0:03

Could you learn to fly a helicopter

0:05

not by practicing, but

0:08

instead by uploading the information

0:10

directly into your brain? What

0:13

would society do if kids

0:15

no longer had to go to school? And

0:17

what does any of this have to do with suntan

0:20

booths or nano robots or

0:22

torking over a presidential address

0:25

or what a cowboy on a hill

0:28

is simply not able to see.

0:34

Welcome to Inner Cosmos with me David

0:36

Eagleman. I'm a neuroscientist and

0:38

author at Stanford and in these

0:40

episodes we sail deeply into

0:42

our three pound universe to

0:45

understand why and how our

0:47

lives look the way they do. Today's

0:58

episode is about the potability

1:00

of really coming to understand

1:03

the tangled forest of eighty

1:05

six billion neurons in your head

1:08

and the trillions of connections between

1:10

them. And if we could do that, could

1:12

we upload information directly

1:15

into your brain? Could we speed

1:17

up education this way? Now?

1:20

At the moment, this is all pure

1:23

fantasy because we simply don't

1:25

have the technology to allow

1:27

us to do that. But the question we're going to

1:29

ask today is whether this is theoretically

1:33

possible and something we can look

1:35

forward to around the corner of the

1:37

next century, and what are the

1:39

caveats, the things to watch out for, and

1:42

the unexpected complexities

1:44

here. So let's get started some

1:47

hundreds of years ago and still

1:49

in many impoverished places in the world,

1:52

children of the species Homo sapiens

1:55

reproduce by the time they are young

1:57

teens. But this situation

1:59

is it's totally different in modern times

2:02

and modern societies. Now, young

2:04

people go to school for

2:06

their first eighteen years or twenty

2:09

one years, and increasingly

2:11

twenty five or twenty six years

2:13

for an advanced degree, and in fields

2:16

like medicine, they take another several

2:18

years of internship and residency.

2:21

And in a field like neuroscience research

2:23

people do a postdoctoral fellowship

2:26

and then they hope to become an assistant

2:28

professor, and then an associate professor

2:31

and finally a full professor. And most

2:33

people are in their forties

2:35

by the time they get there. So

2:37

what accounts for this recent historical

2:40

change. Why do we do so much schooling

2:42

for so much of our lives now?

2:45

Well, it's because we are a runaway

2:47

species. We've gone off in a totally different

2:50

direction than all our animal

2:52

cousins, and we have made thousands

2:55

of important discoveries about

2:57

our world and produced so much art

2:59

invarious forms, And as a result,

3:02

there's so much to learn,

3:04

and so we need to spend decades

3:07

in institutions of learning,

3:09

not to mention, reading books and listening

3:12

to podcasts to understand

3:15

what millions of humans have

3:17

devoted their lives to figuring

3:19

out. But what

3:22

if there were a way that we didn't have to do

3:24

that? What if there were a way to simply

3:26

upload the information, in other words, to put

3:29

the information directly into

3:31

your brain. So let's harken

3:33

back to this great scene

3:36

in The Matrix where

3:38

Neo and Trinity are being hotly

3:40

pursued by the antagonist, agent Smith,

3:43

and our two heroes end up on top

3:45

of a building, and there they spy a

3:48

helicopter parked on the roof, and

3:50

Neo asks Trinity do

3:52

you know how to fly that? And she replies

3:55

not yet, And she flips open

3:57

her phone and she calls Tank, the operator,

4:00

and she says, I need a pilot

4:02

program for a B two twelve helicopter,

4:05

And we see the operator rotate his

4:07

chair in front of his bank of computers

4:09

and he quickly types out a bunch of commands,

4:12

and she closes her eyes and

4:14

one second later she turns confidently

4:17

to Neo and says, let's

4:19

go. So what happened

4:21

is that Tank the operator had

4:23

taken the expertise,

4:25

the complicated know how of flying

4:28

a B two twelve helicopter and just

4:30

uploaded it to her brain. So

4:33

the question we're going to ask today is

4:35

is that theoretically possible from a

4:38

neuroscience perspective, and what

4:40

will make that straightforward? And what

4:42

will make that not straightforward to

4:44

accomplish someday. Now,

4:46

in some ways, the whole idea sounds crazy

4:49

because it seems like we always have

4:51

to earn things if we want changes

4:54

to our brains or body. You can't just get something

4:56

for free. But of course, people for

4:58

decades have been climbing in into suntan

5:00

booths instead of spending days outside,

5:03

and people get botox, which binds

5:05

to receptors the ends of peripheral nerves

5:08

and changes the wrinkliness of your face.

5:10

And people are increasingly doing things

5:13

to not have to go to the gym but instead to

5:15

have your abdominal muscles

5:17

built for you with electrical

5:20

stimulation. You just lie on the table

5:22

and your muscles contract over and over and

5:24

The idea is that your muscles can grow stronger

5:27

and look better without you having

5:30

to do a single sit up. You just lie there.

5:32

So what would be the equivalent in the realm

5:35

of education? Can we imagine a

5:37

time when you don't have to bury yourself

5:40

in a book to master some domain,

5:42

where you don't have to spend hundreds of hours

5:44

sitting in a flight simulator, but

5:47

instead you hook something up to your

5:49

brain and then it is as though

5:51

you already knew quantum

5:53

mechanics or electrical engineering, or Persian

5:55

history, or how to serve for hang

5:58

glide or repair that model of

6:00

dishwasher or whatever. Now,

6:03

how would you push information to the

6:05

brain? We currently do this by

6:08

sitting down dozens of children in

6:11

front of someone who already has the information

6:13

in their brain, and that person uses

6:16

words or pictures, and the students

6:18

attend to those stimuli and

6:21

try to translate those words

6:23

or pictures into changes

6:25

in their own private jungle of

6:27

billions of neurons. They try to convert

6:30

what they're hearing or seeing into

6:32

storage in their own internal model

6:35

in a way that makes sense to them. What

6:37

learning means is that you very

6:40

finely change the networks

6:42

in your head. That's

6:44

it. That's what we pay lots of tuition

6:46

for and go off to college for to

6:48

get someone who already has information

6:50

in their network to translate

6:53

it through the low bandwidth channel of language

6:56

over to your network. So, just

6:58

to be clear on this, before you

7:01

know some factor concept, your network

7:03

is configured in some way, and

7:05

then I tell you, oh, that dog's

7:08

name is Nebula, and then you encode

7:10

that information. This connection in

7:12

your brain gets strengthened and this one gets weakened,

7:14

and this synapse unplugs, it replugs

7:17

over there, and this happens over millions

7:19

of synapses, and then you know something

7:21

that you did not know before. And

7:24

for deeper knowledge, like flying

7:26

a B two twelve helicopter, this

7:28

requires not just the memory of

7:31

a fact, but of a procedure.

7:33

And so those changes happen in

7:35

different brain areas and they're more widespread.

7:38

But what is required in all these forms

7:41

of learning are simply changes

7:43

in the patterns of your network, presumably

7:46

just the synaptic connections, but maybe

7:49

other details as well, like which

7:51

neurotransmitter receptors are being expressed

7:54

on the membranes and whatever. But that's it,

7:56

that's what it means. To learn

7:58

something. So is

8:01

there any way to implement those

8:03

changes besides the old

8:05

fashioned way of sitting for a semester

8:08

in a classroom or spending hours

8:11

in the helicopter flight simulator. Well,

8:13

there's been a lot of excitement about brain

8:16

machine interfaces, such as the

8:18

brain electrodes that are implanted robotically

8:21

by the company Neurallink. So I'll

8:23

just take a quick moment to clarify

8:25

the landscape of electrodes

8:28

in the brain. Even though neuralink

8:30

hit the news recently. The first thing to

8:32

note is that these brain machine interfaces

8:35

have been around for many decades

8:37

since people started inserting

8:39

electrodes. These are just thin metal

8:41

wires into the brain. The idea

8:44

is that you just insert this electrode

8:46

into the neural tissue and you listen

8:49

to the electrical activity of the

8:51

cells. And researchers pretty quickly

8:53

figured out that if you send a little

8:55

bit of electricity down the wire down

8:57

this electrode, you can stimulate

9:00

the cell to make it active where

9:02

it pops off its own little electrical

9:05

spikes that travel around. So you

9:07

put in some electricity and it goes And

9:10

this is the technology behind, for example,

9:13

deep brain stimulation you might have heard

9:15

of this. Take Parkinson's disease.

9:17

There's a tiny brain region

9:20

called the subthalamic nucleus, and

9:22

it was discovered starting from work in the

9:24

nineteen seventies that you can insert

9:27

your electrode into this area and

9:29

zap it with a bit of electricity and

9:31

you get these amazing effects of the

9:34

movement problems of Parkinson's

9:37

essentially disappearing. And

9:39

by the way, the reason you can stick an electrode

9:41

into the brain is because the brain doesn't

9:43

have any pain receptors, so you

9:45

can just dunk the little metal wire right

9:47

in there after you've opened a little

9:50

portal in the skull. So what's

9:52

happening when you put these little bursts of electricity

9:54

in is that the cells

9:56

fire, which has effects on the rest of the network

9:59

that those cells are connected to, and it also changes

10:02

the electrical oscillations. And why this

10:04

works so well in Parkinson's is still a

10:06

bit of a mystery, but you get what

10:08

you want out of it, and people have been using

10:11

this sort of brain stimulation for all

10:13

kinds of purposes. For example, my

10:15

colleague Helen Mayberg puts electrodes

10:18

directly into a very specific area

10:21

near the singulate gyrus, and she stimulates

10:24

and can pull people out of deep

10:26

clinical depression this way. So

10:28

there are many labs and clinics using

10:30

the technique of stimulating individual

10:33

cells in the brain, and the direction of

10:35

the technology over the past couple of

10:37

decades has been getting

10:39

more and more electrodes implanted,

10:41

so that you're not just hitting one or a

10:43

few cells at the tip of the electrode, but

10:45

you're instead exciting tens

10:48

or hundreds or eventually thousands of cells

10:50

by using a whole specific

10:52

collection of electrodes.

10:55

And companies like Neuralink have become famous

10:57

in the public eye because of the idea

10:59

of sewing these electrodes very

11:02

finely into the brain and getting

11:04

a thousand of them and soon more than that.

11:06

And in all these cases, the electrodes can

11:09

read and write, in other words, they can

11:11

record the activity in the brain cells,

11:13

but they can also stimulate the brain cells

11:16

to put activity in there. So

11:33

once you have the electrodes in there, could

11:35

you just send in the right zaps

11:38

of electricity in just the right pattern,

11:40

spread over millions of neurons with precise

11:43

timing of your patterns in such

11:45

a way that you shape the

11:47

network so that you can

11:49

fly a helicopter. Now, all

11:52

that sounds pretty exciting as a theoretical

11:54

possibility, but I think

11:56

there are two major technical

11:59

hurdles here to be able to stimulate lots

12:01

and lots of cells in the brain in the way

12:03

that you might want to upload

12:06

helicopter instructions. The first is

12:08

simply a physical challenge.

12:11

The brain is very delicate, and

12:13

so Mother Nature has surrounded it

12:16

in the armored plating of the skull.

12:19

So it's very very hard to get at

12:21

this fragile, delicate tissue of

12:23

the brain, and so if you want to insert

12:25

an electrode, you have to actually drill a

12:27

small hole in the skull to expose

12:30

the brain and then you can put your electrode

12:32

in. The difficulty is that

12:34

there are eighty six billion neurons,

12:36

and at the moment, even with our

12:38

fanciest technology, we can only

12:41

get to say a thousand of

12:43

these at any time, and so that

12:46

is useless in terms of actually having

12:48

access to the whole system. It

12:50

would be equivalent to if you really

12:53

wanted to say something to all eight billion

12:55

people on the planet, but you

12:57

only had one hundred followers

13:00

on social media. The huge

13:02

majority of the world will have no idea

13:04

that you've ever said anything, or that you even

13:06

exist. And that's the situation.

13:08

When you zap a few hundred neurons,

13:11

the other tens of billions of neurons

13:13

don't even know that you're knocking on the door.

13:16

So to actually insert information

13:18

into the brain, you'd somehow need to access

13:21

all or at least most of the neurons

13:24

to make any meaningful change.

13:26

Now, I'm not yet addressing how you would

13:29

know what you want to change, where I'll come back to

13:31

that in a moment. Let's just imagine for now

13:33

that you know exactly what you want to tweak

13:35

in the brain. Now, I do think that in

13:37

the future there may be a very

13:40

different solution besides electrodes

13:43

to this issue of manipulating

13:45

the network, because I don't think the idea

13:47

of dunking electrodes in there is ever

13:49

going to be a long term solution.

13:52

When I squint into the future, I think the solution

13:55

is something like nano robots.

13:58

So what are nano robots. The idea is

14:00

that you use atomically

14:03

precise three D printing to

14:05

make little molecular machines

14:07

out of atoms. Essentially, you make little

14:10

robots that carry out some

14:13

functions, so they're like little robots,

14:15

but they're microscopically small,

14:18

built out of individual atoms, by

14:20

the way, which is what proteins are. Anyway,

14:23

you could make these super durable,

14:25

for example by printing them out of carbon,

14:28

making them diamond robots.

14:31

The idea, and this is probably not for

14:33

several decades. The idea is that you

14:36

swallow a pill with tens

14:38

of billions of these little nano robots

14:40

in there, and they float through your

14:42

bloodstream and you give them the right

14:45

FedEx labels to pass the

14:47

blood brain barrier, and once

14:49

they're in there in the brain, they

14:52

wiggle their way into your neurons

14:54

where they can read the activity and they

14:56

can cause the cell to spike

14:59

to fire signal whenever they

15:01

need to. So, with proper

15:04

signaling between the nanobots, using

15:06

for example, mesh networking, you could

15:08

in theory generate whatever

15:11

patterns you needed to across the entire

15:13

brain, and if your science is

15:15

really advanced, then you

15:17

hit the correct brain wide

15:20

patterns that will cement in the

15:22

knowledge of how to fly a

15:24

B two twelve. Now, although

15:26

this is not happening anytime soon,

15:29

it certainly seems plausible that

15:31

this could be in our future. But

15:33

wait, there's actually a

15:36

difficult twist to this story. I

15:38

said before there are two technical

15:40

hurdles, and here comes the second. And

15:42

that hurdle is that there won't

15:45

be a single program

15:48

for flying a B two twelve helicopter. Why

15:51

not, because the brain

15:53

inside each of us is totally

15:55

unique. We each have a massive

15:58

forest of eighty six billion euro on each

16:00

with ten thousand connection

16:03

points reaching out and interacting

16:05

with other trees. And it's a living

16:08

forest such as each connection, every

16:11

twig on every branch finds its

16:13

place in life based on the exact

16:15

details of what you have seen

16:18

and heard and experienced in your

16:21

life. You born in your

16:23

hometown, with your family, your

16:26

neighborhood, your culture, your

16:29

moment in history. All those

16:31

things determine the exact wiring

16:33

of your brain. And your brain has a

16:35

network that is different from his brain over

16:37

there, and her brain over there, and everyone

16:40

else's brain on the planet. And

16:42

the exact wiring is

16:44

what makes you you. So

16:48

in the proposed future of the Matrix,

16:50

the operator Tank would have to specify

16:53

that he wants a program to pilot

16:56

a B two twelve helicopter that

16:58

is specified exact exactly for Trinity's

17:01

brain, that is bespoke for

17:04

her neural network only. And

17:06

if Tank tried to upload the

17:08

same program to Neo's brain

17:11

or Morpheus's brain, who knows

17:13

what that would result in. Because if

17:15

the program alters the way

17:18

that neuron nineteen million, three hundred

17:20

fifty six three hundred and two is talking to its

17:22

neighbors, and it does this over

17:25

a million other neurons with high specificity,

17:28

that might teach Trinity how to

17:30

fly a helicopter, but it certainly would not

17:32

work for someone else whose brain

17:35

is different. So how do we get around that

17:37

problem, the problem of everyone having

17:40

a unique neural network. Well,

17:43

the answer will have to rely on

17:45

what is called system identification.

17:48

This is an engineering approach

17:50

where you have some complicated dynamic

17:53

system and you measure lots

17:56

of input output pairs,

17:58

as in, when I put this in, what

18:01

happens? Okay, now it happens if I put that

18:03

in. So imagine you find a

18:05

really complicated machine and

18:07

you don't know exactly what it does. So you tap

18:09

one of the keys and you see how it

18:12

moves, and then you tap three

18:14

of the keys at the same time, and you look at

18:16

what it does as its output, and then

18:18

you hit a series of the keys and you

18:20

see what results. And you do this

18:22

over and over and over to try to figure

18:24

out what is the structure under

18:27

the hood. This system identification

18:30

approach is used in lots of fields. For example,

18:32

in economics, let's say you want to figure

18:35

out the guts of the stock market.

18:37

So you take lots of inputs like

18:39

gross domestic product and inflation and

18:41

unemployment and interest rates and blah blah blah,

18:44

and you look at all these as inputs

18:46

and you look at the reaction of the market this

18:48

way, and you develop better and better

18:50

mathematical models of what the machinery

18:53

of the stock market is doing, even

18:55

though you can't see it. Okay,

18:57

So the question is, could you do system

19:00

identification on a human

19:03

brain. No one's ever really

19:05

done this because there's no purpose for it now,

19:07

but someday it might make sense.

19:10

So the idea is you go into a super

19:13

futuristic brain scanner and

19:15

you get lots of inputs, and

19:17

this sophisticated brain imaging device

19:20

measures the outputs, in other words, which

19:22

cells in your brain are responding.

19:25

So you see a rapid series

19:27

of images and you hear words,

19:29

and you feel touches on your body, and you smell

19:32

smells, and you run through thousands

19:35

or maybe millions of little micro

19:38

experiences while your brain is getting

19:40

measured. And in theory, this is

19:42

how a scientist could say, Aha,

19:45

Trinity's brain is organized

19:47

like this, while Neo's brain is laid

19:49

out like that, and Morpheus's brain

19:52

has a slightly different pattern, And you

19:54

might find that for teaching

19:56

the operation of a B two

19:58

twelve helicopter, in his brain

20:01

thinks about it in analogy to

20:04

riding a horse and controlling it,

20:06

which let's say she grew up riding horses,

20:08

while Neo's brain would learn

20:11

the helicopter in analogy to

20:13

the way a motorcycle feels, which is, let's say

20:15

how he grew up. And for Morpheus,

20:18

the actions of piloting emerge

20:20

from his deep knowledge of surfing, which

20:22

is how he grew up and what is stored in his brain.

20:25

Now, it's not clear how many inputs

20:27

you'd have to ping in there to get high

20:30

enough resolution to make all the

20:32

little changes you need, but presumably

20:35

that would get figured out with enough experimentation.

20:38

Okay, so let's say we

20:41

as a society grow to

20:43

a point where we can do system

20:46

identification on an individual's

20:48

brain and then use nanobots

20:51

to upload knowledge of

20:53

helicopter piloting. I need to emphasize

20:56

that this is not right around the corner,

20:58

but it certainly seems the theoretically

21:00

plausible. Another century

21:03

of advancement, and suddenly the

21:05

network that makes you can

21:08

get directed and shaped

21:10

in a bespoke manner. And if

21:12

we come to a point where we can do it,

21:15

that's possibly the biggest societal

21:18

change. I can imagine you say

21:20

to your three year old kid, Okay, we're gonna upload

21:22

first grade now. Great, Now, go play

21:24

outside for an hour, and then we're gonna upload

21:26

second grade after lunch. Imagine

21:29

that by the end of the week, your three

21:31

year old knows as much as

21:33

a full professor does. Now, so

21:35

what becomes of society and

21:38

the way we run it now? You may

21:40

think the analogy here is to look at super

21:42

smart, genius kids in our current world,

21:45

But these kids often go

21:47

off to attend college at twelve years old,

21:49

and they very often end up lonely

21:51

and socially misplaced, because really what they

21:53

want is to play with their colleagues other kids

21:56

their age, But they get stuck with a bunch

21:58

of older kids who have gone through puberty

22:01

and are running deeply carved evolutionary

22:04

programs that cause their brains

22:06

to be taken over by sexuality, and

22:08

that software hasn't yet turned on in the

22:10

heads of these young genuses, and as

22:12

a result, they can't mesh with what is

22:14

happening around them, and they can feel very lonely

22:16

in these contexts. But the

22:19

future scenario of uploading knowledge

22:22

is totally different because now every

22:25

single kid can stay among colleagues.

22:28

But the question is if

22:30

education is uploaded, what do the kids

22:33

do all day? Do they launch

22:36

startups at the age of six, do

22:38

they write epic novels by

22:40

the time they're eight years old? Do

22:42

they return to reproducing

22:44

as teenagers like their distant ancestors

22:47

did? And is it dangerous that

22:49

they have all the knowledge

22:51

of decades of schooling but

22:53

without the maturity. The most

22:56

slowly developing part of the brain is the prefrontal

22:58

cortex, and this underlies our ability

23:01

to simulate possible futures

23:03

and think about consequences. So imagine

23:06

a kid with an undeveloped prefederal cortex

23:08

who has all the knowledge that Albert

23:10

Einstein commanded at midlife.

23:13

But this child lacks the ability to simulate

23:16

consequences, so they think something like,

23:18

wouldn't it be hilarious to build a

23:21

small nuclear bomb and blow up my neighbor's

23:23

porch, Or wouldn't it be

23:25

a crackup to disrupt

23:27

the presidential broadcast by

23:30

hijacking the frequency and imposing

23:32

a video of me twerking or

23:34

whatever? Because children

23:36

don't yet have a fully developed

23:39

profederal cortex that can't simulate

23:41

consequences the way an adult can, and

23:44

this is why it could be dangerous

23:46

to inject the knowledge of an adult

23:48

into a child's brain. Now,

24:04

perhaps I'm being shortsighted here, and we

24:06

could somehow upload maturity as

24:08

well. We could figure out

24:11

the learning that translates

24:13

to morally complex situations

24:16

and simulate those over and over do

24:18

the synaptic equivalent of working

24:21

through the possibilities and

24:23

feeling the consequences. Maybe

24:25

you could massively speed up emotional

24:28

learning that way. After all, as my

24:30

father would always tell me, the wise

24:32

person learns from experience,

24:35

but the wiser person learns

24:37

from the experience of others.

24:40

So maybe there could be enough uploaded

24:42

knowledge where a kid understands

24:45

various possible scenarios and outcomes,

24:48

and the good decision making simply results

24:50

from a deep knowledge of previous

24:53

examples, things that have happened to other people,

24:56

all of which have been uploaded.

24:58

So maybe the maturity problem could be taken

25:01

care of, but still we're looking

25:03

at massive societal shifts

25:05

that would render our current civilization

25:09

totally unrecognizable. Now,

25:11

we all like to be very thoughtful about the

25:13

future, but it doesn't matter what

25:16

we speculate about it, because we are guaranteed

25:19

to be wrong. We can only envision

25:21

what we're capable of, in this case, a

25:23

cartoonish version of a bunch

25:26

of super intelligent kids running around while

25:28

their parents go off to their jobs. But

25:30

the world is likely to be very

25:32

different by then. Presuming that

25:34

everything is massively sped up

25:37

by artificial intelligence, it seems

25:39

very possible that society

25:41

is going to evolve exponentially

25:44

faster at a pace that we really

25:46

can't conceive of here in the first

25:49

third of the twenty first century. I mean, just

25:51

imagine that AI knocks

25:54

down scientific problems rapidly,

25:56

such that we move from our current

25:58

state of pretty wide spread ignorance

26:01

to perfect, wonderful

26:03

models of everything in the cosmos.

26:05

Just think about the incredibly

26:08

slow pace between the Stone

26:10

Age and the Bronze Age, and then

26:12

the Bronze Age to the Silver Age.

26:15

Now imagine this pace goes up by a

26:17

thousandfold or a millionfold. So we

26:19

find ourselves a few decades from now

26:22

in the Diamond Age, where we

26:24

can manipulate carbon atoms however we like.

26:27

And then a few years later we're

26:29

past that and into a new era where we

26:31

can entangle photons and

26:33

find ourselves in the quantum age

26:36

and so on. Like everyone, I

26:38

love to speculate about the future, but the truth

26:41

is that it is impossible to

26:43

picture what things will become and how

26:45

quickly. And I want to share an example.

26:48

Last month here in Silicon Valley,

26:50

I saw a black and white photograph

26:53

from nineteen forty. It was a man

26:55

on horseback ambling up

26:58

a dirt road on a hills and

27:00

there was nothing particularly special about

27:02

this sandy hill with its

27:04

scrubbrush. So I was intrigued

27:07

to read the caption and find

27:10

out that this little dirt road was

27:13

sand Hill Road. Now

27:15

you may know that sand Hill Road is nowadays

27:18

a road almost as famous

27:20

as Wall Street in New York. Sand

27:22

Hill Road is where many

27:24

of the world's most elite venture

27:26

capitalists do their business. They

27:29

invest hundreds of billions. This road

27:32

is the mecca for startups

27:34

who are seeking investment. Now,

27:36

the thing that was so striking to me is

27:39

that for the horseman sauntering

27:41

up this sandy hillside in nineteen forty

27:43

in the hot sun, there's no way

27:46

he could have imagined that the

27:49

lonely hoof prints he was leaving

27:51

would in just sixty years mark

27:53

this spot of one of the world's economic

27:56

engines. And there's no way

27:58

he could have envisioned what advances

28:01

would get funded on that spot. The

28:03

worldwide light speed network

28:06

that allows anyone on the planet to

28:08

effortlessly communicate to anyone else,

28:10

or rectangles that everyone

28:13

would carry in their pocket like a

28:15

handkerchief or a tobacco tin. But

28:17

these rectangles would contain the

28:20

accumulated knowledge of all

28:22

humankind. Or satellites

28:25

or quantum computers or blockchain

28:27

cryptocurrencies, or large

28:29

language models that could read every

28:31

book ever written. None of these

28:34

would be even vaguely imaginable

28:37

to the cowboy in nineteen

28:39

forty, moving slowly up

28:41

the hill. We are blind

28:44

to the future. I often wish I could

28:46

talk to whoever is listening to

28:48

this historical podcast

28:50

in the year twenty eighty four, because

28:53

the world will be so different by then,

28:55

and I am incapable of

28:57

imagining it. And it's not just that

29:00

we are not being creative about extrapolating

29:03

technology curves into the future. It's that

29:05

there will be new technologies

29:07

and novel sciences and new

29:10

convergences that will make it

29:12

intrinsically unpredictable.

29:15

There will be serendipitous discoveries

29:17

and socioeconomic changes and geopolitical

29:20

events. While we always make

29:23

guesses based on our current trends and

29:25

research, the future is

29:27

shaped by hundreds of things we just can't

29:29

see. Not only that, but you've heard me

29:32

speak before about our limited

29:34

perspective, our inability

29:36

to see past the fence line of

29:39

what we already know. Our current

29:41

knowledge understanding are based on the technologies

29:43

and paradigms that exist right now, so

29:46

it's really hard for us to anticipate

29:49

breakthroughs or paradigm shifts

29:51

that are going to radically alter our

29:54

society in the future. But this idea

29:56

of putting information directly

29:58

into the brain, that's it certainly

30:00

seems like that could be a big shift. So

30:03

when we think about the future, it's

30:05

more than just adults like us

30:07

riding around on a spaceship with a robot

30:10

or two. Things are guaranteed

30:12

to be weirder than we expect.

30:15

While brain uploads our science fiction

30:17

right now, assuming we don't blow

30:19

ourselves up, this inevitably

30:21

seems like it will become science fact.

30:25

So let's wrap this up. This

30:27

episode is not about what's going to happen

30:29

anytime soon, but I think it is inevitably

30:32

what will happen in the future. After

30:34

all, the brain is made of billions of cells,

30:37

each one of which is very complicated, and

30:39

each is connected in very complicated

30:41

patterns. But fundamentally, learning

30:44

and memory take place in the

30:46

changes of connectivity,

30:48

and as far as we can tell, that's all

30:51

learning is. So what we talked

30:53

about is the way that the jungle

30:55

of neurons in your head is wired up differently

30:57

than in your friend's head because you have

31:00

different genetic predispositions, and more

31:02

importantly, you have different experiences

31:04

in life. So in order to upload

31:07

any changes into your network, we'd

31:09

have to know your brain in exquisitely

31:12

fine detail, and we'd have to know those

31:14

patterns right now, because it's just a

31:16

little bit different than it was yesterday.

31:19

But in theory, if we had this information

31:22

and understood the language of the connections,

31:25

we could dial knobs here and there

31:27

in a million other spots, strengthening

31:30

or weakening synapta connections, tickling

31:32

the genome to express a little more neurotransmit

31:35

or receptor over here, a little less over there,

31:38

and after that you might be able

31:40

to suddenly possess some knowledge

31:44

you didn't have before. Now,

31:47

obviously, society will have to be very

31:49

careful about this technology when that

31:51

century comes, because in theory,

31:53

you could use it to implant

31:56

false memories, or to erase

31:58

knowledge, or to do any number of

32:01

nefarious things. So we will enter

32:03

a very strange time, and like every

32:05

technology, a whole raft

32:08

of protections and legislation

32:10

will grow up around it. Again,

32:12

this is likely impossible to achieve

32:15

in our generation because of the

32:17

size of the problem. It would take

32:19

about a zetabyte of information

32:22

to store the detailed structure

32:24

of one human brain, and that, by the way,

32:26

would only tell you the structure of the forest

32:28

of neurons, but wouldn't even tell you anything

32:31

about their individual details,

32:33

like which genes are getting expressed

32:35

and which proteins are getting put where. So

32:37

for us, the citizens of the

32:40

twenty first century, this is likely

32:42

to be an unsolvably huge

32:44

problem to capture a detailed

32:47

description of an individual

32:49

brain. But as a species,

32:52

we're in an interesting situation because

32:55

we can see that this is all coming,

32:58

and we can speculate on

33:00

the size of the changes this will

33:02

have on society writ large.

33:05

Now, what I find amazing is our guaranteed

33:08

inability to correctly picture

33:10

this future world, even though it

33:12

will be populated by our own great

33:15

grandchildren. Given all this,

33:17

I think the only specific

33:19

prediction we can make is that

33:21

we have more in common with

33:24

our ancestors two million years

33:26

ago than we do with our

33:28

descendants two hundred

33:30

years from now. In

33:36

the meantime, go to eagleman dot com

33:38

slash podcast for more information

33:40

and to find further reading. Send

33:42

me an email at podcast at eagleman

33:44

dot com with questions for discussion,

33:47

and check out and subscribe to Inner Cosmos

33:50

on YouTube for videos of each

33:52

episode and to leave comments.

33:54

Until next time. I'm David Eagleman,

33:56

and this is Inner Cosmos.

34:02

You and not you. You