Ep55 "Could a brain plugin instantly teach you to fly a helicopter?"

Could you instantaneously learn to fly a helicopter -- not by practicing, but instead by uploading instructions directly to your brain? What would society do if children no longer had to go to school? And what does any of this have to do with suntan booths, nanorobots, or what a cowboy on a hill is not able to see? Join Eagleman to learn about the possibility of modifying the microscopic structure of your brain and leapfrogging education. What are the possibilities, the caveats, and the unexpected complexities?

Episode Transcript

Speaker 1 (00:03):
Could you learn to fly a helicopter not by practicing,
but instead by uploading the information directly into your brain?
What would society do if kids no longer had to
go to school? And what does any of this have
to do with suntan booths or nano robots or torking

(00:23):
over a presidential address or what a cowboy on a
hill is simply not able to see. Welcome to Inner
Cosmos with me David Eagleman. I'm a neuroscientist and author
at Stanford and in these episodes we sail deeply into
our three pound universe to understand why and how our

(00:47):
lives look the way they do. Today's episode is about
the potability of really coming to understand the tangled forest
of eighty six billion neurons in your head and the

(01:08):
trillions of connections between them. And if we could do that,
could we upload information directly into your brain? Could we
speed up education this way? Now? At the moment, this
is all pure fantasy because we simply don't have the
technology to allow us to do that. But the question

(01:29):
we're going to ask today is whether this is theoretically
possible and something we can look forward to around the
corner of the next century, and what are the caveats,
the things to watch out for, and the unexpected complexities here.
So let's get started some hundreds of years ago and

(01:49):
still in many impoverished places in the world, children of
the species Homo sapiens reproduce by the time they are
young teens. But this situation is it's totally different in
modern times and modern societies. Now, young people go to
school for their first eighteen years or twenty one years,

(02:10):
and increasingly twenty five or twenty six years for an
advanced degree, and in fields like medicine, they take another
several years of internship and residency. And in a field
like neuroscience research people do a postdoctoral fellowship and then
they hope to become an assistant professor, and then an
associate professor and finally a full professor. And most people

(02:34):
are in their forties by the time they get there.
So what accounts for this recent historical change. Why do
we do so much schooling for so much of our
lives now? Well, it's because we are a runaway species.
We've gone off in a totally different direction than all
our animal cousins, and we have made thousands of important

(02:56):
discoveries about our world and produced so much art invarious forms,
And as a result, there's so much to learn, and
so we need to spend decades in institutions of learning,
not to mention, reading books and listening to podcasts to
understand what millions of humans have devoted their lives to

(03:19):
figuring out. But what if there were a way that
we didn't have to do that? What if there were
a way to simply upload the information, in other words,
to put the information directly into your brain. So let's
harken back to this great scene in The Matrix where
Neo and Trinity are being hotly pursued by the antagonist,

(03:42):
agent Smith, and our two heroes end up on top
of a building, and there they spy a helicopter parked
on the roof, and Neo asks Trinity do you know
how to fly that? And she replies not yet, And
she flips open her phone and she calls Tank, the operator,
and she says, I need a pilot program for a

(04:03):
B two twelve helicopter, And we see the operator rotate
his chair in front of his bank of computers and
he quickly types out a bunch of commands, and she
closes her eyes and one second later she turns confidently
to Neo and says, let's go. So what happened is
that Tank the operator had taken the expertise, the complicated

(04:26):
know how of flying a B two twelve helicopter and
just uploaded it to her brain. So the question we're
going to ask today is is that theoretically possible from
a neuroscience perspective, and what will make that straightforward? And
what will make that not straightforward to accomplish someday. Now,

(04:46):
in some ways, the whole idea sounds crazy because it
seems like we always have to earn things if we
want changes to our brains or body. You can't just
get something for free. But of course, people for decades
have been climbing in into suntan booths instead of spending
days outside, and people get botox, which binds to receptors
the ends of peripheral nerves and changes the wrinkliness of

(05:09):
your face. And people are increasingly doing things to not
have to go to the gym but instead to have
your abdominal muscles built for you with electrical stimulation. You
just lie on the table and your muscles contract over
and over and The idea is that your muscles can
grow stronger and look better without you having to do

(05:30):
a single sit up. You just lie there. So what
would be the equivalent in the realm of education? Can
we imagine a time when you don't have to bury
yourself in a book to master some domain, where you
don't have to spend hundreds of hours sitting in a
flight simulator, but instead you hook something up to your
brain and then it is as though you already knew

(05:53):
quantum mechanics or electrical engineering, or Persian history, or how
to serve for hang glide or repair that model of
dishwasher or whatever. Now, how would you push information to
the brain? We currently do this by sitting down dozens
of children in front of someone who already has the

(06:13):
information in their brain, and that person uses words or pictures,
and the students attend to those stimuli and try to
translate those words or pictures into changes in their own
private jungle of billions of neurons. They try to convert
what they're hearing or seeing into storage in their own

(06:34):
internal model in a way that makes sense to them.
What learning means is that you very finely change the
networks in your head. That's it. That's what we pay
lots of tuition for and go off to college for
to get someone who already has information in their network
to translate it through the low bandwidth channel of language

(06:56):
over to your network. So, just to be clear on this,
before you know some factor concept, your network is configured
in some way, and then I tell you, oh, that
dog's name is Nebula, and then you encode that information.
This connection in your brain gets strengthened and this one
gets weakened, and this synapse unplugs, it replugs over there,

(07:17):
and this happens over millions of synapses, and then you
know something that you did not know before. And for
deeper knowledge, like flying a B two twelve helicopter, this
requires not just the memory of a fact, but of
a procedure. And so those changes happen in different brain
areas and they're more widespread. But what is required in

(07:40):
all these forms of learning are simply changes in the
patterns of your network, presumably just the synaptic connections, but
maybe other details as well, like which neurotransmitter receptors are
being expressed on the membranes and whatever. But that's it,
that's what it means. To learn something. So is there

(08:01):
any way to implement those changes besides the old fashioned
way of sitting for a semester in a classroom or
spending hours in the helicopter flight simulator. Well, there's been
a lot of excitement about brain machine interfaces, such as
the brain electrodes that are implanted robotically by the company Neurallink.

(08:23):
So I'll just take a quick moment to clarify the
landscape of electrodes in the brain. Even though neuralink hit
the news recently. The first thing to note is that
these brain machine interfaces have been around for many decades
since people started inserting electrodes. These are just thin metal
wires into the brain. The idea is that you just

(08:45):
insert this electrode into the neural tissue and you listen
to the electrical activity of the cells. And researchers pretty
quickly figured out that if you send a little bit
of electricity down the wire down this electrode, you can
stimulate the cell to make it active where it pops
off its own little electrical spikes that travel around. So

(09:07):
you put in some electricity and it goes And this
is the technology behind, for example, deep brain stimulation you
might have heard of this. Take Parkinson's disease. There's a
tiny brain region called the subthalamic nucleus, and it was
discovered starting from work in the nineteen seventies that you
can insert your electrode into this area and zap it

(09:29):
with a bit of electricity and you get these amazing
effects of the movement problems of Parkinson's essentially disappearing. And
by the way, the reason you can stick an electrode
into the brain is because the brain doesn't have any
pain receptors, so you can just dunk the little metal
wire right in there after you've opened a little portal

(09:50):
in the skull. So what's happening when you put these
little bursts of electricity in is that the cells fire,
which has effects on the rest of the network that
those cells are connected to, and it also changes the
electrical oscillations. And why this works so well in Parkinson's
is still a bit of a mystery, but you get
what you want out of it, and people have been

(10:10):
using this sort of brain stimulation for all kinds of purposes.
For example, my colleague Helen Mayberg puts electrodes directly into
a very specific area near the singulate gyrus, and she
stimulates and can pull people out of deep clinical depression
this way. So there are many labs and clinics using
the technique of stimulating individual cells in the brain, and

(10:34):
the direction of the technology over the past couple of
decades has been getting more and more electrodes implanted, so
that you're not just hitting one or a few cells
at the tip of the electrode, but you're instead exciting
tens or hundreds or eventually thousands of cells by using
a whole specific collection of electrodes. And companies like Neuralink

(10:56):
have become famous in the public eye because of the
idea of sewing these electrodes very finely into the brain
and getting a thousand of them and soon more than that.
And in all these cases, the electrodes can read and write,
in other words, they can record the activity in the
brain cells, but they can also stimulate the brain cells
to put activity in there. So once you have the

(11:34):
electrodes in there, could you just send in the right
zaps of electricity in just the right pattern, spread over
millions of neurons with precise timing of your patterns in
such a way that you shape the network so that
you can fly a helicopter. Now, all that sounds pretty
exciting as a theoretical possibility, but I think there are

(11:57):
two major technical hurdles here to be able to stimulate
lots and lots of cells in the brain in the
way that you might want to upload helicopter instructions. The
first is simply a physical challenge. The brain is very delicate,
and so Mother Nature has surrounded it in the armored
plating of the skull. So it's very very hard to

(12:20):
get at this fragile, delicate tissue of the brain, and
so if you want to insert an electrode, you have
to actually drill a small hole in the skull to
expose the brain and then you can put your electrode in.
The difficulty is that there are eighty six billion neurons,
and at the moment, even with our fanciest technology, we

(12:40):
can only get to say a thousand of these at
any time, and so that is useless in terms of
actually having access to the whole system. It would be
equivalent to if you really wanted to say something to
all eight billion people on the planet, but you only
had one hundred followers on social media. The huge majority

(13:02):
of the world will have no idea that you've ever
said anything, or that you even exist. And that's the situation.
When you zap a few hundred neurons, the other tens
of billions of neurons don't even know that you're knocking
on the door. So to actually insert information into the brain,
you'd somehow need to access all or at least most

(13:23):
of the neurons to make any meaningful change. Now, I'm
not yet addressing how you would know what you want
to change, where I'll come back to that in a moment.
Let's just imagine for now that you know exactly what
you want to tweak in the brain. Now, I do
think that in the future there may be a very
different solution besides electrodes to this issue of manipulating the network,

(13:45):
because I don't think the idea of dunking electrodes in
there is ever going to be a long term solution.
When I squint into the future, I think the solution
is something like nano robots. So what are nano robots.
The idea is that you use atomically precise three D
printing to make little molecular machines out of atoms. Essentially,

(14:09):
you make little robots that carry out some functions, so
they're like little robots, but they're microscopically small, built out
of individual atoms, by the way, which is what proteins are. Anyway,
you could make these super durable, for example by printing
them out of carbon, making them diamond robots. The idea,

(14:32):
and this is probably not for several decades. The idea
is that you swallow a pill with tens of billions
of these little nano robots in there, and they float
through your bloodstream and you give them the right FedEx
labels to pass the blood brain barrier, and once they're
in there in the brain, they wiggle their way into

(14:53):
your neurons where they can read the activity and they
can cause the cell to spike to fire signal whenever
they need to. So, with proper signaling between the nanobots,
using for example, mesh networking, you could in theory generate
whatever patterns you needed to across the entire brain, and

(15:14):
if your science is really advanced, then you hit the
correct brain wide patterns that will cement in the knowledge
of how to fly a B two twelve. Now, although
this is not happening anytime soon, it certainly seems plausible
that this could be in our future. But wait, there's
actually a difficult twist to this story. I said before

(15:38):
there are two technical hurdles, and here comes the second.
And that hurdle is that there won't be a single
program for flying a B two twelve helicopter. Why not,
because the brain inside each of us is totally unique.
We each have a massive forest of eighty six billion

(15:59):
euro on each with ten thousand connection points reaching out
and interacting with other trees. And it's a living forest
such as each connection, every twig on every branch finds
its place in life based on the exact details of
what you have seen and heard and experienced in your life.

(16:22):
You born in your hometown, with your family, your neighborhood,
your culture, your moment in history. All those things determine
the exact wiring of your brain. And your brain has
a network that is different from his brain over there,
and her brain over there, and everyone else's brain on
the planet. And the exact wiring is what makes you you.

(16:47):
So in the proposed future of the Matrix, the operator
Tank would have to specify that he wants a program
to pilot a B two twelve helicopter that is specified
exact exactly for Trinity's brain, that is bespoke for her
neural network only. And if Tank tried to upload the

(17:08):
same program to Neo's brain or Morpheus's brain, who knows
what that would result in. Because if the program alters
the way that neuron nineteen million, three hundred fifty six
three hundred and two is talking to its neighbors, and
it does this over a million other neurons with high specificity,
that might teach Trinity how to fly a helicopter, but

(17:31):
it certainly would not work for someone else whose brain
is different. So how do we get around that problem,
the problem of everyone having a unique neural network. Well,
the answer will have to rely on what is called
system identification. This is an engineering approach where you have
some complicated dynamic system and you measure lots of input

(17:57):
output pairs, as in, when I put this in, what happens? Okay,
now it happens if I put that in. So imagine
you find a really complicated machine and you don't know
exactly what it does. So you tap one of the
keys and you see how it moves, and then you
tap three of the keys at the same time, and
you look at what it does as its output, and

(18:18):
then you hit a series of the keys and you
see what results. And you do this over and over
and over to try to figure out what is the
structure under the hood. This system identification approach is used
in lots of fields. For example, in economics, let's say
you want to figure out the guts of the stock market.
So you take lots of inputs like gross domestic product

(18:40):
and inflation and unemployment and interest rates and blah blah blah,
and you look at all these as inputs and you
look at the reaction of the market this way, and
you develop better and better mathematical models of what the
machinery of the stock market is doing, even though you
can't see it. Okay, So the question is, could you
do system identification on a human brain. No one's ever

(19:04):
really done this because there's no purpose for it now,
but someday it might make sense. So the idea is
you go into a super futuristic brain scanner and you
get lots of inputs, and this sophisticated brain imaging device
measures the outputs, in other words, which cells in your
brain are responding. So you see a rapid series of

(19:28):
images and you hear words, and you feel touches on
your body, and you smell smells, and you run through
thousands or maybe millions of little micro experiences while your
brain is getting measured. And in theory, this is how
a scientist could say, Aha, Trinity's brain is organized like this,
while Neo's brain is laid out like that, and Morpheus's

(19:51):
brain has a slightly different pattern, And you might find
that for teaching the operation of a B two twelve helicopter,
in his brain thinks about it in analogy to riding
a horse and controlling it, which let's say she grew
up riding horses, while Neo's brain would learn the helicopter

(20:11):
in analogy to the way a motorcycle feels, which is,
let's say how he grew up. And for Morpheus, the
actions of piloting emerge from his deep knowledge of surfing,
which is how he grew up and what is stored
in his brain. Now, it's not clear how many inputs
you'd have to ping in there to get high enough
resolution to make all the little changes you need, but

(20:34):
presumably that would get figured out with enough experimentation. Okay,
so let's say we as a society grow to a
point where we can do system identification on an individual's
brain and then use nanobots to upload knowledge of helicopter piloting.

(20:55):
I need to emphasize that this is not right around
the corner, but it certainly seems the theoretically plausible. Another
century of advancement, and suddenly the network that makes you
can get directed and shaped in a bespoke manner. And
if we come to a point where we can do it,
that's possibly the biggest societal change. I can imagine you

(21:20):
say to your three year old kid, Okay, we're gonna
upload first grade now. Great, Now, go play outside for
an hour, and then we're gonna upload second grade after lunch.
Imagine that by the end of the week, your three
year old knows as much as a full professor does. Now,
so what becomes of society and the way we run
it now? You may think the analogy here is to

(21:41):
look at super smart, genius kids in our current world,
But these kids often go off to attend college at
twelve years old, and they very often end up lonely
and socially misplaced, because really what they want is to
play with their colleagues other kids their age, But they
get stuck with a bunch of older kids who have
gone through puberty and are running deeply carved evolutionary programs

(22:04):
that cause their brains to be taken over by sexuality,
and that software hasn't yet turned on in the heads
of these young genuses, and as a result, they can't
mesh with what is happening around them, and they can
feel very lonely in these contexts. But the future scenario
of uploading knowledge is totally different because now every single

(22:25):
kid can stay among colleagues. But the question is if
education is uploaded, what do the kids do all day?
Do they launch startups at the age of six, do
they write epic novels by the time they're eight years old?
Do they return to reproducing as teenagers like their distant

(22:46):
ancestors did? And is it dangerous that they have all
the knowledge of decades of schooling but without the maturity.
The most slowly developing part of the brain is the
prefrontal cortex, and this underlies our ability to simulate possible
futures and think about consequences. So imagine a kid with
an undeveloped prefederal cortex who has all the knowledge that

(23:10):
Albert Einstein commanded at midlife. But this child lacks the
ability to simulate consequences, so they think something like, wouldn't
it be hilarious to build a small nuclear bomb and
blow up my neighbor's porch, Or wouldn't it be a
crackup to disrupt the presidential broadcast by hijacking the frequency

(23:31):
and imposing a video of me twerking or whatever? Because
children don't yet have a fully developed profederal cortex that
can't simulate consequences the way an adult can, and this
is why it could be dangerous to inject the knowledge
of an adult into a child's brain. Now, perhaps I'm

(24:04):
being shortsighted here, and we could somehow upload maturity as well.
We could figure out the learning that translates to morally
complex situations and simulate those over and over do the
synaptic equivalent of working through the possibilities and feeling the consequences.

(24:25):
Maybe you could massively speed up emotional learning that way.
After all, as my father would always tell me, the
wise person learns from experience, but the wiser person learns
from the experience of others. So maybe there could be
enough uploaded knowledge where a kid understands various possible scenarios

(24:47):
and outcomes, and the good decision making simply results from
a deep knowledge of previous examples, things that have happened
to other people, all of which have been uploaded. So
maybe the maturity problem could be taken care of, but
still we're looking at massive societal shifts that would render
our current civilization totally unrecognizable. Now, we all like to

(25:12):
be very thoughtful about the future, but it doesn't matter
what we speculate about it, because we are guaranteed to
be wrong. We can only envision what we're capable of,
in this case, a cartoonish version of a bunch of
super intelligent kids running around while their parents go off
to their jobs. But the world is likely to be

(25:32):
very different by then. Presuming that everything is massively sped
up by artificial intelligence, it seems very possible that society
is going to evolve exponentially faster at a pace that
we really can't conceive of here in the first third
of the twenty first century. I mean, just imagine that
AI knocks down scientific problems rapidly, such that we move

(25:57):
from our current state of pretty wide spread ignorance to perfect,
wonderful models of everything in the cosmos. Just think about
the incredibly slow pace between the Stone Age and the
Bronze Age, and then the Bronze Age to the Silver Age.
Now imagine this pace goes up by a thousandfold or

(26:18):
a millionfold. So we find ourselves a few decades from
now in the Diamond Age, where we can manipulate carbon
atoms however we like. And then a few years later
we're past that and into a new era where we
can entangle photons and find ourselves in the quantum age
and so on. Like everyone, I love to speculate about

(26:39):
the future, but the truth is that it is impossible
to picture what things will become and how quickly. And
I want to share an example. Last month here in
Silicon Valley, I saw a black and white photograph from
nineteen forty. It was a man on horseback ambling up
a dirt road on a hills and there was nothing

(27:01):
particularly special about this sandy hill with its scrubbrush. So
I was intrigued to read the caption and find out
that this little dirt road was sand Hill Road. Now
you may know that sand Hill Road is nowadays a
road almost as famous as Wall Street in New York.

(27:22):
Sand Hill Road is where many of the world's most
elite venture capitalists do their business. They invest hundreds of billions.
This road is the mecca for startups who are seeking investment. Now,
the thing that was so striking to me is that
for the horseman sauntering up this sandy hillside in nineteen

(27:43):
forty in the hot sun, there's no way he could
have imagined that the lonely hoof prints he was leaving
would in just sixty years mark this spot of one
of the world's economic engines. And there's no way he
could have envisioned what advances would get funded on that spot.
The worldwide light speed network that allows anyone on the

(28:07):
planet to effortlessly communicate to anyone else, or rectangles that
everyone would carry in their pocket like a handkerchief or
a tobacco tin. But these rectangles would contain the accumulated
knowledge of all humankind. Or satellites or quantum computers or
blockchain cryptocurrencies, or large language models that could read every

(28:31):
book ever written. None of these would be even vaguely
imaginable to the cowboy in nineteen forty, moving slowly up
the hill. We are blind to the future. I often
wish I could talk to whoever is listening to this
historical podcast in the year twenty eighty four, because the

(28:53):
world will be so different by then, and I am
incapable of imagining it. And it's not just that we
are not being creative about extrapolating technology curves into the future.
It's that there will be new technologies and novel sciences
and new convergences that will make it intrinsically unpredictable. There

(29:15):
will be serendipitous discoveries and socioeconomic changes and geopolitical events.
While we always make guesses based on our current trends
and research, the future is shaped by hundreds of things
we just can't see. Not only that, but you've heard
me speak before about our limited perspective, our inability to

(29:37):
see past the fence line of what we already know.
Our current knowledge understanding are based on the technologies and
paradigms that exist right now, so it's really hard for
us to anticipate breakthroughs or paradigm shifts that are going
to radically alter our society in the future. But this
idea of putting information directly into the brain, that's it

(30:00):
certainly seems like that could be a big shift. So
when we think about the future, it's more than just
adults like us riding around on a spaceship with a
robot or two. Things are guaranteed to be weirder than
we expect. While brain uploads our science fiction right now,
assuming we don't blow ourselves up, this inevitably seems like

(30:22):
it will become science fact. So let's wrap this up.
This episode is not about what's going to happen anytime soon,
but I think it is inevitably what will happen in
the future. After all, the brain is made of billions
of cells, each one of which is very complicated, and
each is connected in very complicated patterns. But fundamentally, learning

(30:44):
and memory take place in the changes of connectivity, and
as far as we can tell, that's all learning is.
So what we talked about is the way that the
jungle of neurons in your head is wired up differently
than in your friend's head because you have different genetic predispositions,
and more importantly, you have different experiences in life. So

(31:05):
in order to upload any changes into your network, we'd
have to know your brain in exquisitely fine detail, and
we'd have to know those patterns right now, because it's
just a little bit different than it was yesterday. But
in theory, if we had this information and understood the
language of the connections, we could dial knobs here and

(31:27):
there in a million other spots, strengthening or weakening synapta connections,
tickling the genome to express a little more neurotransmit or
receptor over here, a little less over there, and after
that you might be able to suddenly possess some knowledge
you didn't have before. Now, obviously, society will have to

(31:48):
be very careful about this technology when that century comes,
because in theory, you could use it to implant false memories,
or to erase knowledge, or to do any number of
nefarious things. So we will enter a very strange time,
and like every technology, a whole raft of protections and

(32:09):
legislation will grow up around it. Again, this is likely
impossible to achieve in our generation because of the size
of the problem. It would take about a zetabyte of
information to store the detailed structure of one human brain,
and that, by the way, would only tell you the
structure of the forest of neurons, but wouldn't even tell

(32:30):
you anything about their individual details, like which genes are
getting expressed and which proteins are getting put where. So
for us, the citizens of the twenty first century, this
is likely to be an unsolvably huge problem to capture
a detailed description of an individual brain. But as a species,

(32:52):
we're in an interesting situation because we can see that
this is all coming, and we can speculate on the
size of the changes this will have on society writ large. Now,
what I find amazing is our guaranteed inability to correctly
picture this future world, even though it will be populated

(33:13):
by our own great grandchildren. Given all this, I think
the only specific prediction we can make is that we
have more in common with our ancestors two million years
ago than we do with our descendants two hundred years
from now. In the meantime, go to eagleman dot com

(33:38):
slash podcast for more information and to find further reading.
Send me an email at podcast at eagleman dot com
with questions for discussion, and check out and subscribe to
Inner Cosmos on YouTube for videos of each episode and
to leave comments. Until next time. I'm David Eagleman, and
this is Inner Cosmos. You and not you. You