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Welcome

0:02

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0:37

Today is October twenty seventh

0:39

twenty twenty two, and my guest is Arthur

0:41

Annie, Duke, Her latest

0:44

book and the subject of today's conversation

0:46

is Quitting. The power of

0:48

knowing when to walk away.

0:50

Anywelcome to EconTalk.

0:53

Well,

0:53

I'm happy to be here, Russ.

0:55

Now, I couldn't help but notice that your

0:57

book has a one

0:59

syllable title.

1:01

which is ideal. It's a fabulous

1:03

thing. But

1:04

it also happens to rhyme

1:07

with

1:07

grit. a

1:10

book with a apparently

1:12

different perspective, but which

1:14

is Angela Duckworth spoke, which we've talked about

1:16

in this program. But talk about what is the

1:18

difference between and grit. They sound like

1:20

they're opposite.

1:22

Yeah. So, yeah, the the fact that

1:24

it's called quit and rhymes with grid

1:26

is not accidental. That is

1:28

by design. So

1:31

let me just first say that I

1:33

really don't have any quibble with the

1:35

the booklet. I think everybody

1:38

should go and read it. I do

1:40

have quibble with the way that people some

1:42

of the takeaways that people take from

1:44

it, which is not anything on, you

1:46

know, on Angela Duckworth's part. because

1:49

she these are not the takeaway she would wish

1:51

that people took from it.

1:52

i'm

1:54

Here Here's the issue is that grit and grit,

1:56

those two decisions, are

1:58

the same decision. And we don't

1:59

think of them that way. We think of them

2:01

as polar opposites.

2:03

But, I mean, if you think about it

2:05

logically, any day

2:07

that I choose to stay in my job is a

2:09

day I'm choosing not to quit. Any

2:12

day that I quit my job is a

2:14

day I'm choosing not to stay And

2:16

so at any moment, given

2:18

that

2:18

we started something, we have

2:20

a choice whether to stick with it

2:22

or or to go and shift in and

2:24

do something else. And where

2:26

are where

2:27

we get into trouble is with the calibration

2:29

issue. Right? Like, when is the right

2:31

time to quit? When is the right time?

2:33

to stick to things. And and

2:36

my quibble with the takeaways

2:38

about grit in general is

2:40

that grit is good.

2:43

Grid is a virtue and

2:46

the people who persevere are the heroes

2:48

of our stories.

2:49

If at first you don't succeed, try try

2:51

again. Quitting never win, winners

2:54

never

2:54

Like, Russ, if I called you a quitter, would I be

2:57

complimenting you?

2:58

Oh, no.

3:00

I'd be insulting you.

3:02

And in fact, if you look up

3:05

in, you know, at thesaurus, you'll see that one

3:07

of the synonyms is cowered.

3:09

And that's where I really that's

3:12

where I I kinda get mad.

3:14

Right? And it's a little bit why the title of the

3:16

book is so in your face because I am

3:18

kind of mad about that. because I think

3:20

that it does incredible damage to people

3:22

in terms of their ability to actually achieve their

3:25

goals, because people are getting stuck

3:27

in things that just really

3:29

aren't worthwhile. It isn't worth

3:31

them sticking to them.

3:32

For fear that somehow, Duke, if

3:34

they quit, they're a loser

3:37

or a failure or

3:39

people are gonna judge them harshly for it. A

3:41

variety of

3:41

reasons that they won't do it And

3:44

the opportunity costs associated with that

3:46

are so great, separate apart

3:48

from the ground that you're losing

3:51

just by sticking to a loser anyway. Right?

3:53

And And I think it's I think it's

3:55

I think it's tragic. And

3:57

we need to start Quitting

3:59

is a skill and

4:01

it's one that you should get good at

4:03

because unlike the idea

4:05

that if you, you know, if you stick to things,

4:07

you'll be successful. It's no.

4:09

If you stick to the stuff that's worthwhile,

4:11

you'll be successful, but you gotta Quitting

4:13

the rest? You

4:14

you have a line in the book, which I

4:17

it's just quite profound. The

4:20

opposite of a great virtue

4:22

is also a great virtue. And that

4:24

seems I think most people

4:26

would say, well, that can't be

4:28

true or worse. that's a

4:30

lie. That that's

4:32

just that's just ridiculous. What

4:34

do you mean by that? And I think one of the reasons

4:36

I love it is that it's

4:38

memorable and it might

4:40

help you make a decision that you would otherwise

4:43

miss if you didn't remember that. So to talk

4:45

about what you made Okay.

4:47

So I let me just give credit, where credit

4:49

is due.

4:50

the When

4:51

I started working on on

4:53

the book, I it was during the pandemic,

4:55

and so asked whole bunch of people that I know to

4:57

get on Zooms with me, and one of them was Phil

4:59

Tattlock, author of Superforecasting. Really

5:03

brilliant man.

5:06

And

5:06

they all knew that I wanted to talk about this

5:08

concept of Quitting. And I got on

5:10

the call with him and he said, you know, I've been thinking

5:12

about this in relation to grit.

5:15

I think it's wonderful because the opposite

5:17

of a great virtue was also a great virtue.

5:19

So he was making a play on the

5:21

opposite of a great truth is also a great

5:23

truth. I think that what

5:25

we need to understand is that,

5:28

you

5:28

know, everything has upsides and downsides.

5:31

Right? So grit is

5:33

a virtue

5:34

when you're sticking to

5:36

things through the hard times

5:38

because the goal that you're trying to

5:40

reach is worth it. And

5:42

that is indeed a virtue because we don't

5:45

you know, when your kid goes out on the soccer

5:47

field and just has one really bad game and

5:49

storms off the field and since I wanna quit,

5:51

Right? You don't you don't want them to do that if they

5:54

overall, if they enjoy soccer, if you think that

5:56

it's something that they're getting great benefit out

5:58

of, you wanna teach them that it's a

5:59

virtue to be able to take the the downs

6:02

in order to achieve the ups.

6:04

Right? That being said,

6:07

quitting is also a virtue because if they get a

6:09

concussion on the field, you don't want them to

6:11

continue the game. And

6:14

that's what we have to remember, right,

6:16

is that in

6:17

circumstances where the world has

6:19

given us new information

6:21

that tells us that what we're

6:24

doing is no longer worthwhile. it

6:26

is virtuous to quit. And

6:29

in fact, I would say that there are certain cases

6:31

where it becomes a moral imperative to

6:33

quit. Yeah.

6:36

So so

6:37

I'll I'll give you I'll I'll give you a

6:39

brief example of moral imperative to

6:41

quit.

6:42

the

6:44

So

6:46

let's say

6:49

let me sort of comment it from two different

6:52

ways. So

6:53

there's a wonderful story of

6:55

quitting that occurs on the top of Mount Everest.

6:58

It's it in fact opens the chapter

7:00

that says an opposite of the opposite of

7:02

a great virtue. It's also a great virtue.

7:04

and

7:06

And this, you know, I think that's we think

7:08

of you know,

7:09

people who climb ever as to sort of the epitome

7:12

of grittiness. Right? Like, that these are the

7:14

stories that you're telling about grittiness.

7:16

But there's a wonderful story about Quitting this.

7:19

That's there. So this story is about Dr.

7:21

Stuart Hutchinson, John Taseke, and Lucasitski.

7:23

and they're climbing up ever, so they're part of one of those

7:25

climbing ex expeditions in the nineties that

7:27

were very popular. There's

7:30

eight climers, three climbing sherpas

7:32

and an and an expedition leader.

7:34

And on Summit

7:37

Day where you leave from camp four, so you've already done quite

7:39

a bit of climbing up to camp four from base

7:41

camp. you leave at

7:43

midnight, and the expedition

7:46

leader has set a turnaround time.

7:48

So, with the turnaround time, it's

7:50

no matter where you are in the mountain,

7:52

if you're not at the summit by one PM, you

7:55

must turn around.

7:56

Pretty simple. The

7:59

reason why the turnaround time time is one

8:01

PM is because they don't want people to

8:03

descend what's called the Southeast Ridge.

8:05

in

8:05

darkness. It's

8:06

very narrow part of the mountain. It's very easy to

8:08

flip if you can't see what you're doing. And if

8:10

you fall, you're either gonna fall

8:12

to your depth into Nepal. or fall to

8:14

your death into Tibet.

8:16

Take your pick, neither of them, I assume,

8:18

would you like to do. Alright. So,

8:21

our three climber is such a fantastic and

8:23

kisitsky. are Quitting. And

8:25

this was, you know, at a time when the mountain was

8:27

starting to get crowded. And they got basically,

8:29

like, literal traffic jams on the mountain

8:31

trying to get to the summit, because so many people were trying to

8:33

go at once. So it's very

8:35

slow going on this day.

8:38

And their expedition leader comes

8:40

up behind them And

8:41

Hutchinson says to that expedition leader, hey,

8:44

what time do you think it's gonna be? You

8:45

know, how long do you think it's gonna be until

8:48

we get to the summit? and

8:50

the expedition leader says three hours.

8:54

Goes on ahead to sort

8:56

of try to make up some ground and and get

8:58

to the summit himself. Hutchison

9:00

holds tasking and Kasinski back and

9:02

says, we have a problem. If it's gonna be

9:04

three hours to the summit, it's already eleven

9:06

thirty AM. Seems to

9:08

me we're not gonna get to this summit till two

9:10

thirty. That's

9:10

well past the turnaround time.

9:12

So

9:13

it appears we have butted up against that

9:15

and we have turnaround now. So

9:17

they did and

9:19

they lived.

9:20

Now, Russ, I'm sure it's obvious to you why

9:22

you've never heard this story. Right?

9:25

Like, where's the drama? Right?

9:27

I mean, three climbers followed the Russ. They

9:29

turned around. They lived. Like, nobody's making a movie out

9:31

of it except they did.

9:33

they were part of the climbing

9:35

expeditionary krona called in John

9:37

Crackers into thin air.

9:39

Rob Hall was their expedition leader. In fact,

9:41

the one who told them that it was three hours to the

9:43

summit. Rob Hall, I think we all know, went

9:45

to the top of the mountain, got there at two

9:47

an hour passage around time.

9:49

waited for

9:51

Doug Hanson to get there until four,

9:53

and they

9:54

both perished and topped them out. They never

9:56

made it a bit down. They they were

9:58

on top of the summit.

9:59

and

10:01

So you might say, okay. Well, if it was in the

10:03

book and also in the movies, maybe

10:05

they just didn't talk about them because what a boring

10:08

story, but they did. they said they were

10:10

the best climbers on the mountain.

10:12

Right? So first of all, the thing number one is why

10:14

don't we even know who they are? Right? And

10:16

that's like all of this drama. Here are these people

10:18

who quit beautifully. and turned,

10:20

you know, and turned around and lived. And yet, we don't

10:22

even remember them. So I think that's important because

10:25

even people who persevere

10:27

in conditions that are bad

10:29

past the turnaround time that he himself

10:31

had set. And

10:32

Russ, we still admire

10:34

them. We still

10:36

consider them the heroes of our story. But

10:38

this is where I think we get into a moral

10:40

imperative,

10:41

right, to be good quidders, which is

10:43

Putchison and Taseke and Kacitsky all

10:45

head families.

10:45

Two

10:49

of them were doctors, they had patients.

10:52

And

10:52

don't they have a moral imperative to turn

10:54

around in that situation? They know that

10:56

they should, the probability of death is too

10:59

high, and now they

11:01

have people that they can go back to.

11:03

and continue on with their lives and make the

11:05

people those people's lives richer for

11:08

their presence in them. And

11:10

so that that I think a little bit at

11:12

this idea of moral imperative. I

11:14

think

11:14

the other place

11:15

where you can see a moral imperative is quite common

11:17

in, for example, in startup culture,

11:20

where a startup will be clearly

11:22

failing. Someone

11:24

will say, you know, hey, it seems like it's

11:26

not going well. You're not hitting any of your

11:28

benchmarks. you're missing all your targets. You have

11:30

them in a cheap product market shit.

11:32

Whatever.

11:32

ever It

11:34

seems like you should shut it down.

11:36

And people will say, but

11:38

I owe it to my employees. Okay.

11:40

So they're using the language of duty

11:42

here. Right? I have a duty to my

11:44

employees to keep it going. But if we

11:46

think about it, they actually have a duty to

11:48

quit.

11:48

Why? Because once they've

11:51

determined that the equity isn't worthwhile

11:53

and so start up employees are generally

11:55

working for very low cash comp and

11:57

compared to what they could get on the market.

11:59

But they're working

11:59

for equity that they deem to be

12:02

possibly life changing. Once

12:04

the founder has determined that

12:06

equity is not worth it,

12:08

they have

12:08

a duty to the employee to

12:10

allow them to go.

12:12

so that they can go get paid what they deserve,

12:15

right, whether

12:15

that's at a new startup where they're going to be

12:17

working for equity that has more value or

12:19

whether it's in an enterprise where they're just going

12:22

to get salary at their market rate.

12:24

And I so I think that we turn that on its

12:26

head. Right? We say, I have a duty to stick

12:28

it out.

12:30

because I, you know, I've convinced these employees

12:32

to come work for me for no money

12:34

and and and equity. And so I got to

12:36

keep trying. Right? Except that the minute

12:38

that you've determined that equity isn't worthwhile,

12:40

the duty is actually the opposite.

12:42

Just

12:43

to shut them up go that you know, shut it

12:45

down and let them go free.

12:47

Yeah.

12:47

Those are, you know, incredible stories.

12:50

Obviously, the average one slightly more incredible

12:53

than the founding employee

12:55

story, but they're both

12:57

powerful

12:57

because they illuminate a moral

12:59

issue that on the surface doesn't seem like a

13:01

moral Russ. And I think you're

13:04

your insight about character

13:07

is is very apropos.

13:09

the

13:10

We often admire

13:12

those people who don't quit

13:14

because they quote persevered when in

13:17

fact it was irrational

13:19

or immoral know the story I

13:21

like to tell of Fred Smith when

13:23

he started FedEx ran out of money

13:25

and he went to Chicago to

13:27

the bankers from Memphis

13:29

and and

13:30

they turned him down. They

13:32

said no. And

13:33

he was

13:35

gonna get back on the plane and fly back to Memphis

13:37

and tell his employees that he

13:39

was

13:39

sorry that he couldn't make payroll. This

13:42

was not a tough decision because

13:44

the cash register was

13:45

empty. The bank account

13:48

was empty. But instead,

13:50

he

13:52

went to Reno. He saw Reno

13:54

on the board of of

13:56

departures put all that he had. I think

13:58

he'd taken money from his sisters,

14:00

the trust Russ sure trust fund.

14:03

And I got he got sued for this too, by

14:05

the way. Yeah. And

14:07

he goes I don't know whether this is the money he

14:09

took or was taking it all along. I can't remember,

14:11

but he ends up in in

14:13

Reno and he puts whatever money

14:15

has on red or seventeen or whatever it

14:17

is and makes just enough to go back and

14:19

make payroll and the rest is history.

14:21

And I love that story because it's about

14:23

gumption and guts and not quitting

14:25

and persevering and believing in

14:27

your dream problem is that's the story we

14:29

hear. The ones where that we don't hear, the ones where it

14:31

was a bad dream. Wasn't gonna make

14:33

it? And the hubris and ego of

14:35

the founder came

14:37

in

14:38

the other

14:39

people paid the price for that. Now in his case,

14:41

he made it. A lot of respect for Fred Smith,

14:43

tremendous amount, but it's a visionary.

14:45

Both missionaries have a

14:48

very

14:50

different quit encompass. It's a

14:52

very bad metaphor. but

14:54

they struggle to make those decisions for

14:57

ego and for this

14:59

delusion. And we celebrate the

15:01

ones who make it. and we don't

15:03

chronicle the people who don't make it. And

15:05

that is their

15:07

their pluses Russ minuses to that, but I think Observe make

15:10

your observations. Fantastic. The

15:12

other the other point I wanna make is that

15:15

I just wanna come back to this mantra

15:17

of Telkonetformer, Pesti,

15:20

Kantar, Gaskaw bless him. the

15:22

opposite of a great virtue is also a great virtue.

15:24

One of the ones I love like that is

15:26

you have to learn how to say

15:29

no. And

15:29

that's a very powerful trick. It's a really

15:31

trick. If you also have to learn how to say yes,

15:33

even sometimes saying yes to things

15:35

that don't look

15:36

promising lead to

15:39

extraordinary changes in your life. And

15:41

so that's all these things

15:43

are a question of nuance. I

15:45

think, and and balance. Before

15:48

we Yeah. Actually speaking of Phil

15:50

Turtler, during

15:51

the pandemic when I was

15:52

somewhat busy, he

15:55

he reached out to me and said, you

15:57

know, we're having trouble creating good training for

15:59

novice forecasters and

16:01

these counterfactual forecasting problems,

16:05

you you

16:05

kinda teach this stuff and consult on

16:08

it. So maybe, like, you would be able to put

16:10

it in to terms or a voice that

16:12

would that would actually create a good training, and

16:14

you could maybe think about the things that actually, like,

16:16

work with your clients and apply

16:18

that to this training. So So I said

16:20

yes. Why? Because

16:22

I love Phil and I was willing to

16:24

and Barb, by the way, his wife, and I was

16:26

willing to make time for that. Right?

16:28

And that turned into four

16:30

very large scale studies that

16:32

were incredibly fruitful. So

16:35

So I completely agree with you. Right?

16:37

I'm trying to work on both. Yeah.

16:39

Right. Being

16:40

more careful about saying no to

16:42

things that I I'm predicting are

16:44

not gonna be worth my time and

16:46

saying yes to stuff that looks kinda wild

16:48

and crazy, but like wouldn't that be cool? And I

16:50

might learn something super new about myself

16:52

or something super new about the world.

16:55

So I love that example because that's a

16:57

good case of like the yin and yang. Right?

16:59

And you might But the

17:00

reason I like it is, is this other

17:02

piece to it for me, which is you

17:04

might make a human connection that

17:06

you otherwise wouldn't Duke. That's not

17:09

gonna make you're more money and it's not gonna lead to all those other

17:11

studies that can help you understand something.

17:13

You're just gonna have a human experience

17:16

that's precious And I

17:18

love that. It's very powerful.

17:20

The I I

17:22

think the in the case of the yes

17:24

and no, what we're saying

17:26

is you have to make room in your

17:28

life for serendipity. There are things that

17:30

are gonna come along. You can't

17:33

predict. can't imagine. And if

17:35

you always say no, you will be comforted

17:37

by the fact that you had more

17:39

time for other things, but you'll never see the things

17:41

you didn't get, and you'd write about that a lot in the book.

17:43

Actually, library. Yeah. So, actually,

17:45

I'd like to

17:46

in in relation to that, I'd like to bring

17:49

up some a little fact about

17:51

ants. because I think this this goes really

17:53

well with that.

17:54

So so

17:55

you know the sound

17:56

Duke the AMSCO marked two one by

17:58

one, hurrah, hurrah.

17:59

Right? So we we know that have that

18:01

image if you've seen any cartoon or

18:03

or you've actually watched Anton in Nature's

18:06

Show. They they're marching in a lot. I'm

18:08

really good at that. Alright. So don't

18:10

Those ants

18:10

are forage or ants. They're a part

18:12

of the colony that's meant to go out and

18:14

find food, basically. And

18:17

so if you watch if you watch these forge your

18:19

ants approach like a new territory, you'll see that they're

18:21

all kind of scattered around, so they're not marching in

18:23

a line yet. and

18:26

then one of them will find

18:28

food and they'll take the food

18:29

and they'll be carrying it

18:30

back to the colony and on the way back they lay

18:32

down a fair amount of

18:34

trouble. So it's

18:35

just the chemical trail that the other ants

18:37

are going to detect. So they're only doing

18:39

it on the way back once they've found food.

18:41

They're laying down this trail. So at

18:43

first, it's pretty, you know, it's pretty faint because it's

18:45

only one ant. But now if

18:47

another ant detects that trail, it will

18:49

now go along the trail, it will find

18:52

the food, And then when it's

18:54

bringing that feedback, it will also lay a

18:56

pheromone trail down on top of that, and you can see

18:58

how this trail is now getting reinforced

19:00

attracting more and more ants to the

19:02

same trail until they're marching

19:04

one by one to whatever

19:06

the

19:06

watermelon that fell on the ground.

19:10

Alright.

19:10

So that's how we think about them. But

19:12

actually, if you look at

19:14

the behavior once there's a strong fair amount

19:16

of trial, laid down what

19:18

you'll see is about ten to fifteen percent of the

19:21

ants don't actually get with the

19:22

program. They're just kind of

19:25

like wandering around. Right?

19:27

So what's the deal with those ants? Right? Like, are they

19:29

ant aren't cats? Like, are they malinguers?

19:31

Like, what's the deal with

19:33

these malignoring ants? And

19:36

it turns out no. They're not

19:38

anarchist at all. They're not malignors. They're

19:40

actually serving an incredibly important

19:42

function for the colony, which is that they are

19:44

continuing to explore. So

19:46

you've got the answer exploiting

19:48

the food source that that's high quality,

19:50

it's a watermelon or whatever, but

19:52

the other

19:52

ants are continuing to

19:55

explore. So they're saying yes in that

19:57

sense. Right? Like, they're like, yeah. Sure. I'll

19:59

keep going

19:59

looking around. And

20:02

what

20:02

is it? Why is that so incredibly important

20:04

that they're doing that? Well, first

20:06

of all, the food

20:08

source might go away. So

20:11

someone might clean the watermelon up. Right?

20:13

Maybe it's like on the back deck or something like that

20:15

and some comes out with the hose. And then

20:17

that that watermelon is gone,

20:19

it's really good

20:20

that this ten percent fifteen percent of the colony is continuing

20:23

to explore their food sources because it means

20:25

they have backups.

20:27

Insurance. Right. it's insurance

20:28

that allows them to sort of cover, you

20:31

know, to your point, right,

20:33

they're increasing the chances for share

20:35

and deputy, for finding something

20:37

out That's really great.

20:39

The other thing, and I think that this is

20:41

an overlooked point, is

20:43

that

20:44

it may be that the food source that

20:46

they have is totally stable,

20:48

but the other ants

20:49

might find a better one.

20:52

And that the issue of opportunity cost. Right? Is that

20:55

once we're once we're

20:56

exploiting something, whether it's like a product

20:58

that an enterprise is selling or

21:02

a

21:02

hobby that we're pursuing

21:05

or a, you know, project,

21:07

a job, whatever

21:10

it is. Right? Once we're doing that,

21:12

we tend to ceased to explore.

21:14

Right? So I think it's funny

21:16

that a lot of the encouragement is

21:18

around say no, because I think we're actually

21:20

quite good at saying no.

21:21

because we actually don't even consider the

21:24

possibility of saying yes or no. And if

21:26

you don't consider the possibility of saying

21:28

yes or no, you're saying no to all of that stuff

21:30

by default. Right? the

21:32

answer doing is saying, well,

21:34

this

21:34

is great. Right? I

21:36

loved it, but maybe there's

21:38

something better out there. and they're

21:40

continuing to explore it. So it's serving dual

21:43

purposes. Right? It's giving them a backup

21:45

plan, but it's also allowing them

21:47

to find something that really to

21:49

have been their plan a. And I think this

21:51

relates exactly to what you're saying. Right? And you

21:53

can see this behavior to,

21:56

you know, this duality in

21:58

the ants because they're doing kind of both

21:59

things at once. Right? They're

22:02

exploring the food source that's there, but they're

22:04

also continuing to explore and basically

22:06

say yes to all the other places that you could

22:08

go look, and they're more

22:10

likely to find something. So obviously, we're

22:12

not ants. We don't have a

22:14

big colony. I

22:15

can't clone myself. But to

22:17

your point, I can say yes to

22:20

stuff. And if I say yes to stuff,

22:22

maybe I'm gonna find something there

22:24

that's awesome or a good backup plan or

22:26

better than what I'm already Duke? I

22:29

wanna

22:29

say something about quitting that I'm curious,

22:32

Gary, action. It's a it's a personality trait of

22:34

mine, and I've often thought of

22:36

it as a as

22:38

a flaw, but it maybe

22:41

it's a featured out of

22:43

bug, and it's consistent with your

22:45

point. I tend to get

22:47

very excited about new Roberts. And

22:50

I'm not the best collaborator. And

22:53

I haven't been

22:55

until I got this job as president

22:57

of Shalom College. I kind

22:59

of picked things where I didn't have to collaborate. Right?

23:01

When you're a research fellow at the Hoover Institution,

23:04

you're it's a deliberately

23:06

lonely life. It's not lonely. It's just

23:08

that you're often alone.

23:11

And you can collaborate with

23:13

other people in your field if you

23:15

want, but you're also free to just on what you love and

23:17

it's really lovely. But

23:19

when you have to

23:21

collaborate in my experience of my

23:23

own self, if

23:25

I get really excited about a project

23:27

and I need your help. Okay?

23:29

Or we're gonna do it together. And

23:31

I tell you about I'm all fired up and

23:33

you go, well, that's really cool. I like it

23:36

too. That's fantastic. And

23:38

then nothing.

23:38

You don't follow-up.

23:40

You don't respond.

23:43

You're just maybe you got

23:45

busy. Maybe decide you didn't like it as much as as

23:47

as I did initially. I lose

23:49

all my enthusiasm. Right? I'm

23:52

I'm very little self because

23:54

I'm gonna find

23:54

another one. I'm like that ant. I'm gonna

23:57

go off. find another thing I'm excited about,

23:59

and I'll find

23:59

somebody who does wanna do it, or I'll

24:02

get you fired up about the new one. And I've

24:04

always wondered whether that's a, you know, a character

24:06

flaw that that I very

24:08

quickly give up on what I

24:09

was so excited about to

24:11

start with. And I'm now

24:14

you're making me feel better about it. Still could it could be of a

24:16

character flaw, but but I think

24:20

it's a a

24:22

recognition of the opportunity cost. If you're

24:24

not enthusiastic and you're

24:26

not crawling through with my with me and I'm gonna

24:28

have to then carry the ball by myself,

24:30

It just I deflate. I'm done. I'm

24:32

gonna find new project. I'm gonna wander off find

24:34

a different piece of watermelon. And I

24:37

I think I've

24:39

ever thought about that as a as a possible good

24:42

character, Trey. Maybe it is.

24:44

Yeah. Well,

24:45

okay. So So here's the thing though.

24:47

I mean, again, it depends on

24:50

your values. It depends on what the signals for

24:52

success might be for you. Right?

24:54

So

24:56

hi for

24:57

you, it sounds like

24:59

you don't feel like you're

25:01

gonna be successful in a project if you

25:03

don't have a collaborator who's equally

25:06

enthusiastic. that's what it sounds

25:08

like. So this goes

25:10

into something that we could call kill

25:12

criteria. If you wanna be softer about

25:14

it, you can call them exit criteria,

25:16

I like the term kill criteria for the same reason that I

25:18

put in very large letters

25:20

that quit right on

25:21

the front of my butt.

25:24

because I want people to think about

25:26

these things this way, right, in the boldest

25:28

possible terms. But at any rate, so

25:30

for you, as you're thinking

25:33

about Oh, I'm

25:33

kind of interested in this idea. I

25:36

wanna explore

25:36

this. What are the things

25:39

that what

25:42

are the things that would tell me

25:44

that this isn't going to be something

25:47

that's a really valuable use of

25:49

my time? Right? Well,

25:51

if I can't get a collaborator to be as

25:53

successful as I am, then I

25:54

really ought not to

25:57

do this. So I'm gonna do very

25:59

little thinking about

25:59

it. I'm gonna sort of form enough of

26:02

an idea to be able to communicate it to

26:04

someone who I would like to collaborate

26:06

with And if they're not as excited and engaged

26:08

as I am, I

26:09

already know it's not gonna be worth my time.

26:11

Right?

26:12

So that's actually a really reasonable way

26:14

to approach

26:14

a project deck. So I actually

26:17

approached books that way. When I have an

26:19

idea for a book, there are a few

26:21

people that I call. I

26:23

hardly form the book idea. I

26:24

I'm able Duke, with

26:27

it was something, like, you know, the

26:29

opposite of grit. I

26:30

said that. you

26:33

know, and I don't mean, like

26:35

I said, I don't mean, like, the opposite, but, like, I

26:37

mean, the dialogue with grit that

26:39

I think that people in general think

26:42

that we quit things too early. I think the

26:44

science tells us that we quit things too

26:46

late, and I would really like to

26:48

explore this topic. That was about

26:49

what I

26:51

had.

26:52

And I wrote I

26:54

think the first person I wrote was Michael Movesen,

26:56

but then I think Danny Conemann followed

26:58

quickly after that. and fill

27:00

toe lock. because I just wanted to see,

27:02

like, how did they react to that? Right.

27:04

And then they just start they

27:06

were really excited. Right. Duke, they were Duke,

27:09

okay. Yeah. So then I'm Duke, okay.

27:11

I think now I should go further. Right?

27:13

So I'm always sort of pushing to

27:15

see, like, is this a no or is this a yes?

27:17

And I know that if I can't

27:20

get if Danny

27:23

Donovan thinks it's a stupid idea and

27:25

it's not worth exploring, that's a

27:27

really good single for me. So I shouldn't put a whole lot

27:29

of work into it until

27:31

I've got those gut checks

27:34

from

27:35

people who are way smarter than

27:38

me, much

27:38

deeper into the science than I

27:41

am, and are going to tell

27:43

me whether it's something that they think

27:45

is worth putting on a piece of

27:47

paper. Right? And obviously, this has to do with in

27:49

particular, what I'd like to write about, which

27:51

is to be fair, their science.

27:54

So if the people who created the science don't

27:56

think it's worth writing about, I'm

27:57

not gonna continue with it. Howard Bauchner: Yeah,

27:58

the the

27:59

the parallel

28:01

thing with with grit is,

28:03

but don't you have enough faith in

28:05

your own idea? What you're gonna rely on

28:07

other people to decide whether this is a pet

28:10

good posture project for you. And I wonder

28:12

sometimes when I get

28:14

shot down with a creative idea I'm not

28:16

really outside the box I

28:18

did. something more crazy than

28:20

just here's an idea for a book, but I propose

28:22

something absurd. I wonder if and

28:25

I get shot down. I go, no one

28:27

no one likes it. it's very hard

28:29

for, I think, most of us emotionally to

28:31

then say, but I think I'm still right. Especially

28:33

if the people were asking, we

28:35

respect and and are smarter than we are.

28:38

And I think I worry

28:40

sometimes that that I

28:42

cast my own decisions in that kind of

28:44

light that Yeah. It was a rational decision because

28:46

I needed to didn't think it was worth it. They're smarter

28:48

than I am, but sometimes I wonder if it's just

28:50

like, I'm a quitter. And and it

28:52

comes to your point about about

28:54

the cultural baggage that

28:56

we have, mostly from our parents.

28:58

You know, you gave the example of the kid on the

29:01

soccer field. a lot of what we do as parents

29:03

and a lot of what our parents did to us

29:05

is to get us to push through pain because

29:07

often, not always, but

29:09

often great rewards come from that. And and

29:11

that is hard for

29:12

human beings to anticipate those rewards

29:15

sometimes, especially when we're young. we're

29:17

we have trouble. Yeah. And let me just let me just emphasize

29:20

that, especially when we're

29:22

young. So I just wanna

29:23

emphasize that because I think that

29:25

stepping apart

29:26

from where parents go wrong with that and

29:28

they they do, they take it too far.

29:31

But I obviously, it's a good lesson to

29:33

take someone who's sick and has

29:35

never sort of gone through the downs

29:37

to see what the ups might be on the back end of

29:39

it. And teach them, you don't need

29:41

to quit. You can push through it. I

29:43

agree, especially when they're young. The problem is

29:45

that we think that applies to thirty

29:47

year olds. That's the problem.

29:49

And it doesn't, because

29:51

thirty year olds aren't walking off the soccer

29:53

field. That's the problem. Yeah.

29:55

Well, I want to take another example

29:57

that Duke in the book

29:59

that will apply to the

30:01

Everest example, and I think it's an

30:03

incredibly pointed and powerful

30:05

example of it.

30:07

the

30:07

example

30:09

you use is that if you finish up

30:11

half marathon, people are impressed, Russ, you

30:13

ran thirteen point one miles. That's a lot. Yeah.

30:15

But if you run a marathon

30:17

and you stop halfway, you're a quitter. And you

30:19

did the exact same thing. And

30:21

I think about the

30:24

absurdity the utter tragic

30:27

absurdity of being three

30:29

hundred meters from the top of Mount

30:32

Everest And it's one

30:34

o'clock. That's one o'clock. And

30:36

you're

30:36

supposed to turn back and you say, I'm

30:38

not gonna stop short of the summit.

30:40

I can see it from here. And,

30:42

of course, the answer one answer you should

30:44

give yourself is, well, I can see the

30:46

summit and I'm three hundred meters Did

30:49

that kind of do what I wanted to do?

30:51

Can I Duke? To that point, you

30:53

know, there was something interesting because these

30:56

are all a cognitive phenomenon. Right? So one of the things that I

30:58

want to be clear about is that what we're

31:00

talking about is the cognitive state of being

31:02

in the losses. So when

31:05

you think about, like, your balance sheet.

31:08

Right? Like, in the losses

31:10

means that you're losing from

31:12

whatever

31:12

a mark was. So

31:14

if you buy a stock, the mark is gonna be

31:16

the price that you bought it at. And

31:18

if you're below that, you're in

31:21

the losses. If

31:21

you're above it, you're in the games. Okay? So

31:24

that would be, like, on an

31:26

actual ledger, right, on an actual

31:28

balance sheet. But we have

31:30

this mental accounting that

31:32

occurs. Right? Which

31:34

gets distorted. So sometimes it

31:36

overlaps. Right? If I buy a stock Justina

31:38

is trading at forty, both on my

31:40

physical ledger and

31:41

my my cognitive ledger,

31:44

my mental I'm in the

31:46

losses in both. But

31:47

if I buy a stock at fifty, it goes

31:49

up to seventy five and is now trading

31:51

at sixty. On my

31:53

actual physical ledger, I'm in the game's

31:56

ten dollars.

31:56

But in my mental account, I'm I'm in the

31:59

is fifteen dollars because I'm

32:00

fifteen short of seventy five now. Right?

32:02

Okay. So

32:03

it doesn't matter that I was

32:05

up

32:06

ten. So when

32:08

we take like a marathon and this

32:10

really interesting thing about it, half marathon

32:13

versus a full marathon or where we are person

32:15

to Everest, if

32:17

it's

32:17

a half marathon, the

32:19

goal, the endpoint is thirteen point one

32:21

miles. So if I complete that, I am now no

32:23

longer in the loss in comparison to that goal. But

32:25

if I only complete thirteen point

32:27

one miles in comparison Duke the context

32:29

of a marathon, I am

32:32

short thirteen point one miles now.

32:34

I'm

32:34

in the losses. No matter that

32:36

if I created a

32:38

physical ledger, I would be in the games

32:41

thirteen point

32:41

one miles. In other words, physical ledgers

32:44

measure from the starting line,

32:46

but mental

32:47

ledgers measure from

32:49

the finish line. Okay. So

32:51

this is the problem we have with Everest.

32:53

Right? I'm three hundred feet from

32:55

the summit.

32:56

Never mind. that I

32:58

just climbed twenty nine thousand feet in

33:00

the air, I'm a loser

33:02

if I turn around because I'm closing

33:04

that mental account in the losses. So if you

33:06

wonder why does somebody continue past the

33:08

turnaround time. Right?

33:10

Or even get to the summit at four

33:12

PM, which is what Doug Hanson did even

33:14

though the turnaround time was one

33:16

PM. It's because

33:17

he was in the losses in

33:19

his head. And as Richard Taylor, like in

33:21

his head so Richard Taylor points out, we do

33:23

not like to close mental accounts in the losses.

33:26

So anyway, Richard sent me something

33:28

hilarious. It was, like,

33:29

it's probably about a

33:31

year ago. And it was, you

33:33

know, a little bit complex. I didn't end

33:35

up in the book, but Basically,

33:36

there's some sort of argument

33:38

now among mountaineers

33:39

-- Mhmm. -- that

33:41

if you look

33:42

at, like, the the

33:45

popular peaks that people

33:47

climb. There's some

33:48

argument about what the

33:50

peak actually is. I

33:53

love it. So now

33:54

all of a sudden, they're saying that

33:56

a bunch of people who say they've Duke, like, the

33:59

seven peaks or whatever,

33:59

the seven summits.

34:02

maybe they didn't actually submit them

34:04

because there is now an argument about what

34:06

exactly is the top of Everest or what is the

34:08

path with

34:10

Jill Amindara? Right? Which just brings up the absurdity of

34:12

all of this. In the first place, it's

34:14

completely absurd,

34:14

but it's the way that we work cognitively.

34:16

But I'm gonna push back a little bit

34:19

because I I do think there's

34:21

there's a a

34:24

powerful reason that we struggle with this

34:26

mental accounting. Right? and

34:28

anybody who's run who's been a

34:30

runner or done the

34:32

equivalent of running in in a

34:34

project, meaning a

34:36

long arduous track. I think it understands this.

34:38

And I just want to say and I used to keep

34:40

this quiet because I thought it was

34:42

too too It

34:44

wasn't it wasn't especially humble. I ran a full marathon

34:47

when I was younger and

34:49

finished in the blazingly fast time of

34:51

four hours and twenty minutes.

34:54

But the fact is, I am very proud of that, and I'm

34:56

proud of the fact that I finished. The

34:58

fact that for the week after, I couldn't

35:00

climb stairs without a great deal of pain.

35:04

was put that to the side and

35:06

let's ignore the fact that I could have really done

35:08

some Russ run damage to

35:10

my body. But

35:12

the reason I finished

35:14

and it was painful, I

35:16

wasn't wasn't spitting out blood or anything.

35:18

and a bone wasn't sticking out of my leg. But the reason it was hard. The reason

35:21

I finished is part is partly

35:23

because of it was my dad.

35:25

Right? My dad said, don't

35:28

quit. finish what you plan, this whole idea of the spendal accounting.

35:30

And the reason that's useful,

35:32

the flip side I

35:34

think of your argument is,

35:37

if you start off

35:39

to climb Everest or run a marathon

35:41

and say, well, I'll just get as far

35:43

as I'm comfortable and I'll I'll try

35:45

to get far and whatever it is will be gravy. If I

35:47

if it's five miles, great. If it's thirteen point one, I'll be

35:50

proud. Twenty would be wonderful. And if by

35:52

some chance I finish,

35:54

that's nice. you

35:56

don't get very far. Often that we feel at

35:58

least maybe it's wrong, but we feel that if

36:00

we take that approach, we're gonna cheat

36:02

ourselves. We're gonna quit too soon.

36:05

So when say we go to the other extreme, which is

36:08

insane, which is gotta finish.

36:10

Gotta finish. Otherwise, I'm

36:12

a loser. and we use

36:14

that as a way to pass

36:16

short run pain for long run benefit. It's

36:18

why we go to grad

36:20

school, it's why we invest in

36:22

a startup, It's why we run marathons,

36:24

and a lot of it by the way, of

36:26

course, is is

36:28

self esteem.

36:29

c I mean, we didn't talk

36:31

about this, but when I read it to thin air, for me,

36:33

it's a great read. Just if you haven't read it, it's

36:35

an extraordinary read.

36:38

I finished that book thinking, this is insane. This

36:41

is To what

36:43

purpose

36:44

did this person lose half his

36:46

nose?

36:48

to what purpose did these people die? They didn't

36:50

achieve anything. And of course, their answer would have been,

36:53

no. And I tested myself. i

36:55

tested myself

36:57

and was not found wanting. And

37:00

there's something deep inside us that needs

37:02

that, whether it's hit the

37:04

approval or or parents

37:06

often no longer alive. We don't

37:08

care. We still push through.

37:10

There is there's value to it, and it's

37:12

also anyways, what you're saying

37:14

is it's Duke, a sickness almost. And it

37:16

is a little complicated that

37:18

way. Yeah. So this is what I would

37:19

say, the opposite of

37:21

a great virtue. is also

37:23

a great virtue. And that's true when it

37:26

comes to goals that we set for

37:28

ourselves. Golds are motivators. Yeah. As you

37:30

said, they get we they get us to push toward

37:32

the finish line

37:32

even when things are hard. And

37:35

that is not a bad

37:37

thing. Now, I

37:37

would argue that if you enter a

37:40

marathon saying, I'll

37:40

run as far as I feel comfortable that you're

37:42

still gonna run toward the finish line.

37:44

Because no

37:45

matter whether you say that, to

37:47

yourself and or not. Like, there's a finish line.

37:49

You're not gonna wanna quit before you get

37:51

to it. So I have

37:53

very little concern. about people saying, you know, but if

37:55

I start, you know, if I'm if I'm not feeling

37:57

good, whatever. Like, III think

37:59

that creating an all or nothing situation

38:02

around the

38:04

finish line, It's probably not helpful since we already do that in our

38:06

heads. But it's true. Right?

38:08

Like, if I'm on

38:09

the last two miles and

38:11

my legs are cramping, they

38:13

don't

38:13

make me finish.

38:15

And I'm gonna feel pretty

38:16

good about that. I'm gonna look back on

38:19

that and feel pretty proud. of having

38:21

pushed through. It's probably a good thing that I did, assuming that I

38:23

wasn't in medical danger. Right?

38:25

But here is the problem. This is where we

38:27

get to that opposite

38:30

of a virtue. It's a Let's Shavano

38:33

Keith. Shavano Keith entered

38:35

the two thousand nineteen marathon Russ

38:39

mile four, she started experiencing pain in

38:41

her leg. On mile eight, her

38:43

fibula bone snapped.

38:48

She

38:48

broke her leg. Now, obviously, the medical

38:50

tent was like, yo,

38:53

stop running.

38:55

but she did

38:58

not. And she finished the

39:00

race. Now, this is where

39:02

we get into trouble with

39:04

this. Right? because the great thing about goals is

39:06

that it sets a finish line and it

39:08

gets you to continue to run toward

39:10

it even when

39:12

it's hard. The

39:13

bad thing about goals is that it

39:15

sets a finish line and it gets you to

39:17

run toward it. No

39:20

matter what, even when your

39:21

leg is broken. And if we take,

39:23

you know, creates in some ways, it

39:25

creates a short termism. Right?

39:28

Like, Grit is really meant you to meant to help you with

39:30

the long view. I know it's bad

39:32

right now, but it's gonna be worth

39:34

it in the long run.

39:37

But weirdly, when we set these goals,

39:39

it creates a short termism because

39:41

the goal itself becomes the object

39:43

of our grit. right, whatever that short term finish line is. Because

39:45

I assumed for Shibano, Keith, the goal was I

39:48

love running marathons and I would like to run

39:50

many of them in my life. This was not her

39:52

first marathon. Russ by

39:54

continuing to run, she was risking grave

39:56

injury that might have prevented her

39:58

from ever running

39:59

another one. So she was

40:02

actually causing herself to lose

40:04

ground toward what

40:05

she herself had declared

40:07

would make her happy. And that's where

40:09

we get into real trouble. You know? And and this really

40:11

goes under another thing that Richard Taylor

40:13

talks about is that goals are really great

40:15

at pass fail.

40:18

And not only does it mean that you're going to head

40:20

toward them no matter what, but he points out that

40:22

it can stop you from starting things that

40:24

are worthwhile. Because as he

40:26

says, if the

40:27

only thing that

40:29

is success is getting a

40:31

gold medal in gymnastics, why would you

40:33

ever take your first

40:35

lesson? You were a

40:36

very successful poker player. One

40:38

thing that's fun about poker. It's

40:41

it's a game

40:43

everybody. can play. Many people have played

40:45

it casually, and most of

40:47

us who played it casually

40:50

had no idea what

40:52

the real serious

40:54

poker is until then it

40:56

became a TV phenomenon. And and I think a lot

40:58

of people got access to it and it created

41:00

great prizes and

41:02

so on. But I think it's another

41:03

wonderful, simple

41:05

simple mantra for

41:06

people to think about outside

41:08

a poker, which is knowing when to fold them.

41:11

And talk about your own

41:14

experiences and what you learn from Poker. First,

41:16

talk about what you achieved in Poker.

41:18

You can you you

41:20

shed some grit. Yeah. You

41:22

pushed the right shirt. I was just I sure you

41:24

pushed through a few losses. I you

41:26

know, I applied for eighteen years. I did

41:28

quit too late, which isn't surprising.

41:30

One of

41:30

the hardest things to

41:32

quit

41:33

is who you aren't. And

41:34

when you're on television known as a poker player, gosh, nose, that

41:36

becomes your identity. And if

41:38

you walk away, what does that mean

41:42

for you? Right? Like, it gets

41:43

very hard.

41:44

the So

41:46

here's the thing about Poker. So

41:47

first of all, you obviously,

41:49

knowing you know, power

41:51

of knowing when to walk away is a nod

41:53

to Kenny Rogers. When I was

41:55

playing poker, I would get very annoyed

41:57

because anytime that I, like, went on the

41:59

radio,

41:59

I was going on a television show, they would usually play that

42:02

song. Yeah. Got a no one told them, no

42:04

one told them, no one to walk

42:06

away, and no one

42:08

to run. as I was coming on, is like the intro to me coming

42:10

on. Oh, I grew to hate that song to management.

42:12

Eventually, they switched it to Poker Face

42:14

by Lady Gaga. So that was a little

42:16

bit better. Russ I

42:18

decided I was gonna reclaim the song

42:20

so that I could I could love

42:23

it again. And here's

42:26

here's the And and I think Kenny

42:28

Rogers actually says something very

42:30

insightful here about the game

42:32

of poker. You gotta

42:33

know one to hold them. That's about sticking. No one to fold

42:35

them. That's about quitting.

42:36

No one to walk away.

42:38

That's about quitting.

42:41

No one to

42:41

run. Also about quitting.

42:44

So

42:44

seventy

42:45

five percent

42:46

of the refrain

42:48

is about quitting,

42:49

not sticking. Yeah. And that's actually very much

42:51

true to poker. So I think that

42:53

when people think about

42:55

makes a

42:56

poker player amazing. And

42:57

then they were gonna list off. It's like

42:59

a real amazing ability to raise read

43:01

the other players hand. you

43:03

know, super aggressive. Like, they

43:06

they're

43:06

bold and

43:07

and courageous like, pushing all their

43:09

chips into the pot. Well, first

43:11

of all, let me just say great poker players try

43:13

to avoid putting all their chips in the pot.

43:15

They're very picky about when they

43:17

do

43:18

that. They

43:20

actually play something called small ball more,

43:22

but that's a whole other story. But

43:24

regardless of that, here's the Quitting,

43:27

if you really wanna know, what separates

43:29

great players from amateurs. It's

43:32

quitting.

43:32

it's quitting So folding

43:36

is quitting. So quitting is just

43:38

cutting your losses. That's all it is.

43:40

Right? That right. And so in game theory,

43:42

all it means is stopping something that you've

43:44

already started And it means it

43:46

means finalizing

43:47

that loss in the ledger. Right?

43:49

It's it means -- Right. Exactly. -- it means

43:51

accepting it and and

43:53

in that part of the ledger in

43:55

the negative, in the red when

43:58

there's always a chance you might get that

43:59

inside straight. And -- Right.

44:02

-- exactly.

44:02

And that that is

44:04

that's something that's been well documented

44:07

originally really in nineteen seventy nine

44:09

from CONOMENT to Versky. that when we have those

44:11

losses on the books, and we have

44:13

to now quit and turn

44:15

those into a

44:16

Duke loss that will become risk seekers.

44:20

In other words, we we wanna keep the gamble on, actually, a

44:22

little bit to the FedEx guy. Right?

44:25

He became a risk

44:26

speaker and went and Russ gamble this

44:29

money, Literally. -- was nuts. Right. Literally. He was

44:32

literally But it was either way, was a

44:34

gamble. Right? Yeah. But it

44:35

was nuts. to go and get you

44:38

know, I I guess he got I would have sued him

44:40

too. What are you

44:42

doing? But

44:44

regardless, Right? We becomes risk seeking

44:46

when we're in the losses. Now in order to

44:48

keep risk on, that means you can't fold

44:50

because fold is risk off.

44:53

all of

44:54

it. Right? It's like I'm

44:56

gonna take all the risk Russ. So that's

44:58

why we think about loss cutting. Right? So

45:01

amateur players are terrible

45:03

at this. So when you look

45:05

at

45:05

amateur players, when you look at their first

45:07

two card starting combinations that they get dealt in

45:09

the game of Texas, hold them in

45:11

all handed game. They'll play over

45:13

fifty percent of the two

45:15

card start

45:15

starting combinations. Now, I just

45:17

want to remind you that there's nine

45:19

people

45:19

at the table. So if you think about sort of

45:21

like what's their fair share, it would be

45:24

one ninth. Now, obviously, you

45:25

don't just play your fair share,

45:27

particularly if you're good. But

45:30

let's agree

45:31

that an amateur should not be doing over fifty percent because

45:33

there's nine players at the table. That's probably

45:35

not a winning

45:36

idea. My

45:38

mom

45:38

mom plays

45:39

a hundred percent. And if she could play a hundred

45:41

and twenty, she would in her in her

45:44

family poker games. She she she I wanna see

45:46

the cards. I get

45:48

it, mom. Yes. Yes. Okay. So

45:50

professionals will play

45:50

between fifteen and twenty five percent of

45:53

the two card combinations that they're

45:56

down. Now think about this. The relationship between how many hands you play and

45:58

how good you

45:59

are, you

46:00

is correlated. Right?

46:02

So the better you are

46:04

and more hands you're allowed to play. And the reason is that you can get

46:07

more edge over the other people at the table

46:09

in terms of the choices that

46:11

you make later. that would

46:14

allow you to play more than your fair

46:16

share of hands. Right? because Duke twenty

46:17

five percent is more than your

46:19

fair share at a nine handed table, except

46:21

you're going to than everybody else at playing them. And

46:24

so therefore, you're allowed to. Right?

46:26

So Russ- but amateur are playing over

46:28

fifty percent. This is part of the

46:30

reason why a pro can play twenty five percent because

46:32

they were playing all these really bad hands.

46:34

Alright. So that's number

46:35

one. Now, to the point

46:37

of your mother, what are the reasons that

46:39

somebody won't fold there? There are a

46:41

variety of them. But right at the

46:43

start, part of it is,

46:45

it's so painful

46:48

to fold a hand where

46:50

you then see the rest

46:51

of the cards and you realize you would

46:53

have made something good.

46:56

that people refuse to do it. There's a there's a saying

46:58

in poker, any two cards can win. Yeah.

47:00

And what professionals add on

47:02

to the end of it very quietly, but

47:04

not enough of the time to be profitable. Right? So

47:07

but but it's,

47:08

like, the number of times someone leaves out, like,

47:11

folded a seven dew. And look, now there's A77 and

47:13

a two on the board. It's Duke,

47:16

okay. Right. I

47:18

mean, like, there's a few people who had continued up Everest and they lived

47:20

-- Yeah. -- about, like,

47:22

frostbite and stuff. Right? But they lived. Right? Like

47:24

or or the FedEx guy, I mean, he

47:26

lived. Right? But would we

47:28

know the story if he went and gambled, then he lost

47:30

on that bet? Not a billion years.

47:32

And that's what's almost always gonna happen.

47:36

particularly by the way, if you're bed in

47:38

seventeen, right, which is one number. So mostly, you're

47:40

gonna lose all your dough and nobody's ever

47:42

gonna hear about you. But

47:44

what if? Right? So this is these what if these

47:46

counterfactuals are incredibly hard

47:48

for us. And so what ends up happening and part

47:50

of the reason why people play these hands

47:53

is that once you've started something,

47:56

the only way to know for sure how it would

47:57

turn out is to

48:00

keep

48:00

going. And what that means

48:02

is that we're gonna butt up against

48:04

the certainty that there is

48:06

nothing else we could do but fold

48:08

or quit before we're willing

48:10

to do so. So your mom plays

48:12

the hand because she wants to see the next

48:14

cards to be guaranteed that they

48:16

have no relationship with ever to her hand.

48:19

so she has no regrets about folding because

48:21

she understands at that point it's

48:23

a certainty that she could not have

48:25

won, but that is long after the

48:27

point that it's correct to walk away from things.

48:29

Because you're already fallen into the crevasse. You're already at the

48:32

top of Everest, and it's two PM.

48:34

But you don't know my mom. She's

48:35

really lucky. So

48:37

It turns out it's a good strategy there.

48:39

Good good

48:40

strategy there. Now when we

48:42

as we get back to Kenny Rogers,

48:44

The other thing amateurs do poorly is fold after they've

48:46

already entered the pot. Okay. So

48:48

once you decide to play the hand, you

48:50

now are putting money in the pot. Okay?

48:54

So what you'll hear people say, they

48:56

literally say this out loud, is, well,

48:58

I couldn't fall because I had too much

49:00

money in the pot already. had

49:03

to protect my chips. And it's, like, not

49:05

your chips anymore. That's money already in

49:07

the pot. What matters is,

49:09

is the next dollar you're gonna

49:11

put in the pot worthwhile. And this is just

49:14

very, very classic, some cost

49:16

effective. We take into account the

49:18

resources that

49:18

we've already spent. and deciding whether to continue

49:21

and spend more, those resources

49:23

have nothing to do with it. The

49:25

only thing

49:25

that matters is if I bet

49:27

a dollar here, am I getting a positive

49:30

return on that dollar? Doesn't

49:31

matter that I already put money in

49:33

the pot? I shouldn't

49:34

care about that. But boy, amateur's really, really,

49:36

really, really care about it. Yeah. The flip side

49:39

of that is if I didn't lose

49:42

the money, because it was a mine. It was the houses. Well,

49:44

once it's in your pile, it's yours,

49:46

and you gave it away. Oh my

49:48

gosh. Right? Right.

49:50

Right. I wanna come back to

49:52

sunk cost, but I'd

49:54

like you to reflect you

49:56

can, and and I don't know if it's

49:58

useful. But Duke you to

50:00

reflect on how that

50:01

experience of eighteen years, you

50:04

know, looking at amateurs and and

50:06

saying that's a mistake. I will

50:08

not make that one. or I made a

50:10

mistake and I won't do it

50:12

again. Did that spill over

50:12

into the rest of your Russ? Or were you

50:15

just a

50:15

really good poker player?

50:17

No. It's it's spilled over into the rest of

50:20

my life. Most of the things that I learned from

50:22

Poker spilled over into the rest of my

50:23

life. Now I will tell you that

50:25

there is evidence that people do get better at

50:27

this stuff with experience. In other words, when you see a lot

50:29

of iterations of it, you

50:32

get better

50:33

So an example of that would be so there

50:35

was a very large scale study that was done by Colin

50:37

Cameron along with a few collaborators,

50:39

including

50:40

Richard where

50:42

they look at trip sheets from cab drivers in

50:44

the eighties. This was before

50:46

Uber, obviously. And back Russ, what

50:48

you would do is rent most people didn't

50:50

own the medallion. You rent a cab for

50:52

a twelve hour shift and then it'll be up to you, Russ,

50:54

to decide when you wanted to drive during

50:57

that. So what they wanted to understand is because they

50:59

have the trip

51:02

sheets. We have drivers driving a

51:04

lot when were lots of fairs and driving

51:06

very little when there were very few, which would be a rational strategy.

51:08

In the same way in poker,

51:09

I want to maximize the time

51:11

I'm playing well. and

51:13

minimize the time I'm playing poorly.

51:15

I wanna maximize my time

51:17

in good games where meaning, where

51:19

the other players are quite bad.

51:21

and I wanna minimize my time in games where the other players

51:24

are quite good. So this is just generally what we

51:26

wanna do

51:28

in life. And so they wanted to know if that was what the character And

51:30

they found something very surprising, which

51:32

was that when there were lots of fairs,

51:36

the cab

51:36

drivers would quit really fast. And when there

51:38

were very few

51:39

fares, they would go forever. So

51:41

this is gonna bring us back

51:42

to Mount Everest and the marathoners. In

51:46

fact, this, by the way, they had this

51:48

strategy was so bad that compared to a

51:50

rational strategy, they would have made

51:52

fifteen percent more money.

51:54

if they

51:55

had actually followed what a rational actor would do. And in fact,

51:57

if they had just said, I'm getting

51:58

the cab, I'm gonna drive

51:59

for six

52:00

hours no matter what.

52:02

they would have made eight percent more than they did. I so question is why why

52:04

when there are no fares? Are they driving for,

52:06

like, the whole twelve hours? And why

52:09

when there are lots affairs? Are

52:11

they getting out of their cabin, like, an hour and a half? And it's because they had a

52:12

goal, they set a finish line. So they had

52:15

an earnings goal for the day. call

52:17

for the day say three hundred. And when

52:19

they hit earnings goal, they

52:21

quit because they're done. They

52:23

crossed Russ. In a

52:26

marathon, nobody keeps running past it. Like, oh, I feel pretty good

52:28

today. I'm just gonna keep going.

52:30

That's a great point. Right. It's why it's

52:32

why people who run half marathons

52:34

don't just

52:36

randomly finish a marathon because they feel in fine federal. Right?

52:38

Like you finish once you're done it. So

52:40

anyway, so they would finish once

52:42

they once they hit their earnings goal.

52:45

But if they hadn't hit the earnings goal, they would keep

52:47

going forever. Okay? So

52:48

we know that that's

52:51

actually quite bad behavior.

52:54

somebody followed up with a study, and I'm just

52:56

blanking on the name. It's in it. It's it's in the book.

52:58

So please go look in the book because I'm blanking. I'll put a

53:00

blanking on it in the sure

53:02

enough. followed up and what they did find

53:04

was that people did get better with experience. So

53:06

they still weren't

53:07

perfect. But the cab drivers who

53:09

are real veterans

53:11

were were much

53:14

better than the

53:14

ones who were not in terms of this

53:16

behavior. Howard Bauchner:

53:17

Yeah, I'm always skeptical that kind of

53:20

study because You don't

53:22

know it could be they

53:24

really need to make three hundred dollars every day because

53:26

they won't make their rent. And you could

53:28

say rationally, well,

53:29

make the three hundred tomorrow

53:31

when

53:32

at the time when the fairs are easier to get,

53:34

but maybe it's not so predictable when

53:36

the fairs are good or when they're not so good.

53:38

And so maybe as you get experience, you get

53:40

better at maybe predicting that and you can

53:42

smooth it a little bit. But

53:46

I

53:46

I have a feeling. Yeah. Except except the difference is

53:48

that it's it's the the experienced drivers.

53:50

They don't stop at their earnings call. They

53:52

just drive when the driving is good.

53:55

But the

53:55

goal of life is to take as much money as possible. Maybe

53:57

they want more leisure. Well, except the

53:59

goal of life, the goal in life, it's also

54:02

not to spend. No, Robert. If

54:04

you want to. Yeah. Right.

54:06

Exactly. Like, that's not fun.

54:08

So so, essentially, if if if

54:10

you're gonna spend some of your time driving around

54:12

in the cambridge twelve hours. Let's make sure that you're making, like, twelve hundred bucks.

54:14

Yes. Do it. And then and then quit

54:16

the day that it's not. Number one. And then

54:18

number two, the other thing

54:20

is that there are predictable

54:22

times when you know there's gonna be lots of fairs, when

54:24

there's concerts -- Yeah. -- concerts around. And if we

54:26

think if we think about an inefficient

54:27

market, this is why when there are

54:30

when you're

54:30

there's a big concert or it's rush hour, it's impossible

54:32

to find a cab because all of

54:34

these calves made their earnings and

54:36

they got off the street. Right? So it

54:39

actually creates kind of an inefficient market as well.

54:41

So, yeah, I don't think it's just like I

54:43

gotta make three

54:43

hundred dollars

54:46

a day. because obviously, that's gonna be three hundred on average. Because what the

54:48

veteran drivers are doing is they're driving past

54:50

the three hundred mark. Because they

54:52

understand, like, no.

54:54

I mean, long as this concert's around, I'm just gonna or, you know, it's a

54:56

busy time at the airport. I'm gonna drop the

54:58

thing off, come right back to the airport, get

55:00

the fair drop the thing

55:02

off, come right back to the airport. And I'm gonna

55:04

do that as long as it's busy. Yeah. I

55:06

if I've been the

55:06

referee on that paper, I'd I'd ask him

55:09

to show that I I check into how predictable the how

55:12

easy it is to figure out when the when there are a lot of

55:14

fairs. Certainly, yeah, when there's a

55:16

concert. Yeah. but day to day. I

55:18

mean, you know, you have morning rush hour,

55:20

afternoon rush hour, Saturday

55:22

night. it's New York City.

55:24

Right? Yeah. But there could be more variability

55:26

we than we expect. But the interesting point

55:28

also for me is that the

55:30

and this is true of Uber also, and

55:34

we had John Lewis talking about in a recent

55:36

episode. It's

55:39

newcomers

55:42

newcomers amateurs, where

55:44

they're poker players, cab drivers, you name it. They

55:47

make lots of mistakes. And the best ones

55:49

learn and get better at it and

55:51

narrow that gap. And the

55:53

others just go, I'm not good at this. Bye.

55:56

And they drop out of the pool after a

55:58

while. So there's a steady inflow

55:59

off at a moment. Not in poker.

56:02

you know, it's not Simparably. It depends

56:04

on how much value you use. Simparably

56:06

point out. Here and

56:08

this is this is where I would this is

56:10

where the problem is in poker, is

56:13

that and I think this is

56:15

generally the problem Quitting. That the

56:17

more uncertain the system that

56:19

you're deciding in. The ease the

56:22

more that it becomes a petri dish

56:24

for cognitive bias. Okay. So

56:26

the the question is why why would people

56:28

continue trying to butt up

56:30

against the dead certainty

56:32

that you have to turn around? Well, because

56:35

the objectively correct moment to quit is a decision

56:37

made under uncertainty. There's this particular

56:39

irony to this, which is that when we

56:41

start things, most things that we start

56:43

are made under uncertainty, There'll be

56:45

an influence of luck on the outcome, like pandemic or

56:47

a recession, or something like that.

56:49

But then there's

56:52

also just we know very little in

56:54

comparison to all there is to be known. Right? So we can think about somebody

56:56

who's investing in a startup, for example,

56:59

right, that maybe maybe is early product market fit

57:01

or pre partnered product market fit. Russ very

57:04

high uncertainty. You have, like, three people on

57:06

the team. You don't really know how that person's gonna be

57:08

as a

57:10

CEO. Is the product really gonna work out or customers gonna buy it? All these

57:12

questions. Think about taking a job. What

57:14

do you know about the company that you're

57:16

going in taking a job

57:18

with? Like,

57:19

nothing. So

57:21

so we know that we have

57:23

to make those starting decisions under considerations

57:25

of uncertainty. Lucky for

57:27

we have this valuable option, which is the option to

57:30

quit, to cut our losses.

57:32

Right? The problem is, and the

57:34

irony is that

57:36

that decision is also made under

57:38

uncertainty. That the objectively

57:40

correct moment to Quitting

57:42

particularly bad. It's gonna it's it's eleven

57:44

thirty AM. You're on the mountain. You have plenty of

57:47

oxygen. There's no blizzard

57:50

nothing is really bad that's happening right then, but it is the

57:53

objectively correct moment to quit. But what that

57:55

means is that if you quit that

57:57

moment, there's still some

57:59

chance there's

58:00

still some chance probably too low, but certainly

58:02

too low, they could still make it to the

58:05

summit and make it back down a

58:08

lot. some people did, I mean, under great duress. Right?

58:10

So so all those

58:12

biases that have to do with, like,

58:14

some cost fallacy with you

58:18

know, not wanting to quit a chance and know what was

58:20

over optimism. Right? Optimism

58:22

bias. For example, dig

58:24

into those environments to make

58:26

us keep going even when we're

58:28

not particularly good at it. And this is

58:30

particularly

58:30

true in poker for this

58:32

reason. If I look

58:34

back on why are one or

58:36

lost,

58:36

I have two things I could think about, skill and

58:38

luck. Right? Now it's usually going

58:40

to be some

58:41

sort of combination in the two, but we're binary

58:43

in the way that we think.

58:46

So as I'm looking back on that, something called self

58:48

serving bias is gonna dig in.

58:50

And self serving

58:51

bias is just this. I won because I

58:54

played awesome.

58:56

And I lost

58:56

because I got unlucky. And

58:58

you hear people say this all

59:01

the time, and they will continue well

59:03

past the time that

59:06

it is obvious. I mean, I'm talking years and

59:08

years that it is obvious

59:10

that they have no business sitting at

59:12

a table.

59:13

But the thing I love

59:15

about the Everest example, which we

59:17

haven't talked about, and I didn't think about

59:19

until this conversation while I was

59:21

reading the book, that

59:23

one o'clock turnaround time,

59:25

that's a veteran

59:28

insight. If you were headed If you were on that mountain and

59:30

you looked ahead, you thought, three hundred meters. I'll

59:32

I'll be there by I'll bake this easily.

59:34

And okay. If I get there by two o'clock, how long

59:36

could it take me to get down to downhill? I believe,

59:39

the fact that

59:41

was understood and accepted as

59:43

the turnaround time. And they still

59:45

didn't do it. Is is so

59:48

fascinating because in

59:50

real life, you rarely know when to cut your

59:52

losses. You might in poker. Spoke is a

59:54

very constrained game. Oh, no.

59:56

No. No. Not in the middle. No.

59:58

You could.

1:00:00

you could, if you're a good player, you could

1:00:02

figure out because the odds are very -- Yes. -- control plus.

1:00:04

But in real life, the

1:00:06

finish line is usually not clear.

1:00:10

the turnaround point is not clear. And so you're always

1:00:12

get it often because of that for

1:00:14

lots of reasons you've been talking about.

1:00:18

gonna push beyond one o'clock. But in this case,

1:00:20

the tragic case about Everest, that

1:00:22

one o'clock wasn't just like, hey, I think one o'clock

1:00:24

could be the time to turn around Russ

1:00:26

think it's gonna take me a while. It would yeah. So so first

1:00:28

of all, let

1:00:29

me just say in poker. The the problem is it it actually is

1:00:31

very hard to figure out for sure because you

1:00:33

can't see the the down

1:00:36

cards. good point. So everybody's cards are faced down. Right? So trying to

1:00:38

figure out when the odds go against you is actually

1:00:42

quite difficult. And

1:00:44

not only that, even when you've decided

1:00:45

that maybe your hand isn't gonna win, you have the

1:00:47

option to bluff. True. So so this is

1:00:50

part of the reason why quitting is so

1:00:52

darn Quitting. Whereas in Cas,

1:00:54

it's a much easier decision for the

1:00:56

reasons that you said. It's pretty obvious

1:00:58

that you're about to get Chuck made it. Right?

1:01:00

you're down -- Okay. -- down a castle.

1:01:02

You're down Russ It's over. But for the good play. Exactly. So you

1:01:05

Duke, you you really know what your position is there.

1:01:07

So this is part of the reason why people can make

1:01:09

a lot of money at the

1:01:12

better I am at figuring out the appropriate

1:01:14

moment to turn around, what the turnaround

1:01:16

time actually is, the better off I'm

1:01:18

gonna be in comparison to other people

1:01:21

And it's actually an incredibly hard problem. It's

1:01:23

actually very much Duke in

1:01:25

life. Right? I don't know I I don't know

1:01:27

all the information. I have if I knew

1:01:29

it, I could calculate the odds. Right? If

1:01:32

if I had the information in front of me, I

1:01:34

could surely do some quant work on it and

1:01:36

figure out what my odds are it'd be pretty simple quant work as a matter of

1:01:38

fact. I could create a game theory optimal

1:01:40

table, and I would know exactly how often

1:01:42

I

1:01:42

should

1:01:44

bluff and exactly how often I should fold and whatnot. But I gotta figure

1:01:46

out what the other person's holding. Right?

1:01:48

So so this becomes this becomes actually

1:01:50

quite a big problem. But yes,

1:01:53

this is the thing is that, you know,

1:01:55

we can think about these Quitting

1:01:57

quitting problems twofold.

1:01:58

One is that it requires you to

1:01:59

be able to forecast into

1:02:01

the future. Right?

1:02:02

So

1:02:03

that's that idea of, you

1:02:05

know, I've got

1:02:07

a startup

1:02:09

and I've missed I've

1:02:11

got money in the bank, but I've missed,

1:02:13

you know, I've missed

1:02:15

some targets. I'm looking at

1:02:18

what month over month, new user growth is,

1:02:20

you know, whatever. And these signs are

1:02:22

pointing to things are

1:02:23

kind of bad, but I've got

1:02:25

money in the bank. what

1:02:27

I able

1:02:28

to do is foresee that the signs that I'm

1:02:30

seeing right now that have to do with, you know, the

1:02:32

exploding cost of acquiring a customer, whatnot,

1:02:35

that they're they're those signals are adverse in in a

1:02:37

way that are gonna tell me that I'm not gonna get to

1:02:39

a venture scale business here and I ought to

1:02:41

quit. Right? So that's a forecasting problem. I gotta

1:02:43

get myself into the future. Now what

1:02:45

you're describing is that there's also a different type of

1:02:48

time traveling that occurs, which is

1:02:50

either the whole of your

1:02:52

past experience. helping you

1:02:54

to figure these things out or people who have

1:02:56

done it before you. So on the case

1:02:58

of Everest, it's people who have done

1:03:00

it before you, who say, one PM

1:03:03

that is the time things that happen

1:03:05

after that are really bad.

1:03:08

And don't keep going after that.

1:03:10

And we need to pay attention to those

1:03:12

people because When we think about life, it's very rare that we

1:03:14

get get to run a Monte

1:03:16

Carlo. But if you've had

1:03:18

lots and lots

1:03:20

and lots people go up that Monte

1:03:22

Carlo based

1:03:22

simulation of many, many trials so

1:03:25

you can get the idea of

1:03:28

the risk. Right.

1:03:29

Exactly. Sorry. Yes. Exactly.

1:03:32

My my the the geek in me comes out

1:03:34

occasionally. So so now

1:03:36

you've got your Monte Carlo simulation, right, because you have all these people who've done

1:03:38

it before you. And man, if you're

1:03:40

not paying attention to them, what a waste

1:03:43

because that's a real that's a real gift that the world is gonna

1:03:46

give you because it's so

1:03:48

rare that we actually can run those

1:03:50

kinds of simulations in order to get

1:03:51

some guidance on what

1:03:53

the appropriate sticking or quitting situation In

1:03:56

real life, the mount you're climbing is

1:03:58

not the same as the one that the other people

1:04:00

climbed, and therefore, you can convince yourself,

1:04:02

etcetera, etcetera. I I wanna

1:04:04

close I wanna close

1:04:06

with another

1:04:07

wonderful image in your

1:04:09

book, which I

1:04:10

think is a very powerful and very useful

1:04:12

and often goes

1:04:14

against our psychological grain,

1:04:16

which is the monkeys of

1:04:20

the pedestals. talk about that image

1:04:22

and what how to use it for your own once on purposes?

1:04:24

Yeah.

1:04:25

Okay. So

1:04:27

the show we've

1:04:28

talked about a lot of the impediments to quitting. Right? Quitting

1:04:32

lines. They make it hard to quit and

1:04:33

those Quitting very

1:04:36

clear goals. good

1:04:38

side to those and bad side to those, issues

1:04:40

that have to do with identity, who you

1:04:42

are. But there's all these

1:04:44

issues that have to do with resources we

1:04:46

put into things. So let's just call

1:04:48

that broadly capital. And

1:04:50

capital isn't just money. It can be your time

1:04:52

and attention

1:04:54

and effort. Right? So we know that once we

1:04:56

started to invest capital in

1:04:58

something, that capital itself

1:05:00

is going to make it hard for us to walk

1:05:02

away. partly because

1:05:04

we we as humans tend to

1:05:06

think about waste as a backward looking problem when

1:05:08

it's really a forward looking problem. Right? I don't

1:05:10

wanna quit now because I'll wasted my time.

1:05:13

Duke, for example, like, if you worked

1:05:15

really hard to get a PhD, it's very

1:05:17

hard to walk away from academics if that

1:05:19

was your

1:05:20

plan. because then I'll have

1:05:21

wasted why was I in the PhD program? I'll have wasted

1:05:23

my time. So on and

1:05:25

so forth. Right? But what we'd really care about is if

1:05:27

your goal is to

1:05:29

be happy and fulfilled the path

1:05:32

forward the way to do that, but we don't think

1:05:34

that way. So monkeys and pedestals

1:05:36

is really trying to get you

1:05:38

to reduce reduce

1:05:40

the debris that you're bringing into any

1:05:42

decision to quit. In other words, to minimize

1:05:44

the capital that you spend, before you

1:05:46

figure out whether something is worthwhile and continuing or not. So

1:05:48

that's the point of this mental model. It

1:05:51

comes from Astra teller, who

1:05:54

is the CEO, otherwise known as

1:05:56

Captain of Moon Shops, over at

1:05:58

Ax, which is Google's in house

1:05:59

innovation hub. So they're

1:06:03

trying to take

1:06:03

world changing ideas

1:06:06

from idea to commercialization

1:06:08

in five to ten years.

1:06:10

So obviously, this is very uncertain. Right? Like, I mean,

1:06:13

they're really working in in places

1:06:15

of high uncertainty. We're not

1:06:17

talking about incremental change. where

1:06:19

you kind of know exactly what the outcome is gonna

1:06:22

be. This they're delving

1:06:24

into the unknowns. And so they

1:06:26

use a mental model and try to try

1:06:28

to help them to figure how to approach these

1:06:30

projects so that when they

1:06:32

find out so they can find out what they

1:06:34

need to know as quickly as possible

1:06:36

in order to be able to as

1:06:37

they think about all these that

1:06:39

they consider, that they can quit all the

1:06:41

options that aren't worth pursuing, that aren't going to get

1:06:43

them to where they want to go

1:06:46

and concentrate the capital on the options that are worth pursuing. is

1:06:48

their goal, just like the cab drivers.

1:06:50

Right? Okay. So

1:06:52

monkeys and pedestals

1:06:53

goes like Russ.

1:06:56

Let's imagine

1:06:56

that you decided you're gonna make a bunch

1:06:58

of money by training a monkey to

1:07:00

juggle flaming torches while standing on

1:07:04

a pedestal. What part of the

1:07:04

project should you approach first?

1:07:08

Building the

1:07:08

pedestal or

1:07:10

seeing if you can train the monkey to juggle

1:07:13

the And Asthma teller's insight

1:07:16

is, you better trade the monkey to juggle

1:07:17

the flaming torches because otherwise, what's

1:07:20

the point?

1:07:21

Right?

1:07:21

So he's

1:07:24

saying

1:07:24

the hard part of the

1:07:25

problem, the thing you don't know

1:07:28

if

1:07:29

you can do. is whether you

1:07:31

can teach that monkey to flaming torches. That's the

1:07:34

unknown. And so there's

1:07:36

no point in doing any other part

1:07:38

of the

1:07:40

project. if you haven't solved for that unknown. That's

1:07:42

insight number one. Insight number

1:07:44

two is that if you do build the

1:07:46

pedestal, you will feel like you made progress

1:07:50

but

1:07:50

you will have made no progress out at all because you already

1:07:52

know you

1:07:53

can do it. So therefore,

1:07:55

you've learned nothing

1:07:58

it doesn't actually advance you towards your goal in really any

1:08:00

way because you you're doing something I

1:08:03

mean, you can turn a milk upside down. Like, if

1:08:05

you're doing something you already know you

1:08:08

can do. So that's that's

1:08:10

three is that in

1:08:14

in in created net false progress by

1:08:16

building the pedestal, you

1:08:18

have now created sunk

1:08:20

costs. You have now

1:08:22

created ownership over the pedestal,

1:08:24

endowment, to

1:08:26

the pedestal. Your identity is now more deeply inclined in the thing that you're trying to do.

1:08:29

And so Duke

1:08:32

you find

1:08:34

out that the monkey is super hard to train, you're

1:08:36

much less likely to quit

1:08:39

because you

1:08:39

have built the

1:08:41

pedestal. Alright. So I'll give you an example

1:08:44

of monkeys and petastole.

1:08:46

I assume you've heard

1:08:48

of the hyperloop. So

1:08:52

trying to sort of

1:08:54

vacuum tube

1:08:55

passengers from New York to LA

1:08:57

in two and a half hours, Duke,

1:08:59

in these vacuum tubes. So -- Yep. --

1:09:01

it's

1:09:01

a Elon Musk project. Yeah. Well, it's also a

1:09:03

Virgin. Virgin

1:09:04

is doing it as

1:09:07

well. Right. Copy. So

1:09:09

Yeah.

1:09:09

So so actual teller so Google, ax was approached

1:09:11

about this project. They were pitched it.

1:09:13

So after they

1:09:16

pitched it, the

1:09:18

team at Ax did a monkey's and pedestals

1:09:20

exercise, which is what they always do when

1:09:22

they're thinking about a project. And they

1:09:24

said, okay, what are the monkeys here? Well,

1:09:27

the monkey that obviously might come to mind

1:09:29

is, can you actually build something like

1:09:31

that that will work? Right? That will

1:09:33

actually cause something to go through a vacuum

1:09:35

and that already proven. So that wasn't

1:09:38

a

1:09:38

question. You could definitely move

1:09:41

things through vacuum

1:09:44

tubes. So So

1:09:44

that was not actually a

1:09:46

monkey. But they did identify two other monkeys. One was a regulatory issue. when

1:09:51

you're building that, you gotta many different townships. I don't even know. Each

1:09:54

of them is gonna have different regulations. I

1:09:56

mean, my gosh, it's a

1:09:58

beast. The regulatory issue is

1:09:59

a beast. And as Astra Taylor

1:10:02

said, we're Peter Pans with PhDs. I don't know if we can solve that one.

1:10:04

So they felt that that

1:10:06

was a pretty big statement again.

1:10:10

They're Peter

1:10:10

Pans with PhDs. What are they

1:10:12

gonna do with the regulatory issue? I mean, they're not

1:10:14

gonna be able to make any progress

1:10:17

on it. Yeah.

1:10:17

That's what they felt. Like, they felt

1:10:20

like it was a pretty hard one. And then the

1:10:22

other thing, actually, the other monkey, which is the more significant one here,

1:10:24

was Russ, gosh,

1:10:27

if things are if

1:10:29

this thing is moving so fast that you can

1:10:31

get from LA to

1:10:32

San Francisco in two and a

1:10:34

half hours, and we actually stop it and not kill everybody

1:10:36

on board.

1:10:37

So that's pretty

1:10:39

big monkey. Yeah. Don't know

1:10:41

if you can keep that monkey

1:10:44

to

1:10:44

So so they thought about that and they said, well, what

1:10:46

would we have to do in order to be able to know

1:10:48

that we

1:10:50

could

1:10:51

stop it safely?

1:10:53

and they

1:10:53

realized they kind of did some math, and they realized we're gonna have

1:10:55

to build almost the whole system to figure

1:10:57

the build almost the whole system to figure that

1:10:59

out

1:11:00

that out. And so we're

1:11:02

gonna build this humongous pedestal before we ever know whether we can solve

1:11:05

before we ever know whether we consult the monkey

1:11:07

the monkey. This isn't for us. That's right.

1:11:10

So they rejected it. Now they rejected it in fifteen minutes. Now

1:11:12

let's really, that's

1:11:14

how long it took them.

1:11:16

let's let's that's why this

1:11:19

mental model is so powerful. So let's now flash forward many

1:11:19

years now flashforward

1:11:22

many years

1:11:23

to virgin. that is doing

1:11:25

it. You can

1:11:26

look it up. There's a recent New York Times article, and Virgin's

1:11:28

hyperloop project

1:11:29

has run into two

1:11:32

humongous problems. I

1:11:34

think they've raised,

1:11:36

like, I think, over Russ hundred

1:11:38

million dollars. So

1:11:39

I spent millions and millions and

1:11:41

millions and millions

1:11:43

and dollars. so much money. So

1:11:44

much time. And they run

1:11:45

into two problems. Can you guess what

1:11:47

they are? Could

1:11:48

it be the regulatory

1:11:50

problem and the stopping problem? Russ.

1:11:53

So the

1:11:54

regulatory problem, they don't think they can solve, it seems

1:11:55

to be really thorny. The stopping

1:11:57

problem, they've managed to

1:11:59

build a sixth problem they've managed

1:12:01

to build the sex they've got they've gotten and they've built

1:12:04

enough of it to get it up to

1:12:06

a sixth of the speed. That's it. So

1:12:08

they haven't really ever

1:12:10

done a real safety test. that's

1:12:12

as far as they've

1:12:14

got. And so now, remember, so remember, Astra teller

1:12:17

also

1:12:17

has this

1:12:20

insight that one who built all these pedestals, which

1:12:22

they've done. Right? because they're building the system, which is a big pedestal because you already know

1:12:26

you can do it. that when you up against intractable monkeys,

1:12:28

you won't stop. That's great.

1:12:31

And that's exactly

1:12:32

what's happening.

1:12:34

because they're not stopping instead, they're pivoting to

1:12:37

say, well, we're not actually

1:12:39

gonna bring people on this

1:12:41

thing. We're

1:12:42

just gonna transport cargo. It's like

1:12:44

cargo. What? That that we already know how to get cargo from

1:12:46

London to the country to the other. We better to have time

1:12:49

a little bit

1:12:51

faster, but It's

1:12:52

a really expensive way to get a little

1:12:54

bit faster. Right. So they were trying to create world changing, innovative change, and

1:12:55

now they're creating an incremental improvement

1:12:58

over the current way that we

1:13:00

transport cargo because

1:13:02

they won't give it up, which would be probably the correct answer at this point. Yeah. I just to say that

1:13:07

Russ

1:13:09

I wanna

1:13:09

reference the Mary Herschelle episode we did where she defended the rationality of

1:13:12

sunk costs and

1:13:14

as an economist who for

1:13:17

years said it was the quintessential example of her rationality. She

1:13:19

did make me think about the that there are

1:13:21

some virtues to ignoring

1:13:24

some costs. even though

1:13:26

in most situations are rational. are commitment And you buying the gym

1:13:32

membership, is a way to and

1:13:34

if you ignore the sunk cost, it's a way to actually maybe get you to

1:13:38

the gym. So We'll put that link up to that episode.

1:13:40

You could see whether you're convinced.

1:13:42

That's true. Although although we know

1:13:44

that people don't use them. So

1:13:47

Yeah. Well, I'm not Okay. Here's a

1:13:49

good example here's a good example of an incredibly perverse use of

1:13:51

that. Okay. So

1:13:54

the so

1:13:56

the

1:13:56

California bullet train which is

1:13:58

supposed to connect LA to to San Francisco

1:14:00

to

1:14:02

the north. In twenty ten, they floated a bond

1:14:04

for nine billion dollars on a thirty

1:14:06

three billion dollars projected budget for high

1:14:08

speed rail. It's gonna be a bullet

1:14:10

train. Duke, you know, you see in Japan. The first

1:14:13

section of track that they

1:14:15

approved was between Madera and Fresno.

1:14:17

So Russ is on flat land

1:14:19

in the central valley. Let's

1:14:21

call that a pedestal because we

1:14:23

know we can build track on flat land. So that was what they approved. They broke

1:14:26

ground around two thousand

1:14:28

fifteen In

1:14:31

two thousand eighteen, someone

1:14:33

says, oh, we have

1:14:35

a problem. We just

1:14:36

happen to notice literally,

1:14:38

I mean, this is basically how it went.

1:14:41

We just happen to notice that there's two

1:14:43

mountain ranges. The Tah Tah choppy mountains

1:14:45

that are to the north of LA.

1:14:46

and the Diablo range even bigger to

1:14:49

the south of

1:14:50

San Francisco. And just

1:14:52

want to let you

1:14:54

know don't

1:14:55

know if we can blast tunnels

1:14:56

through mountains that are in

1:14:59

seismicly active areas, nor

1:15:01

operate a train safely

1:15:03

through those things. Okay. Well, I mean,

1:15:05

come on, those are monkeys. Right? And there's also a monkey which is

1:15:07

nimble issues, which is

1:15:10

kind of similar to the

1:15:12

to the regulatory

1:15:14

issue. my backyard. Yeah. Yeah. So okay.

1:15:16

So

1:15:17

okay so and

1:15:19

So anyway, once they

1:15:19

figured out, there's this problem with the monkeys. The

1:15:22

projected budget now exploded to eighty billion

1:15:24

dollars. It

1:15:26

went to governor Newsom

1:15:28

to

1:15:28

decide what to And he said,

1:15:30

oh, okay. Well, what we'll do is we'll build track the next section of track. We'll between between baker

1:15:35

field and Marsad, also in the central valley on flat Russ.

1:15:38

Big pedestal. Yes.

1:15:38

And then we'll and

1:15:42

then we'll build track from San Francisco

1:15:44

to Silicon Russ, awful

1:15:46

on flat land.

1:15:47

Okay. So he

1:15:49

literally approved two

1:15:52

more pedestals. Now there was there's been some

1:15:54

articles now talking about what a disaster this is. The the budget is now well over a hundred billion.

1:15:56

Russ

1:15:59

they still have not done an engineering feasibility study on the mountains yet.

1:16:01

It was supposed to be completed in

1:16:04

two thousand

1:16:06

twenty one. That's now reforecasted two thousand thirty three,

1:16:08

but who knows? Anyway, I

1:16:10

saw someone on Twitter defend

1:16:12

the offender it,

1:16:15

saying, Well, it's better to do it in Central Valley for

1:16:17

two reasons. One is,

1:16:20

it's easier.

1:16:24

Okay. But who

1:16:24

cares? Like, what are you gonna do?

1:16:26

You're gonna connect Bakersfield to Fresno? Like

1:16:30

because that seems like about what you're gonna do. Yeah. Okay. It's easier. So that's a

1:16:33

big pedestal, but then

1:16:33

they said Russ really what I think is

1:16:36

malign thing.

1:16:38

which

1:16:39

which years is if we spend

1:16:41

the taxpayer money, it's more likely the

1:16:43

NIMDIs will give up. And

1:16:46

what I say to that, I mean,

1:16:48

it's -- Right. -- is, oh, some cost is a cudgel.

1:16:50

So now you spent nine billion dollars of taxpayer money

1:16:54

on a budget that's gone from thirty three billion to

1:16:56

I think it's the last projection was

1:16:59

like one fifteen or so.

1:17:01

Right? And so now you're telling me

1:17:03

that you're trying to beat the nimbies over the head with the

1:17:05

sunk cost when you haven't even addressed

1:17:07

the mountains. So you're gonna continue building something

1:17:09

that you don't know if you can build

1:17:11

in a seismic seizemically

1:17:14

active area, and you're gonna spend a hundred billion more of taxpayer dollars.

1:17:16

insane. Russ mean,

1:17:19

it's not. And

1:17:20

so I

1:17:23

think that's one of the worst things about some what in

1:17:25

a lot of ways, what politics does with

1:17:27

some costs as they end up

1:17:29

using

1:17:29

it as a cudgel. And what a waste of taxpayer

1:17:31

money? See, that's the

1:17:32

thing, is that in service of I'm gonna

1:17:34

I don't wanna waste nine billion in

1:17:37

taxpayer money. They're now looking to waste way

1:17:39

more. which if you wanted to, like, address climate issues in California

1:17:41

or better serve the central valley,

1:17:43

it seems to me if you

1:17:45

had a hundred billion dollars to

1:17:48

create economic prosperity in the

1:17:50

central valley or address climate issues in California, it could be done a lot

1:17:55

easier than building track on flat

1:17:57

land that goes from nowhere to nowhere? I will recommend the episode, eContact

1:18:00

episode.

1:18:00

III

1:18:03

correctly. forgot, but it's Ben Flyberg on mega

1:18:06

projects. If you google EconTalk

1:18:08

projects, you'll find it. We will

1:18:10

put a link up to it.

1:18:13

When you said that Virgin has spent a hundred million, that's a lot

1:18:15

of money, I'm thinking. Not really. That compared to what

1:18:19

they're Snap's spending. solve some of these other

1:18:22

problems. Absolutely. It's still a lot of money. You almost got a PhD and you

1:18:25

almost pursued an

1:18:28

academic career How did that

1:18:30

inform your thinking about this book and your own experience there?

1:18:33

Well,

1:18:36

let me let me just I

1:18:38

I just would like to say that this is a very good lesson,

1:18:40

i'm very good lesson

1:18:43

which is we think about quitting as

1:18:43

closing a door and sealing it

1:18:46

shut. But

1:18:47

for many things that

1:18:50

Quitting we stopped thinking about it as a decision

1:18:52

that we can't reverse, it will

1:18:54

make it a lot

1:18:55

easier for

1:18:56

us because

1:18:57

I am now

1:19:00

an academic. I

1:19:00

do research with Bill Tetlock. I

1:19:02

do research with Marie Schweitzer. I do research with Jay Bambabel up at NYU. Marie

1:19:05

is at the

1:19:08

wharton school. Phil

1:19:10

is in psychology and the

1:19:12

wharton school at University of Pennsylvania. I

1:19:14

currently

1:19:14

teach at the University

1:19:15

of Pennsylvania. Russ

1:19:18

I

1:19:19

am just now enrolled as a graduate student

1:19:22

with Phil Kellogg as my advisor

1:19:24

because those studies that I ended

1:19:26

up doing that I said yes to,

1:19:28

were large scale enough and enough work that he

1:19:30

said, just write them up. You should just reenroll because

1:19:33

then you can

1:19:35

finish your PhD. because I I had

1:19:38

done enough work for a dissertation at that point. So so there you

1:19:41

go. So I

1:19:44

circled back. You know, not everybody

1:19:45

circles back, but but you can. For many things that

1:19:47

you choose to quit, you can go

1:19:49

back. And it's something that you

1:19:51

should think about. I

1:19:54

will say that my quitting man really has informed kind of the of

1:19:56

my life, which is I

1:19:58

became a much bigger quitter. Quitting

1:20:02

I realized,

1:20:03

you know, I just realized,

1:20:04

like, that fear of what's on the other

1:20:07

side should really go away.

1:20:10

they became Right? Because their

1:20:12

stuff on the other side. And I I wanna be

1:20:14

clear. I know that there are people who have circumstances where they can't just

1:20:16

go quit their job.

1:20:18

Okay? I totally get that.

1:20:20

And I'm not suggesting that they

1:20:21

do if they need, you know, they have to

1:20:24

make rent.

1:20:28

So people do, you know, people

1:20:30

have more limited ability to, you know, some people have more of an ability to

1:20:33

quit than other

1:20:36

people do that simply have to do with

1:20:38

their circumstances. But what I did learn from that is that no matter what your

1:20:40

circumstances are, or if you can

1:20:42

create one more option for yourself.

1:20:45

Russ can be a little bit more

1:20:47

ant Duke. Your

1:20:48

life will be better because you'll have

1:20:50

more you'll be more rational.

1:20:51

It will help you to be more

1:20:53

rational. about whether you wanna stay with what you're doing

1:20:56

or quit. So if you can just create one

1:20:58

more option for yourself, you're better off. And then

1:21:00

that comes up with, like, what the really sad

1:21:02

part is is that there's people who have lots and

1:21:04

lots of options, and yet they stay

1:21:06

stuck in things. Right? And think about all the people who don't have those options who

1:21:10

are stuck by circumstances.

1:21:12

who would love to have that optionality to be

1:21:14

able to go switch. Right? So I think that we really do need to be thinking about it

1:21:16

this way. And for me,

1:21:19

because I quit academics,

1:21:22

the what happened and

1:21:23

I was forced to do it, I was

1:21:25

sick. So I had to take time

1:21:27

off. I discovered poker. And

1:21:29

what I realized after that point is that

1:21:31

there's usually something on the other

1:21:33

side

1:21:33

Duke that something

1:21:35

might be really cool. My

1:21:37

guess today

1:21:38

has been Annie too. Annie, thanks for being part of eContact. Well, thank

1:21:40

you. This is

1:21:42

a lovely conversation. This

1:21:46

is Econ talk,

1:21:48

part of the

1:21:50

library of economics

1:21:51

and EconTalk, For

1:21:55

more econ talk, go to econ talk dot org, where you can

1:21:57

also comment on today's podcast and find

1:21:59

links and

1:21:59

readings related

1:22:02

to today's conversation. Sound Engineer for EconTalk is Rich

1:22:04

Goyett. I'm your host, Russ

1:22:06

Roberts. Thanks for listening. Talk

1:22:10

to

1:22:11

you on Monday.