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The No.1 Productivity Expert: 10,000 Hours Is A Lie! This Morning Habit Is Ruining Your Day!

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The No.1 Productivity Expert: 10,000 Hours Is A Lie! This Morning Habit Is Ruining Your Day!

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3879 segments

0:00

I always told that if you do 10,000

0:01

hours in anything you become a master in

0:02

it well that's wrong this idea

0:05

undermines this broader toolbox that you

0:07

need for long-term development if you're

0:09

doing that then you're missing

0:10

opportunities David Epstein is a New

0:12

York Times best-selling author whose

0:14

Infamous work challenges the

0:16

conventional wisdom about specialization

0:18

productivity and what it takes to become

0:20

successful what advice would you give to

0:22

a person that's thinking about how to

0:24

navigate their way to being really good

0:25

at something first of all being a

0:27

scientist of your own development and

0:28

creating what's called a self-reg

0:30

practice what is that so the cycle is

0:32

flect what do you need to work on plan

0:34

come up with an experiment for how you

0:35

can work on that is that getting a job

0:37

is it taking a class Monitor and then

0:39

evaluate and people who do that

0:40

repeatedly they just keep improving two

0:43

so for anything you're doing if you're

0:44

not 15 20% of the time failing then

0:47

you're not in your zone of optimal push

0:48

where you're getting as much better as

0:49

you possibly can what about Focus I get

0:52

distracted easily and I want to be more

0:53

productive in the time that I spend

0:54

working don't start your day with email

0:56

it's been shocking to look at the

0:57

research how big of an impairment that

0:59

is what about notifications so if you're

1:01

getting distracted all the time if you

1:02

say well now I really have to hunker

1:03

down I'm going to get rid of the

1:04

notifications you will start self

1:06

interrupting to maintain the

1:07

interruptions to which you have become

1:09

accustomed really yeah that will go away

1:11

but not immediately but there's a lot of

1:13

things that you can do for a productive

1:14

day for example if you that has enormous

1:18

influence in your productivity

1:20

interesting the other thing I found

1:21

which was pretty shocking was they start

1:22

talking about some of the dangers of

1:24

specialism yes Harvard Leed studies

1:26

found if you're in hospital with certain

1:27

cardiac conditions when the most

1:28

esteemed Specialists are aware way

1:30

you're less likely to die gosh that's

1:32

terrifying the conclusion was that's

1:35

because this is a sentence I never

1:37

thought I'd say in my life um we've just

1:39

hit 7 million subscribers on YouTube and

1:41

I want to say a huge thank you to all of

1:43

you that show up here every Monday and

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Thursday to watch our conversations um

1:48

from the bottom of my heart but also on

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behalf of my team who you don't always

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get to meet there's almost 50 people now

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behind the D of a CEO that work to put

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this together so from all of us thank

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you so much um we did a raffle last

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month and we gave away prizes for people

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that raffle so much that we're going to

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today you can be one of those lucky

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people thank you from the bottom my

2:24

heart let's get to the

2:25

[Music]

2:28

conversation David

2:30

yes how do you summarize the work that

2:33

you do and why you do it and who are you

2:35

really doing it for I am obsessed with

2:40

correcting what I view as

2:41

mistranslations of scientific research

2:43

about human development and so that is

2:46

the core of my work and I think I'm

2:48

doing it for everyone who is curious but

2:51

either doesn't have a scientific

2:53

background or doesn't have that

2:54

particular scientific background curious

2:56

but interested in self-improvement but

2:58

doesn't either have the time or or the

3:00

means to to go sifting through this

3:02

evidence themselves and what is the sort

3:04

of Realms of self-improvement that you

3:06

have focused on thus far in your career

3:08

well earlier on I was focused in

3:10

physical skill acquisition like in in

3:12

athletics but increasingly uh I've moved

3:14

into career and personal development

3:16

generally and looking at that with a

3:19

very very kind of long lens right so one

3:21

of the most important things to me one

3:24

of the most important messages that I've

3:25

been working on the last few years is

3:27

the fact that sometimes optimizing for

3:29

short-term development will undermine

3:31

your long-term development so let's say

3:33

if we're thinking about sports or music

3:35

or something like that the obvious thing

3:36

to do is to get a head start and

3:38

whatever you're doing pick something

3:40

stick with it don't don't switch things

3:42

because then you've lost time Focus ver

3:45

very narrowly and do as much of it as

3:47

you possibly can to the exclusion of

3:49

other things that's such an obvious way

3:51

right and you will jump out to to a lead

3:54

right we see that in sports and music we

3:56

see that in school with certain Head

3:58

Start programs that give people an

3:59

advantage in some academic

4:01

skills the problem is that kind of

4:04

narrow Focus creates short-term results

4:06

but undermines this broader toolbox that

4:09

you need for long-term development and

4:11

so you'll see what scientists call Fade

4:12

Out in these advantages which isn't

4:14

isn't necessarily actually anything

4:16

going away it's the fact that people

4:18

with this broader base will catch up and

4:20

surpass so it appears to be a fade out

4:23

okay so if you take more time to get a

4:24

broader understanding of something

4:26

whether it's in sports If you're sort of

4:27

a child prodigy um over the long term

4:30

that's going to benefit you better and

4:32

help sustain your development but in the

4:33

short term you might lose out because

4:35

there's some kid who is doing you know

4:38

really deliberate practice obsessively

4:40

and he's going to have a it's kind of

4:41

like the tortoise in the hair yeah

4:43

analogy where you know the tortoise uh

4:46

eventually wins the race yeah I mean

4:49

there's a there's a a big body of

4:51

research in Psychology that can be

4:52

summarized with the phrase breadth of

4:54

training predicts breadth of transfer

4:57

okay transfer is the

5:00

ability of someone to take skills and

5:03

knowledge and use it to solve a problem

5:05

they haven't seen before right you

5:07

transfer to a new situation and what

5:08

predicts your ability to do that is the

5:10

breadth of problems you've been exposed

5:12

to in practice if you're exposed to like

5:14

a broader set of problems you're forced

5:16

to build these

5:18

generalizable flexible models that

5:20

you'll be able to apply to new things

5:22

going forward across all of your work at

5:24

the very heart of what people are trying

5:26

to achieve in their lives what is that

5:28

at the very very heart of what they're

5:29

trying to achieve that you're speaking

5:31

to getting better getting better at

5:33

things right obviously people want

5:34

success but I think there's pretty

5:35

significant research showing that people

5:37

are often actually reacting to their

5:39

trajectory as much as their act actual

5:42

absolute performance level that the

5:43

feeling of improvement the feeling of

5:45

moving on it gives them some sense of

5:47

fulfillment right and eventually

5:49

obviously will get them to to a higher

5:51

level and so I think really this is for

5:54

people who are interested in how do I

5:56

get off sort of my plateaus going

5:57

forward and viewing it as as a lifelong

6:00

journey as opposed to trying to Peak

6:02

when they're 12 right it turns out that

6:03

the way to make the best 20-year-old

6:05

30-year old 40-year-old is not the same

6:07

as the way to make the best 10-year-old

6:08

is is there sort of a tie here with the

6:10

subject of just happiness and how to

6:12

live a happy life fulfillment for sure

6:15

yeah those aren't exactly the same but

6:18

they're important so so to think about

6:19

this in a career development perspective

6:22

right I think probably the most

6:24

interesting research on fulfillment in

6:26

careers was this project at Harvard

6:28

called the Darkhorse project

6:30

and this was looking at how do people

6:32

find a lot of these people were very

6:35

financially successful and all that

6:36

stuff but the dependent variable was

6:38

fulfillment okay sense fulfillment and

6:42

when people would come in for sort of an

6:43

orientation in this study they would say

6:46

things to the researchers like uh you

6:49

know I started off doing this one thing

6:51

I was Medical School whatever didn't

6:53

really fit me so I went over to this

6:54

other thing and I I learned I was good

6:56

at something I didn't expect so then I

6:57

went this other direction and you know I

7:00

came don't tell people to do what I did

7:01

because like I came out of nowhere and

7:03

the large majority of people that was

7:06

their story that's why became named the

7:08

Darkhorse project Darkhorse is this

7:09

expression that means coming out of

7:10

nowhere and that the norm in this day

7:13

and age was that people who found

7:15

fulfillment would travel this kind of

7:17

zigzagging path where they would learn

7:19

maybe I'm good at something or bad at

7:20

something that I didn't expect maybe I'm

7:22

interested in something I didn't expect

7:24

and they would keep pivoting and they

7:26

would say instead of saying you know

7:28

here's this person younger than me who

7:29

has more than me they'd say here's who I

7:31

am right now here are my skills and

7:34

interests here are the opportunities in

7:35

front of me uh I'm going to try this one

7:37

and maybe I'll change a year from now

7:39

because I will have learned something

7:39

about myself and they keep doing those

7:41

pivots throughout their career

7:43

throughout their career until they

7:44

achieve what Economist call better match

7:46

quality that's the degree of fit between

7:48

someone's interests and abilities and

7:49

the work that they do turns out to be

7:51

extremely important for both your

7:53

performance and and sense of fulfillment

7:55

uh and your apparent grit if you want to

7:57

talk about that so so just on that

7:59

before we move on to grip the does what

8:01

advice does that then mean you would

8:04

give to a young person at the start of

8:05

their career that's thinking about how

8:07

to navigate their way to being both

8:09

really competent really good at

8:10

something and successful in any sort of

8:12

uh monetary way but also maintaining

8:15

fulfillment um throughout their life I

8:18

think there are two two main things to

8:20

take away from that one is to not over

8:22

focus on long-term planning like I think

8:24

we we lionize having long-term goals and

8:27

that's okay there's nothing wrong with

8:28

having long-term goals

8:30

but those aren't necessarily always so

8:32

useful for you in the moment right when

8:33

I think about myself when I was a

8:35

competitive 800 meter Runner I could

8:36

have a time goal for the end of the race

8:38

but that didn't help me actually do

8:39

anything that just you see the clock

8:41

when you're done and you're either happy

8:42

or sad having goals that are let me try

8:45

let me try moving with 300 meters to go

8:47

that gives you an actionable experiment

8:49

so short-term planning I think is is one

8:52

of the takeaways uh and and creating

8:54

what's called a self-regulatory practice

8:57

so self-regulatory learning

9:00

is means basically thinking about your

9:03

own thinking taking accountability for

9:05

your for your own learning and some of

9:06

some of the coolest studies in

9:08

self-regulatory learning actually came

9:09

out of soccer football done in the

9:12

Netherlands where this woman named Ry

9:14

elfring gemer was following kids from

9:17

the age of 12 right up through some of

9:20

them went on to teams that um you know

9:22

were Runners up in the world

9:24

cup and what she'd see in the kids who

9:26

got off performance plateaus there were

9:28

certain physi measur someone had to have

9:30

like if a kid couldn't hit at least 7 me

9:32

a second sprinting which isn't that fast

9:33

but if they couldn't hit it they weren't

9:34

making it to the top that's so there

9:36

were physiological parameters but also

9:38

the kids who would get off performance

9:40

plateaus were the ones where if you look

9:41

at them in video when they're they're

9:42

younger they're saying going to the

9:44

trainer like why are we doing this drill

9:46

I think I can do this already like I

9:48

think I need to work on this other thing

9:49

and and you know sometimes a trainer

9:50

might be like oh man just get back in

9:53

line you know but these are the kids

9:54

that are thinking about what they need

9:57

to work on what they're good at they're

9:59

making this cycle the the

10:00

self-regulatory cycle is reflect what

10:02

are you good or bad at what do you need

10:03

to work on how do you need to do that

10:05

plan come up with an experiment for how

10:07

you can work on that monitor a way to

10:09

try to measure whether objectively or

10:11

subjectively and then evaluate did that

10:14

experiment that I ran work and making me

10:15

better at this thing or not and people

10:17

who do that repeatedly they just keep

10:20

improving and I think that's what the

10:22

dark horses are doing in their careers

10:24

they're saying I'm reflecting on what

10:26

I've got I'm planning a way to test

10:27

something that'll fit me I monitor it

10:30

maybe subjectively maybe objectively and

10:32

then I evaluate what that tells me to do

10:33

for the next step and you just get

10:35

better and better and better over time

10:36

so if I'm say I'm in my early 20s in my

10:39

career how do I take that and then

10:40

Implement Implement that in a within my

10:43

life to make sure that I'm going to get

10:45

to the World Cup metaphorically speaking

10:47

Yeah so and there's something

10:49

interesting about the 20s that I think

10:51

is worth saying which is there's this

10:53

finding in Psychology called the end of

10:54

History illusion and this is the finding

10:58

that we always underestimate how much we

11:00

will change what we think we're good at

11:02

what we think we're bad at how we want

11:03

to spend our time what we prioritize in

11:05

friends

11:06

Etc and EV at every step in life people

11:11

underestimate how much they'll change in

11:13

the future change continues for your

11:14

whole life it does slow down so we're

11:15

constantly Works in progress claiming to

11:17

be finished constantly through life the

11:19

fastest time of Personality change is

11:21

about 18 to about

11:22

28 when you're telling but it never

11:24

stops but that's about the fastest time

11:26

when we're telling people hey now you

11:27

have to have it figured out right

11:30

and that's when they're changing like

11:31

crazy and so I think it's even more

11:32

important to have this self-regulatory

11:34

practice in a journal I would say I mean

11:36

I do it these questions can be basic

11:39

what am I trying to do why what do I

11:41

need to learn to do it who do I need to

11:42

help me learn that how am I going to

11:44

make sure that person is there to help

11:45

me what experiment can I set up to try

11:47

it and then come back and evaluate the

11:49

experiment and pick a next one be being

11:51

a scientist of your own development I

11:53

think is Inc it it's it's

11:55

counterintuitive because you would think

11:57

that we would just internalize this

11:58

stuff just from doing things M but the

12:00

science is pretty clear that we we don't

12:02

get everything we can out of our

12:04

experiences from a learning perspective

12:05

unless we're doing it more explicitly so

12:07

I would recommend for someone in their

12:08

20s to start this self-regulatory

12:10

practice what got you into the work that

12:12

you do and how did you define your

12:14

profession okay so in my past life I was

12:16

training to be a scientist environmental

12:18

scientist I was like living up in the

12:19

Arctic studying the carbon cycle like in

12:21

a tent um and I had been a competitive

12:24

Runner I had a training partner who was

12:26

one of the top ranked guys in the 800

12:28

meters in his age group in the country

12:31

uh first family of Jamaican immigrants

12:34

was going to be the first one to

12:35

graduate college Dro dead a few steps

12:37

after a

12:38

race uh and our sort of Hometown paper

12:42

said well he had a heart attack I don't

12:44

even know what that means for someone of

12:46

that age and health

12:48

right and I got curious and eventually I

12:52

kind

12:53

of worked up the courage or whatever

12:55

that sounds silly to say it that way but

12:57

um was nervous about it to ask his

12:59

family to sign a waiver allowing me to

13:00

gather up his medical records did that

13:03

turned out he had like a textbook case

13:04

of this disease caused by a single

13:06

genetic mutation that's almost always

13:07

the cause of young athletes dropping

13:10

dead and I said we can save some people

13:12

from this with more awareness and I

13:14

wanted I decided to merge my interests

13:15

in sports and science said I want to

13:17

write about sudden cardiac death and

13:18

athletes for Sports Illustrated which I

13:20

grew up with so I got off the science

13:23

track I left after my

13:24

masters uh kind of weaved my way to

13:27

sports illustra I got in there as a temp

13:29

pitch this story about sudden cardiac

13:30

death and athletes they're like temp sit

13:32

down right and then the Olympic Marathon

13:34

trials for 2008 US team uh came to

13:37

Central Park and the guy ranked fifth in

13:38

the country dropped dead like 10 blocks

13:40

from our office and then they said don't

13:42

you know something about this and so you

13:45

know in a week I was able to write a

13:47

cover story making it look like we had

13:49

done like two years of research in a

13:50

week and I became the science writer at

13:53

Sports Illustrated it was an

13:55

interesting you know I came in there as

13:57

a temp six seven years behind people who

14:00

were younger than me MH doing sort of

14:02

more remedial work for them but I

14:05

realized pretty soon that my Oddball

14:08

background right I I think I was shaping

14:09

up to be like a typical average

14:11

scientist but you take those average

14:12

science skills and you bring them to

14:13

sports magazines like you're like a

14:15

Nobel laurate you know um and so I

14:18

realized I I could just make my own

14:19

ground instead of having to compete with

14:21

anybody but the initial impetus for

14:22

getting into this merger of sports and

14:24

science was was a personal tragedy and

14:27

how did you define yourself from a crib

14:28

perspective of a writer are you a

14:30

scientist how' you I view myself as this

14:33

merger between a science writer and

14:34

investigative reporter because what

14:35

really fires me up is when I view that

14:39

there's a really popular misconception

14:41

about something really important to

14:42

human development and that that's that's

14:45

what led to range I mean I was at Sports

14:48

Illustrated the 10,000 hours rule work

14:53

was the most

14:54

famous science in human development

14:57

perhaps ever in terms of popular

14:59

consumption and I said well I want to

15:01

write about it and then I started

15:03

reading the research and saying this is

15:06

wrong it's the most popular finding in

15:08

our field it's maybe the most popular

15:10

skill acquisition human development

15:11

research ever done and it is not right

15:14

and so those you know these things kind

15:16

of stick in my brain and I I have to do

15:19

something about it 10,000 hours what is

15:21

that for someone that's never heard

15:23

about it before yeah and what people

15:24

think about it probably depends where

15:26

they have heard of it if they've heard

15:27

of it but it's the idea and scientists

15:29

call it the deliberate practice

15:30

framework but it's this idea that the

15:33

only route to True expertise is through

15:36

10,000 hours of so-called deliberate

15:38

practice which is this effortful

15:40

cognitively engaged like not just

15:42

swatting balls at the driving range

15:44

you're focusing on correcting errors

15:46

kind of practice and that there is no

15:49

such thing as Talent differences it's

15:50

really just the

15:51

manifestation uh of 10,000 hours of you

15:54

know of differences in your amount of

15:56

hours of delivered practice so you

15:57

should start as early as possible and

15:59

there's something underlying it this is

16:00

a little nerdy but called the monotonic

16:02

benefits assumption I know scientists

16:05

not going to win any marketing

16:07

competitions but that basically means

16:09

that the idea that two people at the

16:10

same level of performance will progress

16:12

the same amount for the same unit of

16:14

deliberate practice also false and it's

16:17

one of the underlying premises of a

16:18

10,000 hour rule yeah because I've

16:20

always I've always heard that I mean

16:21

it's become a bit of a colloquial phrase

16:23

to say you've not put your 10,000 hours

16:24

in which means you've not put enough

16:26

practice to become a master I I I mean I

16:28

mean I was told that if you do 10,000

16:30

hours in anything you become a master in

16:32

it that's the kind of narrative right

16:34

well to take some chess research for

16:36

example there's uh people have been

16:38

tracked and it takes about 11,053 hours

16:41

on average to reach International Master

16:43

status in chess so that's one level down

16:46

from Grandmas so first of all 10,000

16:48

hours in that case would be a little low

16:50

but some people made it in 3,000 hours

16:52

because they learn a little bit more

16:53

quickly other people were continuing to

16:55

be tracked past 20,000 hours and they

16:57

still hadn't made it so you can have

16:59

11,053 hours rule on the average doesn't

17:03

actually tell you anything about the

17:04

breadth of human skill development so

17:06

why why is that so important for me to

17:08

understand how does that liberate me

17:10

from from wasting my time or aiming at

17:13

the wrong thing well fit turns out to be

17:15

really important so people learn at

17:16

different rates and different things so

17:17

finding where you learn better is really

17:19

important if you want to maximize your

17:20

advantages and I think that goes back to

17:24

one of the reasons why people need to

17:25

try a bunch of different things CU

17:28

you're insight into yourself is really

17:30

like limited by your roster of

17:31

experiences right um and so you kind of

17:35

need to figure out where you have

17:36

comparative advantages but for a lot of

17:37

people that's so-called skill stacking

17:40

where instead of doing the one thing for

17:41

10,000 hours you get proficient at a

17:43

number of things and overlap them in a

17:45

way that makes you very unique and so I

17:47

think this idea of just head down doing

17:48

the same thing I mean we can should we

17:51

go back all the way and talk about the

17:53

the research underlying the 10,000 hour

17:54

Ru because that's where I first got onto

17:56

this I wanted to so I was a walk-on

17:58

meaning I wasn't good enough to get

17:59

recruited as an 800 meter runner in

18:00

college and I ended up being part of a

18:02

university record holding relay so I

18:04

went from being uh you know a nobody to

18:08

being quite good and so I was inclined

18:10

to believe this 10,000 hours like yeah

18:12

just you know just my hard work and then

18:14

when I started reading the research and

18:16

I'm looking through the original paper

18:18

written in 1993 and the original paper

18:20

was done on 30 violinists 30 violinists

18:24

at a world-class Music Academy okay so

18:27

let's let's start dissecting the the

18:29

problems here the first problem was

18:32

what's called a restriction of range

18:34

these people were already in a

18:35

world-class Music Academy already highly

18:38

pre-selected pre-selected for something

18:41

again for the stat heads here that is

18:43

correlated with your dependent variable

18:44

which is skill that's a problem if

18:46

you're trying to develop a general skill

18:48

development framework that would be like

18:50

to give an analogy if I did a study of

18:52

what causes basketball skill and I used

18:54

it as my subject's only centers in the

18:56

NBA and I said well height has no effect

19:00

on skill in the NBA because they're all

19:02

7 feet tall so I've squashed the

19:03

variation in that variable so in in my

19:06

first book actually did an analytics

19:07

project where I took height among

19:09

American male adults and height in the

19:11

NBA as you might imagine there's a very

19:14

high positive correlation between a

19:16

height of an American male and their

19:18

chance of scoring points in the NBA but

19:20

if you restrict the range to only

19:22

players already in the

19:23

NBA the correlation turns negative

19:26

because guards score more points than

19:28

other positions mhm so if you didn't

19:30

know that if you just did that study

19:32

with only NBA players you would tell

19:34

parents to have shorter children to have

19:35

them score more points in the NBA so

19:37

when you don't bring some sense of

19:40

what's going on to your research and you

19:42

rest strict range that way you can end

19:44

up with the wrong message aside from

19:46

that Gods score more points or less

19:47

points they score more points and

19:48

they're shorter ah okay right so if you

19:51

if you don't look at the whole

19:52

population and you just look at people

19:54

who are so highly pre-screened they're

19:55

already at the top you can end up with

19:57

these sort of backward advice

19:59

the other issue that caught my eye when

20:00

I first read the study was that there

20:03

was they only reported the average

20:04

10,000 hours was the average number of

20:06

hours of deliberate practice by the the

20:09

10 best violinists by the age of 20 and

20:13

then there was a second group and a

20:14

lower group and they said there was

20:16

complete correspondence meaning nobody

20:18

who had practiced fewer hours was better

20:19

than anyone who had practiced more hours

20:22

but they only included the average so I

20:23

couldn't tell that so I said oh I would

20:25

like to know if that's true can I see

20:27

the data to see if that's true and I so

20:31

I contacted the you know Andre Ericson a

20:33

wonderful guy who was the so father of

20:36

the 10,000 hour rule although he hated

20:37

that uh moniker actually um and I said

20:42

you know can I see the data or the

20:43

measures of variance to know how much

20:45

variation there was between individuals

20:47

and he said well you know people were

20:50

inconsistent on their repeated accounts

20:52

of their practice so we don't think

20:53

that's important I said well everyone

20:55

has trouble with getting good data that

20:56

doesn't mean they don't report the

20:58

measure variance so after I started

21:00

criticizing This

21:01

research 20 years after the study came

21:04

out they did a paper updating it with

21:06

some of the actual data and you could

21:08

see the original conclusion was wrong

21:10

there was not complete correspondence

21:11

some people who had practiced less were

21:13

better than some people who had practice

21:14

more some people had gone way over

21:16

10,000 hours some people were way under

21:18

and had done better there were all sorts

21:19

of other factors that mattered right

21:20

like I like to call it the 625,000 hours

21:23

of sleep study because the top tier

21:25

group got a lot more sleep they were

21:27

sleeping like 60 hours a week on average

21:28

compared to lower groups and that was a

21:31

a huge difference in the study how much

21:32

they were sleeping so it could have just

21:34

been sleep sleep or but there was just

21:36

tremendous individual variation yeah so

21:38

this idea of an average completely

21:41

obscured the real story which was that

21:43

there were actually people who were

21:44

practicing less and doing better than

21:46

people who practiced more so there were

21:47

all one problem after another I just

21:49

said you know I'm getting Youth Sports

21:52

pitches I'm getting investment pitches

21:53

like citing the 10,000 hours rule it's

21:56

not right and it's giving the wrong

21:58

impression

21:59

of how hum devel and this idea that you

22:02

need to just Pi something and with it

22:04

and that's sampling to try to figure out

22:05

where you have your best shot is

22:06

worthless and that's wrong and so I

22:09

became kind of obsessed with getting

22:11

after

22:12

that I really want to become successful

22:16

in the things that I'm applying myself

22:17

to in the season of my life so whether

22:19

that's podcasting or starting businesses

22:21

my business portfolio is quite varied of

22:23

sort of different industries from

22:25

everything from sort of psychedelics to

22:27

um SpaceX to whatever it might be and so

22:30

when I was you know thinking about

22:32

sitting down with you today I thought

22:34

maybe I'll just tell him where I'm

22:35

trying to get to in my life I'm a I'm a

22:36

30-year old man so you know I'm I'm not

22:39

in the early phases of my career does

22:41

that mean for example that I can't make

22:43

ground now what phase of your career are

22:45

you in I don't know because I had this

22:46

18 to 28 thing so I thought maybe I'm a

22:48

little bit more rigid and you know there

22:50

was research a few years ago from MIT

22:52

and Northwestern and the US Census

22:54

Bureau that found the average age of a

22:55

founder of a fast growing Tech startup

22:57

top one in 10,000

22:59

guess what the average age was on the

23:00

day of founding guess 25 45 and a

23:04

50-year-old had a better chance than a

23:05

30-year-old but we never hear just like

23:07

we never hear the story of these like

23:09

Zig zaggers we only hear the Tiger Wood

23:10

story we only hear like Mark Zuckerberg

23:13

famously said young people are just

23:15

smarter when he was 22 do you hear him

23:17

saying that anymore no surprise surprise

23:20

but we just we never we we like valorize

23:24

precocity so I would not say that you're

23:27

not in the early stages of your career

23:28

you're certainly not by by that metric

23:30

and that's not to say that there aren't

23:32

tremendous companies or if you know

23:34

measured by market cap that some of that

23:36

there are these amazing young

23:37

Founders but they get outsized attention

23:39

compared to what's the norm that that's

23:41

another thing that's really important to

23:43

me is not to say there aren't acceptions

23:44

because there as many different ways to

23:46

the top as there are human beings but I

23:48

think we're constantly focusing on the

23:50

exception when people should at least be

23:52

aware of the norm so the average so the

23:54

fastest growing did you say Tech

23:56

Founders Tech startups but Tech in Tech

23:58

in this context also included things in

24:00

agriculture right it's not just photos

24:02

sharing apps like Tech broadly speaking

24:04

which I think is important because it I

24:05

think it's fair to say that it's less

24:07

likely a 55-year-old would understand

24:12

some of the more emerging platforms that

24:13

are native to say you know like a Mark

24:15

Zuckerberg at 22 who's messing around in

24:17

his dorm room with with computers and

24:19

the internet yeah I think that's fair

24:21

but technology touches a lot of other

24:22

areas of the you know it's like

24:25

yesterday on the way here there was a I

24:26

was learning about a software that I had

24:28

never heard of because all of the

24:29

computers were down in the airport right

24:31

Technologies in all these places that we

24:33

that are not as kind of uh don't have

24:35

the sort of figure head that's publicly

24:37

profiled the same way so if I if I do

24:39

want to become okay so I understand that

24:41

this season of my life I can do whatever

24:42

I want in terms of I can aim at whatever

24:45

I want doesn't mean I'm going to be good

24:46

at it but if I just want to be more

24:47

productive in the goals that I am aiming

24:49

at so say you know this podcast means a

24:51

lot to me so I want to be more

24:52

productive when it comes to figuring out

24:55

how to move this podcast forward how to

24:57

innovate um how to solve some of the

24:59

problems and challenges that we

25:01

face what are the first things that

25:03

spring to mind when I start speaking

25:04

about productivity with a very focused

25:06

task I mean I think your a challenge for

25:08

you is going to be that this podcast has

25:09

gotten so big and you've gotten so

25:11

competent at it that you're going to be

25:13

in what uh a rut of competence or what

25:17

Economist Russ Roberts told me a hammock

25:18

of competence you're in an area where

25:19

you're so comfortable and so successful

25:21

that getting better is going to be

25:23

harder because there's disincentive from

25:25

changing anything that you're doing

25:26

right and you have to take some risks I

25:28

mean you know that you're an

25:29

entrepreneur if you're going to want to

25:30

get better you're going to have to take

25:30

some risk I think that's going to be a

25:32

difficult thing to do because you know

25:34

there are people in this room that

25:35

depend on you uh risk for you is risk

25:38

for them too and so I think you have to

25:40

start thinking about what would be some

25:41

smart risks if you want to innovate with

25:42

the podcast what might that look like

25:44

and finding ways to run small

25:47

experiments I'm a huge fan of low stakes

25:49

practice right how can you set up some

25:51

low stakes practice for what might be a

25:52

worthwhile larger experiment and I think

25:54

that's the same

25:56

for individuals dring in their career

25:58

like I love this phras my my favorite my

26:00

absolute favorite phrase in range was is

26:03

a paraphrase from this woman named

26:05

herminia Ibara who's a professor at the

26:07

London business school and she studies

26:08

how people make work transitions so her

26:11

phrase was we learn who we are in

26:13

practice not in theory so the thesis of

26:15

her work is that there's this idea that

26:16

you can just introspect and go forth and

26:19

know what you should be doing you know

26:20

like like Clark Kent running into a

26:22

phone booth and ripping off his and

26:23

becoming comes out as Superman but work

26:26

is part of identity and it doesn't

26:27

change like that from introspect you

26:29

actually have to go try something see

26:31

how it went what was unexpected what did

26:34

you learn that you might be interested

26:35

in or or that you're better at that you

26:37

didn't what's something that you're good

26:38

at that you realize you're not

26:40

using and then you make your next step

26:43

based on that right and I think when

26:45

you're so competent and successful and

26:46

getting only you know tons of positive

26:48

feedback for something uh it becomes

26:51

hard to take risk and so I think that'll

26:52

be a challenge for you because if you

26:55

take a sufficient amount of risk right

26:57

you want to be in your zone of of

26:58

optimal push so for anything you're

27:00

doing if you're doing practicing

27:02

whatever physical skill anything if

27:04

you're not at least like 15 20% of the

27:07

time failing then you're not in your

27:09

zone of optimal push where you're

27:10

getting as much better as you possibly

27:12

can and I

27:13

think when you have something that's

27:15

very successful that's hard and so I

27:18

would start thinking about what risks

27:20

you're willing to take and it doesn't

27:21

mean it's a failure if something goes

27:23

backward right if the views go down or

27:24

whatever metric you're you're measuring

27:26

on it's interesting it's supp to see

27:27

something it's one of my great

27:28

obsessions in life and it's also one of

27:30

the things that keeps me up at night

27:32

bugs me in the shower is um how to keep

27:35

a team conducting experiments and

27:37

failing more when they are successful so

27:40

when this podcast went to number one in

27:42

Europe I hir ahead of failure and her

27:44

sole responsibility is to increase the

27:46

rate of failure and experimentation in

27:47

our team which means just get all of our

27:49

different departments we've got

27:50

different departments in this particular

27:51

business so there's 40 40 odd people in

27:53

this company called the D CEO and there

27:56

is a production team there is the social

27:58

media team there's the commercial team

28:00

for example and there's the guest

28:01

booking and Logistics team and I I felt

28:05

we're actually in La driving down the

28:06

road and I was speaking to jamaa who's

28:07

the head of the guest booking and

28:09

research team and I was saying like one

28:11

of the the most important thing now now

28:12

that we're number one is that we keep

28:14

like disrupting ourselves because

28:15

there's going to be some kid like we

28:16

were three three years ago that because

28:19

of their naivity that they're not

28:21

encumbered by all of this sort of like

28:23

convention and all this success so hide

28:26

a head of failure and experimentation

28:27

who's in our team has been working and

28:29

now in in the last couple of days we're

28:32

running an experiment where every single

28:34

one of those departments has essentially

28:36

like a failure assistant in it who is

28:39

who's because you know what happens with

28:40

people they they get busy doing their

28:42

job and experimentation and failure is

28:44

always secondary to their job so if we

28:46

put failure people into the each team

28:49

and they drive the experiments they

28:51

understand the team they drive the

28:52

experiments they measure them and most

28:53

importantly they report their failures

28:55

and experiments back to the whole team

28:57

because there's really transferable

28:58

learnings for example there was one the

29:00

other day where the social media team

29:02

discovered this thing on Tik Tok which

29:03

allows us to look at a guest like you

29:06

and find your most popular videos ever

29:08

on Tik Tok with a click and the social

29:10

media team had figured that out which

29:11

was really useful for them but then the

29:13

research team over here that are booking

29:14

guests who are trying to find the best

29:16

videos that a David has ever made they

29:19

also benefited from just the discovery

29:21

of that button because instead of having

29:22

to scroll through the entire Tik Tok

29:23

they can press one button and see your

29:24

most popular videos so it's all there's

29:26

this real 1 plus 1 equal 3 getting the

29:28

teams to share their fails failures and

29:30

experiments so they don't have to fail

29:32

in the same ways so what did you just

29:34

write down this this brings up so much

29:35

stuff because the fundamental problem

29:37

you're getting at here is the one called

29:38

the explore exploit tradeoff right um

29:41

and so explore is what it sounds like

29:43

looking for new knowledge or new things

29:44

that you can do that'll add value

29:46

exploit is taking stuff you're already

29:47

good at that you already know and

29:48

drilling down on it and this is like the

29:51

fundamental challenge for people in

29:53

organizations that did good is once

29:55

they've find something they're really

29:56

good at and they drill down in it

29:58

they tend to ditch explore modee yeah

30:00

right and balancing that explore exploit

30:03

and there's all these of course you know

30:04

these like famous business cases like

30:06

Kodak invents the digital camera and

30:07

scuttles it because they're like why

30:08

would we disrupt our own business but

30:11

there was this fascinating work led by a

30:13

guy named dashen Wong in Northwestern uh

30:15

who does like people will do Career

30:17

Development studies looking at 20 people

30:19

and he'll look at 20,000 people you know

30:20

so his work's just fascinating and he

30:22

what he saw in this work with his

30:25

colleagues was that people tend to have

30:28

hot streaks in their careers their best

30:30

work tends to come in

30:31

clusters most people will only have one

30:34

some people will have more than one if

30:36

they're lucky and reliably what precedes

30:39

a hot Ste he was looking at I think it

30:40

was like 26,000 like film directors

30:43

artists

30:44

scientists reliably what precedes a hot

30:46

streak is a period of exploration where

30:48

they're trying these different styles

30:50

they're going broad they're they're

30:51

keeping a smaller team so they can be

30:53

nimble they're moving between teams and

30:55

then they find something and they they

30:56

drill into it and if going to have

30:58

another hot streak they do it again they

30:59

Zoom back out and they go to this

31:01

explore explore explore and then exploit

31:03

so they toggle between these modes

31:05

instead of staying just in one but the

31:08

clear message of his work is that

31:11

exploration precedes a hot streak and if

31:13

you don't do the exploration you just

31:15

settle into exploit at sort of a

31:16

middling level then you're you're kind

31:18

of sacrificing your your hot streak so

31:20

that that was one of the things that

31:21

came up for me the other thing was this

31:24

you got to something this idea of people

31:26

not only doing things that might fit

31:27

fail and I think that's great that they

31:28

have the title failure right cuz you'll

31:31

have

31:32

the uh you know Adam Grant who I think

31:34

we both know is he he he mentioned me

31:36

some once something called the hippo

31:38

effect where it's like the opinion of

31:39

the highest paid person in the room I

31:41

think the is the acronym where their

31:44

their signaling is really important for

31:46

everyone else so if you're not just

31:47

giving lip service like yeah failure is

31:49

good but actually giving people that

31:50

title I think that's a great signal for

31:52

you're underwriting risk you're

31:54

underwriting risk for people

31:56

psychologically and you're creating what

31:59

what scientists who study sort of

32:00

networks like groups of teams call an

32:02

import export business of ideas and this

32:04

is one of the

32:05

Hallmarks of organizations and and

32:08

ecosystems that learn and adapt to to a

32:11

changing world and the import export

32:13

business of ideas means you need to have

32:15

information flowing through an

32:17

organization you have people doing

32:18

different things maybe people even

32:19

moving teams here and there so I always

32:21

think of the engineer uh Bill Gore who

32:25

created the company or founded the

32:26

company that created gortex and he

32:28

fashioned the company based in his

32:29

observation that organizations often do

32:32

their most impactful work in times of

32:33

Crisis because the disciplinary

32:35

boundaries go out the window and people

32:37

start what can I learn from my neighbor

32:39

you know and working together or do he

32:41

like to say real communication happens

32:42

in the carpool which I think is a funny

32:44

saying but I worry about that with more

32:46

hybrid and remote work where you can't

32:49

necessarily just rely on Serendipity for

32:53

people to be sharing these ideas in this

32:55

informal way and so I actually think we

32:57

have to be a lot more thoughtful about

32:59

setting up our own import export

33:01

business of ideas internally and it

33:02

sounds to me like that's what you're

33:03

doing okay so what about then on in an

33:05

individual level how do I as an

33:07

individual I've got you know lots of

33:09

things I'm doing I'm writing some books

33:10

at the moment I do the podcast lots of

33:12

other things how do I become more

33:14

productive within an organization

33:16

because there's my to-do lists I've got

33:18

10 to-do lists from all of my different

33:19

team members who can put things on there

33:21

um I get distracted easily I think

33:25

because I end up watching a video about

33:26

AI on YouTube or about Rockets or

33:27

something and I want to I want to get

33:29

more done really I want to be more

33:31

productive in the time that I spend

33:32

working so this is when you know what

33:34

you should be doing when I know and you

33:37

know there's nothing wrong with

33:37

sometimes like watching YouTube and

33:39

Rocket like that's you get ideas from

33:40

doing kind of stuff myself but T Todo

33:43

lists is a lot of to-do lists yeah do

33:45

you get most of the stuff done on those

33:46

to-do lists it's more so each team from

33:49

my chief of staff to my assistant to my

33:51

manager has a to-do list on Monday that

33:53

they send things to me on and then I go

33:55

through there and it's either a task or

33:57

it's an approve or it's just letting me

33:58

know something and that's kind of how it

34:00

works so I at one point had when I was

34:02

getting overwhelmed with some stuff I

34:04

had a virtual assistant for a little

34:06

while and we would categorize like

34:07

emails into list a priority b c d all

34:09

this stuff and eventually I realized

34:12

that was empowering me to do a lot of

34:13

low value things I became efficient at

34:15

doing things that I shouldn't be doing

34:16

so I was seeing this public email

34:17

address of mine that when I was

34:19

oblivious to it I wasn't answering and

34:21

that was fine and but once I knew it was

34:24

there I'm like oh I have to answer this

34:25

I have to answer this I have to answer

34:26

this and so one important step for me

34:28

was realizing that only the A-list is

34:31

the stuff that's going to get done

34:32

because I'm a limited person with a

34:34

limited life so one I think it's maybe

34:36

you do need to do all that stuff or you

34:37

just need to be aware of it but some of

34:38

it is just I think there can be a danger

34:41

in someone who has a lot of support

34:44

resources uh where they can lose some of

34:46

the aspect of prioritization where you

34:48

just need to say this is the list that's

34:49

important other things I might not get

34:51

to but for someone like you I would I

34:52

would suggest something like not

34:54

starting your day with email or

34:56

messaging

34:58

because you know we were talking a

35:00

little bit before about this thing

35:01

called the zarnik effect which is this

35:03

idea that an unfinished task leaves like

35:04

a residue in your brain basically and

35:07

makes you it makes it harder for you to

35:09

fully transition to doing something

35:11

else and because I expect your various

35:15

inboxes will always be an unfinished

35:17

task right yeah if you start the day

35:19

with that no matter what you do the

35:22

residue is going to be there for what

35:23

you try to switch to next so I'm not

35:25

saying don't address your email but I

35:27

wouldn't start with I would the day

35:28

before what is the thing that if I get

35:30

done tomorrow it's going to be a good

35:31

day and start with that before you do

35:33

the things that might leave residue on

35:34

your brain and start multitasking how do

35:36

they know that's true have they done

35:37

studies on this aonic effect yeah yeah

35:39

absolutely I mean you can see you can

35:41

give people one you can do it in a

35:42

workplace environment where researchers

35:45

like Gloria Mark for example will be

35:47

tracking everything from someone's

35:48

Vision to what they're doing on their

35:49

computer to their heart rate variability

35:52

and seeing how long it takes them to get

35:53

back to a task um increased switching

35:57

when there's like like a residue in

35:58

their brain so their rate of switching

36:00

will go up uh you know some of their

36:02

indicators of stress response will go up

36:04

or in a cognitive task they'll perform

36:06

more poorly if there's something still

36:07

stuck in their brain so there's also

36:08

sort of laboratory experiments where you

36:10

give somebody something don't let them

36:12

finish it give them a cognitive task and

36:13

you see does it impair their performance

36:15

if they weren't allowed to finish the

36:16

thing that started

36:18

before I want to close off on that point

36:20

of just team culture then how to get a

36:21

team of people to do really exceptional

36:23

Innovative work and to fail faster is

36:25

there anything else that's sort of

36:26

pertinent to you and I'm saying this

36:28

purely selfishly because it's one of the

36:29

things I think a lot about even with

36:30

this podcast is how to get our teams

36:33

failing more often if that's even the

36:34

right thing to be aiming at the type of

36:36

experiments we should be running how we

36:37

should be running them anything else at

36:39

all yeah I mean I don't think I don't I

36:41

don't lionize failure for its own sake

36:43

right it's just I think it's inevitable

36:45

if you're experimenting enough that

36:46

you'll have some failure but I think one

36:48

useful thing to do like a guy I love

36:50

who's made a big impression on me named

36:51

ed Hoffman was used to be the chief

36:53

knowledge officer at Nasa that's like

36:54

after NASA had some disasters most every

36:57

they did was very successful but

36:59

obviously they had some high-profile

37:00

disasters he was brought in because they

37:02

were deemed not a learning organization

37:04

they weren't learning from lessons of

37:05

the past and he was brought in to help

37:06

create a knowledge system so that people

37:09

would learn from the lessons of the past

37:11

and one of the things he does in

37:12

organizations when he goes in because

37:14

now he consults is he goes around he

37:16

asks people what are you good at that

37:18

we're not

37:19

using right and people always have an

37:21

answer for that and that leads to well

37:23

what's some what's an experiment that we

37:24

can run to try to use that thing that

37:27

you're good at that we're not using so I

37:28

think that can be kind of a foundational

37:30

question to help people set up some of

37:31

those experiments but also a big impact

37:34

would be and this is a tough one you

37:37

going ahead and failing in an experiment

37:39

because that's going to set the agenda

37:41

right but you would actually have to

37:42

fail like this can't be you go out for a

37:44

jog and you trip on the curve or

37:45

something like you have to fail

37:47

something of

37:48

consequence uh and and then your

37:50

reaction to that can set a

37:52

tone um so that's on the the team level

37:55

so I just I want to really think about

37:57

how on an individual level I can become

38:00

a better

38:01

learner because one of the things I do

38:03

obviously for a living is I do this

38:04

podcast and I meet all these incredible

38:06

people and they say things to me that in

38:07

the moment change my life but I feel

38:09

like I forget them five minutes later

38:10

often some of them stick some of them

38:11

don't so I've always wondered how can I

38:13

become a better learner people come up

38:15

to me in the street and say you might

38:16

you must know so many things about so

38:18

many things and also my audience they

38:20

they tune in every week they listen to

38:22

these incredible people how can we

38:24

become better Learners what is it we can

38:26

do to ret retain information better and

38:28

then also bring it into practice in our

38:30

lives oh to retain inform okay for

38:32

retaining

38:33

information one repetition and

38:35

familiarity is important right so if

38:37

there's something that's really

38:37

important to you you should reread it

38:39

because the first time you go through if

38:41

you're hearing new things new terms

38:44

you're using your working memory just to

38:47

keep up basically so so to put this in

38:50

kind of a simple way like there's

38:51

research where you look at school kids

38:53

and if they're given um like an essay

38:56

about baseball say the kids that are

38:59

deemed really good readers and there are

39:01

kids who are deemed poor readers and the

39:02

the kids who will do the worst on

39:03

comprehension are the poor readers who

39:05

don't know anything about baseball but

39:06

the kids who know about baseball but are

39:07

not as good readers will still have

39:08

better comprehension than the kids who

39:10

are good readers but don't know anything

39:11

about baseball if they only get to go

39:13

through once because having some

39:14

knowledge helps you fit it into what's

39:16

called your semantic Network the

39:18

spiderweb of all the ideas in your brain

39:20

so one going back over things that can

39:22

be taking notes whatever it is but when

39:25

you learn something new try to fit it

39:27

into your semantic Network when you

39:28

learn something connect it back to

39:31

something you already know so like when

39:32

you have these conversations you

39:34

probably have a better tendency to

39:35

remember things where you say you know

39:37

that reminds me of some other guest that

39:39

either agrees or disagrees with

39:40

something that some other guest said and

39:42

you've attached it if you think of your

39:44

brain as like the spiderweb things are

39:46

attached by threads and if you vibrate

39:48

one thread it's more likely to shake

39:50

these other ideas into your brain so

39:52

when you're learning something new stop

39:54

and try to fit it into your existing

39:56

base of knowledge if you want to return

39:57

better can can I use that to sort of fit

40:00

it into an example so I'm thinking of

40:02

you you said something about um what is

40:05

something I don't use but I'm good at

40:08

would the listener that's listening to

40:09

this now in order to embed that think of

40:11

something that they are not using that

40:13

they're good at because then it kind of

40:15

brings it into their absolutely okay

40:17

absolutely use it as quickly as you can

40:19

again repetition but fit it into your

40:21

network of ideas like stop if you have

40:23

to because you know you can read a ton

40:25

but if you're not kind of and and I

40:27

think I think reading even things that

40:29

you don't retain still change your

40:31

sensibility at some level even if you

40:32

can't consciously pull up all of the

40:34

ideas and statistics and so on but for

40:36

things that you really want to be able

40:37

to

40:39

access connect it to other things that

40:41

you already know and someone's called

40:44

space repetition like if you can have a

40:46

way where you come back to it at

40:49

intervals that'll be much better so I

40:53

use

40:54

this um like readwise as a programming

40:57

I'm not like affiliated with them in any

40:58

way it's just a thing that I use where

41:00

if I have highlights in Kindle books or

41:03

ebooks it will feed me back my

41:05

highlights at intervals things that I

41:07

thought were important

41:08

regularly and that's taking advantage of

41:11

what's called spaced spaced repetition

41:13

where if you you want to actually leave

41:15

a space almost to the point of

41:16

forgetting something and then if it's

41:18

brought up again you're embedding it

41:20

better in long-term memory so this is

41:21

for for learning anything spaced

41:23

repetition language learning all this

41:25

kinds of stuff so you would think that

41:27

you just repeat a thing a million times

41:30

as soon as you have it and that's the

41:31

best way to Grapple on to it that's not

41:32

the most efficient use of time it's

41:34

actually to to space it out and quizzing

41:36

yourself is a great way to retain so

41:38

there's something called The Generation

41:39

effect which is if like if you have to

41:43

do highlighting versus uh flash cards

41:46

flash card quizzing is much better the

41:48

generation effect is being forced to

41:50

come up with an

41:52

answer primes even if it's wrong in fact

41:54

sometimes especially if it's wrong

41:55

primes your brain to then retain the

41:57

right answer it's actually something

41:58

called the hyper correction effect where

42:00

if you're really wrong about an answer

42:01

you're much more likely to remember the

42:03

right answer once it's given to you so

42:05

if you're looking up a piece of

42:07

information I suggest you guess what

42:09

it's going to be before you get the

42:10

answer it doesn't matter if you're right

42:12

or wrong might feel bad to be wrong but

42:14

it doesn't matter you'll better retain

42:15

it when you see the right answer but if

42:16

I'm wrong then I'm I guess I'm more

42:19

shocked so there's even more retention

42:21

of that new answer it's Salient I mean

42:24

this is this is what this is so this is

42:26

one of this kind of quizzing where it

42:28

feels hard because you should do it

42:29

before you know the answer is something

42:31

I wrote about in range called desirable

42:32

difficulties these are things that make

42:35

learning feel less fluent they are

42:37

unpleasant they may slow you down much

42:40

better for long-term retention

42:42

interesting so the more difficult the

42:45

learning the more you learn often I mean

42:49

but I guess there can be a case where

42:50

something so over your head that you're

42:52

not learning anything right but these

42:55

desirable difficulties are like one of

42:56

the most famous ones is called

42:59

interleaving or mixed

43:01

practice and this is if you're training

43:03

at something you you want to vary the

43:07

types of pro so let's give an example

43:10

DJing I'm I'm DJing at the moment okay

43:12

so I don't know all the skills that go

43:14

into DJing but if there's a way to do it

43:16

you should try to instead of doing the

43:17

same skill over and over and over again

43:19

well let me give you let me give you a

43:20

research example and then you can Port

43:21

it into DJing so in a recent study there

43:24

were dozens of uh middle school math

43:27

classrooms Middle School of sixth grade

43:30

that were assigned to different types of

43:31

math learning some of them randomly

43:33

assigned some of them got what's called

43:34

blocked practice that's you give like

43:37

problem type a AAA bbbb

43:40

Etc kids make progress fast they're

43:43

happy rate their teachers highly Etc

43:45

other other classrooms got what's called

43:47

interleaved or mixed practice where

43:49

instead of doing a followed by B it's

43:51

like you took all the problem types

43:52

threw them in a hat and Drew them out at

43:54

random progress is slower they might be

43:57

less happy because they don't feel like

43:58

they're getting it but instead of having

44:00

to just execute a procedure they're

44:02

having to match a strategy to a type of

44:05

problem and when the test came along

44:08

where everyone has to transfer to new

44:09

problems the inter Le group blew the

44:12

block Practice Group away it was like

44:14

the effect size was like taking a kid

44:15

from the 50th percentile and moving them

44:17

to the 80th just by arranging the

44:19

practice in a way that made it more

44:21

difficult what's going on there I think

44:24

I mean it seems to be and this this work

44:27

for physical learning as well I think

44:29

this is one of the reasons why this if

44:31

you want why fotsa is like why like 90%

44:33

of the best footballers grow up on fotsa

44:34

instead of like playing on full-size

44:36

pitch um is that it forces you to

44:39

instead of doing using procedures

44:41

knowledge which is you learn how to

44:42

execute this procedure over and over

44:44

you're doing making connections

44:45

knowledge which is identifying the

44:48

structure of a problem and foring out

44:50

how to match a strategy to it and so

44:52

you're building this like mental

44:53

template instead of just an ability to

44:55

execute this like flexible template that

44:57

can be applied going forward so you're

44:59

getting like a broader context of the

45:01

challenge versus a very narrow solution

45:04

perspective to how the challenge is

45:05

solved you're kind of understanding it

45:07

from a deeper level right from different

45:09

sides and and you're building this

45:10

generalizable model in your head of how

45:12

to approach it I mean my my favorite and

45:15

I'd be the only person to say this but

45:16

my favorite study that went into range

45:18

was this one the one that surprised me

45:20

the most I guess was this one that was

45:23

done at the United States Air Force

45:24

Academy which is this amazing place for

45:26

experiments because they get a thousand

45:27

new students every year those students

45:30

are randomized to math classes that all

45:33

have the same test and same grading and

45:34

everything then they are randomized the

45:36

next year and randomized again so you

45:38

can get these huge experiments

45:39

randomizing people to math classes and

45:41

they looked at 10,000 students and found

45:44

that the teachers who are the best at

45:46

getting students to do well on the test

45:48

in their own class in their own intro

45:49

class right teacher year one has

45:52

students who score highly on their test

45:55

those students go on to underperform in

45:57

the subwing classes and teachers whose

45:59

students sometimes rated them lowly

46:01

poorly because they thought it was hard

46:03

don't do as well on the test the first

46:05

year overperform in subsequent classes

46:07

and the difference is the way to get

46:09

someone to do really well in the test is

46:11

to teach this very narrow body of

46:13

knowledge that they'll have to execute

46:14

at the test the best way to prepare them

46:16

for math learning is to give them this

46:17

much broader connection of ideas that

46:19

will serve them later on so again this

46:22

is like to me the theme on every page of

46:24

range that would have made a crappy

46:25

subtitle is is sometimes what seems the

46:28

best in the short term will undermine

46:29

long-term

46:31

development the tricky thing with that

46:33

as you say is I I think about all the

46:35

areas and industries that I'm playing in

46:36

now so I go do I have the time to go

46:41

broad like if I'm learning to DJ at the

46:43

moment and at at the moment I'm just

46:45

trying to figure out what these [ __ ]

46:46

buttons do you know what I mean like

46:47

there's all these buttons I'm trying to

46:49

press them in the right order but you're

46:51

telling me that the thing that's better

46:52

for my long-term development might be

46:53

just to spend some time understanding

46:55

music and how it's made and how and

46:57

understanding like the the Beats of

46:59

music and make maybe spend some time

47:01

making music myself cuz right now I'm

47:03

just trying to smash two songs together

47:05

at the right time I think this gets at a

47:07

fundamental issue that that that maybe I

47:09

should have brought up earlier actually

47:10

so and it has to do with how you

47:13

characterize the different tasks that

47:14

you're trying to learn so there was a

47:17

period where I was really confused about

47:20

the research I was reading in in

47:21

building expertise because there were

47:23

two camps of

47:25

researchers both led by

47:28

eminent scientists one that would study

47:30

people doing sort of more 10,000 houry

47:33

kind of approach same thing over and

47:35

over and they would get better and this

47:37

other camp that would find if people did

47:38

that approach Not only would they not

47:40

get better they would often get more

47:41

confident but not better which was a bad

47:43

combination and sometimes it would get

47:44

even worse with really narrow

47:47

focus and I could not figure out how to

47:49

reconcile these things why are they

47:51

finding such different results again I'm

47:53

looking through for all these signs of

47:55

you know bad data not not finding it

47:58

and fortunately um I I gave a talk uh

48:02

where I was doing some of the critiquing

48:03

of the science underlying the 10,000

48:05

hours Rule and the Nobel La Daniel Conan

48:06

who wrote Thinking Fast and Slow was

48:08

there and someone asked he asked someone

48:10

for my email address and like months

48:12

later he followed up and invited me to

48:13

lunch and we go and have lunch and I'm

48:16

like I'm and he was he was interested in

48:19

my critique of some of the research and

48:20

I was saying I'm really confused you

48:22

know what are you working on now I'm

48:24

working through my confusion about this

48:27

why do people sometimes get better with

48:29

narrowly focused practice and why

48:32

sometimes don't they he said oh I've

48:33

done I've got the paper for you and

48:36

basically he referred me to this body of

48:37

research about kind versus wicked

48:40

learning environments these are terms

48:42

coined by a psychologist named Robin

48:44

Hogarth kind is like next steps and

48:47

goals are clear rules repeat uh it's

48:50

based on patterns repetitive patterns

48:52

rules never change give me an example

48:55

chess golf uh in chess the grandmaster's

48:58

advantage is largely based on knowledge

48:59

of recurring patterns so you better have

49:00

started studying those by age 12 or your

49:02

chance of reaching Grandmaster drops

49:04

from about one in4 to about 1 and

49:06

155 also why it's relatively so easy to

49:08

automate uh feedback is quick and

49:10

accurate uh not a lot of human behavior

49:12

involved work next year will look like

49:14

work last year on the other end of the

49:16

spectrum are wicked learning

49:17

environments where patterns don't just

49:19

repeat they might fool you rules may

49:21

change if there are any feedback could

49:23

be delayed or inaccurate um work next

49:26

year may not look like work last year

49:29

and so whether or not people get better

49:31

with this very Nar in a predictable way

49:32

with this very narrow practice depends a

49:34

lot on where on that kind to Wicked

49:37

Spectrum the the task happens to be

49:40

what's an example of a wicked lining

49:41

environment so let's say one one of the

49:43

examples uh that I loved that he turned

49:45

me to was uh in medicine because there's

49:48

a lot of areas in medicine where

49:49

something is done and the person making

49:50

the decision actually never learns of

49:52

the consequence of the decision um or

49:55

I'd say I would say like judges some

49:56

cases in like the criminal justice

49:59

system are set up to have maybe the

50:02

worst judgment they could have in some

50:03

ways because they almost never get

50:04

feedback they have like very little they

50:06

can do whatever they want and they

50:07

almost never get any any feedback but so

50:10

in in medicine there was this one

50:12

example in one of the studies that I

50:13

thought was just interesting and

50:14

illustrative where um this this

50:18

physician became famous for being able

50:19

to diagnose typhoid it's a New York

50:21

physician by feeling around palpating

50:23

people's tongues feeling around their

50:24

tongues with his hand and he could tell

50:26

you know we or two before they would

50:27

even get it this person's going to get

50:28

typhoid and as one of his colleagues

50:31

later observed he was a more prolific

50:34

spreader of typhoid than even Typhoid

50:35

Mary he was spreading it with his hands

50:38

by touching their tongue making the

50:40

prediction they would get typhoid which

50:41

would turn out to be correct so would

50:42

reinforce the lesson that he was really

50:44

good at prediction that's a really

50:46

wicked learning environment where the

50:47

feedback he's getting is reinforcing the

50:49

exact wrong lesson right but I would say

50:52

most of the things that most of us are

50:54

doing have feedback that tends to be

50:56

delayed

50:58

sometimes it's accurate and sometimes

50:59

it's not it's never as accurate as like

51:02

I hit that golf shot and I see if it

51:03

hooks or slices and then I changed the

51:06

the club face and and try it again and

51:08

so most of what most of us are involved

51:10

in increasingly right like work doesn't

51:15

next year doesn't look like work last

51:16

year for most of us anymore and in fact

51:18

Andre Ericson again the guy who did the

51:20

research underlying the 10,000 hour rule

51:22

when he eventually wrote a book he he he

51:25

made this caveat the book that said the

51:28

10,000 hours framework uh it applies to

51:31

things where we know exactly how to be

51:32

good and a coach can watch you do it and

51:34

correct everything that you do wrong so

51:35

it doesn't apply to most these other

51:36

things that most of us do like computer

51:38

programming and managing and

51:39

Entrepreneurship and all these other

51:41

pretty big loophole right in those areas

51:43

you want this much broader

51:45

toolbox I am I was really compelled by

51:48

something I saw you talking about which

51:50

was the story of Nintendo and why they

51:52

were so successful in the early days

51:54

because they have a a very Broad they

51:56

take wrote down the quote um a lateral

52:00

thinking with withered technology yeah

52:03

that started with a guy named gune yokoi

52:06

who

52:07

was scored poorly on electronics exams

52:10

in University and so he had to settle

52:12

for a low tier job as a machine

52:13

maintenance worker uh at a at a company

52:16

in Kyoto that made playing cards with

52:17

flowers on them whereas like his more

52:19

prestigious peers went to big companies

52:22

in Tokyo and the company was in huge

52:24

trouble uh it had to diversify if it was

52:26

going to survive survive and he knew

52:29

that he wasn't equipped to work on The

52:30

Cutting Edge but that there was all this

52:33

information available that maybe he

52:34

could just look for technology that's

52:36

already well understood and combine it

52:37

in ways that his more specialized peers

52:40

couldn't see and so he went and he took

52:42

some well-known technology from the

52:44

calculator industry some well-known

52:45

technology from the credit card industry

52:47

and combined them and made handheld

52:48

games and those were those were a hit

52:51

right that's what made Nintendo which

52:54

was a found in a wooden storefront in

52:56

19th century that's what turned it into

52:58

a to a toy and game Operation so he

53:00

moved from machine maintenance to

53:02

developing toys and games and his

53:04

magnopus was the Game Boy right where um

53:09

it was a technological joke in every way

53:11

it's like the processor was a decade old

53:13

the screen looks like you know rotting

53:14

alala or something it's like and it came

53:17

out at the same time as color

53:18

competitors and it blew them out of the

53:19

water because he knew what customers

53:21

cared about wasn't color as much as it

53:24

was durability affordability portability

53:27

battery life game selection by using

53:28

well-known technology people could make

53:30

games quickly and so he kind of set this

53:33

philosophy this lateral thinking with

53:34

withered technology that was his phrase

53:36

which means taking things that are

53:37

already well understood and moving them

53:40

somewhere where they're seen as

53:41

invention and that actually turns out to

53:43

be more the norm than the exception in

53:45

terms of technological innovation

53:47

particularly sort of later in the 20th

53:48

century forward before that it wasn't

53:50

necessarily the case much of the 20th

53:53

century actually the most impactful

53:54

patents if you look at patent research

53:56

were authored by teams and individuals

53:58

that Dove deeper and deeper into one

54:00

area of Technology as classified by the

54:02

US patent office but starting in this

54:05

sort of Information Age period um you

54:07

know particularly 80s and accelerating

54:10

forward suddenly it becomes a lot easier

54:12

to access information more broadly and

54:15

the most impactful patents started to be

54:17

authored by teams that include

54:18

individuals who've worked in a whole

54:19

number of different classes and they're

54:21

often merging things from different

54:22

areas uh for invention so how important

54:25

is focus in this this equation focusing

54:27

on one thing because you're talking for

54:29

much of this conversation about being

54:30

Broad and people will associate that

54:32

with being

54:34

unfocused yeah it's it's a right I think

54:37

the differen is between doing a bunch of

54:39

things sort of over your career over

54:41

your life or a span and doing attempting

54:43

to do a bunch of things at once we can't

54:45

technically do a bunch of things at once

54:47

like we we don't really multitask we

54:49

don't have the capacity to do it we're

54:50

actually just toggling between things

54:52

really quickly um and it's it's been

54:56

shocking to me to look at the research

54:59

how how big of an impairment that is for

55:01

people's performance particularly

55:03

because it takes time to switch and so

55:06

you're not again it it's it the the

55:09

scientist Gloria Mark who who I think

55:10

has been at the Forefront of study of

55:12

attention describes your brain as like a

55:14

whiteboard where you're doing something

55:17

and to do something else you have to

55:18

erase and that residue is left and it's

55:20

still going to be there when you move to

55:22

the new thing for a while and so you you

55:23

can't totally get into the next thing if

55:25

you're

55:26

interrupted um and and it impairs your

55:29

performance and it's stressful that's

55:32

been the most surprising part to me is

55:33

that when people are heart rate

55:35

variability is measured and some immune

55:37

parameters um that when people switch a

55:39

lot like if you just saw how many times

55:42

people switched their task you know

55:43

email to this other thing to some

55:44

notification over a day you'd have a

55:46

pretty good bet at predicting their

55:48

stress level and their performance level

55:49

over the day really yeah they've done

55:51

studies on this she has done that she's

55:53

hooked people up you know at Big

55:55

organizations too like inside Microsoft

55:56

and and places like that um where people

55:58

are wearing heart rate variability

56:00

monitors everything they're doing is

56:01

being tracked in the old days she was

56:03

like sitting behind people with a

56:04

stopwatch but technology obviously

56:06

progressed from then um and I think

56:08

that's a surprising aspect of it one of

56:10

the reasons that email makes people so

56:12

stressed is because it leads them to do

56:15

this like con I think in one of her

56:17

studies people were checking email

56:19

office workers were checking email and

56:20

average of 77 times a day that's a lot

56:22

of switching when you're switching in

56:23

and out of email and that just turns out

56:26

to a stressful thing because there

56:27

there's switching actually takes place

56:30

in two uh kind of phases where you the

56:34

first phase is is shutting down what you

56:36

are doing and the next phase is

56:38

activating the rules for the next task

56:41

so even if you kind of think you're

56:42

doing the same thing like you're working

56:43

on focused writing but you're also in a

56:46

slack Channel or something with a friend

56:47

or colleague those are both writing but

56:49

they're not the same style of writing

56:51

and so you're still having to activate

56:53

different cognitive rules and that that

56:55

comes with a switching cost so if I can

56:58

do something about it what should I do

57:01

to to make sure that I'm both happy um

57:03

more productive and healthier I would

57:05

again not start your day with something

57:07

that is inherently a multitask so if you

57:09

cannot start with email I would not

57:11

start with it because I view that at

57:13

least for me as something that will

57:16

start the day with multitasking and will

57:18

always feel unfinished like never feel

57:20

like it's finished um blockout times

57:23

where you designate on your calendar

57:25

that this is the only thing that you're

57:26

doing and leave some buffer for it

57:28

because there's something called the

57:29

planning fallacy we always overestimate

57:31

how much we can get done in a given

57:33

amount of time so I'd say fewer things

57:34

on your to-do list fewer things and on

57:36

the top maybe even just one thing that's

57:38

if I get this done this this was a good

57:40

productive day focus on that thing you

57:42

know pay yourself first do the important

57:44

thing first and really try to have some

57:46

when you're trying to be focused it's

57:47

important to mingle with people and

57:48

exchange ideas when that's what you want

57:50

to do but when you really have to be

57:52

focused to try to be in a place that's

57:54

as distraction free as possible and un

57:56

that includes even you know turning down

57:58

or off music even though it's Pleasant

58:00

and can help your affect and can

58:02

motivate but it also does have an

58:04

impairment on cognitive function because

58:05

you are paying attention to it to some

58:07

degree so don't listen to music while

58:09

I'm doing my work I mean that's hard to

58:11

say because I do it sometimes too

58:12

because it can have an energizing effect

58:13

or it can have a calming effect and

58:15

those are good but it does take up brain

58:17

space so you have to balance those how

58:20

do they know it takes up brain space you

58:21

can see how people perform on tasks when

58:23

the music is on and when the music is

58:25

off and it's it's a it's it's not as big

58:27

a deal if the music is very familiar

58:28

where you're kind of like it's not novel

58:31

so you're not attending to it the same

58:33

way but you know when I'm trying to be

58:35

super focused now I'll I'll turn the

58:37

music off but if I feel my sort of

58:38

motivation waning then maybe I'll tune

58:40

it back on but I want to use it

58:41

deliberately instead of just having it

58:42

in the background all the time because

58:43

it takes up a little space if it's and

58:45

if it's real noise like decb is a

58:49

logarithmic scale so small differences

58:50

are actually a big deal but if you go

58:52

from I think it's like maybe 70 to 80 DB

58:54

that's like the difference of going from

58:56

a like a washing machine to a vacuum

58:59

cleaner thereabouts in your background

59:02

noise that has a

59:04

enormous influence on your cognitive

59:07

ability and your productivity like like

59:09

a 15% decrement in your because of sound

59:13

yeah volume s because because you attend

59:14

to it you attend I mean our that's how

59:16

our brain

59:17

like focus is a challenge because this

59:20

is not the situation that we evolved in

59:22

right we evolved in a situation we're

59:23

paying attention to novel stimuli is a

59:26

really good thing and sometimes it's

59:27

still a very good

59:29

thing but it's at odds with a lot of

59:32

these modern things that we're trying to

59:33

do that are pretty new tasks for for

59:35

people what about instrumental music

59:38

because I tend to find that if I'm

59:39

listening to music that has lyrics in it

59:42

then I find it quite distracting when

59:43

I'm trying to do some work specifically

59:44

writing work or reading work so when I'm

59:46

researching guests for the podcast like

59:48

I was today in my hotel room I had a

59:50

song playing it was a rap song and um it

59:52

was I could I could feel my brain subtly

59:55

jumping from the screen that I was

59:56

reading to the rap lyrics to the screen

59:59

to the rap lyrics almost like just

60:00

oscillating between the two yeah and I

60:02

thought you got to turn that off cuz you

60:03

you're not reading I turned it off and I

60:05

really made progress but I but I

60:07

sometimes when I write like books and

60:08

stuff like that I put instrumentals on

60:11

and there's actually some apps in the

60:12

App Store now that are called like focus

60:13

music and they're lyric free music and

60:16

maybe like lot not lots of tonal changes

60:18

or not very complex maybe repeating I

60:21

mean I think that's going to be better

60:22

right the less novelty there is for you

60:24

to attend to that's better but think

60:27

it's also worth trying it with with

60:28

nothing and it depends how much you're

60:29

pushing yourself right like a tiny an

60:31

improvement of motivation or your affect

60:33

or feeling good might be worth it if

60:35

you're not all the way at the edge

60:38

pushing yourself right I don't know if

60:39

you've ever been on a there was there

60:41

was a time where I was trying to uh you

60:44

know do some foreign language lessons uh

60:47

that I was listening to while I would be

60:49

running and if I started hitting it hard

60:51

while I was running I couldn't even

60:53

remember what was said because it's you

60:55

switch into being really focused right

60:58

and so I think it it depends if you're

61:00

pushing yourself all the way you need

61:01

everything like there there are times

61:02

when I'm writing where I'm trying to

61:03

balance a lot of ideas in my head and I

61:05

almost feel like I'm overheating a

61:07

little bit yeah and if I'm in that phase

61:09

I I I want every Advantage I can have um

61:12

so push the distractions out but but

61:14

like there's also times to be to be

61:16

pleasant I think I think part of what's

61:18

sensible is working in intervals

61:20

planning to work in intervals Focus hard

61:22

for a little while do the myangelo then

61:24

switch to your your little mind where

61:26

you're we're doing something that's sort

61:27

of more fun and refreshing and maybe let

61:29

you incubate for a few minutes also take

61:30

a shower take a walk you know what about

61:33

notifications uh because you know I have

61:35

a lot of notifications I try to turn

61:37

them all off but they're still there in

61:39

the background and um you was talking

61:41

before we got going about this sort of

61:42

internal barometer of distraction that

61:44

we all have yeah yeah this

61:47

is so this is another aspect of of Dr

61:51

Mark's Work where she found that we have

61:54

this kind of internal mechanism if

61:56

you're getting distracted all the time

61:57

by notifications or whatever it is and

61:59

switching a lot if you say well now I

62:01

really have to hunker down I'm going to

62:02

get rid of the notifications or whatever

62:04

this stuff

62:05

is you will start self- interrupting to

62:08

maintain the Cadence of interruptions to

62:10

which you have become accustomed right

62:12

as if we have some internal like

62:13

distract ometer that is saying this is

62:16

your normal Cadence of interruption I'm

62:17

going to continue it by popping into

62:19

your brain oh here's this thing I need

62:20

to check oh here's this person I didn't

62:22

respond to you know you'll self-

62:23

interrupt that will go away but not

62:25

immediately so if you want to have a

62:27

lower Cadence of

62:29

interruption you need to like build by

62:31

getting rid of those external

62:32

interruptions know that you're going to

62:33

be self- interrupting for a while and

62:35

that'll go down more slowly so it has to

62:37

be more habit formation instead of just

62:39

today I shall be you know

62:41

uninterruptible okay so just want to

62:43

make sure I'm clear on this so say that

62:44

I get a notification every M every I get

62:47

10 notifications a minute and that's

62:50

what I'm used to right and then I decide

62:53

to turn my notifications off because I'm

62:56

used to 10 notifications per minute

62:59

you're saying that I will basically

63:01

think of 10 things per minute to

63:02

interrupt myself with yeah for a while

63:05

because that's what I'm used to so we

63:07

get comfortable with a certain level of

63:09

interruption at a certain Cadence and

63:11

even if you we remove the thing that's

63:12

interrupting us we'll just replace it

63:14

with something else that interrupts us

63:16

that amount at that Cadence yes so you

63:18

can see in studies where people are

63:19

taking cognitive tests if they have

63:21

their phone invisible even if it's off

63:24

the people who are more phone dependent

63:25

or sort of more used to interruptions

63:28

they'll have a a bigger impairment on

63:30

the test if the phone is even like

63:31

visible or around them because they'll

63:34

yeah and so it's you know what thing did

63:35

I forget to do and I think something

63:37

that can help with this is keep a pad

63:39

nearby and when that thing pops into

63:40

your head of the of what you forgot to

63:43

do or who you forgot to respond to write

63:44

it down so at least it's maybe that

63:46

helps it not stick in your mind where

63:48

you're trying to hold it in working

63:50

memory like cognitively Outsource it so

63:52

at least it's not sitting in there and I

63:54

think that can help the adjustment it

63:55

makes me think a lot about people that

63:57

struggle with sleep and just sleep

63:58

hygiene generally because if we're you

64:01

know if our phone is this thing of

64:02

interruption throughout the day then we

64:04

go to bed cuddling our phone which a lot

64:06

of people do um it's probably going to

64:09

have quite a big impact on our ability

64:10

to sleep yeah I mean I wonder if you

64:13

know I think there's some I think our

64:15

phones are really useful for certain

64:16

things and I think they are disruptive

64:18

for other things and I wonder if sleep

64:19

is one of the most important

64:21

because you don't really want to be like

64:23

leaving residue on your brain when

64:25

you're trying to go to sleep so I would

64:27

put the phone as far away as possible

64:30

when you're really trying to sleep and

64:31

not at the last minute either personally

64:33

which you do oh I leave it in a

64:35

different uh floor and airplane

64:37

mode have you always done that no when

64:41

did you start doing that well I

64:44

definitely do it when I'm in the process

64:45

of writing a book because then all these

64:46

things that I take for granted I'm like

64:48

now I really got to lock in and and be

64:49

better um

64:52

and I have a I have a five-year-old son

64:56

and I was more of a night person who

64:58

would work at night like I would do a

64:59

lot of my writing in the wi hours and

65:01

he's getting up early no matter what and

65:04

so I realized that I had to start being

65:06

a lot more efficient about some of my

65:08

schedule and started thinking a lot more

65:11

about having it be dark having it be

65:13

quiet having it be cool not having the

65:14

phone around um the last thing I'm

65:17

reading not being work rated otherwise

65:19

I'll be thinking about that and it'll

65:20

take me longer to go to sleep so I think

65:22

I became a lot better about it when I

65:24

when I had my son when my son came

65:25

around

65:26

it's funny you mentioned that you've got

65:27

a son because much of your work made me

65:29

think about what I'll do when I'm a

65:31

parent someday because you talk about

65:33

how these early years where if a child

65:35

focuses on being a specialist in

65:37

something particular or a generalist

65:39

they have worldly different outcomes and

65:40

I think as a big football fan and a big

65:42

Manchester United fan I've always

65:44

thought when my kid comes out of my wife

65:46

someday the first thing I'm going to get

65:48

him doing from the age of two months old

65:50

is kicking a football around because

65:52

then he'll be a Manchester United player

65:53

I'll get to go to the games I'll be in

65:54

the players box everything will be great

65:56

but your work seems to suggest that that

65:58

if I want him to become a Manchester

66:00

star maybe I shouldn't do that you know

66:02

I'm I'm not convinced that you are going

66:03

to be like a vicarious living kind of

66:05

dad maybe you'll turn out to be but I'm

66:06

not convinced um but let me tell you

66:09

this you just reminded me of an

66:10

interesting story where I was once

66:11

giving a talk about some of this

66:12

research in sports that shows that the

66:14

people who go on to the highest levels

66:16

again there are a ton of different uh

66:18

paths but they tend to follow the Roger

66:20

path not the tiger path so Tiger Woods

66:22

we know are very early specialization

66:24

famously Roger feder played whole bunch

66:25

of different sports uh didn't specialize

66:28

until later than some of his peers so

66:29

tiger was playing golf since he was he

66:32

was um at his father gave him a putter

66:35

when he was 10 months old uh when he was

66:38

two just as a toy he wasn't trying to

66:40

teach him to be a golfer he gave him a

66:42

toy as tiger himself said my father

66:45

never once to ask me to Play It Was

66:46

Always me asking him to to let me play

66:49

but that's ignored but at at two he was

66:52

on National Television you know you can

66:53

go on YouTube see him on national TV

66:55

showing off his swing and then by three

66:58

he's saying I'm going to be the world's

66:59

next great

67:00

golfer uh he's world famous as a

67:02

teenager by the age of 21 he's the

67:04

greatest golfer in the world right on

67:06

the other hand Roger played a variety of

67:09

different Sports basketball uh rugby

67:12

skateboarding soccer mother was a tennis

67:15

coach but declined to coach him because

67:16

he wouldn't return balls normally I

67:17

guess didn't like deliberate practice

67:19

kept doing let's let's see he did

67:21

handball uh he did some

67:23

rugby uh SK swimming wrestling when his

67:28

coaches wanted to move him up to play

67:29

with older boys he declined because he

67:30

just wanted to talk about pro wrestling

67:31

with his friends after practice and he

67:33

was not focused on being the next great

67:35

from an early age like tiger was in fact

67:36

when he became good enough to Warrant an

67:39

interview with his local newspaper the

67:41

reporter asked him what he'd buy with

67:42

his first hypothetical paycheck if he

67:44

ever became a pro and he said a Mercedes

67:46

his mom was a gas right didn't she

67:48

thought this was like go sure and so she

67:51

asks the reporter to hear the interview

67:53

recording turns out he just said M CDs

67:56

in Swiss German he just wanted more CDs

67:58

not a Mercedes right she was fine with

68:00

that so he went on to be every bit as

68:04

famous as Tiger Woods but even tennis

68:07

enthusiasts don't usually know anything

68:08

about his developmental story even

68:09

though it's the norm according to the

68:11

science we only tell we only tell the

68:14

tiger stories even though that that

68:15

one's the exception right and this is

68:18

why do we only tell the tiger story this

68:19

is part of the debate I've had with with

68:21

Malcolm Gladwell when we're running

68:22

together and he said well he told me

68:23

it's a human cat video you know you go

68:25

YouTube and see them at two years old

68:27

and you can't you got to share it I

68:28

think that's true but I think it's also

68:30

because it feels like this tidy

68:33

narrative that we can extrapolate to

68:34

anything we want to be good at in our

68:36

own lives the problem is as we talked

68:39

about golf is almost a uniquely horrible

68:41

model of almost everything else that

68:42

humans want to learn it's like the

68:44

epitome of a Kind learning environment

68:46

where the situation isn't isn't changing

68:48

you're not having to react so I think

68:49

it's a bad model and we we underplay

68:52

even for famous people the normal

68:53

developmental trajectory like I once

68:55

gave a talk to a small group of people

68:57

about some of this research in sports

68:59

showing that the typical path to

69:00

becoming Elite is with a sampling period

69:03

you learn a broad range of skills learn

69:05

about your own interests and abilities

69:06

delay specializing till later than peers

69:09

and Serena Williams sat in the second

69:10

row and I'm freaking out because you can

69:14

present all the data you want but if the

69:16

goat stands up and says you're an idiot

69:18

it's going to be a bad day right and I'm

69:22

like please don't let her ask a question

69:26

of course she raises her hand for the

69:28

first thing and she

69:29

goes I think my father was ahead of his

69:32

time he had me do uh ballet track and

69:35

field gymnastics Taekwondo uh learn to

69:38

throw a football for the overhand

69:40

snapping motion of a serve when there

69:42

was too much travel on like the you know

69:44

a youth tour he took me off so I could

69:46

focus on

69:47

school I'd been a senior writer at

69:49

Sports Illustrated and I had never heard

69:50

that like I assumed that she was this

69:52

kind of quintessential tiger story so I

69:54

think even those stories

69:55

when you look more more deeply uh

69:58

they're not as clearcut as we tend to

69:59

think well I I learned this myself when

70:03

I I didn't know this as as the rule but

70:06

I I found the story of lomachenko

70:09

because I I my friend of mine brought me

70:10

ringside to a fight in New York City and

70:12

I sat at the side of the Ring watching

70:14

this guy called Vil lenko that I'd never

70:15

seen in my life and I just couldn't

70:18

believe his footwork I'd never seen

70:21

anything like it in my life and then I

70:23

after the fight he won the fight of

70:25

course after the fight I looked into his

70:26

win record and it was something like

70:28

he'd won 300 of his amateur fights and

70:30

only ever lost one and then he' gone

70:31

back and beat the guy that he had lost

70:33

against um and in my mind I'd never seen

70:35

a boxer like it ever and then when I

70:37

read into your work you've mentioned him

70:40

as well as being one of these examples

70:42

that had a really varied early

70:43

upbringing didn't just focus on boxing

70:46

and that's ultimately what made his

70:47

skill stack so unusual and therefore

70:49

probably what made him the best his

70:51

story surprised even me where he took

70:54

several years off

70:55

to learn dance like d i mean I wouldn't

70:59

usually expect someone to take years off

71:00

it's just sort of do things in those

71:02

same years so that was amazing but his

71:04

father's called Anatoli and I think it

71:06

was his father that took him off into

71:07

Yeah dance classes or something and then

71:09

let him go back to boxing so for your

71:11

perspective child I wouldn't say like

71:13

don't expose them to soccer I think

71:16

because I think a lot of this is I think

71:18

there's there's a few things going there

71:20

are three buckets of things going on

71:22

with why this delayed specialization

71:23

Works in sports one is match quality

71:26

again the degree of fit between who you

71:28

are and what you do is that about

71:29

passion like what you're passionate

71:30

about ability and interests both and the

71:33

earlier you force selection the more

71:35

likely you put the wrong person in the

71:36

wrong spot so especially when selection

71:38

is way pre puberty okay you're probably

71:40

putting people in the wrong my kid might

71:41

want to be a boxer but I'm forcing him

71:43

to be a soccer player and he might miss

71:45

his potential with boxing premature

71:47

optimization yeah okay and and that's

71:49

also why we often see on junior teams

71:51

the relative age effect you know where

71:53

kids born earlier in their Birth Cohort

71:55

are way over represented on Junior and

71:58

youth national teams because when

71:59

they're eight or whatever and selected

72:02

if they're eight and 10 months versus

72:04

just turned eight that's a huge

72:06

difference of development in that age

72:07

and coaches mistake that biological

72:09

maturation for talent and so youth teams

72:12

are overloaded with kids born early in

72:14

their youth cohort and also in school

72:17

especially boys if they're younger in

72:18

their age C are much more likely to get

72:20

diagnosed with ahd but they're just

72:21

acting like the younger boys that they

72:24

are um okay and so and then that

72:26

disappears at the top level so it's not

72:28

it's not a good thing so there's the

72:30

relative age effect that's one or

72:31

premature you know choosing there's

72:34

injury which is we now see a lot of

72:35

adult style overuse injuries in kids and

72:37

the main predictor of that is nine

72:39

months a year of one sport and one sport

72:41

only so this isn't about less Sports

72:44

there seems to be a protective effect of

72:46

diversifying that is separate from just

72:47

doing less but actually you know

72:50

balancing yourself out in some way but

72:52

then there's a skill learning Advantage

72:53

where it's similar to language where

72:55

you know kids who grow up in a like with

72:57

multiple languages they will often show

72:59

a little delay in some of their language

73:01

skills but that delay is totally wiped

73:02

out in the long run and they have an

73:04

advantage for subsequently learning

73:06

other languages looks very similar in a

73:08

lot of these skills where if you're

73:10

diversifying there may be some delay but

73:13

you have an advantage for picking up

73:14

other skills later on and I don't think

73:16

this is about whether you're putting on

73:17

a basketball jersey or a football jersey

73:21

I think it's about variability in your

73:23

problem solving which is why I think so

73:24

many of the great footballers grew up on

73:26

fotsa where what's foots it's foot's

73:29

with a small ball soccer like game with

73:31

a small ball um I think I think the the

73:35

Brazilian name is like football day Salo

73:37

which it means like football in a room

73:39

small ball stays on the ground played in

73:40

a small space and kids will be playing

73:43

on you know cobblestones one day and

73:45

concrete the next day and and it's like

73:47

in a phone booth you know at hypers

73:49

speed and so there's no no one's

73:51

drifting down the field and everyone's

73:54

having to judge even if you don't have

73:55

the

73:56

ball pick up on body movements to try to

73:58

anticipate what's coming next and the

74:00

touches are about six times as frequent

74:02

uh as in as in full scale football and

74:04

so I think it engenders a lot more of

74:06

this sort of

74:07

variability um than does just sort of

74:11

the full scale game it makes your

74:13

reactions a lot faster as well you have

74:14

to make decisions faster with the ball

74:15

but under yeah it's funny when you're

74:17

talking about the tiger example and why

74:20

people um broadcast that story more than

74:23

they broadcast what you consider to be

74:25

the the average which is just people

74:27

having this varied upbringing and then

74:28

eventually finding one thing and taking

74:30

it forward it made me think that from my

74:32

experience people broadcast that they

74:34

basically broadcast anything that's the

74:36

exception because it's the exception so

74:38

the story of you know tiger WS as one

74:41

example but the on the other side with

74:43

someone like Anthony Joshua who started

74:46

boxing at I'm going to Butch of this but

74:48

let's say

74:50

24 I hear that all the time because it's

74:53

so unusual that he would become world

74:56

champion but start at 24 and the other

74:59

story that you hear all the time is like

75:00

the child prodigy story of like I don't

75:01

know Michael Jackson or Tiger Woods that

75:04

started when they were two you don't

75:05

hear about the person that starts at

75:06

like 15 right because it's not

75:09

interesting right because it's the norm

75:11

right or who ramps up in sort of a

75:12

normal way if they started because early

75:14

exposure is great yeah early exposure is

75:16

good but yeah and and it's a little it's

75:18

a little more equivocal right it's a

75:20

it's less of a prescription also like so

75:22

when when someone starts late we think

75:24

they defied the odds this is amazing and

75:26

when someone starts early that's a very

75:28

easy example to emulate and so I think a

75:31

lot of it is about that ease we

75:33

referenced the word match quality but

75:35

also we talked about passion a little

75:36

bit which kind of is one factor of match

75:39

quality a lot of people are trying to

75:41

figure out what they should be aiming at

75:42

in their life and they one of the most

75:44

popular questions I get from young

75:45

people is um how do I find my passion

75:48

how do I know what it is or at least

75:50

like what's the process def finding it

75:52

and it's they refer to it as if it's

75:53

this sort of Easter egg that one of them

75:55

and have to find it there's not one and

75:57

it's singular passion is a singular word

76:00

yeah no I don't I first of all I think

76:02

losing the idea that it is sing I mean

76:03

that's like the idea that there's like a

76:05

single soulmate out there for you you

76:07

know and I mean obviously I found my

76:10

single soulmate but for most of the rest

76:11

of

76:12

you uh there's a lot of things you might

76:15

be interested in in

76:18

fact the more things you try you'll

76:20

probably figure out the more things that

76:22

that you're interested in I was just I

76:24

was just like last week spending a

76:25

little time I was at the Pentagon

76:27

spending uh some time with a lieutenant

76:29

general who helped with a program they

76:31

call talent-based branching there where

76:33

they were losing a lot of their the

76:34

people they identified as The Highest

76:36

Potential were leaving the the Army and

76:38

they started this pilot program called

76:40

talent-based branching where instead of

76:41

saying here's your path you know here's

76:43

your your career path get uper out

76:47

they'd pair them with sort of a coach

76:48

like figure and they'd have them dabble

76:50

in like five different career paths a

76:51

little bit reflect on it with their

76:53

coach take some tests how this fits you

76:55

they have to keep track of the

76:56

Reflections in online portal again

76:57

self-regulatory learning got to do it

77:00

explicitly and in that process

77:04

90% of the army Cadets who went through

77:06

that process changed their career

77:07

preference 90 and this is just from a

77:09

little bit of dabbling because you don't

77:11

know what's out there you don't know

77:13

what the opportunities are and that and

77:15

you know it helped retention so people

77:17

were more likely to stay if they find

77:18

better fit this is I think actually one

77:20

of the really important things

77:22

about um and I'll I'll Circle back back

77:25

to Passion a little bit there but when

77:28

we think about grit right which everyone

77:30

thinks of is I think about this and the

77:32

reason that the Army made me think about

77:33

it my semantic network is that the most

77:35

famous grit research was done at West

77:36

Point at the United States military

77:38

academy by Angela Duckworth and her

77:39

colleagues and it found that the grit

77:42

survey the grit survey is a 12 question

77:44

survey half the points are awarded for

77:46

consistency of interests not changing

77:49

what you're interested in and half the

77:50

points for Persistence of effort or

77:51

perseverance turns out to be a good

77:54

predictor of who would get through this

77:55

very rigorous orientation at West Point

77:57

called

77:58

Beast also has some predictive value for

78:00

who would graduate so just to give you

78:02

some context for the listeners that from

78:04

the way that I understood this is that

78:06

Angela Duckworth did this study to

78:07

basically figure out what it was that

78:09

made people more likely to get through

78:11

this very rigorous selection process at

78:12

an army barracks or something and she

78:15

determined that this this grit as she

78:17

she called it was the thing that allowed

78:19

people to be successful so from that

78:21

study I've heard this all over the place

78:23

that actually what makes people

78:24

successful even in my team is great yeah

78:27

yeah and that survey turned out to be a

78:29

better predictor than were some

78:30

traditional metrics of who would get

78:32

through Beast like test scores and stuff

78:33

like that it also had some value for who

78:36

would get through the military academy

78:39

as did some of those traditional

78:41

metrics but tons of those like since

78:43

about the mid1 1990s those very gritty

78:45

cadets at West Point have been almost

78:46

half of them have been quitting almost

78:48

on the day that they allow they have a

78:49

5-year active duty service commitment

78:50

after they graduate and almost half of

78:52

them have been quitting and so the army

78:54

at a certain point said oh we've got a

78:57

millennial grit problem you know like

78:59

too much avocado toast not enough

79:00

mortgages or like

79:02

whatever and then some scientists who

79:04

also officers decided to study the

79:06

problem and they said we don't we

79:07

haven't gotten a grit problem overnight

79:09

we've got a match quality problem right

79:13

when the Army looked like the rest of

79:15

the economy where it was more upper out

79:17

and you fac the same kind of problems

79:18

year-over-year and you could have a

79:19

period of training followed by a period

79:21

of working doing similar things lateral

79:23

Mobility was limited

79:25

that was fine it just mimicked the rest

79:26

of the economy then you move into this

79:27

whatever you want to call it knowledge

79:29

creativity information economy and

79:31

people who can engage in Creative

79:32

problem solving and knowledge creation

79:34

have tremendous lad Mobility they have

79:35

lots of opportunities these young people

79:37

are learning things about themselves in

79:38

the early 20s and they have no agency

79:40

over career switching to match it so

79:42

they were just quitting right when the

79:44

Army first didn't realize this so they

79:45

threw retention bonuses at

79:47

people and the ones were going to stay

79:49

took it ones are goingon to leave left

79:50

anyway half billion dollars taxpayer

79:52

money didn't didn't uh fix the problem

79:55

but what I think it shows is that how

79:57

limited your insight into what you might

79:59

want to do is based on the things that

80:01

you've tried again Herman bar as we

80:02

learn who we are in practice not in

80:04

theory and so I think the biggest

80:06

problem for young people is if they're

80:07

sitting around introspecting to try to

80:09

figure out what their passion is go and

80:11

try something it's not it's almost

80:13

certainly not going to be the first

80:14

thing it may be you may get lucky but

80:18

it's probably not going to be the first

80:19

thing so you should get going on that

80:21

experiment process and start building a

80:22

model of the world so that you can

80:24

understand what your options are cuz I

80:26

also think the issue with passion and

80:28

happiness is again like I was talking

80:30

about I think it was can't remember

80:32

everything that was before the recording

80:33

started and after um but like when I

80:38

used to run the 800 meters or now when I

80:39

write books if you ask me to any given

80:41

moment am I enjoying this am I happy

80:44

about it you know am I passionate about

80:45

some's like no I want to throw my

80:46

computer out the window are you crazy

80:48

but it's so engaging it's so compelling

80:51

and it pushes me in a way to learn that

80:53

I can't do just on my free time and so I

80:55

don't think we have to think about just

80:57

passion find something that is so

80:58

incredibly engaging to you uh and then

81:02

go from

81:03

there and engaging really is how do you

81:06

know that it's engage it's when you sort

81:07

of FL drop into that flow state where

81:09

nothing else seems to matter or flow I

81:11

mean flow is a tricky one because it's a

81:13

lot easier it it shows up a lot more in

81:15

people that are like surfing or painting

81:17

than it does in some kinds of knowledge

81:18

work but I think it when you when you

81:23

get really engaged in something you a

81:24

curiosity about how you can get better

81:26

at it what else you can learn next so I

81:28

think it it stimulates this kind of

81:29

curiosity That You Don't See in people

81:31

when they're just in something where

81:32

they're kind of going through the

81:33

motions so you you start to understand

81:35

like when I I remember when my my then

81:38

girlfriend now wife um it was important

81:40

to me you know for health that like both

81:43

of us be lifelong exercisers for example

81:45

and the first time we we moved in

81:46

together and I'm saying like all right

81:47

we got to

81:48

identify uh something that works for you

81:50

and I take her to a gym and drop her off

81:52

and not realizing I have you know

81:55

Decades

81:56

of learning how to do stuff in a gym

81:59

that I take for

82:01

granted and then I realiz okay I need to

82:03

sort of walk this walk with her and so

82:05

we would try different things like

82:06

running she wasn't as into that so then

82:07

you know try some other thing etc etc

82:09

and finally she found one kind of class

82:11

and she comes home this day we did this

82:13

and then we did this it was so hard let

82:14

me show you this other thing we did I'm

82:15

like you found your thing and the one

82:18

problem was then when we were looking at

82:19

moving States we had to be within 15

82:22

minutes of that kind of class walking

82:23

distance for any house that we were

82:25

going to buy but it's like you can see

82:26

this curiosity develop uh when someone

82:29

hits something it's so engaging that

82:30

they want to understand how to be better

82:31

they want to talk to other people doing

82:33

it they get so curious about it but you

82:35

have to experiment you have to

82:37

experiment I wish there were a way out

82:38

of that I wish you could say this is the

82:39

thing that's going to work for you may

82:41

maybe someday with AI I maybe but highly

82:45

unlikely highly unlikely um and and AI

82:48

just like changes the field that you're

82:50

playing in right and so I think

82:53

experimentation I think it's going to be

82:54

even more important as people can't

82:56

expect to be doing the same thing their

82:57

whole careers anymore I mean they're

82:58

threads that they can expect to to carry

83:01

through but not the same exact thing

83:02

when I saw your video called why

83:04

Divergent thinkers beat Geniuses in the

83:06

real world I thought you were going to

83:08

talk about neurod Divergence in the

83:10

video so someone that was you know

83:12

diagnosed with ADHD maybe when I was

83:13

about 30 years old I thought oh he's

83:15

going to explain why neurod Divergence

83:17

things like ADHD and autism result in um

83:21

better outcomes in the real world has

83:23

your work ever had any crossovers with

83:24

NE Divergence not a lot but I mean I

83:27

have read some of that work and I do

83:29

think something that's really important

83:31

is the more different types of thinking

83:33

that we can like get into a stew the

83:35

better off I think I think we all are I

83:37

mean there are reasons

83:38

why um ADHD like there's there's some

83:42

it's not it's not a big body of work but

83:44

I think it's relevant where you can look

83:46

at nomadic populations that then settled

83:49

and you can see certain genes that are

83:52

associated with and these are these are

83:53

small effects

83:56

um but you can see certain genes that

83:57

are associated with uh like novelty

84:00

seeking with with ADHD um will

84:03

apparently start to be like selected out

84:06

once they settle and it's more common

84:09

when they're nomadic and what that

84:10

suggest to me is that these are things

84:12

this attentiveness to lots of different

84:14

stimuli that are really important have

84:16

been important for us ancestrally and

84:18

are still important and so they're still

84:19

here they may be maladaptive if you're

84:22

telling someone they have to sit still

84:23

in a classroom for 10 hours a day which

84:25

I think is a difficult environment for

84:27

anyone to adjust to but I think to some

84:30

extent and I think this has happened

84:32

sometimes in in some companies um that

84:34

look for opportunities for people with

84:35

Autism where you say okay where is this

84:38

adaptive where is this type of thinking

84:40

adaptive instead of maladaptive so

84:42

useful instead of unproductive and I

84:44

think if we're not doing that then

84:45

you're missing opportunities to really

84:46

use people who think differently from

84:48

you yeah I mean it's interesting because

84:50

your work does whether it is endeavoring

84:53

to or not it really does make a great

84:55

case for diversity in the workplace yeah

84:58

yeah yeah uh you want to do a quiz sure

85:02

pretend you're a doctor okay and I'm

85:05

your put my white coat in my head with a

85:07

little stethoscope around my neck yeah

85:08

okay because that's that's what all

85:09

doctors look like um and and I'm your

85:12

patient okay and I've got a malignant

85:13

stomach tumor and there's a new type of

85:16

Ray or Focus radiation that can destroy

85:17

the tumor if it's at sufficient

85:19

intensity the problem is at that

85:21

intensity it will also destroy healthy

85:23

tissue in my stomach so how can you save

85:26

me okay while you're thinking of that

85:28

tell you a story there was once this

85:30

General had to capture a fortress to to

85:32

liberate a country from a brutal

85:33

dictator and he had plenty enough troops

85:35

to do it and there were roads radiating

85:37

out like wheel spokes from The Fortress

85:40

but they were strewn with landmines so

85:42

if he marched all his troops down any

85:43

one road he'd suffer a lot of casualty

85:45

so he had the idea let's split up into

85:46

single file lines go to the different

85:49

spok likee paths and we'll synchronize

85:52

our watches and they converge there at

85:53

the same time and they Liberate the

85:55

Fortress okay or they capture the

85:57

Fortress Liberate the country One More

85:58

Story Once a fire in a small town in

86:01

danger of spreading to neighboring

86:03

structures fortunately was near Lake so

86:05

neighbors are coming and they're filling

86:06

pales and bailing water on it not

86:08

working fire chief shows up she says

86:10

stop what you're doing everyone get in a

86:12

circle fill up your buckets get in a

86:13

circle around the fire on the count of

86:14

three one two three dampens the fire and

86:18

good they put it out fire chief gets a

86:20

raise okay have you can you save me now

86:22

doesn't matter you should this is I'm

86:23

giving you a very quick version but the

86:25

answer is you can arrange multiple low

86:27

intensity Rays around me so they

86:29

converge at the focal point so they go

86:31

through my torso without damaging me

86:32

because they're low intensity but they

86:34

converge at the right spot making high

86:37

intensity and this is a very truncated

86:40

version don't like if you were getting

86:42

the real test you would have had a lot

86:43

more time and still most people don't

86:44

solve it so don't worry it's called the

86:46

dunker radiation problem this is a very

86:48

truncated version of a large body of

86:50

research that shows that when you're

86:51

facing a novel problem the number of

86:53

solutions and the chance of coming up

86:54

with a good solution are predicted by

86:56

the number and breadth of

86:58

analogies that your group can come up

87:00

with and what predicts that is the

87:02

breadth of experience of the people in

87:04

the group so if you're facing a novel

87:06

problem and you have only people with

87:08

the same expertise it's not much better

87:09

than having one brain okay what you want

87:12

to do is come up with what's called a

87:13

reference class where you sit down you

87:14

come up with as many structurally

87:16

similar analogies from all sorts of

87:17

different areas like this sounds kind of

87:19

like this and this other thing and they

87:21

don't have to be as far flowing as what

87:22

I just did but in in the studies where

87:25

people have more time with each

87:26

successive story you tell them more

87:27

people will start solving the original

87:29

one even though they don't know that

87:31

they're related and so you want to get

87:33

people together who are really

87:35

different come up with a whole bunch of

87:38

uh of these like this kind of feels like

87:40

this look for which ones are

87:41

structurally similar and you'll start

87:43

thinking of possible solutions yeah I

87:45

mean that's just such a brilliant

87:46

brilliant case for diversity in thinking

87:48

and experience when you're building a

87:49

team when you're co-founding a team when

87:51

you're coming coming at a problem and I

87:53

was thinking actually yesterday about um

87:55

microphones so this is the first podcast

87:57

we've ever recorded if people watching

87:59

they might notice this all of a sudden

88:01

it' be interesting to know if you notice

88:02

this before I mentioned it but there's

88:03

no microphone here and this is the first

88:06

podcast we've ever recorded where there

88:07

isn't a microphone here and I was

88:08

thinking as you were speaking then about

88:10

how when we had the debate about how to

88:12

solve this problem with and the problem

88:14

that we were trying to solve for is that

88:16

there's guest bang on the table and it

88:18

comes through the microphone people send

88:20

me messages on LinkedIn saying hey it's

88:21

so annoying that people bang and then

88:23

whatever um so the microphones are now

88:25

above us and coming down and as we sat

88:28

around the three of us yesterday it's

88:30

kind of a little analogy for what you

88:32

what you're describing you've got will

88:34

who's got his experience in audio you've

88:36

got Jack who's got his experience and

88:37

then you've got me who's got basically

88:38

no experience but I do do a TV show

88:40

called Dragon's Den where we wear a

88:41

different type of microphone and we were

88:43

all chucking in our solutions to this

88:45

problem based on our own perspectives of

88:47

audio recording so um we Jack's solution

88:51

one but my solution before that was

88:53

while on drag and then we have one glue

88:55

to our chest so why can't we just glue

88:57

it to the guest's chest and it was

88:58

interesting watching us all it iterate

89:00

through these different solutions that

89:01

come from different places um doing this

89:03

kind of cost benefit analysis on each of

89:05

the solutions obviously one of the

89:07

problems with my solution is guests will

89:08

touch their chest right and then that'll

89:10

[ __ ] that up so yeah yeah yeah they

89:12

touch so and then also we have to grope

89:14

them when they arrive which we also we

89:16

didn't like but it's the same thing and

89:18

you need you need a really diverse set

89:20

of experiences to hone in on the winning

89:22

solution um but in most Pursuits what we

89:25

do is we collect people who have done it

89:26

before collect people who've done it

89:28

before and and that it's not that you

89:29

don't want those people you just don't

89:30

want only those people yeah and and the

89:32

tendency also is often to use the first

89:35

analogy that comes up you don't want to

89:36

do that either you want to like have a

89:38

menu of possible solutions to to look at

89:41

because like there's this thing called

89:42

the creative Cliff illusion people think

89:44

their most their best ideas and most

89:46

creative ideas will come either quickly

89:48

or not at all and in fact they tend to

89:50

come later as you're trying to come up

89:52

with ideas interesting yeah so but our

89:55

inclination is that it's like this flash

89:57

of lightning and either it comes or it

89:59

doesn't [ __ ] that's made me question a

90:01

lot of things I do because sometimes I

90:02

get an idea I write it down and I share

90:03

it straight away oh there's nothing

90:04

wrong with sharing the idea right but if

90:05

you're if you're like trying to solve a

90:07

real problem I wouldn't stop at your

90:08

first idea throw it out there for

90:09

discussion and then allow it to and then

90:11

keep yeah stay open to it and and don't

90:12

assume that you know if something didn't

90:14

come to you with like a flash of insight

90:16

that you should just stop thinking

90:18

you're writing a book about constraints

90:19

yeah and you you know I'm not going to

90:21

give away all all of the things in the

90:22

book because you know you to sell it

90:25

especially since like half of it isn't

90:26

written so it's I can't even give away

90:28

half but I found this story about Apple

90:30

really important because it's helped me

90:31

think about some of the things I'm doing

90:33

in business but also in my life are you

90:35

able to share that story of of Apple

90:36

what you've discovered in terms of focus

90:38

and constraints sure not not not Apple

90:40

so much as as um another company uh

90:45

called General magic that was uh a lot

90:48

of the team that designed the original

90:50

Mac came to this company and it was like

90:53

the the the hottest thing in Silicon

90:55

Valley and they were going to build um

90:58

uh the iPhone they had the idea they had

90:59

the vision like the drawings they have

91:01

look like the iPhone they had the team

91:03

from the Mac they had this incredible

91:04

Talent uh they went public in a

91:06

so-called concept IPO they didn't have a

91:08

product yet but the idea was so hot that

91:11

they were taken public uh and long story

91:13

short it turned into a disaster because

91:16

they had no boundaries they had as much

91:18

money as they wanted they didn't have

91:20

any customer in mind um they uh anything

91:24

they thought was cool they built it and

91:26

so the project just grew and grew and

91:28

grew and grew and never found the focus

91:31

to to kind of turn into anything usable

91:33

but a lot of the alumni that came out of

91:35

there realized that that was a problem

91:37

and so going forward they would have

91:38

lessons like you're better off

91:40

envisioning a customer even if it's the

91:41

wrong person than none at all and just

91:43

building something that's cool because

91:44

even if it's wrong you can learn that

91:46

you were wrong by trying something

91:47

whereas if you don't have one you don't

91:48

even have sort of a feedback mechanism

91:50

for Learning and so it was spending some

91:53

time with with some of those alumni um

91:55

got me really interested in in

91:56

constraints and uh I'm still putting

91:59

together some of that some of that

92:00

writing so I don't know that I can do it

92:02

justice at the depth um that I could if

92:05

I'd already written it but it's

92:06

interesting with the words you use

92:07

because there appears to be a bit of

92:09

kind of like a paradox or contradiction

92:10

in this idea of like breadth and then

92:14

constraints and focus and it's this

92:15

interest you know I mean that's part of

92:17

the reason I got interested in it

92:18

because a question after range that

92:20

people had for me was you know how do

92:22

you know when to focus right like so it

92:25

really very much came out of this

92:26

question because eventually you get this

92:27

broad toolbox you have to focus it into

92:29

achievement at some point right you

92:30

don't want to just pinball forever which

92:32

is what you said as your like hot

92:33

streaks hot streaks right you want to

92:34

folus into a hot streak eventually and

92:37

it also came out of this aspect of me

92:38

search you know research is research um

92:42

where my own biggest challenge the

92:44

bigger my projects are and the you know

92:46

books being big projects for me the

92:48

harder it is for me to draw the

92:50

boundaries of what is in Bound because

92:52

the the topics I take on in my my books

92:54

are by definition can't be perfectly

92:56

answered balance of Nature and nurture

92:57

and developing a skill how broad or

92:59

specialized to be and when and so I've

93:02

had so much trouble saying this is the

93:04

boundary for what fits in here and so I

93:06

myself wanted to get better at at

93:08

learning how to use constraints uh in in

93:11

my own work so for the first time with

93:13

this book for the first time I said

93:15

because I I for both of my previous

93:16

books I've written like 15% the length

93:19

of a book and then had to cut back

93:20

because I just shove in everything I

93:21

think is interesting this time I said

93:23

I'm going to have an architect ahead of

93:24

time forc myself to adhere to that and

93:27

one of the first things I noticed was

93:30

it's I I usually don't write the

93:32

chapters in order and I I started with

93:34

this book with my normal process of I'm

93:35

going to jump in with chapter five

93:37

because I just did the research and I

93:39

realized because I was starting to see

93:41

like this is going to break some of the

93:43

structure up and

93:45

downstream I'm leaving all these blanks

93:47

because I don't know what I will have

93:48

already said so I actually have to go

93:49

back and start an order so now you know

93:51

after being in writing for whatever like

93:53

almost 20

93:55

years suddenly I have a totally new work

93:57

process and I'm writing an order for the

93:59

first time which is interesting and and

94:00

a bit scary but I'm writing at length

94:02

too I'm actually going to turn in a book

94:03

at the length of a book for the first

94:05

time are you not um at all concerned

94:07

about AI as a writer because you know

94:10

these models are getting smarter and

94:11

smarter every single week and just

94:13

generally how do you look at the the

94:14

sort of future of work in a world of AI

94:16

it feels like it's going to be such a

94:17

disruptive force in you know oh I think

94:20

it is career planning and like what do I

94:22

do with my future I mean it might touch

94:24

everything but one I love playing with

94:26

it so I'm I have these competing forces

94:28

of like maybe it'll um you know I'm a

94:32

very curious person and so if I'm I I I

94:36

play with probably about four different

94:37

AI programs a day but the the one that's

94:40

the most useful to me is called site.

94:42

again is it I don't have like any

94:45

affiliation with any of these things I'm

94:46

just a subscriber s. where I can put in

94:51

a scientific paper and it'll make like a

94:53

app showing all the other papers that

94:55

cite it and it'll try to automatically

94:56

sort them into those that agree and

94:58

disagree and it really helpfully will

95:00

show the snippet of how that the target

95:03

paper was cited in these other ones that

95:06

I used to have to spend like go sit in a

95:09

research library and be doing that by

95:11

like scanning down a paper to find that

95:13

so it's like a day now is an hour so and

95:18

I love that like if that means my books

95:20

don't sell as well but I get to learn 10

95:23

times as science that's a trade-off I'm

95:25

definitely willing to make personally

95:27

I'm not saying everyone should be

95:28

willing to make that but I'm willing to

95:30

make that tradeoff but in terms of work

95:32

generally being

95:34

disrupted yeah I mean I think the the

95:37

model that I think of for sort of

95:39

there's no singular model but for how

95:41

technological

95:43

innovation has disrupted work in the

95:45

past a model that I like that I can tell

95:47

sort of

95:48

quickly is the introduction of the ATM

95:51

in in the United States happened around

95:52

1970 uh so cash machine mhm um and I

95:57

went back and looked at news coverage

95:58

and it says like every uh you know

96:01

300,000 bank tellers are going to go out

96:03

of business overnight and instead what

96:05

happened over the next 40 years as there

96:07

were more ATMs there were more bank

96:09

tellers not fewer because ATMs made

96:11

branches Bank branches cheaper to

96:13

operate so there are fewer uh branches

96:16

overall a fewer tellers per Branch but

96:18

more branches overall

96:19

sorry um but it fundamentally changed

96:22

the job from someone who's doing these

96:23

repetitive transactions repetitive cash

96:25

transaction to someone who's like a

96:27

marketing professional and a customer

96:29

service representative and uh you know

96:31

maybe a financial adviser it shifted

96:33

them to these

96:34

strategic goals where it's much broader

96:37

mix of strategic skills so if we can

96:39

Outsource some of that Kinder learning

96:41

environment repetitive stuff to shift

96:43

humans to being more strategic I think

96:45

that's like a good thing right we think

96:48

about I I know Radiologists have been

96:50

some of the people deal with medical

96:51

imaging have been some of the people who

96:52

have often in these reports by banks

96:54

that say who's going to be replaced

96:56

they're often high on the list because

96:58

they say the technology can you know

96:59

read these pictures very easily radio

97:01

just looks at a scan and tells you if

97:02

you've got a cancer or something yeah

97:04

but first of all I have yet to hear the

97:07

problem of like wow too many people are

97:09

having too easy access to Radiology

97:11

right like I think we want more of this

97:12

service but I think most doctors are not

97:15

doing doctor house you know most of the

97:18

stuff they're seeing is something

97:21

they've seen a million times and I think

97:23

a really important role for them is

97:25

strategic of well what should this mean

97:27

to the person how should I deal with

97:28

them and what what's reasonable to

97:30

implement in their life and what's

97:32

feasible for them to do to make a change

97:34

and so I think it'd be great if we could

97:36

Shi I don't think it will replace those

97:37

doctors I think it might shift them to a

97:38

more strategic role where they don't

97:40

have to spend time doing the sort of

97:43

more tactical stuff and can do the more

97:44

strategic stuff so that's that's been e

97:47

even in even in chess you know like

97:50

when well like when when IBM's deep blue

97:52

beat Gary casprov in chess in 1997 and

97:55

he noticed that it beat Gary casprov he

97:57

was so much better when he was he was

97:58

the best in the world at the time now

98:01

like a free app on your phone would be

98:02

Gary casprov but and he noticed the

98:05

computer was so much better at tactics

98:06

these are these like small patterns of

98:08

moves that he had spent his life

98:09

memorizing but he noticed it wasn't as

98:11

good at strategy which is how to arrange

98:13

the battles to wage the war so he

98:15

promoted what he called freestyle chess

98:17

tournaments where humans and computers

98:18

could play in any combination and the

98:20

winners were neither supercomputers nor

98:22

Grandmasters nor grandm with

98:24

supercomputers two amateur chess players

98:26

with three laptops they knew something

98:28

about Chess they knew something about

98:30

algorithmic search and they could coach

98:32

the computers where to look like they

98:33

couldn't even analyze their own games in

98:35

like the winners press conference at a

98:37

deep level because they didn't know

98:38

enough about chest but I think the

98:40

lesson there is it when the Tactical

98:41

part was outsourced it shifted it first

98:45

of all changed the people who were the

98:46

best at the task like this and it

98:48

shifted the humans to the more strategic

98:50

level and so I think that's what we need

98:51

to be ready to think about what can we

98:54

hand off so that we shift to a more

98:55

strategic level how might you be wrong

98:58

maybe the Strategic level maybe these

99:00

tools will be better at the Strategic

99:01

level than we would ever be I still

99:03

think there'll be a role for us in

99:04

determining what their goals should be

99:06

and that's a whole other level of

99:07

strategy is like what kind of world do

99:09

we want to live in I don't think in the

99:11

near term that we're going to be taking

99:12

our cues from them in that role but I

99:14

think even the people like last year I

99:17

was sitting around a campfire with one

99:19

guy who's running a generative AI

99:21

company and another guy who was like his

99:22

first investor

99:24

and who himself had worked in AI like

99:27

you know they were both uh

99:28

technologically Adept incentives

99:31

aligned and one guy was saying we'll

99:33

have artificial general intelligence

99:35

within three years for sure and the

99:36

other guy was saying I think this is a

99:37

glorified toy I still use Google more

99:39

and these were two people with similar

99:41

expertise with incentives aligned which

99:43

to me suggests the degree to which even

99:45

the people working on this stuff don't

99:46

totally understand what its capabilities

99:49

are or what it's doing um and so I think

99:51

there's a lot that's I think there's a

99:53

lot that's unknown someone made the case

99:55

to me that they said uh think about it

99:57

like this Steve you've got this Steve

99:59

here say my IQ is 100 and there's

100:00

another Steve through that war whose IQ

100:02

is a thousand what would you give me to

100:05

do as a task versus what would you give

100:07

him to do as a task who would you want

100:09

to drive your kids to school who would

100:12

you want to I don't know answer you're

100:13

saying we give everything to that person

100:15

well this is the analogy he gave me he

100:16

was like what are you left with okay

100:18

even even if it comes to that point even

100:20

if it comes to that point there'll still

100:22

be the issue of comparative Advantage

100:23

which is that these these models are

100:25

incredibly energy intensive right and so

100:27

you'd want to delegate energy to them

100:30

for the things that you really want them

100:31

to do so even if they are do end up

100:33

better than us at everything because

100:35

energy is not unlimited there will still

100:36

be things that are more valuable to have

100:38

us doing than to have them doing right

100:40

even like I mean that's the case all the

100:42

you may be better at certain things in

100:43

your business but you're not doing them

100:46

because it's a comparative advantage for

100:48

you to do this instead of those other

100:49

things so I think even if they do get to

100:52

the point where they're better than us

100:53

at everything there's still roles for

100:54

humans but incredible amount of

100:55

disruption right like what really

100:58

worries

100:58

me I mean I was reading

101:01

about last year about technological

101:03

innovation in history you know and we

101:06

have like to put it in a very coarse

101:08

nutshell it's like for 300,000 years we

101:10

lived like squirrels and then for 10,000

101:12

years we lived like farmers and then 250

101:14

years it's like everything changed every

101:15

generation like

101:17

crazy um and that's been hard to to

101:20

adapt

101:21

to um and I think

101:24

you know I thought that the Industrial

101:27

Revolution this you know which pulled

101:30

ultimately led to pulling billions of

101:32

people out of poverty you know changed

101:34

everything I thought that because

101:36

productivity increased so much that

101:37

wages and things would have increased

101:39

right along with them but it turns out

101:41

that there's pretty good evidence that

101:42

there was actually a gap of probably

101:43

about 40 years between the increase of

101:45

productivity and the increase of

101:47

Wages that's not good like a 40-year gap

101:50

between a huge technological disruption

101:52

and like Shar shared

101:54

Prosperity that's not something I think

101:55

we can really afford and and what sort

101:59

of helps solve the problem is that when

102:00

lots of people got urbanized for the

102:02

Industrial Revolution and looked around

102:03

and said hey you have the same problem

102:04

that I have we need to band together for

102:05

Collective action I think the challenge

102:08

now is we're like an invisible Factory

102:09

so it's it's harder to get people to

102:11

collectively act because we're not

102:12

sitting next to each other dealing with

102:14

this problem but I think we need to

102:15

start thinking as a group

102:18

of this technology is

102:21

cool but identifying problems that we

102:23

want it to work on not just building it

102:25

out be for the sake of Jus it's cool

102:27

what kind of world do we want to live in

102:28

I think we need to be asking those

102:29

questions I think it's quite unlikely

102:31

that we'll be intentional with it in the

102:32

way that you're hoping it'd be

102:34

unfortunate I mean I think a good sign

102:36

though I think is that even

102:39

the kind of technologists who I think

102:42

are usually prone to Hyperbole and

102:44

saying like this will be the greatest

102:45

thing even when it's obviously not going

102:46

to be are sounding some notes of caution

102:48

with this one in an early stage and so I

102:51

think that's a tuned other people to

102:53

some of those notes of caution I don't

102:54

think that gets us out of the woods by

102:56

any stretch the notes of caution worry

102:59

me oh well that's the point they should

103:01

worry I think if we if if we were where

103:03

we are and not worried right now I think

103:05

that would be a lot worse what is the

103:08

most important idea in your work that we

103:10

haven't discussed in your opinion in the

103:12

sports Gene I think the most important

103:13

idea um that we haven't discussed is

103:16

that uh Talent at

103:19

Baseline like the talent you if you take

103:22

a test in something your let's say you

103:25

haven't trained in that thing that we'll

103:27

call that your talent

103:28

Baseline is sometimes correlated with

103:32

your ability to improve from training so

103:34

people training looks just like medicine

103:37

because of differences between us some

103:40

medicine might work for you in a way

103:41

that it doesn't for me training is

103:43

similar two people will get different

103:45

results from the same exact training and

103:47

sometimes how good you are to start is

103:49

predictive of how rapidly you'll improve

103:52

but very often it is

103:54

not and that's a huge deal because we

103:57

usually judge people's potential based

103:58

on what we see right now or what we see

104:00

at Baseline before they've really had a

104:01

chance to train what I think the science

104:03

shows is that this Talent of

104:05

trainability is even more important than

104:07

Talent at at Baseline and so if you're

104:09

trying to evaluate people before they've

104:11

really had a chance to find a training

104:13

that fits for them again it's a messy

104:15

answer because it means people have to

104:16

experiment with the kind of training

104:17

that works for them and that

104:19

trainability is the most important kind

104:21

of talent and I think that's a different

104:22

picture of talent okay this is quite

104:24

this is very important because it

104:25

immediately as a employer I thought when

104:27

I'm hiring

104:28

people I you know if I'm hiring a

104:31

producer for one of our podcasts

104:32

whatever I shouldn't be focusing so much

104:34

on if I'm was planning for them to work

104:36

with for me and with me for 10 years I

104:38

should be thinking about their

104:40

trainability yeah I was going to say it

104:41

depends how quickly you need them to get

104:43

going right if you need them if you need

104:44

to know what they know today and they

104:45

need to be using that thing tomorrow

104:47

yeah that's one thing um but if if it's

104:50

about how good they're gonna get in the

104:52

long run you just shouldn't assume that

104:54

what you're seeing today predicts like

104:55

their ability to improve at a certain

104:57

can you measure someone's train ABY I

104:59

mean you can measure it very easily and

105:00

things like their aerobic capacity you

105:02

know the amount of oxygen that they can

105:04

uh move through their body I mean some

105:05

of the initial studies of this were done

105:06

in in scenarios like that where you had

105:08

everyone doing the exact same training

105:10

and you were literally measuring

105:11

physiological parameters you can do it

105:13

in other types of cognitive testing and

105:14

ability testing if you're looking for a

105:16

sort of specific task that's a little

105:19

harder if you're looking for a task

105:20

that's customized to something in your

105:21

business I think that's more difficult

105:23

it's going to be a little more

105:24

subjective I guess you could you can

105:26

kind of look at other areas of their

105:27

life I guess in the professional context

105:29

to see how quickly they developed one of

105:31

the things I look at when people apply

105:32

for jobs to work in one of my businesses

105:34

is I look at their LinkedIn resume but

105:36

specifically how quickly they got

105:37

promoted and moved through departments

105:39

because that's kind of an indicator it's

105:41

obviously not the most important thing

105:42

but you'll go you click on someone's

105:43

LinkedIn and you'll see they joined as

105:44

an intern and then a year later they

105:46

were a manager of the team then a year

105:47

later they were the like director of the

105:49

team then a year later they moved up to

105:50

a different department a year later they

105:51

became the global head and I'm like oh

105:53

my God that this person really moves

105:55

through the system well um and that is

105:57

an indicator of a few things they get on

105:58

with people because someone's pulling

106:00

them up and saying that person go up

106:02

their team are also um basically voting

106:05

that they should be the manager um they

106:07

have Proficiency in in learning rapidly

106:10

because especially if they jump between

106:11

sort of departments from HR to um

106:13

culture whatever um and I I always think

106:16

that makes them a bit more adaptable and

106:18

teachable if they've shown that track

106:20

record of

106:21

changing profession and moving up the

106:23

organization quickly interesting because

106:26

that feels a little related to I think

106:27

the an important idea that we didn't

106:29

talk about from range has to do with

106:31

so-called serial innovators these are

106:32

people who make repeated creative

106:33

contributions to their organizations no

106:35

matter where they are even when they're

106:36

changing like I said changing places and

106:39

these people like a woman named Abby

106:40

Griffin a professor and her colleagues

106:42

who studied these people some of the

106:44

descriptions of who they are uh these

106:46

are like literal phrases from her work

106:48

they are systems thinkers they read more

106:52

and more widely than their peers they

106:54

have a need to learn outside their

106:55

domain they have a need to communicate

106:57

with people with expertise outside of

106:58

their own area they appear to flit among

107:00

ideas which doesn't usually sound like a

107:02

compliment um they repurpose things are

107:04

already available in new ways all these

107:06

sorts of things and you can feel in her

107:08

writing almost she's almost like talking

107:09

to HR people saying just so you know

107:12

when you define a role too narrowly

107:14

you're making sure you select these

107:16

people out or force them to go somewhere

107:18

else to try to cultivate that kind of

107:19

breath and I don't think you can create

107:22

these people from Whole cloth but I

107:24

think you can absolutely stifle them by

107:27

not allowing them to do that kind of

107:29

moving around internally and so I think

107:31

when you're looking at

107:32

hiring I think the organizations that

107:35

I've been around at least that disrupt

107:37

themselves continually instead of

107:39

waiting to get disrupted Reserve at

107:41

least some of their hiring for instead

107:43

of saying here's a square peg for a

107:45

square hole that we need tomorrow they

107:48

say what is something we want that we

107:51

would have trouble teaching

107:53

let's go get someone with that and we

107:54

can coach them up on the stuff we're

107:56

good at so

107:57

like an extreme example of this was this

108:00

investment firm in Scotland I spent some

108:02

time with bayy gford this like

108:03

incredibly uh successful firm and I

108:08

think they this is Extreme but someone

108:09

there told me like they won't hire

108:10

anybody with an MBA I think that's I

108:12

don't think you should rule out things

108:14

like that but anyway but what they would

108:15

go is they'd say we want someone who has

108:16

experience in this or that or this kind

108:18

of thinking let's go get them because we

108:21

can't teach that thing and then we can

108:23

coach them up on finance it's going to

108:24

take them an extra few months to get

108:26

going because we're gonna have to teach

108:27

them but the stuff that why should we

108:30

hire for exactly the stuff that we can

108:31

most easily teach let's hire for the

108:33

stuff we want but that we would have

108:34

trouble teaching and then we can teach

108:36

them on it and I think the places that

108:37

are looking to disrupt themselves keep

108:39

sort of an eye open for that kind of

108:40

thing not for every hire but for some I

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the things I really love about your work

109:47

is you always cite different studies and

109:48

they're particularly fascinating I wrote

109:50

down tons of different studies from

109:51

different points that you've made made

109:52

today but are there is there a favorite

109:55

study that you that surprised you the

109:58

most or shifted your your sort of

109:59

Paradigm the most some of the the

110:01

research about forecasting totally

110:05

shocked me so the most famous work ever

110:06

done on on forecasting making

110:08

predictions was a

110:10

20-year uh program of research that had

110:13

people making predictions about

110:15

geopolitical you know social

110:16

technological events and they had to get

110:20

they got 83,000 probability predictions

110:22

because people had to make specific

110:24

probability predictions of the

110:25

likelihood of an event by a specific

110:26

deadline so like 20 20% probability of

110:29

this happening by this time correct like

110:31

that there's going to be and it would be

110:33

very specific it would be a 20% chance

110:36

that within the next 12 months there

110:37

will be a military confrontation that

110:39

causes at least five casualties in the

110:41

South China Sea like it had to be very

110:42

specific so that they could say if

110:43

someone was right or wrong and they

110:45

needed so many because they had to

110:46

differentiate luck from uh good luck and

110:49

bad luck from skill and the worst

110:51

forecasters turn turned out to be like

110:53

the most narrowly specialized people who

110:55

were it do not that these people are not

110:57

important for generating knowledge but

110:59

who came to see the whole world through

111:00

sort of one lens or mental model and

111:03

would they had spent their whole careers

111:04

kind of studying one problem and and

111:07

would see the whole world around that

111:10

and they would wrap everything into that

111:12

story basically so in in this this

111:15

research they were called The Hedgehogs

111:16

who knew one big thing whereas the good

111:18

forecasters were the foxes who knew many

111:21

little things and sometimes

111:23

they had an area of expertise and

111:25

sometimes they didn't but more important

111:26

than what they thought was how they

111:27

thought they would collect different

111:30

perspectives they use social media

111:32

anything they had to take their own

111:33

hypothesis and tell get other people to

111:36

falsify it for them uh and those people

111:39

turned out to be the the best

111:42

forecasters and when they were put

111:43

together in groups with one another they

111:45

became even better because they had this

111:47

approach of of sort of borrowing from

111:50

the scientific method to test their own

111:51

ideas basically

111:53

and it just surprised me that these sort

111:55

of random people in many cases in a

111:58

tournament where they were pitted

112:00

against the intelligence community in

112:02

the United States that had access to

112:04

classified information that they did not

112:06

they beat them

112:08

handily and I just wouldn't have

112:10

believed that unless I unless I saw it

112:12

that that body of research about

112:13

forecasting the ability to see around

112:14

the corner a a big aspect of what made

112:17

people good at it was actually the

112:19

researcher who led this work described

112:21

those people as having dragonfly eyes

112:22

dragonfly's eyes are made of thousands

112:24

of different lenses each one of which

112:27

takes a separate picture and they are

112:28

synthesized in the dragonfly's brain and

112:30

so these people are gathering all these

112:32

different perspectives and they can seem

112:34

sort of confused and equivocal so they

112:36

might not make for good TV guests they

112:37

actually found in the research because

112:38

they don't go on and say this is how it

112:40

is like the housing crash is coming and

112:42

bl blah you know they're more

112:44

circumspect in some ways they might not

112:45

be as good TV guest but they're very

112:47

good forecasters it just made me think

112:49

that on a personal level I need to keep

112:51

pushing myself out outside of my zone of

112:53

comfort more that's one of the big

112:54

things I took away from the book range

112:56

but also just much of your work is it's

112:59

easy to get complacent in What I Know

113:01

Who I Am My identity what I do and in

113:03

fact that's probably the biggest risk to

113:05

my future success but also probably to

113:07

my fulfillment as well and it it goes

113:10

against our natural inclination to push

113:13

into uh unknown territory yeah because

113:17

the older we get the more like you know

113:18

they say you can't teach an old dog new

113:19

tricks I think it's more like the old

113:20

dog doesn't really want to know learn

113:22

new Tri tricks you know can't see the

113:23

point in learning a new trick and to

113:25

that point of the of the so-called Big

113:28

Five personality traits in Psychology

113:30

one of them is called openness to

113:32

experience which is the most predictive

113:33

of creativity and in in middle age it

113:35

reliably goes down goes down but

113:38

actually a study I loved in the book

113:40

found that if you force older people to

113:43

do something new can be some sodoku or

113:46

something even if they don't get good at

113:48

that thing if it's new to them it will

113:51

improve their openness to experience so

113:52

you can actually stem the decline of

113:54

openness to experience it's not

113:55

inevitable just by forcing yourself to

113:57

do new stuff that you're not competent

113:59

at is like great for brain health uh it

114:02

makes your life feel longer because our

114:04

memory Works in sort of chapters where

114:06

when you try new stuff it's like a new

114:07

chapter so it'll make your life feel

114:08

like it's not passing as quickly and it

114:11

keeps your openness to experience from

114:12

declining and so just like picking

114:14

something to do that's new even if

114:16

you're not planning on getting really

114:17

good at it I think is important it's

114:18

funny I said that thing a second ago

114:20

about um when I look at someone's

114:22

LinkedIn and then I looked down and I

114:23

found this little research um piece that

114:27

LinkedIn did that I'd pulled out that

114:29

said one of the best predictors of who

114:31

um would become an executive in a

114:33

company yeah was the number of different

114:35

job functions that individual had worked

114:38

across an industry so that's research

114:39

done by LinkedIn wasn't it yeah wasited

114:41

that was on about a half million members

114:43

yeah and and the interesting thing about

114:45

that was I when I was in contact with

114:47

LinkedIn uh talking about that and

114:49

trying to get some of that

114:51

data I said I kind of feel like your

114:54

guy's product might militate against

114:55

people doing this because you're saying

114:59

this is this is who's doing the best but

115:01

they might want a much cleaner kind of

115:02

linear trajectory yeah um so maybe you

115:05

should build another product where they

115:08

can build a narrative into it and say

115:10

Here's why I switched here's what I

115:11

learned and what so what's the actual

115:13

can you recap to me what the actual

115:15

finding was I mean that was that was

115:16

pretty much it that across a half

115:18

million members that the strongest

115:20

predictor of who was going to go on to

115:21

become a future executive um was uh the

115:25

number of different job functions that

115:26

they' worked across in industry in a

115:28

specific industry in Industry so not

115:30

changing Industries not changing

115:31

Industries although changing Industries

115:33

there was a bunch of lower level stuff

115:34

and changing Industries was useful at

115:36

times also but to be an executive in a

115:39

particular industry lots of job

115:41

functions across that across an industry

115:43

and does that mean different departments

115:44

within that industry they characterize

115:46

job functions you have to be doing

115:47

something fundamentally different okay

115:50

so give me an example I mean let's say I

115:53

think probably the easiest one is where

115:54

you go from being a a a a performer or a

115:57

good performer to being someone who's

115:58

managing other performers right classic

116:00

one doesn't have to be progression

116:02

though because but that's I think a very

116:05

a very simple one right or in my

116:06

industry it'd be like going from writing

116:08

to editing would for sure be one which

116:09

is kind of a mix of writing and and

116:11

managing but that's the side step in

116:13

your industry and side step yep for sure

116:15

I mean some people would well I guess it

116:18

depends some people would would view

116:20

that and in some places it's going up

116:21

but i' a side step the other thing I

116:23

found which was uh pretty shocking was

116:25

the in the part of your book where you

116:26

start talking about some of the dangers

116:28

of specialism and you referenced a study

116:30

that found cardiac patients were less

116:32

likely to die if they were they were

116:33

admitted to a hospital yeah when the

116:36

doctors were away we can tie in a few of

116:39

the things we've been talking about to

116:40

uh uh cardiac s to surgery here so so

116:43

this was this study so I think because

116:45

I'm I'm conscious when I write about

116:46

dangers specialization hugely important

116:49

obviously and in medicine it would be

116:52

crazy to say that specialization in

116:54

medicine increasing specialization

116:56

hasn't been both inevitable and

116:57

beneficial in many

116:58

ways but the point I was trying to make

117:01

is that it's also an underrecognized

117:02

double-edged sword to the point where

117:03

these two Harvard Le studies found that

117:05

if you're checked in to a teaching

117:07

hospital with certain cardiac conditions

117:09

on the dates of a national Cardiology

117:11

convention when the most esteemed

117:12

Specialists are away you're less likely

117:14

to die that that makes no sense right

117:17

that's suboptimal outcome and and the

117:19

conclusion was that's because these

117:20

researchers or these these

117:23

surgeons have done the same procedure so

117:27

many times that they will continue to do

117:30

it even if it's not the right solution

117:31

to the problem or if data shows that it

117:33

doesn't work anymore and so this called

117:35

the einstellung effect in Psychology

117:37

where you've done you've solved a

117:38

problem a certain way so many times that

117:40

you will continue solving problems that

117:41

way even if the problem has changed or

117:43

if new data emerges that shows it's not

117:44

the right solution so it's not to say

117:46

those people aren't important but they

117:48

are human and so they fall prey to the

117:50

Ein stong effect that's again why you

117:51

want some of this this mixture and to

117:53

tyion surgery you know we've also been

117:55

talking about distraction and focus one

117:57

of those same researchers did some work

117:59

that showed that if you have a surgical

118:02

procedure and this this research looked

118:03

at 980,000

118:06

procedures that if you have a procedure

118:08

on the surgeon's

118:10

birthday you're more likely to die

118:12

within the 30 days after the surgical

118:14

procedure and they attribute it to the

118:15

increased distractions that the surgeon

118:17

is having on their birthday they don't

118:19

know whether it's external or internal

118:20

distraction um but you might not want to

118:22

have your again and you know and this

118:25

these are not huge

118:26

effects but over a large number of

118:28

people it makes a difference and if yeah

118:30

gosh that's

118:32

terrifying so you one of the things I've

118:34

come to learn today really is that

118:35

knowledge is a double-edged sword like

118:37

deep knowledge on one thing really is a

118:39

double-edged sword it will be your

118:40

making but in the long term it might

118:42

also be your breaking yeah and that

118:44

really resonates with me because as we

118:46

started the conversation with there's a

118:47

lot of things that I'm like really

118:48

knowledgeable about and know a lot about

118:50

and in fact that's my biggest curse and

118:52

I have to find a way to basically self-d

118:54

disrupt myself continually and always

118:56

assume that I am wrong and not not

118:59

always assume I'm wrong always assume

119:00

that there's a significant possibility

119:02

that I'm wrong today and maybe yesterday

119:05

I was correct but today I could be

119:06

entirely wrong um I mean I've changed my

119:08

mind about like fundamental beliefs I

119:10

had you know when I was younger and it's

119:12

weird to

119:13

think I mean like I was a grad student

119:16

environmental sciences and I was firmly

119:18

of the belief that uh environmental

119:21

preservation and technological progress

119:23

were at odds and I feel completely the

119:25

opposite now you know I think there are

119:27

technological things we can do that ruin

119:28

the environment but I actually think the

119:29

salvation of the environment requires

119:32

technological progress It's just like

119:33

fundamental beliefs about the world so I

119:35

think we should be open to that updating

119:36

and from a career perspective you know

119:38

if artificial super intelligence and

119:40

like some new form of free energy does

119:42

everything better than us then it does

119:43

and we'll have to reorient life in some

119:45

pretty dramatic ways uh but until then I

119:48

think we need to dispense with the idea

119:50

that you can live in a world where you

119:52

did a period of training for most of us

119:55

and then you're just going to benefit

119:56

off only that training for the rest of

119:57

your life you don't have to keep

119:59

relearning we have a closing tradition

120:01

on this podcast David where the last

120:03

yeah I know I love this tradition I want

120:04

to do it to like my friends when they

120:05

come

120:06

over interesting the last guest leaves a

120:09

question for the next guest interesting

120:11

oh boy it's so funny watching people's

120:14

body language when I open this book they

120:16

start to get quite nervous and it's so

120:17

funny I've asked I don't know [ __ ]

120:19

[ __ ] 100 questions today and it's when I

120:22

come to this question that people take

120:23

the longest time to answer so I'm like

120:25

these questions just better than my

120:26

questions um no some reason people get

120:29

nervous those other questions are things

120:30

that are so top of mind for me that

120:32

there's it's like a choice between which

120:34

of the three things that are in my mind

120:35

should I spit out this is like yeah this

120:38

is very different yeah uh what's your

120:40

favorite sandwich I'm joking imagine if

120:42

that was it after all I'm going to get

120:43

off easy no it's much more difficult

120:45

than that the question is what what is

120:48

your biggest fear and how

120:53

do you plan to face

120:55

it I have

120:58

a

121:01

tendency that I think in some ways is

121:04

good um and fits with some of the things

121:06

I've said but in some ways is bad to

121:08

want to start things over a lot and

121:11

sometimes that means burning them down

121:13

even if they're going well and in the

121:15

past I think I had that tendency with

121:17

some of my personal relationships to I

121:20

couldn't accept something going well

121:22

and it had to change or get better and

121:26

that led me to sometimes I think burn

121:29

down some personal relationships in ways

121:32

that I'm embarrassed of that I

121:34

regret um and I see this even in my own

121:38

work where I actually value it because I

121:39

end up doing all these new novel things

121:41

but it's almost like I can't and it's

121:43

good because like after my first book

121:44

they're like brand yourself as a sports

121:45

Gene guy I'm like no that's dead to me

121:46

now it's dead to me before it's even

121:48

published it's dead to me and that led

121:50

me to do these other interesting things

121:51

but I sometimes worry that I have this

121:53

like

121:54

pathologic why can't I just accept this

121:57

is this thing is good um and and let it

122:00

be good and it worries me much less in

122:02

my work life it worries me a little in

122:03

my work life that I'll always want to

122:04

burn something down and start over but

122:06

it does worry me there but I have a more

122:09

of a fear of it in the context of like

122:11

friendships because I know what I've

122:13

done in the past I think I'm better with

122:15

it now but thinking about the values I

122:18

have in my life going forward I don't

122:20

want

122:22

you know several relationships that were

122:24

hugely important to

122:26

me uh went away for things that were

122:29

preventable because I was like if it's

122:32

not perfect burn it down and I think

122:34

that was a really destructive impulse

122:38

um what is that in you what is that

122:40

where does that come from I don't know I

122:42

think it's like this feeling of always

122:44

want to be in becoming like this feeling

122:46

of starting over and improving that I

122:47

find

122:48

intoxicating um but I don't think that

122:51

has to apply to to personal

122:53

relationships uh and so a value that I

122:56

really want to work on I read this this

122:57

book that kind of influenced me about

122:58

philosophy and it's centered what's

123:00

called narrative values these values

123:02

that are objectively across cultures

123:06

things that people value so it's could

123:07

be like heroism right loyalty people

123:10

value that other country and that you

123:11

are subjectively attracted to and one of

123:13

the ones that I think is valued in a lot

123:15

of cultures that I'm attracted to but

123:17

that I've not been good at is

123:18

forgiveness and so my project is that's

123:22

a narrative value I want to start

123:23

building into my story to be a more

123:25

forgiving person because it's not it's

123:27

I'm not good at it uh and I need to get

123:30

good at it and I'm afraid that I won't

123:31

get good at it but I really want to well

123:34

we learn don't we and that's um that's

123:36

much of what is what is at the very

123:38

heart of your work how to become better

123:40

at learning and you've clearly

123:41

demonstrated that you're learning in

123:42

that regard I think much of the first

123:44

the first step in learning is figuring

123:46

out that we have a problem or some

123:47

something to solve as you said with your

123:48

experiments book and your books are so

123:50

unbelievably wonderful because they

123:52

present a completely original

123:53

challenging unconventional approach to

123:56

solving problems and you you do go at a

123:58

lot of the things that many of us have

124:00

accepted as narratives in our life and

124:01

if we've accepted them as narratives and

124:03

they're false then they're probably in

124:04

some way doing us a dis service in the

124:05

short or long term and that's why I find

124:07

your work so wonderfully important

124:09

because in many respects it is that

124:10

counternarrative to a lot of the things

124:12

that we've accepted and you do go the

124:14

extra mile even though it probably gives

124:16

you a headache I'm sure because a lot of

124:17

authors that I speak to don't go the

124:19

extra mile to figure out um if if what

124:21

we're being told is true and ultimately

124:24

that's a means to an end and the end is

124:25

to allow all of us to live more

124:27

optimized fulfilled and happy and

124:30

productive lives in whatever domain in

124:32

whatever definition we class those words

124:34

so thank you David for doing the work

124:36

you do I'm so excited to read whatever

124:37

you make next um and you're writing a

124:39

book on constraints and I just already

124:40

know that if it's anything like these

124:41

two books range and the sports Gene it's

124:43

going to be one of the most important

124:44

books I've ever read so thank you that

124:47

was a wonderful compliment I don't want

124:48

to add anything to that

124:51

[Music]

124:54

perfect Ted has quite frankly taken the

124:56

nation by storm a small green energy

124:59

drink that you've probably seen popping

125:01

up through a Tesco or through waitrose

125:03

they've grown by almost

125:06

10,000% in a very short period of time

125:10

because people are sick and tired of the

125:12

typical unhealthy energy drinks and

125:14

they've been looking for an alternative

125:16

perfect Ted is the drink that I drink as

125:18

I'm sat here during the podcast because

125:20

it gives me increased f focus it doesn't

125:22

give me crashes which sometimes might

125:24

happen if I'm having a 3 4 5 6 hour

125:27

conversation with someone on the podcast

125:28

and it tastes amazing it's exactly what

125:31

I've been looking for in terms of energy

125:33

that's why I'm an investor and that's

125:34

why they sponsor this podcast and for a

125:36

limited time perfect Ted have given

125:38

Diary of CEO listeners only a huge 40%

125:43

off if you use the code diary 40 at

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checkout don't tell anybody about this

125:49

and you can only get this online for a

125:50

limited time so make sure sure you don't

125:52

miss out

125:53

[Music]

126:13

[Music]

Interactive Summary

David Epstein, author of 'Range' and 'The Sports Gene,' argues against the popular 10,000-hour rule for expertise. He advocates for 'breadth of training,' suggesting that diverse experiences lead to better long-term development, transfer of skills, and 'match quality.' He emphasizes the importance of self-regulatory learning—reflecting, planning, monitoring, and evaluating—and highlights that exploration is essential for sustained productivity, fulfillment, and achieving 'hot streaks' in one's career.

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