case studies, but where is
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Where is the development of these processes happening?
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Is it a cross between behavioral science, economics, game theory, philosophy?
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This is one of the reasons why the topic was so interesting to me because I do tend to work
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And part of what I try and do in my books is to show connections between disciplines.
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Actually, it's funny, when I was a kid, not a kid, when I was in college and I knew that
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I wanted to write books, I used to tell people like, I'm going to write these books that are,
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you know, jump around from discipline to discipline and no one will know where to put them in the
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And then I ended up growing into that person and becoming that kind of author.
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And I realized now that's a terrible way to write books because nobody knows where they're
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supposed to go in the bookstore and nobody knows where to find them.
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But it turns out with decision theory, it does draw upon all these different kinds of
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There's a bunch of kind of management theory, right?
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There's a bunch of, you know, the one place where people are taught how to make decisions
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But there's a lot of research from, you know, psychology and kind of group psychology, some
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interesting findings from hardcore kind of neuroscience, like about how the brain actually makes
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decisions and, and also, you know, philosophy and literature.
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There's a lot of wonderful kind of probing look kind of analyses of people making decisions
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And I think there's a lot to learn from those kinds of interior portraits of, of other people,
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Watching somebody else through the lens of a great novel, making a choice is, is a wonderful,
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it's almost kind of practice for us to, to rehearse the decisions that we actually make in our
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We're going to take a quick break for your word from our sponsors.
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Yeah, we'll get into that little tactic to make better decisions, but let's talk about
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sort of broad overview of this process that you found that you're, you, you see happening
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when groups or individuals are making complex decisions.
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So, you know, mapping in a way we've, in a sense, begun to touch on, which is the idea of,
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look, there's so many different variables and values that are at play in a, in a full
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So part of your job in this initial stage is, is not to, is not to try and kind of narrow
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Like have a, have an initial phase where you're just trying to identify as many factors that,
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It's all the different kinds of planes of existence that, you know, would be implicated
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by moving to California or opening up this new branch of your business or whatever it is
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But the other key part of this phase that, that most people don't do is to spend time
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in this opening stage, trying to identify other options that you might not have initially
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And this, this is based on some, some great kind of management theory research by a guy
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named Paul Nutt, who was a scholar of corporate decisions in the, in the kind of seventies,
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And, and he analyzed hundreds and hundreds of actual real world decisions that people
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made and interviewed people extensively about their process or their lack of process as
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And, and, and then he went back and interviewed people to find out, did the decision work out?
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Like, were they happy with the results in the end?
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And what he found was that most people did not have an initial mapping phase where they
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tried to identify other options to, you know, that they could potentially explore.
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So the way Nutt described it is most decisions were what he called whether or not decisions,
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It was just one option on the table and it was just a binary choice.
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Those people in the long run ended up more likely than not to be unhappy with the outcomes
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But there was a subset of people who actually did add this early kind of mapping phase where
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they tried to, you know, have a really a kind of a creative kind of brainstorming process
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Yeah, we're looking at option A, but let's, let's try and identify options B and C and D,
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And the folks who did that were more likely than not to be happy with their choice in
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It's a significant kind of bonus in terms of the outcomes by adding that phase.
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Even if they ended up going with option A, the one that they'd originally looked at,
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because they just, they were making a more informed choice.
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They understood more of the variables by going through this kind of process.
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So, I mean, Nut describes it as change your decision from a which, a whether or not decision
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And that it's, it's a very elemental kind of idea.
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But I think that that's, that's a, it's a great exercise to do in this kind of initial
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So the initial exercise, just trying to get a big, don't eliminate things, don't eliminate
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You're actually trying to grow options, which I think would be counterintuitive.
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You're like, well, I'm trying to make a decision.
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But you're telling me the first step is actually make more choices available.
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Yeah, it's actually, it has a lot of overlap with some of the stuff that I've written about
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It's a similar process that people talk about when you're trying to be creative, that you
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And the divergence phase is you're not trying to narrow down on, on the final answer.
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You're trying to just generate options and, and come up with lots of ideas.
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And then let, you know, and liberate yourself during that period to contemplate lots of different
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And then later on, go back and weed through everything and try and figure out what, what
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Are you also in this phase exploring all the possible consequences as well?
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That's really, I mean, this could be a good transition.
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That's, that's really the, the, the prediction phase, right?
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So you've identified five top kind of contenders for, you know, what you might want to do.
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And so we've identified these five cities that might be interesting as options that we
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can move to or, or rural areas, whatever, it doesn't have to be cities.
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So then, so then you got to think about like, what would happen if we moved to each of these
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And, and that's where you're really moving into a prediction stage where you're kind of
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analyzing like what really will be the consequences of this path versus this path versus this
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And so that's the, in my book, I kind of shift, there's, there's a shift from mapping to predicting
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And once you get to predicting, you're effectively in a kind of a storytelling mode.
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And in a way, it's a very creative process because you're trying to imagine these, you're
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trying to make a list of things that would never occur to you as Thomas Schelling put
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it, you're trying to imagine consequences that might not occur to you originally.
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And, and there, there are a bunch of useful exercises here.
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I mean, this is where you draw upon some of the techniques that have sometimes been called
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Kind of a corporate technique where you bring in people to look at the next five years of
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your market, say, and, or the world that you're selling your products in.
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And the important thing is that you tell multiple stories in this phase.
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All of us make predictions when we get excited about something.
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Like when I was excited to move to California, I had this beautiful story of like, we will
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The children will get outdoorsy and they'll never play video games again.
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So we always make these predictions, but the point is to challenge them, right?
00:25:13.400
Because you're, whatever prediction you have is somewhere wrong.
00:25:16.540
And it's probably too optimistic if you're excited about this, and it's probably too
00:25:21.380
And, and so what scenario planners do is they tell multiple stories so that we can kind of
00:25:28.060
And one kind of shorthand way to do this, which I think is pretty cool is you're facing
00:25:34.100
Tell three stories about, you know, the option you're looking at.
00:25:38.440
One where things get better, one where things get worse, and one where things get weird.
00:25:42.820
And I, and I think there's something like the, the exercise of trying to imagine what
00:25:48.060
the weird scenario would be, even if, again, even if it doesn't come to pass, it forces
00:25:53.660
you to kind of get outside of your expectations and to challenge your assumptions and to, and
00:25:58.100
to perceive new possible futures that you might not have otherwise imagined.
00:26:02.860
And I imagine the, the mapping and predicting steps, like they're not discreet, like they're
00:26:09.240
Like you mapped, then you start doing the prediction stuff, doing some, the storytelling
00:26:12.980
or red teaming, for example, in the military, where you kind of play this out, simulating
00:26:18.400
Then you like actually start seeing new stuff pop up that you otherwise wouldn't have seen
00:26:25.260
I think there is an inevitable kind of bleeding back and forth, but I think trying to keep
00:26:29.200
yourself in that framework in general, where you're like going through the, it, it also,
00:26:34.420
a lot of this depends on your kind of temperament and your thinking style, right?
00:26:39.040
Some people are very organized and they really want to have the, the, the phases.
00:26:43.880
Some people are more creative and the lines are going to be blurrier.
00:26:46.740
It's also another kind of group of people that actually I didn't really address in the
00:26:50.700
book, but it's come up a lot in kind of book tour conversations, which always happens with
00:26:55.760
There's something you've, something in your blind spot that you didn't see in your writing,
00:26:58.700
but, but people who are, um, who, who suffer from the kind of opposite problem, who
00:27:03.360
were, who spend too much time deliberating generally in the book and making the argument
00:27:07.760
for slowing down and trying to see all the different variables.
00:27:10.940
But there is this class of people who get paralyzed because they just want to, you know,
00:27:16.720
And for those people, I think actually the phases are really nice because you can kind
00:27:19.820
of use them as a way of delineating or demarcating basically stages and making the choice like,
00:27:25.800
okay, look, I'm going to spend a week mapping this thing and I'm going to spend a week predicting
00:27:31.600
And then I'm going to spend the last week actually making the decision.
00:27:34.020
And then I'm going to be done with it and having that clarity to the pro like having
00:27:39.280
a distinct process with kind of markers over time, I think can really help people like that
00:27:44.700
who tend to get just stuck over overthinking everything.
00:27:47.920
So when you're making the prediction, like, what are you looking for?
00:27:50.460
Are you just looking for like things that will, are more likely to happen based on all
00:27:54.740
the scenarios you run, the storytelling you run, or are you just, I mean, cause like you
00:27:59.500
have to use those predictions to ultimately make that decision.
00:28:02.720
I mean, this is one of the things that's really, the human beings are really bad at
00:28:06.740
There's a great line from, um, Tversky who, you know, did all the work that led to
00:28:15.480
And he has a line about humans that he says humans are probability that human beings basically
00:28:29.340
And so trying to kind of really imagine like thinking rigorously about like, okay, what
00:28:33.680
is the likelihood that, that, that this comes to pass?
00:28:40.800
Like, or how confident do I feel about this outcome?
00:28:43.800
Like, I think this can happen, but I really don't know.
00:28:46.340
Like trying to like measure those things in the way that we predict is really important.
00:28:50.140
And then the other thing with certain kinds of choices that is very important is kind
00:28:55.220
of low probability, but highly catastrophic outcomes.
00:29:01.680
So I have a whole riff in the book about the way that the kind of the algorithm that Google's
00:29:05.640
self-driving car project uses in making all these kind of short-term decisions as it's
00:29:10.720
And one of the things that it does is constantly looking at the situation and saying, here are
00:29:13.900
the various things that could happen given where I am in the road.
00:29:16.580
And it ranks them both in terms of probability, but also in terms of, I think they call it
00:29:21.220
risk magnitude, like how bad would it be if this happened?
00:29:24.440
So there's a high probability if I swerve a little bit to the right here that I will
00:29:28.420
ding the car to the right and scratch, you know, the side of my door.
00:29:32.040
There's a very low probability that if I swerve a little bit to the left, that I will kill a
00:29:36.060
pedestrian in the sidewalk, you know, to my left.
00:29:39.420
And, but that is a huge, has a huge risk magnitude, right?
00:29:44.360
So even if it's very low probability, I'm going to avoid that.
00:29:47.600
And so there, there is a whole other sets of, sets of exercises you can do if you're
00:29:52.720
inclined to do this kind of thing of kind of mapping out, you know, what is, are there
00:29:56.600
any really catastrophic downsides to one of these paths that I should, you know, that
00:30:01.300
are, that are so catastrophic that even if they're low probability, I should avoid them.
00:30:06.020
You have the example of, should we send signals out to aliens?
00:30:08.600
Like low probability, but the cat, it could be catastrophic if they, they answer.
00:30:15.380
Well, I got, I went down a crazy rabbit hole with that.
00:30:18.880
I wrote a long piece for the times magazine about this.
00:30:20.840
This is the question of, should we act instead of just listening for signals from outer space?
00:30:25.760
Should we, now that we've identified planets that actually are out there that might potentially
00:30:32.140
harbor life, should we be targeting those planets with messages saying, hey, we're here, we're
00:30:36.240
humans, we're on earth, you know, are you, are you, are you living at this address?
00:30:41.400
And there's a lot of people who think we should.
00:30:43.520
And then there are a lot of people think, oh my God, we're going to get, you know, they're
00:30:46.120
going to immediately like kill us with a death ray of some sort.
00:30:48.840
You know, Elon Musk is very worried about this.
00:30:50.660
Stephen Hawking was very worried about this before he died.
00:30:53.380
And I found that a very interesting kind of choice because one, it deals with the existential
00:30:58.200
threats or risks as we were talking about, but two, it's the ultimate long-term decision
00:31:03.200
because the transit time for that information, given the speed of light, in some cases we're
00:31:08.880
talking about, you'd make the choice to send the message and the consequences of that choice
00:31:14.140
would not be visible for like 10,000 years or 50,000 years or something like that.
00:31:19.080
So I think it may be the longest term decision that human beings are capable of making.
00:31:24.900
I can't think of another choice where there would be an actual result that would kind of
00:31:28.520
show up 50,000 years later, like, hey, we figured out, you know, whether this turned out well
00:31:36.620
Anyhow, that's a whole, there's a longer version of that, but it's fascinating kind of
00:31:41.460
the astronomy of it and the astrophysics of it all is pretty interesting as well.
00:31:45.720
Well, I want to go back to a point you made earlier about one thing we can do to sort of
00:31:51.860
So we can do the mapping where we're trying to see more options than we otherwise thought
00:31:56.580
Then we can do some prediction where we run some scenarios out, maybe do some red teaming,
00:32:01.060
maybe, you know, actually just maybe do an experiment.
00:32:03.660
Like if you're a startup, you maybe just do a little ad player, right?
00:32:08.740
But then, you know, making the decision itself, you are, you talked a lot about reading novels
00:32:14.680
can actually help us fine-tune our ability to make decisions.
00:32:19.100
How can reading, you know, I'm right now, I'm reading, what am I reading right now?
00:32:25.160
How can reading Comanche Moon help me make better decisions?
00:32:28.640
Well, you know, it's funny, like, there's one of those things where you write a book and
00:32:32.240
you suddenly, you know, it creates this lens that you look at everything through.
00:32:36.460
But one of the things that I realized in writing the book is that so many of the best points
00:32:43.080
in stories, in novels, but also I've been thinking about this a lot in terms of, you
00:32:48.800
know, in a way, the equivalent of the novel in our age, which is, you know, great long
00:32:53.220
format television shows, you know, The Wire and Mad Men and Sopranos and all those shows
00:32:59.240
is the moments where you really, you know, are leaning forward and just like being drawn
00:33:04.840
into the narrative is when a character faces a complicated choice and a full spectrum choice.
00:33:10.940
You know, the better, one of the ways in which we evaluate, I think, implicitly great narratives
00:33:15.860
is like, does it bring in the full range of human experience in the choices the characters
00:33:23.200
And if it doesn't, then it's just kind of superficial and not that interesting.
00:33:27.140
And so we were, for instance, again, this is TV, not novels, but we've just been watching
00:33:32.400
Friday Night Lights, the great, you know, kind of Texas football show, one of the greatest
00:33:37.280
And we're watching it with our kids, with our teenage kids.
00:33:39.760
And it's an amazing show to watch for them because every episode, someone, in fact, normally
00:33:46.140
often multiple, you know, characters are like wrestling with a hard choice where there's
00:33:50.400
pressure from their peers or the town is doing something or they're trying to stay true
00:33:55.000
to their ethics, but they're challenged because of their situation or the, you know, and it's
00:34:00.420
just, and I, you know, I was in the middle of writing Farsighted as we were doing this
00:34:04.800
and I was like, yeah, this is such a great show because we watch these people and often
00:34:08.260
what they end up doing, the, like, the thing that makes the narrative interesting is that
00:34:13.860
they figure out an original surprising solution to the, to the choice that they were, that,
00:34:20.260
that, that hard choice that they confronted and seeing somebody make a creative solution
00:34:26.200
that solves the, the, the problem that they're wrestling with is that's the payoff, right?
00:34:30.680
Instead of being like, oh, you know, it's a chase scene and he escaped from the bad guy.
00:34:34.540
It's like, oh, you know, the coach figured out a way to keep that player on the team while
00:34:39.400
still managing his relationship with his wife and what, you know, like, and that's, it's
00:34:44.860
And, and in a novel, I think a novel can do that even in some ways better because it
00:34:49.720
gives you access to the interior life of a character.
00:34:54.260
I talk a lot about Middlemarch, arguably like the greatest novel ever written in the English
00:35:00.200
And you see, there's a big choice at the center of it that Dorothea Brooke has to make.
00:35:04.320
And you see her, because Elliot is such a brilliant novelist, you see Dorothea wrestling with
00:35:10.380
And I just think what that does is, as I said, kind of at the beginning of the, our
00:35:14.900
conversation, you know, we're, when we, when we see great fiction or narrative like that,
00:35:22.000
the choices that people are making are not themselves our choices, right?
00:35:28.180
We're not, most of us are not high school football coaches or whatever, but when we run
00:35:33.300
these kinds of simulations of other people's lives, and particularly when we can see into the
00:35:38.560
kind of inner monologue that people have when they're making a complicated choice, those
00:35:42.740
simulations just, it's almost like going to the gym, right?
00:35:46.180
It's like an exercise of your mind, like practicing making choices, thinking about all the
00:35:50.380
implications so that we then turn to our own lives.
00:35:55.040
So I think that's, I mean, that's one of the great arguments for having stories, I think,
00:36:00.700
in our lives, having complex stories is that we get, is that we get a, it gives us a kind
00:36:08.560
You use the Osama bin Laden raid that happened a couple of years ago as an example, as the
00:36:13.780
case study of an organization, a large organization, multiple organizations using this process you
00:36:20.660
I mean, can you highlight some of the things that they did, for example, to map and how
00:36:23.840
they take those mappings to make predictions and then make that decision ultimately?
00:36:28.340
Yeah, I wanted to put that story in there because, you know, we tend to celebrate the
00:36:32.880
results of great decisions for understandable reasons.
00:36:37.060
Like in that case, the result of the decision was a daring moonlit raid, you know, over Pakistan
00:36:45.680
where they actually do manage to kill the great villain of our time.
00:36:50.020
And so it's understandable why you would celebrate that part of it.
00:36:53.020
But before that set of events happened, something else critically important had to happen, which
00:37:00.940
is, is that people had to make the decision of what to do.
00:37:05.420
They had to decide, is this mysterious figure that we've identified in this, you know, compound
00:37:11.500
in Pakistan outside of Abbottabad, is that Osama bin Laden?
00:37:16.320
And then once they reached reasonable confidence that they thought that it was, what should we
00:37:30.580
And that process was like a nine-month process.
00:37:33.400
And it was explicitly considered, you know, as a process using, as you said, a lot of the
00:37:47.880
That's, that was, that was the thing that set up the whole success of the raid is that
00:37:52.220
they had gone through and looked at all the different options and thought about it really
00:37:55.480
And unlike earlier military decisions like, you know, weapons of mass destruction in the
00:38:02.580
Iraq war or Bay of Pigs or the rescue attempt to the hostages in Carter, in the Carter
00:38:09.520
administration, they, they specifically tried to challenge their assumptions.
00:38:14.140
They had a kind of an initial mapping phase where, for instance, they, they had one kind
00:38:19.660
of brainstorming process where they were trying to just like come up with as many possible
00:38:23.760
crazy ways that they could figure out of identifying who this mysterious guy was in the compound.
00:38:29.420
And if you read the list of them and that's kind of reproduced in the book, it's, some of
00:38:35.200
They're like going to like set up a loudspeaker system to say like, this is the voice of Allah,
00:38:41.520
like leave the compound, like, you know, like that would have never worked, but they were
00:38:46.160
in that kind of divergent stage where they were trying to just propose ideas to, to get around
00:38:54.220
And then the other thing was, and this is really important in kind of group decisions.
00:38:59.520
They, they went through a number of different exercises to challenge, um, their assumptions
00:39:05.160
and to, and to make sure that they weren't victims of groupthink where everybody gets around
00:39:09.200
the room and people just naturally have a tendency to kind of align with each other and whatever
00:39:13.860
seems like the most likely explanation, the room kind of gravitates towards that.
00:39:18.300
And people get increasingly confident that, that, that choice is the right one.
00:39:21.960
And so they were constantly like being asked to challenge their assumptions, to evaluate
00:39:26.800
their, their confidence, all the things that we've talked about, um, at every step of the
00:39:31.660
And I, and I just, I wanted to spend some time with that narrative one, because it, it's a,
00:39:37.340
it's a great story and it creates a little bit of a through line through the book, but
00:39:41.140
it's also like, if you think about the, the, the, the questions we ask when we elect our
00:39:50.140
leaders or when we're contemplating who should be our leaders in government or in a, in a
00:39:54.820
business or whatever, like, you, you know, I watched a lot of the presidential debates.
00:39:59.620
I've watched many, many presidential debates in my life.
00:40:02.080
And I don't remember anyone ever saying as a question, how do you go about making decisions?
00:40:09.980
And if you think about it, like that is the most important part of the job, right?
00:40:14.420
You're going to elect someone who's going to make decisions in governing the country and,
00:40:19.440
uh, they better make them, but they better be good at it.
00:40:23.300
If they're bad at making decisions, they shouldn't be running the country.
00:40:25.820
And so I wanted to kind of focus on that as an example of like leaders that actually did
00:40:31.060
go through these exercises and did use that kind of deliberative process.
00:40:34.760
And, and in a case where there was actually a really positive outcome in the sense that
00:40:39.600
the, the goals, most Americans, I think would agree were, were realized.
00:40:45.120
Well, Stephen, this has been a great conversation.
00:40:47.000
Where can people go to learn more about the book and your work?
00:40:49.120
Well, I have a, you know, kind of a old fashioned website at, at stephenberlinjohnson.com hosted
00:40:55.780
at medium, but just Stephen Berlin Johnson, like this is my middle name, Berlin, like the
00:41:03.540
And, uh, those are, those are good places to start.
00:41:12.400
He's the author of the book Farsighted, How to Make the Decisions That Matter the Most.
00:41:16.260
It's available on amazon.com and bookstores everywhere.
00:41:18.360
You can find more information about his work at his website, stephenberlinjohnson.com.
00:41:23.360
Also check out our show notes at aom.is slash farsighted, where you can find links to resources
00:41:41.480
Well, that wraps up another edition of the AOM podcast.
00:41:44.200
Check out our website, artofmanliness.com, where you can see all of our podcast archives
00:41:48.960
And you can find thousands of articles on just about anything, how to make better decisions.
00:41:52.240
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00:42:09.400
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