00:00:00
After many many decades of people debating this, you might have figured out the reason why we dream. Yes. And
00:00:05
it's a simple answer. So if you go blind, the visual cortex in the back of the brain gets taken over by hearing and
00:00:12
by touch and by other things. In fact, our colleagues at Harvard did an experiment where they blindfolded
00:00:16
normally cighted people. And you could start seeing that takeover happening after 60 minutes. And that's when we
00:00:21
realized, wow, the purpose of dreaming is to defend the visual territory from takeover from the other senses. But what
00:00:29
fascinates me about brain plasticity and what I've devoted my career to is figuring out the way that we can be the
00:00:34
sculptors of our own brains and how it gives us an opportunity to become the kind of person we would like to be.
00:00:40
>> And can we do that? >> Yes. Here's the thing. Your brain peaked
00:00:44
at the age of two. Okay. So at the beginning you've got fluid intelligence, meaning you could learn anything. But
00:00:50
now that you have grown up in this world, you've got crystallized intelligence, meaning you know how to
00:00:55
drive a car. You know how to operate a cell phone. You know how to run a business. And so your brain doesn't
00:00:59
require as much change which means that the structure of the brain is always degenerating.
00:01:05
>> So what are the set of actions that will fundamentally change my brain and make
00:01:08
me that type of person who's motivated and disciplines and who has high agency
00:01:12
and attacks the world. >> So this is something I've studied in my lab for decades now. And the key is that
00:01:18
>> and what about AI and the social media debate as it relates to brain development?
00:01:22
>> Well, I happen to be a cyber optimist for young people. I think it's going to
00:01:26
make them much smarter than the generation that came before. And here's why.
00:01:31
>> Interesting. This is super interesting to me. My team given me this report to show me how many
00:01:36
of you that watch this show subscribe. And some of you have told us according to this that you are unsubscribed from
00:01:41
the channel randomly. So, favor to ask all of you, please could you check right now if you've hit the subscribe button
00:01:46
if you are a regular viewer of the show and you like what we do here. We're approaching quite a significant landmark
00:01:50
on this show in terms of a subscriber number. So, if there was one simple free thing that you could do to help us, my
00:01:56
team, everyone here, to keep this show free, to keep it improving year over year and week over week, it is just to
00:02:02
hit that subscribe button and to double check if you've hit it. Only thing I'll
00:02:05
ever ask of you, do we have a deal? If you do it, I'll tell you what I'll do.
00:02:08
I'll make sure every single week, every single month, as we fight harder and
00:02:12
harder and harder and harder to bring you the guests and conversations that you want to hear, I've stayed true to
00:02:16
that promise since the very beginning of the D of Sio, and I will not let you down. Please help us. Really appreciate
00:02:22
it. Let's get on with the show. Dr. David Eagleman, what made you so fascinated about the brain? And why
00:02:35
should everybody listening be fascinated about the brain as well? Here's what I
00:02:38
think it is. When I was 8 years old, I fell off of the roof of a house that was under construction and I fell 12 feet
00:02:45
and broke my nose on the floor below. But the whole thing seemed to take a long time. I did the calculation and
00:02:52
figured out that it only took 6 of a second to get from the top to the bottom. And I couldn't figure out why it
00:02:57
seemed to have taken so long. So I think that got me really interested in perception and the machinery by which we
00:03:05
view the world and taken in and what is actually real versus what's a construction of the brain. And that's
00:03:12
how what I've devoted my career to is figuring out how the brain which is locked inside the skull. It's about
00:03:18
three pounds. How it constructs this model of the world and which things we can take as reality and which things we
00:03:25
shouldn't. >> I think most people don't even know they have a there's a brain there almost. It
00:03:29
sounds like a strange thing to say, but we've never really most of us haven't
00:03:32
really seen our own brains at all. We've never been able to touch our own brains
00:03:35
at all. So, it's it's easy to fall into the trap of thinking that everything I
00:03:40
experience is true and is reality. So, I'm wondering how a deeper understanding
00:03:45
of all this stuff can help me live a better life. >> Yeah. One of the things that I started
00:03:50
writing about years ago is that I think we're not I think we often think of ourselves as individuals, meaning not
00:03:57
divisible into other things. But really, you are a team of rivals. So, you've got
00:04:04
all these neural networks that have different drives making different suggestions to you.
00:04:08
>> What's a neural network? >> Um, so in the brain, you've got 86
00:04:12
billion cells called neurons. And these are communicating with each other at a blindingly fast rate. Many of these
00:04:18
cells are hooked up in networks. So, they're, you know, this guy's talking to
00:04:22
this guy and this guy, and they're all in particular networks. The thing is,
00:04:25
you can actually get competing networks. So, for example, Stephen, if I drop some
00:04:31
chocolate chip cookies in front of you, part of your brain wants to eat it. It's
00:04:34
a good energy source. Part of your brain says, "Don't eat it. I'll gain weight."
00:04:37
Part of you says, "Okay, I'll eat one, but I'll go to the gym tonight." The
00:04:40
point is you are arguing with yourself. You are conflicted. This is what makes humans so interesting is that we have
00:04:49
all these voices trying to drive us to different conclusions about our behavior.
00:04:54
The way that your ship of state moves depends on the vote of the neural parliament at any time. So understanding
00:05:02
this I think is really critical to navigating our own lives because all of us do things where retrospectively we
00:05:08
regret it. We say I shouldn't have eaten that whole bag of chips or done the you
00:05:13
know the alcohol or the drugs or what like everybody has regrets all the time with things and it's because you have
00:05:20
different voices in charge at different times. Okay. >> Part of what this leads to is what we
00:05:26
call the Ulisses contract. So a Ulisses contract is where you do something now to prevent yourself from behaving badly
00:05:33
in the near future. Just as an example, you know, when people go to Alcoholics Anonymous, the first thing they're told
00:05:39
is clear all the alcohol out of the house. Because even if you feel like, look, >> I'm in a moment of sober reflection. I
00:05:46
don't want to ever drink again. If you have alcohol in the house, you're going
00:05:48
to bust into that cabinet at some point on a festive Saturday night or a lonely Sunday night or whatever. So, what you
00:05:55
do is you constrain your future behavior by setting things up in the right way so
00:06:01
your future uh the future you can't behave badly. We naively think, okay, well, I know who I am. I'm just one
00:06:08
person. But but you're not. And under different circumstances, you're tempted
00:06:12
by different things and you'll do different kinds of behavior. So having a sense of what's going on under the hood
00:06:18
gives us an opportunity to be more closely aligned with the kind of person we would like to be
00:06:24
>> because it feels like there's just one well I do argue with myself in my head
00:06:28
sometimes but it feels like there is just one me >> and so when I hear that voice say Steve
00:06:34
you should have that cookie and it's 1:00 a.m. And then the other voice says,
00:06:36
"No, you shouldn't." I think it's kind of the same person just tussling with
00:06:40
himself, >> right? Well, but that tustling with himself implies different political
00:06:44
parties that are all battling it out. You know, when you look at a parliament, you've got all these political parties
00:06:49
that all love their country. They just have different ideas of how to steer it. And this is what's going on uh in in the
00:06:56
brain all the time. >> So, what does one do about that? How do I make do I do I have to make a list
00:07:01
contract? I think it's very useful to make that sort of thing. But also just
00:07:05
understanding oneself. I mean part of the you know there was this Greek admonition to know thyself. This was a
00:07:11
sign they had in various places, various temples and stuff. But I think that becomes know thyelves. And the better we
00:07:19
know ourselves, the more we can get rid of the illusion that we are one person. Because all any of us need to do is look
00:07:25
back on our behavior to say, "Oh yeah, in some circumstances I would do that.
00:07:29
and other circumstances I think is a terrible idea. So this is all to the goal of understanding who you are.
00:07:36
>> What are the big misconceptions about the brain that people have gone through
00:07:40
their life believing? I mean that's one of them. Something that is true that
00:07:42
kind of could fall in place of that is just this fundamental idea that our brains are plastic or sort of adaptable
00:07:50
because when I found out that I could change my brain by what I do, I found that to be really really inspiring.
00:07:56
>> Yes, that that's exactly right. So brain plasticity, if someone hasn't heard that
00:08:00
term before, it sounds like a weird term, but the reason it came about 100 years ago is because the great
00:08:06
psychologist William James pointed out that, you know, if you take a piece of plastic, what we like about that
00:08:10
material that we call plastic is that you can mold it into a shape and it'll
00:08:14
hold that shape. And that's what your brain does. So if I ask you the name of
00:08:18
your third grade teacher, you can remember that name even though it's been a long time because your neural networks
00:08:25
changed and held on to that piece of information. Okay? Well, our whole lives our brains are changing every moment. So
00:08:33
now we have certain doors that close at different times. So just as an example, um you need to learn language in the
00:08:41
first several years of your life. If you don't learn language, you can never get
00:08:45
the concept of language. Your brain will never figure that out. >> You're not saying you can't learn a new
00:08:49
language as an adult. You're saying the concept of >> the concept of language, the concept
00:08:53
that I can name things and I can ask for things and so on. Just that never clicks
00:08:57
in the brain. For example, in Romania at the fall of Chuchescu, there were tens of thousands of kids in the orphanages
00:09:05
because their parents had been killed. It was too many kids. And so the staff there said, "Look, the kids will get,
00:09:11
you know, clingy if you pay too much attention to them. So here's what we're
00:09:14
going to do. We're going to feed the kids, but we're not going to hold them
00:09:16
and we're not going to talk to them." And all these children grew up with real
00:09:20
cognitive deficits as a result. Here's the thing about brain plasticity. Human
00:09:25
beings have a a similar brain to all our neighbors in the animal kingdom. If you
00:09:30
compare our brain to a horse brain, a dog brain, anything like that, it's the
00:09:33
same general structures and stuff. But what we have is much more of the wrinkly outer bit called the cortex. It's the
00:09:40
outer 3 mm. And maybe we'll come back to why that matters so much. But the other
00:09:46
thing that mother nature tweaked with us, it's small genetic tweaks. But we have much more plasticity, adaptability
00:09:53
such that when a horse drops into the world, it's doing the same thing that horses did 100,000 years ago. It's just,
00:09:59
you know, eat mate. But when a human drops in the world, we learn everything that's happened before us. And then we
00:10:06
springboard off the top of that. So we living in the 21st century, we say, "Oh
00:10:11
great, you know, physics, math, this, that, art, blah, blah, great. We got everything that's happened before us.
00:10:15
Now let's do our own thing." And that's what's so special about the plasticity
00:10:19
of the human brain, the adaptability of it. The downside, the gamble is that mother nature drops human brains into
00:10:28
the world kind of halfbaked and we then get to absorb everything. But in the rare circumstance where you're not
00:10:34
getting the right input, then then that ends up really in trouble because it's
00:10:39
only halfbaked. So when it comes to language, we can learn multiple languages when we're young. That's very
00:10:44
easy, but it gets harder and harder as that goes along. And various other things become harder. And here's why.
00:10:50
It's because I I mentioned this earlier, but the job of the brain is to make a
00:10:55
model of the world so it can operate within it. So, for example, you're an entrepreneur and you love doing
00:11:02
business. So, you get it. You okay, here's how, you know, here's how you
00:11:06
structure business. Here's how you hire. Well, here's how you set up a board.
00:11:09
Well, you're doing everything because you've got a really rich internal model
00:11:13
of how to structure a business. That's what the brain wants to do is get that
00:11:18
stuff right. As a result, if you suddenly ended up, you know, taking a trip to Mars and there's a whole very
00:11:25
different society there that does businesses very differently, you would have to relearn stuff really quickly.
00:11:32
So, here's the thing. You went from having a brain that had high fluid intelligence to now having a brain that
00:11:40
has high crystallized intelligence. What that means is at the beginning you can learn anything. You could learn any
00:11:46
language. You could have dropped into any area. You could have dropped into 13th century Japan when I was young.
00:11:51
>> When you were young, when you were a baby, if you had dropped out of the womb
00:11:54
in, you know, 10th century Mongolia, you would have said like, "Okay, cool. Learn
00:11:59
lang." You would you would be a 10th century Mongolian. But as it happens, you dropped into this era, you know, a
00:12:06
certain place and time and neighborhood and culture and family. And so you learn
00:12:09
that that's who you become is that person. We often think that plasticity diminishes as you age. But it's not
00:12:17
simply that it's diminishing. It's that you are getting the right answers about
00:12:22
how to operate in the world. And so you don't have to change as much. Your brain
00:12:26
doesn't require as much change. >> What if I want to change? >> Yes. So it turns out you still can
00:12:32
change. That's the key is that the reason brains change less and less is because they don't have to. But when
00:12:40
things get upside down, just as one example, everything about the pandemic really stunk, except for one thing, I
00:12:47
think the tiny silver lining is that all of us had to reassess. Oh my gosh, wait,
00:12:54
how is the world working? I thought I knew how the world worked, but now I don't know if there's going to be toilet
00:12:59
paper at the store. I don't know if the bank's going to be open. I don't know if
00:13:02
I can get coffee at the coffee shop. Like, everything was different. As awful as it was, it's really useful to
00:13:09
challenge your internal model of the world and get to do that as an adult. We don't usually get to.
00:13:15
>> So, if I want to change, what would you recommend that I do? If I want to if I
00:13:18
want to change who I am, say I'm stubborn, I'm not motivated, >> um, and I want to be a different person.
00:13:24
>> The key is challenge. The key is seeking challenge. So, it turns out that where
00:13:28
we always want to be is in between the levels of frustrating but achievable. and you want to take on new tasks. You
00:13:35
want to seek novelty to find yourself in that zone and push yourself to do things
00:13:40
that you just haven't done before. And one of the things that's so wonderful
00:13:44
about the modern world, you know, everyone's got complaints about the internet and social media and stuff like
00:13:48
that, but the good news is it deep it exposes you to so much more than you ever even knew was out there. The key is
00:13:56
to actively seek those challenges and seek new things and seek to become expert in various sorts of fields. And
00:14:02
and I think the key is that once you become good at something, you you have to drop that and take on something
00:14:08
you're not good at. This is the best thing that you can do for your brain. The reason is because what you're doing
00:14:14
is you're constantly building new roadways and pathways in the brain. There's a study that's been going on for
00:14:19
for decades now called the religious orders study where a bunch of Catholic nuns agreed to donate their brains for
00:14:26
autopsy when they passed away. What the researchers discovered when they look at
00:14:30
the brain carefully is that some fraction of these nuns had Alzheimer's disease. Their brains were physically
00:14:37
degenerating with the ravages of of this dementia, but they didn't show any of
00:14:43
the cognitive deficits that one normally has. They didn't seem to be having memory problems and so on. It turns out
00:14:49
it's because all these nuns lived in these convents till the day they died. They had social challenges and they had
00:14:56
fights with their fellow sisters and they played games with their fellow sisters and they were they had chores
00:15:01
and responsibilities and they were doing stuff. What that means is even as the tissue the brain tissue was physically
00:15:07
degenerating, they were making new roadways and bridges all the time. >> And so that's what kept them cognitively
00:15:14
healthy. We call that cognitive reserve. Contrast this with with people who retire at 65 and they go home and they
00:15:21
watch television and their social circles shrink and so on. That's when you've really got concerns because
00:15:27
you're not building the new pathways. Is there data to support that that when you
00:15:31
retire, if you retire early or if you retire say in your 60s, it increases your probability of an earlier death or
00:15:38
cognitive decline? Almost certainly with cognitive decline because you're just
00:15:43
not getting the challenge at that point. You're just coasting on your internal
00:15:46
model. this. It's tragic, but what happens often is that people's hearing gets
00:15:51
worse. And so by the time they retire, let's say in their mid-60s, it's not
00:15:55
really that fun for them to go out to parties and restaurants anymore because they can't quite hear. And so there
00:16:00
there all these converging reasons why their social lives shrink. But it turns out social life is one of the most
00:16:07
important things that we can do for our brains because there's an expression we
00:16:11
sometimes use in neuroscience, which is that nothing is as hard for the brain as
00:16:14
other people. because you never know what the other person's going to say and
00:16:17
do and how they'll react emotionally and so on. So, you're constantly on your
00:16:21
toes with other people. And if you're not doing that anymore, that ends up being a problem.
00:16:25
>> H interesting. And as a as a I'm 33 years old, so if you were to plot where my
00:16:33
brain is on like a graph of decline, I is it the case that I should be doing as much as I can now to build as many
00:16:40
pathways I can so that when I'm 80, my decline sort of levels out in a in a better place? Oh yeah, for for sure. But
00:16:49
this is true for many reasons actually. Okay, so look, the truth is your brain peaked at two at the age of two because
00:16:56
that's when you get the most connections between neurons, between these cells in
00:17:00
the brain. You get this, at first you're born with these 86 billion neurons and
00:17:05
they connect and connect and connect and it finally becomes like a overgrown garden at the age of two and from there
00:17:10
you're pruning. From there you're taking connections away. Now it happens that
00:17:14
that's not a bad thing. That's a good thing because that's how you're
00:17:18
resonating with the world that you are in. you know, 21st century London and LA versus, you know, 10th century Mongolia
00:17:26
because you're you're just strengthening those pathways that resonate and you're
00:17:31
getting rid of everything else. Okay, fine. But over time, your brain cells die. You know, every time you hit your
00:17:36
head on something or whatever, your brain cells are going down. Um, so in that sense, you've peaked. But your
00:17:42
crystallized intelligence that you've been building your whole life, you know,
00:17:46
that keeps going and you'll you'll have decades ahead of you where you can start
00:17:49
doing stuff. But yes, the reason to learn everything you can is because all that stuff cashes out at various points
00:17:56
in your life when you're starting your next business or you're, you know,
00:18:00
wanting to do the next great thing where you're surfing the way web of AI. You
00:18:04
know, you'll say, "Oh, I learned this thing when I was 16. I learned this
00:18:07
thing when I was 22." And and these are these are paying off now. I think I
00:18:10
heard Andrew Hubman say that one of the most fascinating discoveries of the last
00:18:14
century is a particular part of the brain called the anterior mid-sul cortex and it links to what you were saying a
00:18:21
second ago about challenge and doing things that are difficult. >> Yeah, it turns out that area of the
00:18:27
brain is involved and other networks as well because when you're doing something
00:18:32
new and challenging and difficult, you have stress and anxiety. Your whole brain is active. Let's say I measured
00:18:40
your brain even with something like EEG, electronphilography. That's where I
00:18:44
stick electrodes on the outside. Let's say I measure your brain in my brain.
00:18:47
We're doing something that let's say you're an expert at what's something
00:18:50
you're really good at juggling. I don't know some physics. >> Let's go for juggling.
00:18:55
>> Okay. Let's say you're an expert juggler. Let's say I've never juggled.
00:18:58
Okay. If we're both juggling, you're going to be much better than I am. But
00:19:01
your brain will be less active. You won't have as much activity in your brain. all my brain is on fire with
00:19:08
activity because why I'm trying to figure out okay where do I put my hand how do I throw this and blah blah blah
00:19:13
so when I'm in novice at something my brain is using much more activity not just the anterior made singulate but
00:19:20
tons of activity all over because I'm trying to figure out the rules I'm
00:19:22
trying to figure out what's going on you as an expert you know you got it you
00:19:26
don't you don't need to burn much activity this is what the brain's goal
00:19:29
is is to say hey once I've practiced something along once I get something about the world I'm going to burn it
00:19:34
deeper and deeper into the circuitry So I don't have to burn a lot of energy on
00:19:38
it. >> On this part of the brain, the anterior mid singular cortex, Andrew human was
00:19:41
saying it's larger in people that do things that they basically don't want to
00:19:44
do hard things. If you spend your life doing things you don't want to do, then
00:19:48
it happens to be bigger. And so people have now thought of this part of the brain almost like the willpower muscle
00:19:52
because for some reason those that are doing hard things have bigger ones and those that are not have smaller ones. I
00:19:58
mean it wouldn't be so much the willpower of muscle. It would be some indication retrospectively of how hard
00:20:04
you have worked. Look, the fact is you can see changes in brain size with lots of things. I'll give you an example. If
00:20:11
you are a pianist, if you play piano, then we can actually see physical changes in your motor cortex. This is
00:20:18
the part of the brain essentially underneath where you would wear headphones. For those who are looking
00:20:22
visually, it's this red part here. You actually get a bigger loop of tissue here than you do in a normal brain. Why?
00:20:31
Because you're doing so much fine motor activity with your fingers with both
00:20:35
hands. Okay? In contrast, if you're a violinist, you're only really doing that kind of
00:20:41
detailed activity with one hand. The other hand is just boeing. And so you only get that activity here in one half
00:20:47
of the brain for violinists. So I can look at a brain and tell, hey, is the person a pianist or a violinist or an
00:20:53
either? I can tell just by looking at the visual cortex because you see changes in the brain based on what you
00:21:00
do. For example, jugglers, people who play music, even you can tell this with medical students who study for final
00:21:05
exams. You actually see changes in the distribution of of their cortex. >> Why would it be getting bigger?
00:21:12
>> The reason is the brain's devoting more real estate to that. In this case, let's
00:21:17
say we're talking about fingers on a piano or a violin. The brain is devoting
00:21:20
more there's more relevance to that and so it more real estate so that you can
00:21:26
do it better in the future. >> Exactly. The key about the cortex this wrinkly outer part is that it is a
00:21:32
one-trick pony. This is often overlooked because even this brain that I'm holding
00:21:36
here uh is colorcoded so that we think oh okay that's clearly labeled this that's clearly labeled that and so on.
00:21:42
But in fact it's all the same stuff and it can change. So for instance, if you
00:21:47
are born blind, then this area that we normally call the visual cortex gets taken over by the rest of the brain. If
00:21:54
you're born deaf, then this part that we call the auditory cortex gets taken
00:21:58
over. It gets devoted to other tasks. And so this whole system is very very fluid. And this is what fascinates me
00:22:04
about brain plasticity is the way that we can be the sculptors of our own brains because we can devote ourselves
00:22:13
to particular things and have the brains real estate get involved in that. So if
00:22:19
I was currently someone that couldn't get out of bed, I didn't have a lot of
00:22:22
discipline or motivation and I wasn't very good at committing myself to hard
00:22:27
things. With everything you know about the brain, is it possible to take a set of
00:22:31
actions that will fundamentally change my brain and make me that type of person who runs marathons, who does hard
00:22:38
things, who's motivated and disciplines, and who has high agency and attacks the
00:22:41
world. >> Yes. Yeah. But it's much more than simply resolve because I mean just look
00:22:47
at New Year's resolutions. You know, by by February, most people have dropped
00:22:50
most of them. So, it's really a psychology problem about figuring out okay, what are the things that motivate
00:22:57
me? So, let's say you want to become a marathon runner. You've got that distant
00:23:01
dream. You figure out like what actually motivates me in the short term? Who am I
00:23:05
trying to impress? What am I trying to accomplish in my life? How can I structure things like this Ulyses
00:23:12
contract that I talked about earlier where I'm actually locking myself into a
00:23:16
contract? Like, you know, I call Bob and I say, "I will meet you every morning at
00:23:21
7:00 and we're going to run until we drop." Like once I've committed to those
00:23:25
sorts of things, that's how you set things up so that you do the right thing.
00:23:29
>> It's a bit of a cycle, right? Because then my brain will adapt and then
00:23:32
presumably that will make it easier for me to run. >> Yeah. >> And then I'll run more and then my brain
00:23:36
will adapt. >> That's right. >> And the cycle continues. >> And it's not just your brain, of course.
00:23:40
In this case, it's your body. You're getting better. You're getting stronger.
00:23:42
You don't get as out of breath. And so all these things help. Exactly. But in
00:23:46
order to keep the cycle going, you need to figure out what is spinning this flywheel and what are the all the other
00:23:52
things in your life. Whether good motivations or bad, it doesn't matter. You just figure out what it is that you
00:23:58
can do to to get there. >> Are there certain physical exercises that are particularly good for the brain
00:24:03
from what you've understood? >> The general story is exercise is really
00:24:08
important for the brain. I'll give you just one example of that, which is there's still this debate going on about
00:24:13
whether we get new neurons in the brain. The general story has always been you're
00:24:18
born with 86 billion neurons and those slowly die with time. But in rats, for example, there is a little trickle of
00:24:26
new cells, new brain cells. And there's been a debate for a long time about whether that little trickle happens in
00:24:32
humans or not. Still unresolved. But in rats, what you can see is that exercise causes the trickle to increase. If you
00:24:39
stick the rat on the wheel and it's doing physical exercise, you get more new brain cells. Now, we don't know for
00:24:45
sure that this happens in humans, but lots of things about physical fitness and exercise matter a lot to the brain.
00:24:52
This is nothing new. Exercise, sleep, diet, these are really important things for keeping the health of this organ. Is
00:24:58
there anything else that's important to know for someone that is trying to change and improve and keep their brain
00:25:03
in a healthy state as they age that we haven't touched on? >> There is something that that all of us
00:25:09
are thinking about which is about um social media and the internet in general. I do think one of the
00:25:14
interesting things about the internet and social media is that if we were growing up in a village 500 years ago,
00:25:22
you just know the people in the village and what they can do and so on. But let's say no one in the village was an
00:25:27
entrepreneur or a neuroscientist. And so we we can't even picture that as a thing. We don't know anything about
00:25:34
that. One thing that the internet has done for kids growing up in the digital age is that you get a lot of more
00:25:40
exposure to things. You you have so much more exposure. I actually think this is
00:25:44
one of the positive things that I would say about social media is that you not only get exposure, wow, that kind of
00:25:51
thing is possible and that kind of thing is possible, but you also have people teaching you how to get there.
00:25:56
>> They say like, hey, I'm a fitness influencer and I'm going to show you
00:25:58
exactly how to do the thing. Or, you know, you say, "Hey, here's exactly how
00:26:02
you start a business." Or I say, "Hey, here's the the route that you go through
00:26:05
undergrad and grad school to become a neuroscientist." And that's great. I
00:26:08
mean, there's just there's so much more uh of a talent window now that that
00:26:13
everyone gets exposed to. So, I think that makes a better brain. >> What are we doing to our children that
00:26:18
you think we probably shouldn't be doing as it relates to brain development?
00:26:22
>> Here's the thing that's really important about this debate is that nobody really
00:26:26
knows. And I'll tell you why. It's because to do anything in science when
00:26:29
you're saying something about a group, you need to have a control group that
00:26:32
you're comparing against. And when it comes to asking the question of, hey, kids growing up now with social media or
00:26:38
the internet, how do they compare to other brains of kids who don't grow up with that? Well, we don't have a control
00:26:43
group unless you look at kids who are incredibly impoverished or let's say Quakers who don't believe in technology.
00:26:51
And with both those groups, there's a hundred other important differences. So,
00:26:54
you can't just say, "Oh, look, I'm comparing to this kid who grew up
00:26:57
without food and and I'm going to say there's this difference." Who the heck
00:27:00
knows why the difference is there? even a generation ago. There's so many differences in terms of diet and
00:27:06
pollution and politics and blah blah blah what like everything that you can't
00:27:10
do it. So I I only mention this because I think it's very important. A lot of
00:27:14
people pipe off with things about oh the younger generation their brain this that
00:27:17
but we don't actually know and I will tell you that I happen to be a cyber optimist on this point about what
00:27:25
growing up with the internet does for young people. I think it's going to make
00:27:28
them much smarter than the generation that came before. And here's why. It has
00:27:32
to do with the size of the intellectual diet that they can bring in. So when I was a kid, I grew up pre- internet. You
00:27:40
know, I wanted to know stuff. So my mom would drive me to the library, which was
00:27:45
25 minutes away, and I would pick up the Encyclopedia Bratannica and I would flip
00:27:48
through it and hope they had an article about the thing that I wanted to know about. And that's how I was able to get
00:27:53
my little straw of knowledge. But now kids are growing up with access to anything they're interested in. And this
00:28:02
is so good for the brain. And from a plasticity point of view, the reason this matters is because change happens
00:28:08
in the brain when you are curious about something. So when a kid asks a question
00:28:13
to Alexa or Siri or whatever and they get the answer, that sticks because they have the right cocktail of chemicals
00:28:19
going on in their head. In contrast, when I grew up, I learned tons of just in case knowledge. I mean, that's all
00:28:25
that the teachers could teach us is just in case you ever need to know this fact,
00:28:28
here it is. But kids are in a really great situation now. So, there are pros and cons to to all this stuff, but I
00:28:35
think I'm very optimistic about what this means for the for the warehouse of
00:28:41
knowledge that that kids can build up now. And by the way, I saw an interview with Isaac Azimoff in 1988. He was the
00:28:48
great science fiction writer who wrote Foundation and so many other books. And he was saying on this show in 1988, he
00:28:55
said, "Look, I envision a day when there will be one central supercomput and
00:29:01
every house will have a cable running to that supercomputer and you can ask any question you want and it knows the
00:29:07
entirety of humankind's knowledge on that computer." You know, what he was
00:29:11
foreseeing here was the internet. He got the details wrong, which doesn't matter.
00:29:14
The idea is he saw how this would be so incredible for education because he pointed out look in any
00:29:21
classroom it's going too fast for half the kids too slow for the other half of
00:29:24
the kids and if you could just pursue the sphere of humankind's knowledge if
00:29:29
you could enter in whatever door you wanted to that's the way to do it because you'll be motivated now he
00:29:36
wasn't talking about brain plasticity or anything but this is exactly what I'm
00:29:39
saying from a brain plasticity point of view really matters I I'll just mention something which is a
00:29:46
lot of people are concerned that oh with with AI we're going to get lazy. We
00:29:50
won't you know know how to do anything anymore because we can outsource it. It
00:29:53
just so happens that I I love doing home improvement. I'm always fixing my house.
00:29:56
I have 3xed myself in the last half year because of AI because I take a picture of something. I say hey I've never seen
00:30:03
this kind of thing before. How does this work? Whatever. And chat GPT says oh you
00:30:07
do this and you take this out and here's the bolt and blah blah. It's not me
00:30:10
outsourcing it. It's me being curious about something and so I remember how to
00:30:14
do everything now. I know how to do much more than I used to because I like it. >> What about the you there's been a couple
00:30:21
of studies that have come out that say things like your brain's going to atrophy if you don't continue to write
00:30:25
or um if you just defer all of your learning to things like chatgbt or other AI models. Um, one I guess one of the
00:30:32
areas that I think in one of the studies, was it a Stanford study that everyone was talking about where the the
00:30:38
participants used Google and AI and then they'd learned something themselves.
00:30:43
>> But one of the things I've wondered is if I'm going through my business life
00:30:48
and I'm encountering hard problems and every time I encounter a hard problem, I
00:30:51
drop it into an AI. The AI spits out a textbased answer. I copy and paste that and send it as my response. presumably
00:30:59
there's some kind of important part of the learning cycle or the you know neurological development that I'm like
00:31:05
foregoing there I'm missing that I probably should you know you said earlier about doing hard things what I'm
00:31:11
doing there is I'm avoiding the hard thing which is like thinking about it and trying to understand it
00:31:15
>> yeah here's I think the really important distinction there's vicious friction in
00:31:20
our lives and there's virtuous friction so vicious friction is all the stupid
00:31:25
stuff that you have to do like hey Stephen for your business I need you to cop copy this spreadsheet over here and
00:31:30
fill in all these cells and and do your taxes and whatever. Okay, that if we can
00:31:35
push that off to AI is massively important for for improving human lives. There's really not benefit in vicious
00:31:41
friction. But virtuous friction is, hey Stephen, I really want you to think about what is the optimal way to do this
00:31:49
business. What is the best structure for this? How do we actually go DT to C? How
00:31:54
do we go B2B on this? What's the what's the approach here that we're going to
00:31:58
take that you haven't done before that would be amazing? That's virtuous
00:32:03
friction because you're really using your brain to learn stuff that way. So that's the first distinction that
00:32:08
matters is get rid of all the busy work. There's no honor in that. I mean I'll
00:32:13
just mention in the 1990s there was this big debate about whether we should have
00:32:17
kids use desk calculators or not. And thank god that finally got resolved and we let kids use calculators so that we
00:32:23
can learn, you know, couple we can spend a couple days learning long division, but you don't have to spend six months
00:32:27
on it because who cares? With the virtuous friction, there's real opportunity to surf the wave of AI so
00:32:35
that you are figuring out these tough problems with the aid of somebody who cares about your problem and is willing
00:32:42
to talk with you 247 and never gets tired of talking to you about it. And so you are not just copying and pasting,
00:32:48
but you're working with the AI to come up with ideas that were beyond what you
00:32:53
would have come up with. Because I mentioned earlier about internal models, we have pretty narrow fence lines and
00:32:59
you can think of all these things, but you don't even know what you don't know.
00:33:02
So, if you can have somebody who's willing to talk with you, an expert in all of humankind's knowledge, willing to
00:33:08
talk with you about it as much as you want, there's a real opportunity there
00:33:12
to have a synergy where collectively you both come up with a better idea than either of you could have alone. But is
00:33:19
there a way for that relationship to take place so that I actually benefit? Because, you know, in the example I
00:33:23
gave, I'm just I take the question I was asked, I put it into an AI, it gives me
00:33:27
an answer, I copy and paste it back to the person that asked me the question. that would happen if you really didn't
00:33:32
care about the person asking you the question or the question. I mean >> I mean this is what a lot of people are
00:33:36
doing like I get so many email because you know we interview a lot of candidates who join the business and so
00:33:39
I see tens of thousands of emails sometimes a week that I mean I don't see all of them but the ones that I see I
00:33:44
often know that you know because we've sent them five questions or a task and I
00:33:49
look at it and go this is I can almost predict the exact model that sent it to me because they all have a different
00:33:55
personality so I go oh this one the person put into Gemini or this one the person put it into chatbt. Yeah,
00:34:00
exactly. And it's full of contrastive constru construction like >> it's not this, it's that. Yeah, exactly.
00:34:06
And then the M dashes. Exactly. >> I'm really asking like is the person
00:34:09
that did that benefiting from from it? >> No. >> Well, no, but for a couple reasons. One
00:34:13
is that, you know, you and it it triggers your red flag and so that does not do anyone any good. see so many of
00:34:20
my colleagues posting on LinkedIn these very obvious AI things and it irritates me because I feel like I'm not going to
00:34:26
spend my time reading that because of I call this this the effort phenomenon which is um in in psychology we care a
00:34:35
lot about things that seemed like they took a lot of effort and there's something about seeing an AI post that's
00:34:40
just irritating because it's so obviously AI >> that's a really interesting idea the
00:34:44
effort phenomenon >> yeah I've been I've been writing about this for a while because um it turns out
00:34:48
there are psychology ology studies where if I offer you two pieces of art and one
00:34:52
of them looks like, you know, let's say it's a a red dot in the middle of a
00:34:55
white canvas and the other one is, you know, bottle caps stacked up and glued in this great shape or whatever, you'll
00:35:02
pay you'll pay much more for the thing that looks like it took a lot of effort.
00:35:05
People will pay more for a real diamond than a synthetic lab grown diamond, which is exactly the same thing. It's
00:35:12
just carbon in the matrix. But they feel like, oh well, mother nature took hundreds of millions of years of effort
00:35:17
on this one, but not over here. It just took a few days in the lab. So, there's
00:35:21
a million ways where we care about that a lot. When it comes to this AI thing, um, yes, anybody who's just popping back
00:35:28
something to you, it just feels like, all right, they took the the path of least resistance, and I'm not so
00:35:33
interested. >> I want to know from a neuroscience perspective whether they benefit.
00:35:37
>> Presumably, they don't benefit too much either. I mean, it's hard to know
00:35:40
exactly how many times they went back and forth with it. They could have said, "Hey, Chad GPT, thank you for this, but
00:35:46
I'm kind of this more of this person. When I really think about it, this is the thing that inspires me." Not not
00:35:51
what you suggested. So, so somebody could put effort into it. It's just that
00:35:54
we can't know that when we get the AI response. It seems to be a pretty consistent principle of life generally
00:35:59
that like when you do something hard or when you put in effort, as you say, you tend to get back like an equal and
00:36:05
opposite return like relatively. So I I would think that if I fought through, you know, maybe even using AI as a
00:36:13
companion, but I fought then to write it out myself instead of just copying and pasting.
00:36:18
>> Yeah. >> One of the things I've learned from doing this podcast and all these
00:36:20
episodes is everything is a trade-off. >> Yeah. >> And and if you don't know what the trade
00:36:26
you're making, then you're often at great risk. And so like some of my friends will say, "Oh, I take this pill
00:36:32
and it's amazing. It does all these things for me. It's the most amazing
00:36:34
thing ever. I can just focus for 24 hours a day and I'm so productive now. And I go, "What's the what's the
00:36:39
downside?" And they go, "Oh, there's no downside." And I go, "Hm." Like, so
00:36:43
that's what I mean. It's even worse when you don't you don't know the trade
00:36:46
you're making. And so with AI, I go, "Okay, if it's making me wildly more
00:36:50
efficient or productive, what trade am I making?" I think understanding this it's
00:36:56
probably not two categories but a spectrum from vicious friction to virtuous friction but really paying
00:37:02
attention to what is virtuous friction what would make me a better person if I actually put the effort into this that
00:37:09
matters a lot and I will say for us as professors for you looking for job candidates we need to change how we're
00:37:17
asking the questions if we just say hey write answer these five questions of course everyone's going to use it for
00:37:22
example in my classes is at Stanford. I I don't have people turn in a final paper anymore. That was from previous
00:37:29
life before AI. Now I have them do projects as their final thing where they're uh you know running an
00:37:35
experiment on something. And of course they use AI to help them generate some of the issues, but they have to deal
00:37:40
with other people and look at the data and figure out what's wrong and that kind of stuff. I worry that it's getting
00:37:44
into the age of, you know, the whole calculator thing you said where maybe actually it is now you need to assess
00:37:50
them on their ability to use the AI, >> not to succeed without it. >> Yeah, agreed. This is the whole game for
00:37:57
all of us, I think, is figuring out how to surf this wave of AI where it can make us super human. We can just be
00:38:02
better, so much better than anything we ever were doing before because we have immediate access to knowledge and facts
00:38:09
that either we had forgotten or we never knew existed. And so we should be surfing that wave. So I I I totally
00:38:15
agree with you on that point. If you can figure out how to change your interview
00:38:18
questions so that you're seeing, hey, can this person really get the speed? With everything you know about learning
00:38:23
and neuroplasticity and expanding one's brain, is there a anything else you can
00:38:28
say to the audience about how they should use AI so that they become a superhum?
00:38:33
>> Interesting. I you know, look, I I have been talking to my friends about this
00:38:36
issue a lot lately and I I mentioned how I've become so much better at home improvement stuff. I just know so much
00:38:42
more. Each one of my friends has something like that where like, hey, you know what? I've actually gotten so much
00:38:47
better at this super random thing that I never even thought I, you know, I never
00:38:51
thought about it explicitly, but because I'm always asking AI questions about
00:38:55
that and it's giving me the answers. It's not simply that it gives me the
00:38:59
answers and I forget it. It gives me the answers and I remember it. I become better and better because it's like the
00:39:04
way that Alexander the Great had Aristotle as his tutor and could ask him anything and learn great stuff from him.
00:39:11
We've all got Aristotle in our pocket now and we can become better at the things that we want to do, the things
00:39:17
that resonate with us for whatever reason. If everyone's got Aristotle in their pocket, how does one create an
00:39:22
edge? >> I think it has to do with we're all just going to be running faster. In the same
00:39:27
way that when Steve Jobs introduced Apple computers, he said this is like a bicycle for the mind. What he meant by
00:39:32
that was that for millions of years we've been walking bipedily and then just in the last nancond of evolution we
00:39:39
invented the bicycle and suddenly humans can move faster because of the bicycle and he said having a personal computer
00:39:46
is like a bicycle for the mind and I think of AI now as like a motorcycle for the mind it's it allows us to move so
00:39:55
much faster so now it's a motorcycle race and there will be people who are much faster than other people because
00:40:01
they're really using that optimally. >> And that's what I mean. It's like how do
00:40:04
I create an edge versus my whoever I'm competing with in whatever industry I'm
00:40:07
in. >> Well, for sure the people who are just copying and pasting the AI slop that'll
00:40:12
be easy to beat that crowd. But otherwise, I think it's just a matter of, hey, these are the newest things.
00:40:18
It's like in history when the new sword gets invented or the new gun or the new
00:40:22
cannon, you know, you have to keep improving and and using that. And that's what's going on now with AI
00:40:28
>> and with from a neuroscience perspective. If I wanted to use AI to based on all these things you've told me
00:40:34
about novelty and all these other points that expand the the connections across my brain and give me a big cognitive
00:40:40
reserve. What might I I install as a practice every week when I'm speaking to my AI?
00:40:46
Oh, ask it questions that you're curious about about anything. Just asking questions. Here's one thing I do all the
00:40:52
time. I'll say, "Hey, I've been thinking about this. You know, I on my podcast, I
00:40:56
do a lot of monologues and so I'll start talking to it and I'll say, "Hey, I've
00:41:01
got this idea that I'm thinking about. What if blah blah blah blah." And then
00:41:03
I'll say, "Here's my idea. Give me pros and cons." You know, tell me why this is
00:41:08
wrong. And I do that pretty much with everything that I ask it if I'm proposing some, you know, stupid seed of
00:41:14
an idea and it really gives me the counter arguments and I really engage with it. That is the important part, I
00:41:21
think. And by the way, I just want to say I think for the next generation that we're teaching this, there really only
00:41:27
two things we can teach because all the details of, you know, hey, let's teach
00:41:31
computer programming or something, that's probably already gone as a useful thing. So what we can teach is critical
00:41:37
thinking and creativity. That's it. I think that's such an important point,
00:41:42
this point about asking your AI why you might be wrong. >> Yeah. I I think I've had most of my
00:41:47
paradigm shifting moments when I've come to an AI model that I was using with a
00:41:52
very with very high conviction. And the prompt that always I think is most sort of expansive in terms of my intellectual
00:41:59
knowledge is when I say to it, be brutally honest about your opinion. Think for yourself and be objective and
00:42:06
tell me where my blind spots are. There's something innate with within us all where we don't actually want to be
00:42:14
wrong. We often I think as a natural reflex and this is why people get really sort of trapped in echo chambers of
00:42:18
political opinion and you know Leon Fesser talked about this idea of cognitive dissonance when something you
00:42:23
believe contrasts with new information and how it makes you feel uncomfortable there's something when I type that out
00:42:29
when I when I love the idea or the thing I've written or the memo I've written
00:42:32
this new idea and I go on tell me why I'm completely completely wrong and it
00:42:36
eviscerates me it is both uncomfortable but it feels incredibly important because then then it's like I've I've
00:42:44
grown. But these AIs, they're they're programmed almost to like kiss my ass.
00:42:49
>> Yes. Although, you know, Chatupati released a very sickopantic version, I
00:42:54
don't know, maybe a year ago. Meaning it compliments you. You give some idea and
00:42:58
it says, "Oh, Stephen, that's the best idea I've ever heard. You're a genius
00:43:01
and blah blah." And that didn't last very long, that model, because nobody
00:43:05
actually liked it. So, you're exactly right. And and I'm sure most listeners
00:43:09
know this, but you can tell your AI to be brutally honest with you all the time. You can tell them to do that all
00:43:15
the time and it'll do that. So you can you can establish the kind of person that you're talking to. Here's the
00:43:21
thing. You're right. Of course, people don't like to be wrong. It can be
00:43:24
socially embarrassing. It can be uncomfortable. And yet, there's something very different when you're
00:43:28
talking to your AI. It's a very private thing. And you say, "Hey, tell me why
00:43:31
I'm brutally wrong." And when it tells you, you think, "Oh, thank God it's
00:43:34
telling me that instead of like a real human." So I I think a lot of that is
00:43:39
alleviated with AI. We we don't feel as bad about being wrong there. >> As you were saying that, I just went on
00:43:45
chat and I typed this in. Is my joke funny? And the joke I typed in is knock. Who's there? A letter. Let us who? Let
00:43:54
us in and I'll tell you. >> Okay. You didn't laugh. I didn't laugh.
00:43:58
>> Okay. >> Chapati said, "Yes, it works as a joke. solid structure, uses the classic pun
00:44:03
payoff, which is exactly how most not jokes land. And then it's done a laughing emoji. I then said, "Be
00:44:08
brutally honest and completely objective. Was that funny?" It said, "It's not very funny."
00:44:16
Interesting. You know, but but that's interesting because it depends, right? A
00:44:20
little child actually finds that joke funny and and for a little child, they then get to repeat that to their
00:44:26
classmate. They're learning how to do a joke and so on. So I'm not I'm not sure
00:44:31
I think there's a single answer to whether that can be funny or not. >> But the interesting thing is it just
00:44:36
reinforcing what I already believed. And therefore when we think about growth or
00:44:40
having a growth mindset if someone's just always reinforcing what you already
00:44:44
believe and know I don't know if it's ever going to be a growth mindset. I
00:44:47
mean I just asked it again. I said be really honest and it said it's absolutely not funny.
00:44:52
>> Yeah. But but remember all it's doing is it's just it's a statistical parrot. And
00:44:57
so when you say be brutally honest, it it thinks that's what it should answer.
00:45:02
>> Also, be even more honest. It says it's basically not funny at all and you
00:45:05
shouldn't say that to people. >> Okay. >> And it says comedic originality 1 out of
00:45:09
10. Likelihood of real laughter 1 out of 10. >> Well, that's that's quite good. That's
00:45:12
quite accurate. Um, here's the thing. I've been thinking about this issue a
00:45:16
lot about whether AI can be funny. And at the moment, it can't be. It It's
00:45:22
great at repeating jokes, but it doesn't understand humor on its own. what it
00:45:27
knows if you ask it to make up a new joke, what it'll do is it'll have, you
00:45:31
know, the first guy walks in the bar, then the second guy walks in the bar and does X, and that establishes the
00:45:36
pattern, but then the third guy, it'll have break that pattern, which is the
00:45:39
structure of a joke, but it doesn't know how to break the pattern in a way that's
00:45:44
funny. It's just the third guy does some random thing. So AI as it stands now,
00:45:48
the way it's structured with what's called a transformer model, doesn't know
00:45:52
how to think of the punchline and then go back and make the joke lead to that punchline.
00:45:57
>> A lot of people don't either. >> Do you know what I mean? Like I say that
00:46:01
not in an offense way, but just to say that like >> I don't know. I often hear the claim
00:46:04
that AI could never be creative. >> It's massively creative. Here's why.
00:46:09
Creativity in the brain, all creativity is is you absorb your world. the whole world around you, every experience
00:46:15
you've ever had. And then you're bending and breaking and blending those
00:46:19
cognitive concepts into new remixes. That's all creativity is. And you're
00:46:24
doing that all the time. Whether you're just trying to think of what to say next
00:46:27
or what recipe to make next or what patent to do or what company to start, you're just remixing the stuff that you
00:46:33
already know. And that's why, you know, I don't know, take Beethoven, he could
00:46:38
have written any kind of music that was being done anywhere in the world. But of
00:46:42
course, he didn't. like that's what he grew up with was the music and his local
00:46:45
culture and so on. What we have now is a much broader diet as I mentioned before
00:46:50
where we can get everything going in. But the point I want to make here is that AI that's what it does. It remixes
00:46:57
stuff that's come in. So AI is massively creative. The part of creativity that AI
00:47:01
can't do right now is selection. Meaning it can generate a 100 pictures but it
00:47:07
doesn't know which one to pick. It doesn't know which one is going to be
00:47:09
the most appealing to you. But it can remix beautifully. >> But neither do humans, right? So if I
00:47:15
asked an intern to make me 100 pictures, I mean, I could get my AI to pick one, but it wouldn't know what the intern or
00:47:21
the AI wouldn't know which one I loved. >> The intern would have a much better shot
00:47:25
at it. And as the intern is there for a while, he or she becomes quite good at getting, oh, okay, I get Steven's taste.
00:47:31
It would be this one. >> And the AI can't learn that what my taste is. I don't think the AI could
00:47:35
learn that about visual images because when it generates the pixels, it's doing
00:47:39
this, you know, this magical stuff under the hood where it's deciding which pixels and how they diffuse together
00:47:43
and, you know, mix the image, but it doesn't know how to read that image like, oh yeah, the way this is and blah
00:47:50
blah that'll really appeal to Steve. It does it it's not seeing the image except
00:47:54
as a bunch of pixels. Hm. Hm. >> You need to be a human for that >> cuz I feed um I was doing an experiment
00:48:01
recently where I took our my behind the scenes channel which is a 30 minute long
00:48:04
video. I dropped it into Gemini and I'd say things to it like predict where people would drop off on the video and
00:48:10
then we upload the video to YouTube. we get the retention data back and Gemini uh in the last two times that I've done
00:48:16
it has a 100% record of knowing that at minute 7 where insert person talked for too long and might have been a bit more
00:48:24
sight might have tried to sell a hoodie for example in that part it would say you're going to lose people here and it
00:48:30
would and it very accurately say why it would say because there's you talked for
00:48:34
74 seconds and it was jarring versus the the the moment that came before it and when I feed the AI I don't let's say
00:48:41
thumbnails and say which thumbnail is going to perform the best. We did a test recently where we put four thumbnail
00:48:47
test results that we knew the answer to into Gemini and said which one's going
00:48:50
to win on YouTube AB testing and it got 100% accuracy of predicting on data we already had which one would win. And so
00:48:59
now I I don't know I I keep having these paradigm shifting moments where only
00:49:03
humans could could do that. But increasingly the the AIs that we're experimenting with are making better
00:49:10
creative decisions than now I can make myself as if the outcome of that creative decision is which one is people
00:49:15
going to prefer. >> Yeah. >> I'd say a year ago that wasn't the case.
00:49:18
>> Okay. So I totally agree with you. But but let me just mention one thing which
00:49:21
is fascinating which is that often the way it's doing it is not at all the way
00:49:25
that a human would do it which might be fine for our purposes but the data and the way that it's picking up on it. It
00:49:32
might be something about you know how much I'm making this up you how much green was in the YouTube thumbnail image
00:49:37
or how much red or whatever whatever the thing is or just noticing that there's
00:49:42
big font versus smaller font or whatever. the next time you try it, it says, "Oh, yeah, this thumbnail is going
00:49:48
to be great." And it's some ridiculous thumbnail that doesn't make any sense to
00:49:51
you as a human, nor to your fellow humans, but it might say, "Oh, yeah, this would be great." Because it's
00:49:57
judging things on very weird dimensions that we can't always see. You know, the
00:50:00
example you gave about maybe it's cuz the text is bigger or the color red, but
00:50:04
those are the same factors we think about as a human. We think if we know that if the font is bigger, it performs
00:50:10
better. We know that red performs better than green. >> Quite possibly. But here's the
00:50:13
interesting thing. Human art constantly evolves and all AI is trained on is what
00:50:18
has been done before and what has worked. And so if I asked it, let's say we composed five different songs and
00:50:25
said, "Hey AI, which song is going to be better?" It's going to say something
00:50:28
that's right in the middle of the distribution of popular songs. But that's not what actually makes it next
00:50:33
year and the year after. It's new things. It's new twists that that nobody
00:50:37
has seen before. That's what we love. That's what we seek as consumers. And so
00:50:41
because AI can only be trained up on what already exists, it's never going to
00:50:46
get the new thing at the edge. >> But if if the AI was asked to cuz I think the reason why a new song would
00:50:52
break out, let's say, you know, a new Drake song comes out and it's a smash
00:50:57
hit. If we think about that distribution curve, so like if I draw on the GR, you're saying that um this middle
00:51:02
section here is what sort of AI will aim at because it's the popular in the known. Well, if I tell AI to make a
00:51:10
million songs, which is kind of what I guess is what's going on every day um
00:51:13
around the world, if you scattered them on on this graph at like, you know, >> Absolutely.
00:51:19
>> And then the AI's most unusual song ends up taking off. But it's just because
00:51:23
there's so many of them. >> Quite right. But that's the human selection part that we're seeing over
00:51:28
there. If you asked, okay, out of all these dots, which do you think AI is going to be best? It's going to have to
00:51:33
tell you the middle of the curve. But the surprising part is the part that you circled there, which is the one on the
00:51:38
edge is the one that humans like. Why? Because we're constant novelty seekers.
00:51:43
We care about the things that are new. I think the the point I'm getting at is
00:51:47
that um the creation of it, the creative process is still the same, which is like
00:51:53
>> totally >> AI or humans just trying a bunch of and then the world going, "Ooh, that
00:51:58
one." >> Oh. Oh, yeah. I totally agree. This is consistent with what I was saying, which
00:52:01
is that AI can be massively creative in terms of the generation of something, but you need humans to do the selection.
00:52:07
I'm only arguing the point that AI is not good at saying, okay, I've generated
00:52:11
a 100 songs. This is the one humans will choose. We end up saying, hey, wait, this one is just weird and unique enough
00:52:18
that I really like that. It's interesting because when you um when you speak to like record labels about music,
00:52:24
what they're often doing is getting a format of a song that they know will work. So they're like, "Right, so it's
00:52:33
got to be eight bars here. It's got to be this here. You got to have a chorus
00:52:35
that's like hookie. It's got to come back around. It's got to build up pace.
00:52:38
And there's like a rough format to it." And it's no surprise that Ed Sheer
00:52:42
someone like Ed Sheeran has written so many songs for so many people. >> Yeah. When I spent some time working
00:52:47
with Sony, they had a brand new boy band in the wake of One Direction. And when I
00:52:51
sat with the boy band um and was introducing myself, they said they said to me, "Oh yeah, so um here are their
00:52:55
his the boy band's first three songs and um Ed Sheeran has written all of them."
00:53:00
And I was like, "What?" I thought I thought like they're like, "No, Ed Ed
00:53:03
Sheeran's written all of them." And then what we do is we give them to the boy
00:53:06
band and then the boy band sing them and they're pretty much guaranteed to be
00:53:10
hits because Ed Sheeran has like a formula. the way he writes is really in like vogue right now. You people tend to
00:53:17
think a lot that the songs that are number one in the charts are there because just because someone had
00:53:23
creative genius and of course that is the case sometimes but there is a lot of this writing going on and then handing
00:53:28
the formula over because someone has cracked the code of a hit, >> right? But here's the thing and you know
00:53:33
that we all know this which is that the code never lasts. So humans have this pull where they're always seeking things
00:53:41
between novelty and familiarity. So we like things where we recognize the brand and we recognize what the singer has
00:53:48
done before. But there has to be novelty or else we're not going to go for it.
00:53:52
We're not going to listen to that boy band for the next 10 years doing the same song over and over. So you're of
00:53:57
course right that we, you know, we want a bit of familiarity. We want to be anchored, but we definitely seek the
00:54:03
new. This is what humans always do. This is why car companies always release the
00:54:07
next model even though the current model is perfectly fine. This is why haircuts
00:54:11
evolve. This is why fashion evolves through the years. Um because we always care about novelty. And the other thing
00:54:17
in the music industry that I think is is also creating a hit is I was reading many years ago about some psychology
00:54:23
which you'll probably know much more about that says exactly what you just said which is we love something when it
00:54:28
is familiar but new. >> Exactly. So the way that the record industry and the radio industry make
00:54:35
something familiar is they blast the same song at you on every radio station for a long period of time until it
00:54:42
breaks past being just novel, just new and it becomes familiar. And like I saw this graph which shows that the a song
00:54:50
that you'll love is right there in the middle of like it's new enough that
00:54:55
you're still into it but it's um familiar now because you've heard it so
00:54:59
many times that you love it and you'll if anyone listening the first time you
00:55:03
hear a song you might not love it as much as once you've heard it like 20 times
00:55:07
>> and then at some point you've heard it too much. >> Yeah. >> And it comes back down the other side of
00:55:11
the cover where it's now too familiar. >> Yeah. That's exactly right. And so we're
00:55:15
always seeking that tension in the middle. And yeah, companies run into this all the time. Like sometimes they
00:55:21
try things that are too novel that just completely fail. You know, Coca-Cola tried this a long time ago with
00:55:26
introducing new Coke and no one liked it, whatever. Um, and other companies like what was that company? Blackberry
00:55:31
with the the little thumb things that you can press the physical keyboard on the phone. They failed because they
00:55:36
wouldn't change fast enough. But anyway, companies that make it are always staying in that uh sweet spot.
00:55:47
Whoa. What's that on your face? >> This is my Bon Charge face mask. I've
00:55:51
been wearing this for some time now. They're a sponsor of the podcast. I put
00:55:53
this on for 15 20 minutes a day. I can sit here in the chair and wear it. Boosts my collagen production. Helps
00:55:58
with fine lines, blemishes, my complexion gets better, and then more people listen to the podcast cuz I I
00:56:03
look better. Professionalgrade equipment in such a small box. It's noninvasive.
00:56:08
And having sat here with so many of the world's leading health professionals,
00:56:11
there's various things that I repeatedly hear work and some things I'm a bit
00:56:14
skeptical about. This is one of the things that almost all of my guests on this show have confirmed works. It is
00:56:20
really, really, really effective. And they offer fast, free shipping worldwide with easy returns and exchanges. And
00:56:26
you'll also get a one-year warranty on all of their products. And they're HSA
00:56:29
and FSA eligible, giving you taxfree savings up to 40%. And you can get 20% off when you order through my link at
00:56:37
bondcharge.com/doac. That's bondcharge.com/doac. The deal applies sitewide. I'm 100% more
00:56:46
productive using this app despite spending 50% less time typing. And that might confuse you, but let me explain,
00:56:53
which is exactly why I invested in Whisper Flow. They're also one of our sponsors on this podcast. Whisper Flow
00:56:58
turns your speech into text, so you can send it in any app or device at any time. And I promise you, it doesn't seem
00:57:05
to ever make mistakes. This is the most accurate voice dictation I have ever used after a decade of trying to get one
00:57:12
to work. Not only does it save me a ton of time, it also corrects your speech if
00:57:16
you change your mind mid-sentence before turning it into text on the device. I love it and I know my team loves it too
00:57:21
because when I posted it in our Slack channel asking if anybody wanted a pro version, half the office said yes and
00:57:26
they had it within an hour which tells me everything. This is the tool you and your team need to speed yourselves up
00:57:32
and to capture those important ideas so that they don't disappear. Head over to
00:57:37
whisperflow.ai/stephven to download it now. That's wispr.ai/stephven. When you think about the brain and how
00:57:48
it's built and then you think about the exact technology that they've used to
00:57:53
create AI, isn't it very very similar? And if so, if it is similar, what does
00:57:58
that say about humans role in the future? It's similar, but it's not the
00:58:02
same. Which is why with AI, you get what what we call jagged intelligence, meaning that it can do something so
00:58:09
extraordinarily smart and then in the next moment give an answer that's weird
00:58:12
and doesn't make any sense. AI still is doing this. It's not it's not yet
00:58:16
thinking like we think. Okay. Why? It's because AI as we think about it now really
00:58:22
started of course decades and decades ago where people said look you've got all these billions of cells neurons in
00:58:28
the brain that are connected to each other. What if we ignore all that complexity and we just say look imagine
00:58:34
that you have units that are connected to each other. We're going to forget about you know a single cell in the
00:58:38
brain is as complicated as a city. It's got the entire human genome. It's
00:58:42
trafficking millions of proteins. Let's put all that aside. Just imagine it's a
00:58:45
circle and it's connected to other cells and each connection has a certain strength and that's what we call an
00:58:50
artificial neural network. Now that went off in its own direction and the kind of
00:58:55
amazing surprising part is how successful it's been to just get rid of all the detail but it's still super
00:59:02
different than what human brains are like. So just an example uh this thing I mentioned at the very beginning about
00:59:08
how we're a team of rivals under the hood. You got all these different competing neural networks that are
00:59:13
trying to drive your behavior and so on. The fact that we're emotional, the fact
00:59:17
that we are driven by different appetites, whether food or sexuality or whatever it is, but you know, you're a
00:59:24
your chat GPT, you don't want that in the chat GPT. So, it's just an artificial neural network many layers
00:59:29
deep and it's extraordinary at what it does, but it's so different than a
00:59:32
human. For example, the fact that it's read everything on the planet and remembers it and you haven't, you would
00:59:38
need to lead a thousand lifetimes to read that much. And of course, you wouldn't remember much of it. It It's
00:59:43
very different is the point I'm making. They both have converged on something
00:59:48
that we would call intelligence, but it's a pretty different structure. Even
00:59:51
though AI was inspired by the brain, that's what Jeffrey Hinton was telling me. He was telling me that like much of
00:59:56
the the breakthroughs that have made AI what it is today came from understanding
01:00:00
how the brain works. >> Yeah. But that's interesting because Hinn isn't is incentivized to say that.
01:00:07
But a neuroscientist >> incentivized to say that >> people doing AI of course are paying a
01:00:13
lot of attention to how this is structured like the brain because before that people would do things like
01:00:19
probability theory or rules or you know they were trying to do AI by trying to say okay if this then do that but when
01:00:27
people started doing artificial neural networks that led to a lot of success I'm only pointing out that the
01:00:32
artificial neural network looks a lot like the brain on the surface You say, "Hey, you've got units and you've got
01:00:38
connections, but beyond that, there's a lot of differences." >> And why are those differences
01:00:43
significant as it relates to what's possible? >> Because what we've developed is this a
01:00:48
new species essentially that is incredibly impressive, but it ain't a human brain. It's different than a human
01:00:54
brain. There may be all kinds of similarities, things that we even come to understand are similar, but there are
01:00:59
so many differences. Here's an example. You know, we humans do one trial learning all the time. Meaning if I say
01:01:06
or when you were a kid and and your mom said, "Hey, Stephen, this is a pomegranate." You say, "Okay,
01:01:10
pomegranate. Got it." But you can't when you're training up a an artificial
01:01:15
neural network like at OpenAI or Gemini or Anthropic, you have to give thousands
01:01:21
or millions of examples of everything for it to learn anything. There's no one
01:01:24
trial learning on those uh systems. And they have to be trained at the cost of billions of dollars. then they can do a
01:01:31
run where you ask a question and and it answers the question. But brains in the real world don't have that luxury of
01:01:38
having a training phase and then an action phase. We have to learn on the fly. It's very different.
01:01:43
>> So I guess the the pertaining question is does it change what's possible for the
01:01:49
brain versus the artificial neural networks we see in AI? like is there some limitation based on what you've
01:01:57
just said that means the this brain in front of me, this human brain in front of me will always be better than the AI
01:02:02
at something because I'm trying to track forward about what this means for the
01:02:05
future of humans. >> Yeah. >> Um >> I think it's an interesting question um
01:02:09
that we'll have to see. But it's clearly the case that we know what it is to be a
01:02:15
human from the inside. And when I'm making a model of you and who you are and you're making a model of me, we have
01:02:21
assumptions about what it is like to be a human. AI only watches human behavior from the outside. And so it can tell a
01:02:28
lot of great stuff, but it doesn't really know what it is to be a human. So if I ask it some question about what
01:02:35
would it be like if this or that happened, it can answer based on observing lots of things, but it can
01:02:41
only ever know from the outside >> in terms of why that matters. >> Yeah. Because you know if I ask my AI my
01:02:47
fiance's been like this today or if I ask my best friend my fiance's been like
01:02:50
this today. If it both of them give me the same useful answer it doesn't really
01:02:54
matter what's >> I agree with you. I agree it may I I I'm actually writing a new podcast on this
01:02:58
about what you can tell from the outside and what you can tell from the inside and whether that difference matters.
01:03:04
Look an example is you know I last year got a Tesla with full self-driving and I
01:03:09
was watching as it was full self-driving. I was coming up on a very complicated traffic situation. And I
01:03:13
thought, well, what's my car going to do here? How's it possibly going to
01:03:15
understand? But what it did is it slowed down and came to a stop, which was exactly the right thing. And I thought,
01:03:20
oh, that's interesting. Algorithmically, it might think of it very differently
01:03:24
than I am thinking about the situation. Doesn't matter. It comes to the same
01:03:28
conclusion, ends up in the same place. Yeah, I agree. We have yet to see where these differences matter and and what it
01:03:35
is to be a human. But I can tell you one thing. We care about other humans. So here's my little prediction is that
01:03:41
there's going to be actually a renaissance in things like live theater and live performances. When when things
01:03:47
first came out like Napster, everyone thought, okay, that's the death of concerts. Like who's that's the death of
01:03:53
musicians, right? But in fact, you look at a a Taylor Swift concert, gajillions of people there paying lots of money.
01:03:59
Like everyone loves the the thing. Why? Because they're going to see the real
01:04:03
Taylor Swift in person. And I have noticed I give a lot of talks on the road. I have noticed an increase in the
01:04:08
number of talks since AI came out a few years ago. The first thing that my friend said to me is hey did you know
01:04:15
David that you can you know use uh 11 labs and hey Jen and you know you can make an avatar of yourself and you can
01:04:22
use your voice and and use chat to generate what you're going to say and have a fully virtual version of you. He
01:04:28
said my friend who gives talks too he said maybe we can start doing this and do virtual talks. I said nobody's going
01:04:33
to want that. In fact, what's happened is more people want to fly us across the
01:04:38
country to have us stand there in person because it really matters to see fellow
01:04:43
humans. And I think that's only going to increase. >> I completely agree with you. I think I
01:04:48
think it's so funny. I did a post on LinkedIn the other day saying that maybe
01:04:52
the like interesting paradox or interesting outcome of AI is that every other iteration of technology made us
01:05:01
less human. And maybe the intelligence now has gotten to a point where >> it's now forcing us to be more human
01:05:10
because that is all that kind of remains in a way that maybe the the technology has gotten so good like social media
01:05:16
didn't make us more human in any capacity. But maybe this is the moment where it goes we've got this now
01:05:21
>> go do what only you as a human can do which is like go out there Taylor Swift
01:05:25
and sing in front of people IRL. >> Go and do something in the real world.
01:05:28
Even for like nurses um and doctors, maybe they shouldn't be filling out admin and paperwork anymore. Maybe they
01:05:33
should be holding your hand and giving you, you know, in real life care that only a human could do.
01:05:39
>> I totally agree. >> And so maybe that's the like the the positive upside to all of this is um
01:05:44
finally, you know, we've been on this journey with technology and finally it's
01:05:46
delivered upon its promise. >> I totally agree. And by the way, you know, AI relationships, by one estimate,
01:05:52
there's a billion people having relationships with AI, like a girlfriend or boyfriend kind of thing.
01:05:57
>> Okay? And so for people like us who grew up before that existed, we think, "Oh my
01:06:02
gosh, that's weird." But in fact, I think it might become helpful because it
01:06:06
can be a sandbox as long as we have the proper feedback. In the end, we have millions of years of evolution driving
01:06:12
us towards being with the person you love, touching another human being, watching the stars, taking her out to
01:06:19
dinner with your parents, like all you know, we care about that. And so this worry that people sometimes talk about
01:06:25
about oh people are just going to be on their phone with their AI relationship I
01:06:28
don't think is realistic for almost everybody because it gives us the chance
01:06:33
to you know hopefully sandbox some things about relationships and get over some dumb things with relationships and
01:06:38
then we can actually be with our fellow humans. counterargument would be that maybe there's going to be a bifocation,
01:06:43
a splitting of society where some people are going to become even more addicted to the technology because the AI is now
01:06:51
much smarter at retention. Like I know exactly what I need to say to you based on your brain, Dr. David, to make you
01:07:00
not put this device down. Yes. But fundamentally, I want to be in contact with my wife. I mean, that's that's the
01:07:09
evolution of hundreds of millions of years is that I want to make babies. I want to go and
01:07:16
eat dinner with somebody. And and as much as I might find my phone appealing, I'm not going to sit it across from me
01:07:22
at a nice Italian restaurant and sit there like that. So, I a lot of people do. >> Me and my me and my friends are at
01:07:29
restaurants cuz we have a rule where we don't touch our phones when we're at
01:07:32
date night. And I have to look around and I'm like, "Oh my god, like how is
01:07:35
how are all these guys getting away with this?" Like, but do you see what I'm
01:07:38
saying? Like some some people they just have a different sort of proclivity or they have a different wiring which means
01:07:44
that you know instead of doing the hard thing of going out there and going on a first date and being rejected,
01:07:49
pornography or a virtual uh wife might be a substitute for that. >> Yeah. No, I agree with you. There will
01:07:55
be bifurcations. One question I don't know the answer to, but one question is
01:07:59
what would that person have done in previous generations? You know, is it really the case that person would have
01:08:06
gone out and had a great successful relationship or would they always have had troubles relating to people?
01:08:12
>> Yeah, I sat with um a few neuroscientists and experts that are studied dopamine. Dr. Anna LMK was one.
01:08:19
>> Yeah, she's my colleague. >> She's your colleague. Yeah. And uh she
01:08:22
talks a lot about how we all have different types of addictive substances and like you know we will think like
01:08:30
heroin's addictive for everybody and alcohol's addictive and I used to think
01:08:33
of it on a spectrum but actually she said like for her addiction was romantic erotic novels.
01:08:39
>> Yeah. and she she almost ruined her relationship because of erotic novels,
01:08:42
which is something that I would read and just throw in the bit like but so maybe
01:08:46
this new technology is particularly addictive to a certain type of person. >> Yeah, I I think that's exactly right.
01:08:53
And I think we're going to see that with everything. I mean, >> the wild part about human society is
01:08:57
that there's so little that we have in common, meaning everybody is really different. And this is something I've
01:09:04
studied in my lab for for decades is this issue about what are the subtle differences from person to person. Not
01:09:10
big things like oh this person is a psychopath or this person has schizophrenia but the more subtle
01:09:16
things. I'll just give you an example like if I ask you to imagine to visualize let's say an ant on a purple
01:09:25
and white tablecloth uh crawling towards a jar of red jelly. Do you see that in your head like a movie or do you have
01:09:34
like no particular picture at all or somewhere in between? What what do you experience?
01:09:38
>> An ant crawling towards a jar of jelly. >> Yes. >> Yeah. I see a big black ant and then
01:09:44
this jar of jelly is like overflowing down the sides with a wooden lid on top of it and the ant is almost there.
01:09:50
>> Oh wow. Okay. So you have a Okay. So what you have I'm just guessing where
01:09:55
you are but you are on the end of the spectrum that we call hyperfantasia which means you have very rich
01:10:00
visualization. You're like seeing it like a picture or a movie. Is that is that accurate? Okay. I happen to be at
01:10:06
the other end of that spectrum called aphantasia where I don't have any visual
01:10:10
images at all. There's no I I don't see things visually in any way. >> And it turns out the whole population is
01:10:16
spread evenly along this spectrum. I'll just give a quick side note which is
01:10:20
that for many years I've been talking with Ed Catmull about this. He's the guy
01:10:24
who started Pixar films. So he's got all the patents on how to do ray tracing and
01:10:28
how to make these beautiful animated characters, right? Ed Catmull is afantasic like I am. And when he learned
01:10:34
about this, he got really interested and he gave the questionnaire to everybody at Pixar. And it turns out many of his
01:10:38
best animators and directors are aphantasic. They don't picture anything inside their heads. Now this seems
01:10:45
surprising and strange, right? But it turns out that if you are an aphantasia kid, you're going to become better at
01:10:50
drawing because you have to really pay attention to the subject out there and really have a dialogue with the page
01:10:56
with your pencil. Whereas a kid who's hyperfantasic might say, "Oh, I know
01:10:59
what a horse looks like." And just draws it. Okay. So anyway, >> got tracks.
01:11:03
>> Yeah. Yeah. So it turns out there's a real spectrum across the population,
01:11:07
meaning inside your head and my head, we're having pretty different experiences. But I've studied this along
01:11:13
dozens of different axes and everyone's got different things going on. Just as
01:11:17
one example, do you know about synesthesia? Have you ever heard of this? Forget is that forgetting or
01:11:20
something? >> No. Sesthesia is having a blending of the senses. So someone with sesthesia
01:11:25
might look at letters and it triggers a color experience in their head. So they look at J and that triggers green and
01:11:29
they look at M and that triggers blue and whatever. It's different for each person. Or you might hear music and it
01:11:34
triggers a visual experience. Or you might taste something, it puts a feeling on your fingertips or whatever. It's
01:11:39
just it's a blending of the senses. At least 3% of the population has this. It's not a disease or a disorder. It's
01:11:45
just an alternative perceptual reality. So if you have aphantasia, does that mean that you can't picture your kids?
01:11:53
>> It means that the way I picture them is not visually. I mean there's sort of a
01:11:59
very g but for me it's more motoric imagery and you know I I and audio imagery. Like I'm I'm imagining talking
01:12:07
to them and being with them and being close to them and probably some old factory imagery meaning you how they
01:12:12
smell and the whole thing like I have a very rich notion of what it is to be with my kids but it's a pretty terrible
01:12:18
visual picture. Not much there. >> So I imagine people at home have done that same experiment while they were
01:12:24
listening. Could they picture an ant walking towards a jar of jam and if they find themselves on the aphantas I can't
01:12:31
remember the two. >> Aphantasagasic. Yeah. Or hyperfantasic. So hyperfantasia is you can picture it,
01:12:36
aphantasia because you can't. >> Yes. >> What does that potentially suggest about
01:12:41
nothing? Now here's the interesting part. So we've done lots of studies about what this translates to in terms
01:12:46
of your capacities in the world. Nothing. Why does it translate to nothing? It's because you can
01:12:52
accomplish tasks in a hundred different ways. And so some people are doing this very visually. Other people are doing it
01:12:59
where they're like picturing it with their motor systems. Others are doing it, you know, as I mentioned, with sound
01:13:05
or smell or whatever, or others are doing it just purely conceptually, just thinking through how the steps would go.
01:13:11
But there's nothing there's nothing obvious other than this thing I mentioned about visual artists often
01:13:16
being aphantasic. Um, otherwise you can kind of accomplish anything. >> I run multiple companies that have
01:13:23
multiple sales teams. And one of the things as a founder of a company that's
01:13:26
often confusing is you find it hard to figure out where sales are. So about 10 years ago, I started using Pipe Drive in
01:13:32
my former company and it's also the reason why I switched over all of my commercial teams in my current media
01:13:37
company called Steven.com to use Pipe Drive as well. Not only do they sponsor this show, but they've been an
01:13:41
incredibly effective way of scaling our sales engine over the years. Pipe Drive is an easy to use intelligent CRM. And
01:13:47
at its very core, it makes your sales process visible through one dashboard, a visual pipeline showing every deal, what
01:13:55
stage it's in, what needs to happen next, and it's all in real time with no
01:13:59
delay. It doesn't magically close the deal for you, of course, but it does replace complexity with clarity. If you
01:14:05
want to join over a 100,000 companies already using Piperive, you can use my link for a 30-day free trial with no
01:14:11
credit card payment needed. Head to piperive.com/ceeo to get started. That's
01:14:17
piperive.com/ceeo. I'll see you over there. This is something that I've made for you. I
01:14:24
realized that the diio audience are striv goals that we want to accomplish. And one of the things I've learned is that
01:14:33
when you aim at the big big goal, it can feel incredibly psychologically uncomfortable because it's kind of like
01:14:40
being stood at the foot of Mount Everest and looking upwards. The way to accomplish your goals is by breaking
01:14:45
them down into tiny small steps. And we call this in our team the 1%. And actually this philosophy is highly
01:14:52
responsible for much of our success here. So what we've done so that you at home can accomplish any big goal that
01:14:58
you have is we've made these 1% diaries and we released these last year and they
01:15:03
all sold out. So I asked my team over and over again to bring the diaries back but also to introduce some new colors
01:15:08
and to make some minor tweaks to the diary. So now we have a better range for you. So if you have a big goal in mind
01:15:17
and you need a framework and a process and some motivation, then I highly recommend you get one of these diaries
01:15:22
before they all sell out once again. And you can get yours at the diary.com. And if you want the link, the link is in
01:15:29
the description below. I heard that you might have after many, many decades of people debating this,
01:15:36
you might have figured out the reason why we dream. >> Yeah. Yeah, it's actually after
01:15:41
millennia of people debating this. This is the cool part. So, okay, remember I mentioned earlier that if you go blind,
01:15:49
the visual cortex of the back of the brain gets taken over by hearing and by touch and by other things and it's no
01:15:54
longer visual cortex. Well, what we realized is that because we live on a planet that rotates into darkness for
01:16:02
half the time, the visual cortex, the visual part of your brain is at a disadvantage. So what I realized is that
01:16:10
the purpose of dreaming is to defend the visual territory from takeover from the
01:16:16
other senses. So every 90 minutes you've got these um you've got this very
01:16:21
ancient thing in your midbrain that shoots random activity into the visual system and only the visual system only
01:16:28
this very tiny part of the visual system. Every 90 minutes you just blast random activity in here and the reason
01:16:33
is you are just defending that territory against takeover. Now, the reason that all this came together is because our
01:16:40
colleagues at Harvard did an experiment where they took normally cighted people and they blindfolded them tightly for 60
01:16:46
minutes. And it turns out that 60 minutes was sufficient for the visual cortex to start responding to sound and
01:16:53
to touch. You could start seeing that takeover happening after 60 minutes. And that's when we realized, wow, this this
01:17:00
part of the brain really needs a way of defending itself now because the brain is a natural storyteller. If you blast
01:17:07
random activity in there, it'll, you know, put that together in some sort of
01:17:10
visual story about what's happening, mostly based on what connections are hot
01:17:14
from the day. But that's why we dream. So we we dream to stop the other parts
01:17:20
of our brain overtaking the visual part of our brain, um, overpowering it, and I
01:17:27
guess ultimately making us go blind. >> Yeah, that's exactly right. If we lived
01:17:30
on a different kind of planet that did not rotate into darkness, then we would we presumably wouldn't dream.
01:17:37
>> Would we even need to close our eyes? I mean, >> not necessarily. Yeah. It may be that in
01:17:41
the sleeping state, in the state of deep sleep, the brain is doing particular things like taking out the trash and
01:17:47
cleaning some things up. That might be necessary. Who knows? But yeah, I don't
01:17:51
think we would need to dream. We wouldn't need to blast random activity in there. um you know if if if our eyes
01:17:57
were always open for example and it was always light out >> are there other examples in the animal
01:18:01
kingdom which support this? >> Yes, thank you for asking that. It's this is why this new theory about why we
01:18:08
dream is taking off because we can make quantitative predictions across animal species. So for example in our last
01:18:13
paper we looked at 25 different species of primates, apes and monkeys and we looked at how plastic their brains are.
01:18:21
In other words, how flexible the whole circuitry was and how much they dream at night, which you can tell by looking at
01:18:27
rapid eye movements. You know, when you dream at night, your eyes are shooting back and forth like that. It's called
01:18:31
REM, rapid eye movement sleep. So, you can measure that in other animals, their eyes moving back and forth. So, we
01:18:37
correlated how plastic the brain is and how much dream sleep you have. And it correlates perfectly, which is to say,
01:18:44
humans, which are the most plastic, have dream sleep all the time. And by the way, when you're an infant, you sleep
01:18:50
for you have dream sleep for half of your sleep time, 50% of the time. As you get older, you get less and less dream
01:18:56
sleep because you just don't need it as much anymore. But anyway, when we look
01:18:58
across species, it correlates perfectly if you're a monkey that drops into the
01:19:02
world sort of already fully baked and you don't need to have much plasticity.
01:19:06
You don't have much dream sleep either. Interesting. Seems like a very strange thing. It
01:19:12
sounds like it's a very strange thing for the for the brain to do, but it also
01:19:16
is perfectly plausible based on everything you've said. >> Yeah. And by the way, I just want to
01:19:19
mention dreaming is across the animal kingdom. Everybody dreams. All animals dream at night. Even like animals at the
01:19:25
bottom of the ocean. Uh, yes. It's harder to measure stuff all the way at the bottom of the ocean. But fish do
01:19:30
have what is equivalent to dream sleep where you're just zapping activity in
01:19:34
there. And by the way, even animals that have gone blind, like there's a there's
01:19:38
a mammal called the blind mole rat, which lives in darkness and has eyes, but they're blind because over
01:19:44
evolutionary time, they've lost vision. But they still dream because the dream
01:19:49
circuitry is so ancient. This is so ancient that all animals have to defend themselves against the darkness by
01:19:56
keeping their visual systems going. And so even though the animal went blind, the rest of the brain didn't catch up. I
01:20:02
mean, that's how evolution goes. >> Funny. It's funny because it's kind of
01:20:05
like that evolution gave us this TV that comes on at nighttime when the real TV, our real life turns off and it just
01:20:14
puts on this fake TV set to keep that part of the brain doing something so that it doesn't deteriorate and um
01:20:21
atrophy. >> It's exactly right. Yeah, it's exactly right. Which means dreams are quite
01:20:26
pointless outside of just protecting our neurological matter. >> I suspect so. It might be that the
01:20:34
particular pathways that could travel down, you know, maybe there's some meaning there. I my own suspicion is
01:20:40
that it's like if I went to your bookshelf and I picked picked a random book up and I flipped to a random page
01:20:45
and picked a random sentence. I might find some meaning in that. I might say, "Oh, that was just the sentence that I
01:20:51
needed to hear." But it's not really. It's just that it has some meaning to
01:20:54
me. Anyway, the point is if you blast random activity in there, I might dream about something where I wake up and say,
01:20:58
"Oh, that was pretty useful." But the thing that I think gets overlooked is
01:21:03
that most dreams are totally useless and bizarre. Dr. David, what is the most important thing we haven't talked about
01:21:08
that we should have talked about as it specifically relates to people that are trying to improve their lives, get
01:21:15
better at whatever their subjective mission is and the brain. There are probably a lot of things, but
01:21:22
I got to say the thing that I've been thinking about so much lately is just about our political uh interfacing with
01:21:29
one another. And so I do feel that really learning the skills of dialogue with our fellow humans where we listen
01:21:38
to what they're saying and try to better understand what their internal model is.
01:21:42
It's not equivalent to agreeing with them. But it is saying, "Hey, somebody
01:21:45
is coming from this perspective. Let me see if I can understand that." I think
01:21:49
that matters a lot. And I also think that because we're so highly predisposed
01:21:55
for in-groups and outgroups, it's really useful to figure out how to complexify
01:22:00
those relationships. Meaning, how do you figure out the all the things that cross
01:22:05
cut in the relationship so that you say, "Hey, you know what? I shouldn't dismiss
01:22:08
this person as a member of my out group right away because actually they belong to the same group I do and
01:22:15
they love surfing as much as I do and they love golden retriever dogs and they you know grew up in my hometown and
01:22:21
whatever. Like finding those things uh explicitly helps the brain to keep these circuits on that are involved in seeing
01:22:30
another person as a person. We have we have all this social circuitry that is all about understanding other people and
01:22:39
when things get dehumanized that actually gets dialed way down. When we look at you know let's say a homeless
01:22:46
person or a drug addict or someone who we think of as our enemy or an out group that gets dialed down so we don't think
01:22:53
of them as a person anymore. We think of them as an object to to get around. Mhm.
01:22:58
So, this is what I think is really important is figuring out what we can do to keep that social circuitry still
01:23:04
going, which includes the things like eye contact and conversation. And this is this is one of the most important
01:23:10
things we can do as citizens in a rapidly changing world as it relates to things like dementia, which I know is a
01:23:20
fear that a lot of people have. A lot of people are suffering with dementia, I think increasingly. In fact, if I was
01:23:25
trying to save off dementia, what advice would you give me, David? >> Yeah, keep your brain active. Keep it
01:23:30
active till the day you die. Take on new challenges. And as soon as you get good
01:23:34
at something like, you know, sudoku, drop it and pick up some that you're not
01:23:39
good at. >> And in simple terms, why? >> It's because you're forcing your brain
01:23:43
to make changes. Otherwise, your brain says, "Okay, I got this. I got the world. I understand what's going on.
01:23:49
There's no real particular need for me to change." And the fact is that the
01:23:52
structure of the brain is always degenerating. And when you get something like a disease like Alzheimer's disease,
01:23:58
it degenerates much faster. And what you want to always be doing is building new
01:24:02
roadways and fashioning new paths that had not been walked before. >> So that there's more to degenerate,
01:24:09
which gives me more left over once that degeneration begins. >> Yeah, I that's Yeah, I think that's a
01:24:16
good way to look at it. your pathways are falling apart and if you can build new pathways which requires effort you
01:24:22
have to actually care and pursue and do the thing even as parts of the thing have fallen apart you still have ways of
01:24:28
getting from A to B >> what do I need to stay away from in terms of chemicals or supplement I don't
01:24:33
know or food I don't know >> yeah obviously there's just been a lot
01:24:36
more emphasis on getting good sleep and good diet and this stuff really matters I think that's really useful for the
01:24:42
brain I mean it's fascinating to watch what's happened in the latest generation
01:24:46
in terms of alcohol ol consumption. I live up in Silicon Valley and there's a
01:24:49
lot of people who have wineries just north of me and they're like selling half their acorage. It's absolutely
01:24:55
fascinating to see what's happening there. I will say I have a friend who's
01:24:59
who's in her 20s who said that she's in favor of bringing drinking back. Why?
01:25:05
Because she said we go to parties and everything's so awkward and no one knows
01:25:08
how to talk to one another. And so they're missing something else. they're
01:25:12
missing the the dumb mistakes category that we all got to enjoy growing up. So, it it is a really interesting balance of
01:25:20
of how abstious one wants to become. >> David, we have a closing tradition where
01:25:24
the last guest leaves a question, the next guest, not knowing who they're leaving it for.
01:25:27
>> Question left for you is, what do you wish most for our planet over the next
01:25:33
10 years? >> Well, the whole list are the top 10. >> Yeah. um can't be world peace.
01:25:44
>> You know, I think I would come back to this piece about the complexification of
01:25:47
relationships, which is to say, if we could just get a little bit smarter about understanding people out groups as
01:25:58
being humans with lives with their own thing going on. doesn't mean we have to
01:26:03
love them or agree with them, but if we can just get to that point, I don't think we'll ever hit world peace, but at
01:26:10
least we'd have slightly less polarization. So, I'm I'm definitely in
01:26:13
favor of that and I do think it's possible and I do think AI can help us get there by challenging us on these
01:26:18
points and saying, "Hey, that group that you've already dismissed as an out
01:26:23
group, what if I told you this story about this person? What if I introduced you to this person?" That kind of stuff.
01:26:29
and you know having there's all kinds of social movements that have sprung up
01:26:33
that allow people of different political opinions to come together in a room and
01:26:37
talk with one another again it's not that anyone has to change their mind but
01:26:40
they can say hey you know what I really like that person I thought that was a cool person a sweet person nice person
01:26:46
and and now I understand that somebody who I have seen with my own eyes has a different opinion on this than idea
01:26:51
>> is that wishful thinking to some degree >> I don't think so because these things
01:26:54
are happening all over the place and and >> the macro is is division isn't it It's
01:26:59
polarization echo chambers. There's now I think there's now 20 social networks
01:27:03
or some crazy number that have more than 20 million people on them which means that social networks are splintering off
01:27:08
into niches and interests and you know there's like Rumble and Bumble and then
01:27:12
there's like threads and X and Facebook snap Instagram and and what we're seeing
01:27:16
is more and more >> interest group and also the other thing with algorithms is we went from having
01:27:22
like a social graph where if I had a thousand people follow me those thousand people would see my stuff to now these
01:27:27
interest graphs where it doesn't matter if I have one follower or million followers, the algorithm is going to
01:27:32
decide who's interested in that thing and it's going to serve it to them
01:27:35
because that's the most retentive thing if you're a publicly listed company
01:27:38
that's driven by ad revenue. So, you've got this algorithm that's actually
01:27:41
forcing you into what you know into this into tighter and tighter and tighter echo chambers. And even as someone
01:27:46
that's been on social media 15 years and ran social media companies, this is one
01:27:48
of the great things I've noticed is when I had a million followers back in the
01:27:51
day, I would reach those people because they'd hit follow or subscribe. Now,
01:27:56
even on our YouTube channel, 61% of you don't subscribe. Um, and please subscribe. Um, and that's in part
01:28:04
because the algorithm is now doing the work of deciding who to show it to, who it will
01:28:10
>> on the basis of who will be retained. >> Yeah. Here's what I would say. There's
01:28:14
absolutely nothing new about echo chambers because it was always the case that your neighbors and your community
01:28:20
and whatever, that's what you thought was reality. I'm actually quite optimistic about the existent the mere
01:28:25
existence of the internet because at least we are exposed to the fact that there are lots of different points of
01:28:30
view. It used to be in places like the USSR, they controlled the media tightly so that everything you saw was a news um
01:28:37
approved story, but now you see all the points of view. Now, many of them might drive you crazy and whatever, but at
01:28:43
least you know that there are people out there that believe in that. And I think
01:28:47
that's really useful. If I had to decide between state control where there's a
01:28:50
single story or seeing the whole messy spectrum of opinions, I'd rather see the
01:28:56
latter. >> What about the middle? You know, they always one of the phrases that's again a
01:29:00
principle that's helped me think is that the truth is in the middle. And generally I try understand what the
01:29:04
middle looks like. So you've got state controlled over here. You've got aggressive algorithm that's sort of
01:29:09
reinforcing whatever you currently believe. >> Is there not some kind of middle ground
01:29:13
where um the algorithms have to let up a little bit and of course we're not going
01:29:18
to go for state controlled. Here's my prediction in 2026 is that there is a market opportunity for a new social
01:29:25
media company to come along because everybody is aware of exactly this problem that you're pointing out.
01:29:30
Everyone hates when they surf and they get served exactly what they're supposed
01:29:34
to get served and they get off after an hour or two and they feel like they've
01:29:38
wasted their lives. I think there's a real opportunity for a social media company to come along and say, you know
01:29:42
what, we're not building our algorithm like the other guys. It's not about just
01:29:46
trying to get engagement at any cost with, you know, um, incendiary posts, but instead we're looking for ways to
01:29:54
connect people. So, if you and I both love this particular thing, this particular cuisine or or location or
01:30:03
whatever it is, we get connected. We see each other's stuff and the algorithm
01:30:08
carefully, temporally sequences things so that we come to have a certain connection threshold before we find out,
01:30:15
whoa, you have a totally different political opinion than I do on on subject X. Wow, I didn't know that, but
01:30:20
I really like Stephen, so I'm going to lean in and listen a little bit more. I
01:30:24
think this is very easy to do and I think it can actually be part of the selling point of the media company is
01:30:29
saying hey we are here not to enrage you but to to actually build connection >> sounds like how social media started
01:30:37
>> yeah it's a return >> I think there's probably a neuroscience
01:30:42
basis as to why we ended up yeah >> no it's an economics basis >> but the fact is there's now an economic
01:30:49
opportunity now that everyone sees the landscape >> what I'm trying to say is that that
01:30:53
social network wouldn't be that retentive by design because it wouldn't trigger my dopamine. It wouldn't be a
01:30:58
slot machine like in Tik Tok is a slot machine. Ping ping randomized returns. Ping ping ping. Dopamine hit. Ping ping
01:31:05
ping. So this other social network that wasn't playing with my dopamine in such
01:31:09
a way. I don't know whether I'd be addicted enough to return. Therefore,
01:31:12
they wouldn't sell their ads the economic return. Therefore, they wouldn't do very well.
01:31:16
>> Here's the thing. I don't know if the story is that simple that we all want to
01:31:19
do slot machines all the time. >> Exactly. Because the fact is that a lot of people go to Las Vegas and do slot
01:31:25
machines sometime, but we don't do that all the time. It's kind of rare actually. What we really desire are
01:31:31
meaningful connections. We really desire feeling like, hey, you know what? I met
01:31:36
this person online that I'm following and he's following me and we really
01:31:40
connect on all these points and oh by the way, I then found out interestingly he's got a totally different opinion
01:31:46
about Iran or abortion or whatever than I do, but that's cool. Now we're we're
01:31:50
listening to each other. It kind of goes back to your point earlier about at the
01:31:53
very start where we're talking about, you know, the brain having an internal
01:31:56
battle like, do I want the cookie or do I want the salad? >> And unfortunately in the world we live
01:32:00
in, you know, this the cookie is going to give me a dopamine hit. >> Yes. But we don't eat cookies all the
01:32:05
time. This is the point. We do eat salads much of the time because we're not just unconscious automaton that are
01:32:12
doing the cookies. >> Dr. David Eagleman, thank you so much for the work that you do. I'm going to
01:32:16
link your book below um so everyone can read this book. You've got a new book on
01:32:20
the way which I'm very excited about as well. What's that book going to be about
01:32:22
and when is that out? >> That's about the Ulisses contract and that'll come out in 2027.
01:32:26
>> June. Okay. Um for anyone that wants to know how to change your life by changing
01:32:29
your brain, I think this is the perfect book to read. It's a New York Times bestselling um author. Um and the book
01:32:36
is absolutely fascinating. It was actually learning about this subject matter in LiveWire that helped me to um
01:32:43
pursue more of a growth mindset and just a growth mentality across my life and to
01:32:46
realize that if I'm not something now, it doesn't mean that I can't be
01:32:49
tomorrow. So, thank you so much for the work that you do, David. And, um, it's
01:32:53
been truly illuminating, and I'm sure my my neural pathways have expanded in
01:32:57
really important ways because of this. Great. Thank you, Stephen. >> YouTube have this new crazy algorithm
01:33:02
where they know exactly what video you would like to watch next based on AI and all of your viewing behavior. And the
01:33:08
algorithm says that this video is the perfect video for you. It's different for everybody looking right now. Check
01:33:15
this video out and I bet you you might love