The Art of Manliness - #486： How to Get Better at Making Life-Changing Decisions

00:00:00.000 Brett McKay here and welcome to another edition of the Art of Manliness podcast.

00:00:18.760 How do you make the biggest decisions you face?

00:00:20.900 The ones that have significant consequences and can change your life.

00:00:24.040 Choices like whether to get married, move, attend a certain college, take a particular

00:00:27.800 job and so on.

00:00:28.780 If you're like most people, you just kind of wing it and maybe draw up a basic pros and

00:00:32.840 cons list.

00:00:33.500 My guest today has studied the latest research in decision-making theory and has formulated

00:00:37.040 a better approach.

00:00:38.180 His name is Steven Johnson and his latest book is Farsighted, How to Make the Decisions That

00:00:42.260 Matter the Most.

00:00:43.060 And today on the show, he walks us through how to move beyond listing pros and cons to

00:00:46.760 using a more effective three-step decision-making process.

00:00:49.740 We begin our conversation discussing how most people make decisions and how it hasn't changed

00:00:53.540 much in hundreds of years.

00:00:54.640 Steven then walks us through the phases of a better decision-making mythology, including

00:00:58.540 developing a more creative map of the possibilities before you, accurately predicting the outcomes

00:01:02.660 of those options, and questioning the narratives you have about your choices.

00:01:05.900 Steven then makes the case that reading novels and watching quality television shows can be

00:01:09.440 a great way to train our brains in the skill of decision-making.

00:01:12.240 And we end our conversation discussing what the raid on Osama bin Laden can teach us about

00:01:16.500 making good decisions.

00:01:18.060 After the show's over, check out our show notes at aom.is slash Farsighted.

00:01:22.200 Steven joins you now via clearcast.io.

00:01:33.520 Steven Johnson, welcome to the show.

00:01:35.920 Hey, thanks.

00:01:36.580 I'm delighted to be here.

00:01:37.800 So you got a new book out, Farsighted, How We Make the Decisions That Matter the Most.

00:01:42.220 Curious, how did you get started thinking about decision-making or the philosophy and science

00:01:47.020 of decision-making?

00:01:47.520 Because you've written all about where ideas come from, this idea of emergence.

00:01:52.200 You know, how we, innovations that got us to where we are now.

00:01:54.720 What got you thinking about decision-making?

00:01:57.200 You know, this project I have been working on for a really long time.

00:02:00.380 It's actually the longest kind of incubation period of any of my books, which is maybe appropriate

00:02:05.660 for a book that in some ways is about long-term thinking and decision-making.

00:02:09.480 But I started actually working on it originally right after my book, Where Good Ideas Come From,

00:02:14.700 came out about the patterns of innovation.

00:02:17.680 I think I started taking notes on it in 2011 or something like that.

00:02:22.320 And it was really sparked by two things.

00:02:25.200 One, a story from history and one, a story from my own personal life.

00:02:30.080 The story from history is this, in Where Good Ideas Come From, I had a whole long riff about

00:02:34.580 Darwin and his notebooks.

00:02:36.960 And, you know, there are these incredible personal notebooks that Darwin maintained, particularly

00:02:42.320 during the 1830s, late 1830s, as he was developing the theory of evolution.

00:02:46.900 And it's a beautiful case study and watching a mind kind of come up with a radical new idea.

00:02:52.880 And that's why I'd written about it.

00:02:53.940 But I knew from that research that there's a kind of a comical moment in those notebooks

00:02:58.040 where Darwin takes up two facing pages of his notebooks, kind of interrupts his scientific

00:03:03.040 musings and starts wrestling with another question, which is a little bit more intimate,

00:03:07.760 which is, should he get married?

00:03:09.560 And he basically creates this pros and cons list of, you know, pro-marriage and anti-marriage.

00:03:17.180 And it's kind of comical.

00:03:19.960 And it's funny to read it now because some of them are kind of like, well, if I get married,

00:03:24.220 I might have children.

00:03:25.240 But on the other hand, he says, I might have to give up the clever conversation of men in

00:03:30.040 clubs, which I thought was pretty funny.

00:03:32.820 But I thought about it.

00:03:33.760 It was like, you know, the pros and cons list is the one technique that most of us actually

00:03:38.200 learn in adjudicating a complicated choice in our lives.

00:03:43.200 And here it was, you know, almost 100.

00:03:45.900 That was 1837, 1838 when he was doing that.

00:03:48.580 And so here we are, you know, 150 years later, and we're still using the same technique.

00:03:53.620 And so I was like, surely there must be, you know, some interesting science and research

00:03:58.680 into how to make complicated decisions.

00:04:00.500 And maybe they're better tools than just making a pros and cons list.

00:04:05.600 And the personal story was right at that point in my life, I was wrestling with my wife with

00:04:13.120 this equally complex choice, which is we were, I had, as my kind of version of a midlife crisis,

00:04:18.880 I had gotten obsessed with the idea that we should move to the West Coast.

00:04:22.100 We'd lived in New York our entire adult lives.

00:04:24.300 And I was getting sick of winter and needed more nature in my life.

00:04:28.980 And so I really wanted to move to, you know, the Bay Area.

00:04:31.660 And I tried to persuade my wife that we should make this big momentous choice for us and for

00:04:37.720 our kids.

00:04:39.240 And she was appalled at this idea.

00:04:42.200 It was not something she wanted to do at all.

00:04:43.820 All her friends are in New York, whatever.

00:04:45.040 And we had this along back and forth.

00:04:46.640 And I started thinking about, like, you know, how do we make these kinds of, that's a choice

00:04:52.540 that the consequences of which will, you know, reverberate for decades, you know, in both

00:04:58.820 our lives and our kids' lives.

00:05:00.360 And how do you make a choice like that?

00:05:02.300 What's the best approach when the stakes are so high?

00:05:05.900 And so I put those two things together.

00:05:07.360 And then I figured there would be a really good book to write about that.

00:05:10.640 And then I kept getting distracted with other projects.

00:05:13.960 And I kept taking notes in the background for it and finally, finally put it kind of

00:05:18.140 front and center a couple of years ago.

00:05:19.700 And here we are.

00:05:21.040 Well, yeah.

00:05:21.200 As you said in the book, this is an important topic because every day we're making decisions,

00:05:25.720 like small ones, but even really big ones that will affect the rest of our lives.

00:05:29.420 Like, where do I go to college?

00:05:30.960 Should I take out a loan?

00:05:32.500 Should I buy a house?

00:05:33.640 What job should I take?

00:05:35.240 And no one really tells you how to go about making these decisions.

00:05:38.920 You just sort of, you sort of wing it oftentimes.

00:05:41.540 Sometimes I think you don't even actually make a decision where there should be a decision

00:05:47.520 made, right?

00:05:48.240 I mean, for instance, where do you live, right?

00:05:51.680 I mean, in our case, we had a period of time where we actually put that front and center

00:05:57.060 and said, you know, let's decide what city, what part of the country, you know, suburbs

00:06:03.660 versus city, countryside, you know, all that kind of stuff.

00:06:06.300 What country do we want to live in?

00:06:07.420 Like, we actively had a decision about that.

00:06:09.060 But I think actually most people don't have a kind of crossroads moment in their life

00:06:13.860 where they really decide where they want to live.

00:06:16.500 It just is something that happens to them, you know, that they stay at home where they

00:06:21.560 were born or they, you know, stay where they, if they go to college, they stay near their

00:06:26.720 college or they move somewhere kind of accidentally when they're 22 and they get stuck there.

00:06:31.040 And so some of the most important choices in life, we don't even make, which is, which

00:06:36.700 is weird.

00:06:37.100 So, so trying to recognize and also trying to differentiate between the choices, as you

00:06:43.700 say, that we do make day in and day out that actually aren't that significant, that don't

00:06:47.720 require the kind of deliberation that I'm talking about in the book and the techniques that I

00:06:51.820 talk about in the book.

00:06:52.640 Like, it's fine to make, you know, what you're having for dinner or even, you know, 99% of

00:06:57.860 the decisions you make at work don't require this much thought.

00:07:01.460 But when you do confront a choice that really does have significant long-term consequences,

00:07:06.520 to take time out to do some of the exercises that I talk about in the book, I think is a

00:07:11.480 really healthy thing to do.

00:07:12.440 And you give this great example to start the book off of decisions being made that have

00:07:17.220 had lasting consequences, but people weren't really making decisions.

00:07:20.720 They were just doing whatever they thought was the next best thing.

00:07:24.560 And this is the story of Collect Pawn in Manhattan.

00:07:27.580 Yeah.

00:07:28.000 Yeah.

00:07:28.260 So I should say the book is both about personal intimate decisions, like should I get married

00:07:34.340 or should I move to California?

00:07:35.700 And also group decisions, collective decisions, business decisions, but also planning.

00:07:40.060 There's a lot of urban planning in the book, for instance.

00:07:42.020 And that's why I started with this story about Collect Pawn.

00:07:44.600 It's a crazy story.

00:07:45.660 So there was for many, many years, for centuries, for millennia, there was a freshwater pond in

00:07:52.680 lower Manhattan, what became Manhattan, which was actually really the only major source of

00:07:57.620 drinkable water in lower Manhattan because the East River and the Hudson River are tidal

00:08:02.760 estuaries, so they're very salty.

00:08:04.480 And the Native Americans who lived there and then the early Dutch settlers, you know, relied

00:08:09.680 on Collect Pawn for drinking water.

00:08:11.340 And it was apparently very beautiful.

00:08:12.800 There was a kind of a rocky hillside next to it and people would skate on it in the winter.

00:08:18.140 And it was a kind of lovely part of early New York life.

00:08:21.940 But, you know, New York being what it was and continues to be, people started, you know,

00:08:26.280 dumping their garbage there and old dead, you know, barnyard animals and the occasional

00:08:31.760 murder victim.

00:08:32.520 And some tanneries opened up that started polluting it with chemicals and all that stuff.

00:08:37.820 And so by the 1770s, 1780s, it was just, you know, a stinking hole, basically, as it was

00:08:44.220 described at the time.

00:08:45.720 And so basically the city tried to decide whether, like, maybe we should turn it into a park.

00:08:51.100 But they were like, oh, no one will ever, it's too far north.

00:08:54.580 No one will ever live around that place, which was ridiculous because this is like, if you know

00:08:59.040 Manhattan, this is, you know, below Canal Street, basically.

00:09:02.120 And so they kind of trashed their plans to build a park.

00:09:04.820 And then they basically just decided to fill it in and get rid of the pond.

00:09:08.360 And they built some houses over it, but they'd done a poor job at the landfill and the houses

00:09:13.340 started to kind of decay and all these noxious smells came out and people fled from the neighborhood.

00:09:18.040 And that neighborhood became the legendary Five Points neighborhood, the first kind of

00:09:22.280 famous slum in New York City where Gangs of New York was set and all these things.

00:09:26.960 And it was all because they just kind of didn't know what to do with this beautiful natural

00:09:30.580 resource.

00:09:31.000 And if they had built that park, that would be today one of the great urban parks in the

00:09:36.280 world, right?

00:09:36.780 And it probably would have survived for 500 years or longer, this beautiful lake in the

00:09:42.000 middle of lower Manhattan.

00:09:43.140 So you can think of it almost as like a 500 year mistake that they made that they failed

00:09:48.220 to capitalize on this wonderful natural resource.

00:09:51.180 And part of what I'm trying to argue in the book is actually as pessimistic as we can sometimes

00:09:57.000 be, we wouldn't make that same mistake as cavalierly as we did back in the 1790s, early 1800s.

00:10:06.780 You know, we are actually better at kind of planning decisions like that and looking at natural

00:10:12.840 resources in big cities.

00:10:14.260 And we've advanced the art of making those kinds of choices in many ways.

00:10:18.900 And all of us can learn from the way in which we've advanced that art and that science.

00:10:23.780 Well, before we get to some of the advances we've made in decision making theory, let's

00:10:28.100 talk about sort of the development of that.

00:10:29.280 So you mentioned for most of human history, probably we've been using the pros and cons

00:10:33.180 list.

00:10:33.800 But you also highlight cases of individuals who were getting a little more sophisticated

00:10:38.560 with their decision making.

00:10:40.080 For example, Benjamin Franklin sort of developed a decision calculus when he was a young man.

00:10:44.260 Yeah, he called it moral algebra, which is actually the title of the first chapter, which

00:10:49.960 I think is such a great phrase.

00:10:51.200 But he basically proposed a pros and cons-like list.

00:10:55.580 But he had one correction to it, which is really important, which is he had a kind of a

00:11:01.880 rudimentary scheme for what we now call weighting, i.e. giving a weight to each of the values that

00:11:09.520 are listed in your pros and cons list.

00:11:12.420 Because the problem with the pros and cons list, if you're just like write up a list

00:11:15.520 of pros and write up a list of cons, you know, and whichever one is longer, that gives you

00:11:20.460 your answer.

00:11:21.440 That doesn't really work because presumably some of the things on the list are more meaningful

00:11:25.720 to you or more consequential than other things on the list.

00:11:28.960 So think about Darwin's pros and cons list.

00:11:31.300 Having children, presumably, was more important to him than clever conversation of men in clubs,

00:11:37.660 right?

00:11:37.940 I mean, maybe he really liked this conversation, but I think knowing what we know about Darwin,

00:11:42.680 he was actually more interested in the kids.

00:11:45.920 And so when we kind of list the different kind of assets, we can't have them all have

00:11:52.740 the same magnitude or the same weight, right?

00:11:55.280 We have to have some way of measuring that.

00:11:57.840 Franklin proposed this system where you create your list and then you kind of cross out ones

00:12:02.580 that are equal in weight to you.

00:12:05.040 And then you look at the remaining ones.

00:12:06.620 But that actually doesn't, that helps a little bit, but it doesn't really get to the issue.

00:12:11.260 So they're now much more advanced versions in a sense where you give a score to each

00:12:15.880 of the different values that you've ranked.

00:12:17.440 And you say, okay, this one is like, you know, on a scale of one to 10, this one's a nine,

00:12:20.840 this one's a two.

00:12:21.720 It's important, but it's not that important.

00:12:23.260 And the other problem with the pros and cons list is it really only works well when you're

00:12:28.160 looking at one option, right?

00:12:30.580 Should I get married or not?

00:12:32.460 But what if you're looking at a choice where there are five options?

00:12:35.320 The pros and cons list effectively doesn't scale up to handle a choice with multiple variables,

00:12:42.540 multiple alternatives.

00:12:43.960 But you can't do that with a weighted scale.

00:12:46.660 Yeah.

00:12:46.920 Yeah.

00:12:47.200 There's a technique that I talk about at the end of the book that's sometimes called a

00:12:53.080 values model or linear values model that is actually used in environmental planning,

00:12:58.020 urban planning in some cases.

00:12:59.760 And it's the kind of thing you actually really build in a spreadsheet.

00:13:03.480 It's funny.

00:13:03.860 You know, sometimes there's some choices in life, like, should I get married?

00:13:06.940 Where maybe you don't want to create a spreadsheet and sit there.

00:13:10.640 But if you were Darwin, you probably would.

00:13:12.220 Yeah.

00:13:12.580 Sit your perspective spouse down and say, look, darling, I've run the numbers here and it

00:13:16.200 looks very promising for us.

00:13:18.340 But other decisions I think can be like that.

00:13:20.040 Like, where should we live?

00:13:21.120 I think is one of the things.

00:13:22.160 And so what you do is like, you create, you know, a list of all the different places you

00:13:25.580 might want to live.

00:13:26.580 And then you create a list of the values that are important to you in your life.

00:13:30.200 And then you kind of score each of those values in terms of how important that value is.

00:13:36.300 Like, you know, happiness for, you know, access to nature is more or less important than good

00:13:41.300 schools, et cetera.

00:13:43.040 And then for each of the options you're looking at, you give it a score for each of those values.

00:13:48.640 You say, hey, I think, you know, if we move to the country, we'll have more access to nature

00:13:52.860 and, you know, much worse restaurants.

00:13:54.820 And you score it all out.

00:13:56.220 And then you basically multiply, you know, the weight or magnitude of each value by the

00:14:01.680 score for each option and add it all up and you get an answer.

00:14:04.940 It's not always the, for some people, I think that kind of approach is maybe too mathematical

00:14:12.200 for an important life choice.

00:14:13.980 And it's maybe not the last stage of the process, but it's a way of visualizing all the things

00:14:19.940 that are at stake in a complicated choice.

00:14:21.820 And in the book, I call them these kinds of choices, I call them full spectrum choices

00:14:25.820 because they involve so many facets of what it is to be alive, right?

00:14:31.880 I mean, where you live, right?

00:14:33.820 That involves your economic issues.

00:14:36.380 That involves, you know, the future education of your kids.

00:14:39.840 That involves things like nature and your friends and your politics.

00:14:44.760 Like, do you want to live in a sidewalk culture or a car-centric culture?

00:14:47.980 I mean, just all these different elements and it's just really hard to keep all that

00:14:51.820 kind of coherent in your head.

00:14:53.720 And so creating a kind of matrix or grid like this and in a sense kind of running the

00:14:58.840 numbers on it, I think is a really good tool for helping you see it all in one place.

00:15:04.100 And there's also like with complex, well, with these complex decisions, there are second

00:15:07.500 order and third order consequences that you don't think about, right?

00:15:10.300 With like the collect ponds, like, well, if we throw in the dead animal carcass, they don't

00:15:14.860 think, well, the water's not going to be drinkable and then they don't think, well, the water's

00:15:18.620 not drinkable to cover it up.

00:15:20.040 And then if we had to cover it up, then we build houses, but then the houses are going

00:15:22.760 to sink.

00:15:23.600 You don't think about those things typically.

00:15:26.120 You know, this is one of the things that I didn't fully wrestle with when I first came

00:15:30.420 up with the idea for this book that became increasingly important to me as I researched

00:15:34.720 it and wrote it, which is that really when you're making a complex long-term decision,

00:15:40.360 whether it's, you know, a civic decision or a personal decision or a business decision,

00:15:46.380 a huge part of it is about predicting the future, right?

00:15:50.040 It's, you know, this book is like a third of it is about prediction because anytime you're

00:15:56.200 making a choice like that, you're making a prediction.

00:15:57.820 I think if I choose this, that in five years, things will turn out this way.

00:16:03.020 And so I got, it sent me down this whole rabbit hole of like, okay, well, what do we know about

00:16:07.420 prediction?

00:16:07.800 What are the places where people have gotten better at predicting?

00:16:11.560 And there's a lot of great, I mean, if you could write, many books have been written,

00:16:15.220 in fact, about how we predict and how bad in general we are at predicting the future.

00:16:19.640 But as you say, a lot of that prediction process is trying to imagine consequences that don't

00:16:29.140 initially appear to you.

00:16:31.400 There's a great quote, one of my favorite quotes in the book from Thomas Schelling, the Nobel

00:16:34.740 Laureate, who, among other things, kind of half invented game theory and other things.

00:16:39.500 He has this great quote that more or less is, the one thing a person cannot do, however

00:16:44.640 brilliant they are, is write up a list of things that would never occur to them.

00:16:50.380 And I love that because that is, in a sense, what you're trying to do when you're making

00:16:54.760 a really complicated choice.

00:16:56.080 It's like, okay, I know there's a blind spot here.

00:16:59.160 There's something in the future that I'm not anticipating, that I'm going to choose this

00:17:02.920 path and I'm going to get blindsided by this development down the line.

00:17:07.240 And so part of it is just going through these exercises to try and see around those blind 1.00

00:17:11.820 spots.

00:17:12.240 And to get better, you can't, no one has a perfect crystal ball, but there are techniques

00:17:16.880 that make people more aware of the alternatives and potential consequences than they would just

00:17:20.980 with their initial impression.

00:17:22.580 So you said that we're getting better at decision making.

00:17:24.320 We'll talk about some of the ways we've gotten better in some case studies, but where is

00:17:28.940 this thinking happening?

00:17:30.240 Where is the development of these processes happening?

00:17:32.900 Is it interdisciplinary?

00:17:33.920 Is it a cross between behavioral science, economics, game theory, philosophy?

00:17:38.320 What's going on there?

00:17:40.080 This is one of the reasons why the topic was so interesting to me because I do tend to work

00:17:45.260 in a very multidisciplinary way.

00:17:47.840 And part of what I try and do in my books is to show connections between disciplines.

00:17:52.420 You know, they tend to jump around.

00:17:54.460 Actually, it's funny, when I was a kid, not a kid, when I was in college and I knew that

00:17:57.780 I wanted to write books, I used to tell people like, I'm going to write these books that are,

00:18:02.960 you know, jump around from discipline to discipline and no one will know where to put them in the

00:18:07.000 bookstore because they won't fit any category.

00:18:09.460 And then I ended up growing into that person and becoming that kind of author.

00:18:12.660 And I realized now that's a terrible way to write books because nobody knows where they're

00:18:16.980 supposed to go in the bookstore and nobody knows where to find them.

00:18:19.040 But it turns out with decision theory, it does draw upon all these different kinds of

00:18:25.480 disciplines.

00:18:26.340 There's a bunch of kind of management theory, right?

00:18:28.260 There's a bunch of, you know, the one place where people are taught how to make decisions

00:18:31.980 is sometimes in business school.

00:18:35.220 But there's a lot of research from, you know, psychology and kind of group psychology, some

00:18:40.800 interesting findings from hardcore kind of neuroscience, like about how the brain actually makes

00:18:45.360 decisions and, and also, you know, philosophy and literature.

00:18:48.520 There's a lot of wonderful kind of probing look kind of analyses of people making decisions

00:18:55.000 that show up in fiction and novels.

00:18:57.520 And I think there's a lot to learn from those kinds of interior portraits of, of other people,

00:19:02.520 even if they're made up.

00:19:03.600 Watching somebody else through the lens of a great novel, making a choice is, is a wonderful,

00:19:08.900 it's almost kind of practice for us to, to rehearse the decisions that we actually make in our

00:19:14.360 own lives by reading, by reading novels.

00:19:16.720 We're going to take a quick break for your word from our sponsors.

00:19:20.080 And now back to the show.

00:19:21.860 Yeah, we'll get into that little tactic to make better decisions, but let's talk about

00:19:25.180 sort of broad overview of this process that you found that you're, you, you see happening

00:19:29.900 when groups or individuals are making complex decisions.

00:19:33.800 So this first process, you call it mapping.

00:19:36.420 What does that look like?

00:19:38.460 So, you know, mapping in a way we've, in a sense, begun to touch on, which is the idea of,

00:19:43.120 look, there's so many different variables and values that are at play in a, in a full

00:19:47.540 spectrum decision.

00:19:48.520 So part of your job in this initial stage is, is not to, is not to try and kind of narrow

00:19:57.800 things down and make your choice.

00:19:59.040 Like have a, have an initial phase where you're just trying to identify as many factors that,

00:20:05.860 that could be relevant to this choice.

00:20:07.720 It's all the different kinds of planes of existence that, you know, would be implicated

00:20:12.200 by moving to California or opening up this new branch of your business or whatever it is

00:20:18.740 you're, you're weighing.

00:20:20.440 But the other key part of this phase that, that most people don't do is to spend time

00:20:26.160 in this opening stage, trying to identify other options that you might not have initially

00:20:32.340 considered.

00:20:32.980 And this, this is based on some, some great kind of management theory research by a guy

00:20:37.560 named Paul Nutt, who was a scholar of corporate decisions in the, in the kind of seventies,

00:20:43.980 eighties, early nineties.

00:20:44.940 And, and he analyzed hundreds and hundreds of actual real world decisions that people

00:20:49.720 made and interviewed people extensively about their process or their lack of process as

00:20:55.760 it normally was.

00:20:56.520 And, and, and then he went back and interviewed people to find out, did the decision work out?

00:21:01.880 Like, were they happy with the results in the end?

00:21:03.560 And what he found was that most people did not have an initial mapping phase where they

00:21:09.400 tried to identify other options to, you know, that they could potentially explore.

00:21:14.660 So the way Nutt described it is most decisions were what he called whether or not decisions,

00:21:21.520 i.e.

00:21:21.880 should we do this or not?

00:21:23.040 It was just one option on the table and it was just a binary choice.

00:21:25.740 Those people in the long run ended up more likely than not to be unhappy with the outcomes

00:21:32.560 of their choice.

00:21:33.840 But there was a subset of people who actually did add this early kind of mapping phase where

00:21:39.240 they tried to, you know, have a really a kind of a creative kind of brainstorming process

00:21:44.140 where they tried to identify other options.

00:21:45.820 Yeah, we're looking at option A, but let's, let's try and identify options B and C and D,

00:21:51.140 and then we'll make our choice.

00:21:52.540 And the folks who did that were more likely than not to be happy with their choice in

00:21:57.460 the end.

00:21:58.060 It's a significant kind of bonus in terms of the outcomes by adding that phase.

00:22:02.660 Even if they ended up going with option A, the one that they'd originally looked at,

00:22:06.440 because they just, they were making a more informed choice.

00:22:08.920 They understood more of the variables by going through this kind of process.

00:22:12.140 So that's, and it's a very simple rule.

00:22:13.740 So, I mean, Nut describes it as change your decision from a which, a whether or not decision

00:22:18.580 to a which one decision.

00:22:20.480 And that it's, it's a very elemental kind of idea.

00:22:23.220 But I think that that's, that's a, it's a great exercise to do in this kind of initial

00:22:27.560 mapping phase.

00:22:29.260 So the initial exercise, just trying to get a big, don't eliminate things, don't eliminate

00:22:33.380 options.

00:22:33.700 You're actually trying to grow options, which I think would be counterintuitive.

00:22:36.680 You're like, well, I'm trying to make a decision.

00:22:37.820 I'm trying to narrow things down.

00:22:39.020 But you're telling me the first step is actually make more choices available.

00:22:43.220 Yeah, it's actually, it has a lot of overlap with some of the stuff that I've written about

00:22:46.840 innovation.

00:22:47.280 It's a similar process that people talk about when you're trying to be creative, that you

00:22:51.120 have a, a divergence and a convergence phase.

00:22:54.600 And the divergence phase is you're not trying to narrow down on, on the final answer.

00:22:58.040 You're trying to just generate options and, and come up with lots of ideas. 0.99

00:23:02.980 No idea is too stupid, that kind of mode. 0.97

00:23:05.000 And then let, you know, and liberate yourself during that period to contemplate lots of different 0.99

00:23:10.020 things and not try and find the answer.

00:23:12.000 And then later on, go back and weed through everything and try and figure out what, what

00:23:15.280 really is the right choice.

00:23:16.740 Are you also in this phase exploring all the possible consequences as well?

00:23:20.760 Are you just looking at possible decisions?

00:23:23.220 That's really, I mean, this could be a good transition.

00:23:25.600 That's, that's really the, the, the prediction phase, right?

00:23:30.180 So you've identified five top kind of contenders for, you know, what you might want to do.

00:23:37.140 Let's say you're moving.

00:23:38.160 And so we've identified these five cities that might be interesting as options that we

00:23:42.400 can move to or, or rural areas, whatever, it doesn't have to be cities.

00:23:46.980 Right.

00:23:47.660 So then, so then you got to think about like, what would happen if we moved to each of these

00:23:51.580 five?

00:23:52.340 And, and that's where you're really moving into a prediction stage where you're kind of

00:23:55.620 analyzing like what really will be the consequences of this path versus this path versus this

00:24:01.840 path.

00:24:02.220 And so that's the, in my book, I kind of shift, there's, there's a shift from mapping to predicting

00:24:06.600 at that point.

00:24:07.760 And once you get to predicting, you're effectively in a kind of a storytelling mode.

00:24:13.520 It's a very narrative process.

00:24:15.700 It's interesting.

00:24:16.980 And in a way, it's a very creative process because you're trying to imagine these, you're

00:24:23.180 trying to make a list of things that would never occur to you as Thomas Schelling put

00:24:26.180 it, you're trying to imagine consequences that might not occur to you originally.

00:24:30.940 And, and there, there are a bunch of useful exercises here.

00:24:34.860 I mean, this is where you draw upon some of the techniques that have sometimes been called

00:24:38.160 scenario planning, right?

00:24:39.580 Kind of a corporate technique where you bring in people to look at the next five years of

00:24:44.700 your market, say, and, or the world that you're selling your products in.

00:24:49.660 And the important thing is that you tell multiple stories in this phase.

00:24:55.680 All of us make predictions when we get excited about something.

00:24:58.320 Like when I was excited to move to California, I had this beautiful story of like, we will

00:25:01.460 take hikes in the Redwoods every day.

00:25:04.140 The children will get outdoorsy and they'll never play video games again.

00:25:08.000 And, you know, that kind of feeling.

00:25:10.280 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

00:25:19.780 negative if you're not excited about it.

00:25:21.380 And, and so what scenario planners do is they tell multiple stories so that we can kind of

00:25:26.220 imagine multiple outcomes.

00:25:28.060 And one kind of shorthand way to do this, which I think is pretty cool is you're facing

00:25:33.240 a choice.

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

00:26:07.260 probably going on all at the same time.

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

00:26:18.040 it.

00:26:18.400 Then you like actually start seeing new stuff pop up that you otherwise wouldn't have seen

00:26:22.700 during the initial mapping phase.

00:26:25.040 Yeah.

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

00:26:55.460 a book.

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,

00:27:15.260 overthink everything.

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

00:27:30.920 this thing.

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.

00:28:01.800 Right.

00:28:02.380 Yeah.

00:28:02.720 I mean, this is one of the things that's really, the human beings are really bad at

00:28:05.500 actually human beings.

00:28:06.740 There's a great line from, um, Tversky who, you know, did all the work that led to

00:28:12.640 Kahneman's famous thinking fast and slow book.

00:28:15.480 And he has a line about humans that he says humans are probability that human beings basically

00:28:20.240 have three settings for probability.

00:28:22.640 It's going to happen.

00:28:24.020 It's not going to happen.

00:28:25.140 And maybe that's like, that's all we can do.

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?

00:28:37.720 Like we're really, is it a 20% chance?

00:28:39.580 Is it an 80% chance?

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

00:29:10.000 driving around.

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. 0.78

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?

00:29:43.280 That's a terrible thing.

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.

00:30:05.560 What are you talking about?

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.

00:30:15.140 Yeah.

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 0.89

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

00:31:32.520 or not.

00:31:33.740 Not my problem.

00:31:34.900 Yeah, not my problem.

00:31:36.100 Wipe my hands.

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

00:31:49.440 fine-tune our decision-making ability.

00:31:51.860 So we can do the mapping where we're trying to see more options than we otherwise thought

00:31:55.720 there were.

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?

00:32:07.420 And you can see if people respond to it.

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?

00:32:22.580 Comanche Moon, Larry McMurtry.

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

00:33:21.540 are forced to make?

00:33:23.200 And if it doesn't, then it's just kind of superficial and not that interesting.

00:33:26.040 If it does, it feels like art.

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

00:33:36.320 TV shows of all time.

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

00:34:43.900 great drama, right?

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

00:34:58.940 language, I would say.

00:35:00.200 And you see, there's a big choice at the center of it that Dorothea Brooke has to make. 0.55

00:35:04.320 And you see her, because Elliot is such a brilliant novelist, you see Dorothea wrestling with 0.99

00:35:08.980 this choice and all of its complexity.

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?

00:35:25.980 We have different issues, presumably.

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.

00:35:53.220 We've had that rehearsal for it.

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

00:36:05.720 of a practice for our own experiences.

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

00:36:20.000 laid out.

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?

00:36:27.160 Just the highlights, just a few highlights.

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 0.53

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.

00:37:03.700 They actually had to make two decisions.

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

00:37:22.040 do, like, what should we do about it?

00:37:23.680 Should we bomb it?

00:37:24.820 Should we send people in to get them out? 0.96

00:37:26.980 Should we try and keep them alive?

00:37:28.660 You know, a whole range of different things.

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

00:37:43.280 techniques that I talk about in the book.

00:37:45.380 And we don't talk about that enough, right?

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

00:37:55.140 carefully.

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 1.00

00:38:33.460 them are just incredibly stupid. 1.00

00:38:35.200 They're like going to like set up a loudspeaker system to say like, this is the voice of Allah, 1.00

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

00:38:51.180 this mystery, basically solve this mystery.

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

00:39:31.320 process.

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?

00:40:07.280 Like, what's your, what's your method?

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. 0.99

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

00:41:00.020 city in Germany.

00:41:00.560 And then I'm Stephen B. Johnson at Twitter.

00:41:03.540 And, uh, those are, those are good places to start.

00:41:06.820 All right.

00:41:06.940 Well, Stephen Johnson, thanks for your time.

00:41:08.380 It's been a pleasure.

00:41:09.200 Yeah, I really enjoyed it.

00:41:09.980 Thanks for having me.

00:41:11.160 My guest today was Stephen Johnson.

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

00:41:27.960 where you can delve deeper into this topic.

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

00:41:47.640 over 480 there.

00:41:48.960 And you can find thousands of articles on just about anything, how to make better decisions.

00:41:52.240 We've got articles on that, physical fitness, social skills, personal finances, you name

00:41:55.980 it, we've got it.

00:41:56.760 And if you haven't done so already, I'd appreciate it if you take one minute to give us a review

00:42:00.120 on iTunes or Stitcher.

00:42:01.180 It helps out a lot.

00:42:02.080 And if you've done that already, thank you.

00:42:03.700 Please consider sharing the show with a friend or family member who you think will get something

00:42:06.840 out of it.

00:42:07.260 As always, thank you for the continued support.

00:42:09.400 And until next time, this is Brett McKay reminding you not only to listen to the AOM podcast,

00:42:12.980 but put what you've heard into action.

The Art of Manliness - February 27, 2019

#486： How to Get Better at Making Life-Changing Decisions

Episode Stats

Summary

Transcript