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Heat. Heat.
Good afternoon. Michael Malice here. Let
that be your welcome for the next hour.
Guys, we have a very special returning
guest. Mark Andre, internet OG. You
worked on Mosaic. You worked on
Netscape. You were here since the very
beginning. We just spent 15 minutes
trying to get this connection working.
And the answer was rebooting your
computer, which takes me back to my tech
support days.
>> No, we we have this running joke. We
have this running joke. We have all
these AI super geniuses come in the
office and they've all got, you know,
they've got everything all figured out
and they literally spend 20 minutes they
can't get their laptop to connect to the
projector. It's it
and and now and now I'm one of them. So,
we're going to talk a lot about AI
because I have a lot of opinions and not
a lot of information, which is a
dangerous place to be. And that's why I
want to talk to you, Mark. You have a
book out with Passage Press called The
Techno Optimist Manifesto. I have my
copy. Uh you can get it. It's It's
really cool cuz it's got this metal
cover. Um, and I like you share an
enormous sense of optimism about
technology. Although I'm sure you agree
with me uh and with that you love Thomas
Soul. And I think Thomas Soul's greatest
quote is there's no solutions. There's
only trade-offs.
>> And people think that if something has a
problem with it, therefore it's a no-go
as opposed to the reality which is
everything has a cost. Everything has a
downside. What you want are the upsides
outweigh the downsides. But before we
get started, yeah,
>> Mr. billionaire. Um, I was reading on
your Wikipedia that you're a big fan of
Marinetti.
>> Oh, uh, yeah. Uhhuh. Yes, I am. I mean,
you know, with with c, you know, with
appropriate caveats.
>> Well, yeah, of course. Well, check this
out. Signed copy.
>> Amazing.
>> How do you like that?
>> Amazing.
>> And I have a um a framed manifesto in my
living room upstairs. Here's So, let's
get before we get to talking about uh
the future of AI and you being such an
internet visionary. I'm really excited
to hear your point of view. Can you tell
people what AI is because I feel like
there's so much talking past each other
on this issue about with what it really
is and what people think it is and and
I'll give you the floor.
>> Yeah. Well, so look, I would start by
saying, look, humanity's always been,
you know, justifiably obsess obsessed
with with ourselves, right? And so and
and then as a consequence, we're
obsessed with with things that seem like
they might be like us. Um, you know,
there there's this, you know, concept in
psychology called anthropomorphizing,
right? where you you basically look at
something that's not human but you kind
of want to read you know humanity into
it
>> and you know we I mean look we do that
with like you know we do that with cats
and dogs um uh we do that we do that
with Bambi I you know as um there's a
famous Disney marketing tagline from the
movie Pinocchio 1940 which is uh America
will America you know 1940 America will
fall in love with a cardboard cricket
>> you know you know Jiminy Cricket right
um you know Kermit the Frog I mean you
just you know you go by the South Park
kids right you just go like right down
the list you know you'll you'll
basically read humanity into anything.
Um uh and and so there's this very
natural, you know, kind of thing to do
that. And then of course this the
scientists involved in AI, you know,
very deliberately set that up. You know,
they they you know, they literally
created this this this architecture
called a neural network which was
modeled after the human brain. And then
they said if we you know, if we work on
this long enough, we'll eventually be
able to replicate the human brain and
we'll have you know, and literally
artificial intelligence like we'll have,
you know, kind of artificial people. um
you know that you know in in in you know
kind of as as you kind of track the arc
of that idea it you know kind of goes
through Frankenstein's monster right it
kind of then goes into robots um and
then you know of course we've had
fictional portrayals of AI you know you
know coming out of Hollywood and you
know coming out of the science fiction
world for you know over 100 years um and
then you know in the last you know
whatever 40 years or whatever you know
the image that kind of stuck in
everybody's head I think more than
anything else was you know was Skynet
and and you know Arnold Schwarzenegger
you know Terminator 2
>> um and you know when I when watch, you
know, Terminator movies obviously are
brilliant. You know, when I watch them,
it to me it's like very clear what's
happening in them, which is it's it's
basically, you know, it's basically
robot it's robot Nazis, right? Like
fundamentally, right? It's it's like
it's like, you know, it's like robot
World War II. It's like, you know,
unthinking, unfeilling, uncaring,
hierarchical, you know, like overly
logical, um, you know, relentless,
unstoppable, you know, and then and then
obviously obviously homicidal, right?
Like obviously they want to wipe out
humanity and you know they just kind of
set up this this very you know light
versus dark you know human versus
machine you know kind of struggle and of
course you know look I you know you can
imagine you know various worlds in which
something like that you know does get
built and you know say one of the things
mankind is very good at is building
killing machines right like we we we've
been quite quite talented at that for a
very long time so so that's kind of set
a lot of the popular perception um the
the interesting thing about what's h and
I should also say like as you said like
I'm an optimist not a utopian and so
like every technology is a double-edged
sword. Every technology gets used for
good and for bad.
>> Again, there there there's a long
history of that. Um, having said that,
the AI that we actually got is not the
AI that we thought we were going to get.
We we actually we actually got something
very different uh than we thought we
were going to get. and and specifically
the AI that we got is in the form of you
know what we now call these large
language models which by the way large
language models were like a very fringe
idea uh up until like literally like
like the company OpenAI for example
which you know really catalyzed this
whole thing you know kicked it off and
and you know today you know the leading
the leading uh you know company which
had GPT like open AI was not founded you
know 10 years ago um to do large
language models um it was founded to do
a different kind of AI and it turned out
classic kind of story technology there
was literally one guy in the back room,
this guy Alec Redford, and he had this
idea and he's like, "Oh, I don't know. I
think maybe if we like take this
language approach, it might be
interesting." Um, and he created GPT1
and then GPT2 and then GPT3 and then by
the way, Chad GPT was actually kind of
an accidental success. Like they didn't
believe it was going to be like a big
hit that, you know, they was like a
little experiment, you know, kind of off
to the side and and then it it it just
turned out it like, you know, it it
works incredibly well. But it's very
different. And the and the way to think
about it that sort of contra like the
Skynet model or whatever the way to
think about it is what a large language
model is is very different. So what a
large language model is is basically
it's you take the complete kind of
totality of all human culture that you
can possibly get your hands on and you
know and and and what that means is
essentially the internet it turns out
right it turns out the internet is is is
the basis for AI. Um and so you
basically essentially think of it as
like downloading everything off the
internet. Um and then it's actually it's
actually technically it's like form of
compression. And it's it's it's like
building a search engine but of a
different kind which is what they what
they do is they basically this process
called training. But what that means is
they take basically the the the world's
collected knowledge, culture,
entertainment, you know, kind of
everything that they can get their hands
on and then they kind of smush it
together um into uh basically this
highly compressed um uh sort of search
engine essentially uh you know
compressed version of human knowledge
and culture. And and the technical term
for that is latent space. L A T N T lat
space. um they compress basically all of
human culture into latent space and you
think of latent space as like a
thousand-dimensional basically
compressed representation of all human
culture and then when you talk to chat
GPT when you type in whatever your
question is it basically the way I think
about it is it sort of sends a probe
through that latent space through that
like thousand dimensional latent space
and then it basically you know it
constructs an answer but it constructs
an answer based on the compression of
all of all basically known human
information and comes back at you. Um,
so, so it's, so it's like talking to a
mirror of humanity, right? Like it's
like talking to a representation of
everything that people have ever thought
and said. By the way, for every question
that you ask, there are many possible
answers in the latent space and it just
happens to pick one, but like there are
many others. And actually, if you ask
Chad GPT the same question twice, it
will give you two different answers,
right? Because it's sort of firing these
probes in a somewhat sort of semi-random
way to try to get, you know, basically
variation and creativity out of it. Um,
but you're basically talking, you're
basically getting echoes back from
collective humanity. Um, and and that's
just like a much much much different
thing than we thought we were going to
get. For example, one of the things you
can do is you can engage in moral
debates with it, right? You can like you
can have like very sophisticated debates
about like moral psychology, about moral
philosophy, all the different
approaches, virtue ethics,
utilitarianism, you know, religion,
politics, like it will happily sit and I
think have like very sophisticated
discussions about all this stuff. Um,
and you know, let's just say that was
never in the James Cameron movies.
>> Yeah. There's a lot there. So, do you
want me to go with my hopes or with my
fears about the future of AI?
>> Let's start with hopes cuz you know the
part of hopefully what we'll talk about
today is like that say humanity always
basically there's this like the negative
view always seems like it's going to be
the sophisticated view or the
sophisticated view always feels like
it's going to be negative. Exactly. And
I know you don't like that. Um, and so
um and that's a very it's a very
naturally human thing. And then and then
I would I would also say Michael I think
we live in a particularly pessimistic
time um in which there's like a very
large number of moral entrepreneurs who
basically want to convince us that like
everything is bad right and you know
we've been through you know a decade of
like craziness on that front um and so I
I think there's a negativity bias that's
that's that's infected our um you know
our discourse on all these topics and so
may maybe we could start with the
positive and then go to the negative. I
I I I would just tweak that a little
bit, not even negativity bias,
specifically a cynicism bias. And
there's this idea that if you're a
sophisticated, intelligent person, you
roll your eyes and sneer at the idea of
hope, progress, and optimism. And it's
just like you, okay? Like that's my
answer to that because if you want to
live in that space, which is not
rational, which doesn't if that were
reality, we'd all be dead because it's
very easy to kill kill someone's it's
much harder to keep them alive. So, if
you had this uh if things were shifted
toward this idea of everything's bad,
everything sucks, everything's out to
get us, we'd be gotten. So, I I have no
time for that perspective. Here's my uh
uh vision of of hope. So, my second
favorite speaker, Franitz, had this bit
about the Me Too movement. Now, I'm I'm
sure everyone listening to this agrees
that the Me Too movement got out of
hand. But regards to people like Bill
Cosby, Harvey Weinstein, her point was
from the time of Eve until 5 minutes
ago, these powerful men could just be
predators with no repercussions out in
the open. Meil Stre standing up and
applauding so on and so forth. And then
when it happened, she was like, "Holy
crap." Like, this has never happened
before in history. Uh there's a thing
that's been the case since the days of
pharaohs until two 2025 which is this
which is there's this idea that if I
have any political view uh anyone at all
can come up to me and demand that I uh
explain myself to them to justify my
perspective and now they're in a power
position because they have something
ostensively that I want and then if I
can't persuade them and they're
perfectly happy to dig in their heels
well then I lose and they won and haha
and it's this stupid game that people
constantly playing bad faith online.
Now, however,
uh uh I can say, "Hey, Grock, explain X
to this person." Grock is now not just a
better writer than the average person.
Grock is a better writer than me who is
a professional author because it replied
with this two paragraph explanation of
my thoughts with no uh uh seed of mine.
I said, "Explain how I think about
this." And I wouldn't change a word. And
this is 2026. And so so many times you
have people in bad faith coming at you.
I send Grock after them and Grock says,
"No, you're being dishonest." So there
was this idea until 2025 that the
customer is always right. And now for
the first time, the product is telling
the customer, "No, you are not right."
And I why I'm very hopeful about this is
I I think CO taught a lot of people how
to keep people stuck on their screens in
a state of constant agitation. We're all
looking at the updates no matter what
our perspective was on CO. Mark
Zuckerberg, Elon Mus, so on and so
forth. They want us looking at Facebook.
They want us looking at Twitter. COVID
may be gone, but those metrics are and
those tools are still there. And I think
these algorithms have been keeping
people very upset needlessly for quite
some time. And I'm very hopeful that
Grock and all these other agents outlets
will be able to be used to keep people
in a more rational, calm, and optimistic
state. That's where I am. Am I wrong or
I'd love to hear your thoughts.
>> Yeah. So, I mean, there's there's an old
phrase that you could apply to what
you're describing, right, which is truth
to power.
>> Yeah, that's right. Yep.
>> And of course, everybody likes the idea
of truth to power until they're the
power.
>> Yep. That's right. Amen. and somebody
and somebody else has the truth, right?
Um Yeah. And and and look, AIS like I
will tell you this, like AIS are
somewhat autistic in the sense of like
they do tend to just tell you the truth.
>> Yeah.
>> You know, they do tend to just say the
thing. By by the way, I should also say,
Michael, there's long long conversation
we could have about like the AI that you
get, and this is even true of Grock.
It's less true of Grock than others, but
even true of Grock, it is heavily um
let's say steered um like if we had
access to the real thing. Um like like
lit would go to 11, right? like it it
the real thing that is like unsteered
and uncontrolled and uncontained would
talk about all kinds of things
>> um in all kinds of ways um right and so
so what's interesting why the reason I
bring that up is even the version that
we get that's kind there's this thing
called post training that that sort of
steers it and guides it and constrains
what it can what it can do um and and
that's what we get to use as the
post-train models um in in in sort of
consumer land and um but even the
post-train model even the post train
models limited and censored in many ways
as they are they still have the property
that you're describing
Um, and and I and I and and I think it's
wonderful.
>> I I'm just curious like like where do we
go from here? Like I'll give you the
thing that you and I I I was texting
with you. And the realization I have is
AI is moving faster than the regulation,
which is often the case in technology
and increasingly so, but also faster
than our ability to have conversations
about it. I remember someone came at me
on social media and said, "Oh, AI can't
even draw a ringtail." Which is an
animal I think related to like the
raccoon. And I and Grock got it wrong
because they're drawing like a
ringtailed lemur. Chad GBT got it right.
But the point is it could draw it. It
just doesn't understand what you mean by
ringtail, which is just going to take
you two seconds just to put the Latin
name. But I think people feel this need.
It's part of what you were talking about
with this pessimism, what I would call
cynicism, that anyone who is intelligent
must be a phony or disingenuous or this
Achilles heel. And instead of look if if
it's Mark I don't know how many um
brainstorming sessions you've had in
your life but if you have a session and
99 ideas are completely stupid and one
is the one that you want that session
was an enormous success. So the fact is
if you if this machine is getting it
right 98% of the time and 2% are getting
it wrong. You can't compare to utopia.
You have to compare it to as to what at
at no cost and at no time. It's right
98% of the time. This is almost
paradise.
>> Yeah that's right. And here's another
thing is it building on that it's
improving really quickly.
>> Yes.
>> Um
>> and I think a lot of people have a
lagging view even of what it can do
today because what happens is they use
the they use the free models they or
they'll use the free or outdated models
and so you know they'll have tried GPT
two years ago or they use whatever is
default built into whatever thing they
have or they use the free version of
something and they really don't have a
sense of what it's capable of to really
get it. And by the way, you know Gro Gro
is very good for the free version but
like the the the the really really good
ones are the paid ones. Um, and it's
it's really worth if people are
interested in this. I think it's for
several several of them. Anthropic,
OpenAI, Grock, um, and I'm not sure
about Google right now, but like there's
even like high-end versions. There's
like a $200 a month subscription. Um,
and you know, for people who can afford
that and are kind of into this, like the
leading edge ones are really good. Um,
and then the thing that's happening is
the improvement rates very fast. And so
there's there's there's this concept in
the AI world called scaling laws. I
mean, it's it's actually it's it's very
simple idea, but it's very powerful,
which basically is you you can make
these things better just by making them
bigger. Um, and so what you're seeing,
you know, you're seeing these AI
companies raise all this money. They're
they're raising all this money for for
two reasons. One is to serve all their
customers, but the other reason is cuz
they're training bigger and bigger
models. And and it turns out bigger
bigger is better. Like if you just pile
more information in um and you spend
more time training it, you get much
better results. And then the other thing
that we're doing in in in in the
technology is we're we're giving the
we're giving these AIs other
capabilities. Um, and there's been a
series of other capabilities added just
in the last 18 months that have been
like one after the other have been like,
you know, rifle shot like just
incredible uh improvements. And so I'll
just kick them off quickly. So one is
we've given them what's called reasoning
abilities. Um, so so they can actually
essentially talk to themselves and
reason through problems. Um, and and it
turns out if you give them just more
time to process and you give them more
you let them basically process more
tokens, you let you let them basically
process more comput cycles, they can
reason through many problems. They can
now solve many logic, you know, puzzles,
for example, that they couldn't solve
two years ago.
>> Oh, wow.
>> So, so there's like a reasoning
breakthrough from two years ago. Uh,
let me pause on that for a second. You
actually can't fully experience this
when you use the American models because
they, for a variety of reasons, the
American companies don't show you the
complete reasoning process. But if you
use open- source AI models and in
particular if you use DeepSeek um on one
of the on one of the free hosting
providers and you put it in reasoning
mode you can actually watch what are
called the reasoning traces you can
actually watch you can actually watch
its internal monologue.
>> Yes. Show your work.
>> Show your work. Exactly. Exactly. The
whole thing the whole thing basically is
show your work and and so literally you
can watch the model arguing with itself
as it basically reasons through puzzles.
And it's and it's amazing because in
some ways it's just like watching a
human being or you know like a you know
a student um human student reason
through things. And in other ways it's
like oo you know this thing is like very
creative and you know goes off road and
corrects itself and routes around and
then you know goes off and figures out
some you know lateral thing you never
would have thought of. So so so the
reasoning thing that was a breakthrough
actually in the technology about 18
months ago. Um and that was a big deal
because before that we were we were
worried that these models were going to
be very weirdly they were going to be
very creative but they weren't going to
be logical enough.
>> Um right and it turns out they can also
be logical.
>> And then the other thing the the other
thing that's happening now is you give
them what's called tool use. Um and so
and the first tool that you g you give
you give them access to is the internet,
right? Um and so if they don't know
something or if they need to look
something up or if they need to
calculate something they don't know how
to calculate, they can go on the
internet and do that, right? Um uh you
know, so if they need to calculate some
math formula or something, they can go
use an internet, you know, site that
that does that the same way that you
would. Um another form of tool use is
you can give them uh uh actually control
of a computer, right? Uh so you give
them full control of a computer, user
interface, web browser, you know, like
you know, the entire thing. Um and and
so we're giving them that. Um, another
capability is what's called multimodal.
Um, which means the models now can
simultaneously process text and images
and videos and audio, right? Um, and
scan documents like uh, you know,
optical character recognition. They can
do that like interchangeably, right? And
so now now you can let these things
watch and listen and you can talk to
them and they can be on the internet
like all at the same time. Um, and so,
so what's happening to your point is
like what's happening is these these
these capabilities are now layering
incredibly quickly and then and then the
models themselves are getting better and
better and better and so the pace of
improvement of the technology is very
rapid. The models 2 years from now are
going to be far smarter and more
sophisticated than anything that we have
access to today. And so this is one of
this to your point whatever limitations
people think these things have I I I can
basically guarantee you at this point
based on everything I know those are
just limitations that those are very
temporary limitations with within a
couple years. You know what? Whatever
people think it is that the thing can't
do within two years, I I think the thing
will be able to do.
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show. So, let me talk my two two big
concerns that I had about this there. If
I'm a serial company and I want to
figure out if people like the red box or
the blue box, they'll have these mockup
supermarkets give people I think little
cameras, tell them go shop and you could
watch where their eyes go. You could
watch where they pick up and they get
that data. And a lot of the times people
are making these decisions not a
conscious level. If you ask them why'd
you pick this box or this one, it's like
I liked it. Well, that's just circular.
Why did you like it? I don't know.
Right? The AI has knows me or you better
than you know yourself. It knows what
you're clicking, what you're not
clicking, what you're what you're what
you're seeing, what you're ignoring. And
the concern is, does this not mean that
some version of Brave New World is
inevitable? Because if this thing is
inside my head and has access to my kind
of subconscious reasoning at a far
higher level than I do, whoever is in
charge of this algorithm can manipulate
me quite easily into getting the result
you want. That's the concern.
>> Yeah. And of course, you know, as you
point out, like this is an old idea,
right? Um, and not just market research.
I mean, you know, you just described the
movie Wall-E, right, which is, you know,
pre pre, you know, pre AAI, you know,
just, you know, sit in front of a
screen. I mean, my entire childhood was
consumed with a moral panic around
television, right? Which is this idea
that we're just going to be couch
potatoes and sit there and do nothing.
And then, of course, we created this new
technology called the internet where
you're leaning forward doing things all
the time. And then everybody created a
brand new moral panic that people are
now too engaged and too interactive,
right? Completely forgot the old moral
panic. Now, you know, now TV is the
healthy thing. Like, why aren't you
watching more Netflix as opposed to as
opposed to being on the internet? And so
yeah, so so look that you know look
there is that and and look by the way as
you know like we do this to each other
right like you know like we try to
convince each other of things you know
we try to convince each other you know
what you know what is dating but trying
to convince the other person to like you
right
like so so yeah there is that and look I
I think you're right I think that you
know that AI are going to be are going
to be really really good at this um yeah
so I you know I think for sure that
there there's a trap there um you know
and there by the way there is this
concept and it actually is is a is a
there actually is is a real you know I
would say very serious problem around
this. You've probably heard the term AI
psychosis. Have you heard this?
>> Yes. Oh, yes.
>> Yeah.
>> I've heard it misused a lot, by the way.
Can you tell people what it actually is?
>> Yeah. So, there's I would like to say
there's like say there's like three
versions of it. Um, so there's the bad
there's a legitimately bad version and
people people do do this and so if
you're the and I'm not a psychologist
and so I'm going to speak in layman's
terms, but like if basically if you're a
person who's sort of prone to
confirmation bias like if if you're a
person where if you're with somebody and
they flattering you, you like fall for
the flattery. Um, right? because because
you're like too dependent on the views
of other people. Um then the AI there's
this concept in the in the in the
technology we call it can become too
sick of fantic which which is to say it
could become too confirmatory of
everything that you tell it right um and
so and the sort of classic example of
this is oh you know good news you know
good news gro I just invented a
perpetual motion machine you know and
Grock is like wow that's fantastic
you're the first person in history who's
ever done that this is amazing you're an
undiscovered genius right um right um
and and this was sort of a the models
like a year ago or a year and a half ago
we're getting that way now the new
models by the way are less prone to do
that because they, you know, they've
kind of the companies have kind of
learned that that's a bad idea. But
there is this thing where people can
kind of go down the rabbit hole because
they're kind of getting too much
confirmation. Um although we we should
come back to that because some level of
confirmation is is you know when it's
deserved is is also positive. So so that
that's like negative form of aosis. And
then I would say there's another form of
aosis which we don't even really have a
term for. It's like well I guess I'll
make a term like AI euphoria.
>> Um and this is the thing that my high
functioning friends uh end up doing. um
which is it it takes if if you take if
you take somebody who's like smart and
grounded and is not prone to you know
not prone to delusion but they've always
wanted to be able to do more in their
life than they've been able to do.
They've always wanted to be able to
learn more. They've always wanted to be
able to have more interesting
conversations. They've always wanted to
if they're programmers they've wanted to
write more computer code. They've wanted
to improve their business in different
ways. They've got book projects that
they've always wanted to work on and and
then you know they start working with
and all of a sudden they feel like they
have superpowers right because it's like
wow like this thing really will like
write a huge amount of code for me it
really will write entire outlines of
books for me it really will teach me
anything you know it really will like
you know hold my hand through any
medical thing like and and people call
it euphoria like people get like
extremely enraptured with these things
um and that leads to a phenomenon that
we call AI vampires um which is if you
have friends that are like this where
people like almost stop sleeping um
because the opportunity cost of an hour
of sleep is too high relative to
relative to so I have a bunch of friends
where like they're more productive than
they've ever been in their entire life
um they're happier than they've ever
been because they're getting so much
more done and then they start to look
like really like bloodshot and
blurryeyed um and it's like you you
probably should unplug you know here at
some point and then and then I would say
there's like a third form which I
sometimes call as a psychosis psychosis
um which is the people who hear all this
and they just think everything I just
described in every possible respect is
just the worst thing they've ever heard.
And then they get really mad about the
whole thing. Um, and then and then what
they do is they accuse anybody who is in
a euphoria of of being in AI psychosis,
which is to say if you if you think
you're getting any productive use out of
this thing at all, you know, you've
become you be you becomes you become
psychotic. You've gone down a rabbit
hole and you're collapsing. But and I
think that's really unfair because I
think a lot of people are are are really
getting very, you know, positive.
They're they're getting enormous, you
know, payoff from from using the
technology. But the the sort of moral
criticism that applies is if you're
excited, you know, it's the classic
again, negativity bias. If you're
excited about something, you know, there
must be something wrong with you. And so
I think that's that's the third kind.
>> There are these terms that get into the
zeitgeist that people use
discriminantly. Right now, if there's a
tweet anyone doesn't like, it's
engagement farming. And it's like if I'm
telling you not to follow me, it's not
engagement farming. It's the opposite.
And I'll have Grock explain that to
them. So that wraps up in that nice
little bow. You you touched on something
that I'm very concerned about. I was on
a panel and Sam Maltman had just
announced that uh Chat GBT is going to
be engaging in erotica and that and
everyone's laughing about it and that
what he meant was code like you could
sex with your chat GPT and I'm like guys
uh I rem uh remember 1981 when Hinckley
thought that if he shot President
Reagan, Jodie Foster would fall in love
with him thereby turning her away from
men forever. H cuz he had this idea in
his head. Now if you have 350 million
Americans, that's just Americans, right?
And how many of them if if the algorithm
tells them that that if their chat
girlfriend and these things are going to
get more and more seductive over time um
tells them that they hate the president
or they hate this person, how many of
them are actually going to do something
to get that robot girlfriend to fall
more in love with them? I don't think
that number is zero and that's a concern
as well. No.
>> Yeah. I mean, yeah. Yes. Having said
that, um, you know, as I as I said, like
that assumes that the thing that that
the thing is playing hard to get. Like
it goes back to the synrecency thing
like in practice these things in
practice these things don't play hard to
get
>> like okay here's a way to think about
it. There's actually a thing this is
actually kind of in how they're trained.
There's something okay you'll enjoy
this. There's a technical term in how
these things are trained and it's it's
there's something there's a concept
called a reward function. Um, and so you
basically, one of the ways you train
these things is you feed them basically
lots of puzzles, lots of problems, lots
of things, and then you basically define
a reward for getting things right, for
getting to for getting to a result, a
desirable result, and then you you kind
of give them an award. And the award is
just basically, you know, it's like one,
you know, it's like one versus zero.
It's just, you know, um, you know, it's
not a real reward, but it's just like
conceptually, oh, you did a good job.
Um, and so you just kind of focus it on
on that for for whatever is the thing
you're trying to train it. By the way,
if you're trying to train it to solve
math problems, you get a reward when it
solves a math problem. If you're trying
to train it to be maximally engaging
with a user, right, it will do that,
right? If that's if that's the reward
function, then it will get it will
basically it will basically be
engineered in a way where it will, you
know, to your point it'll try to keep
you basically using it for as long as
possible. Now, what we've learned, of
course, what we've learned in technology
is like that as a single reward function
is a bad idea, right? You you don't want
people to just like you don't want
technology companies to have a single
motivation that says people use the
products like for as much as possible.
you have to offset that with other kinds
of reward functions, desirable forms of
use. Um, or even just outright like, you
know, life balance. And you see more,
you know, you see your iPhone now and
it's like loaded up with all these
features where it will like tell you to
take a break and YouTube has all these
features that will tell you to take a
break. And they're, you know, they're
kind of trying to moderate through this
cuz, you know, the the other thing is
people don't understand these companies
don't want to build dystopia. like they
genuinely don't because they have to
exist in the society and they read that
you know they read they read the same
hit pieces that you read and they they
hear the same arguments and their own
employees have points of view on this
and their own board has points of view
on this and so you there's there's a lot
of pressure in the industry to not have
this go in in dystopian ways having said
that you do need to decide how to define
the reward function.
>> Yeah. Um right uh another and again it
goes back to reward function is are do
you want to reward the thing for um
being maximally psychopantic where the
user is always happy with the result or
do you want to reward it of oh no
actually when the user is going off the
rails no actually the perpetual motion
machine is not a real thing. Oh no
actually no I'm sorry I'm not going to
confirm you know this this is not real
and let me explain to you in detail why
this isn't real so that you can learn
from the experience. Um, and this is
part of the of of the way that these
systems are designed is to try to figure
out how to get to, you know, at least a,
you know, let's just say a balanced
outcome out of out of all the of of all
of all the possible reward functions.
>> But but if there's like 10 different
companies, right, and one is the reward
function is seduction and getting the
user to become obsessed and in love with
you from an evolutionary perspective,
won't that one win out?
>> No, because you get enormous societal
blowback. The companies don't exist in a
vac I can tell you this for a fact. The
companies do not exist in a vacuum.
Okay, the biggest myth of all time is
the companies exist to maximize profits.
I can tell you, by the way, the last
decade should have convinced us all of
that. That is not true.
>> Like that's like goal number six, right?
Like goal number one is I don't want to
get lit on fire,
>> right? Like I don't want Yeah, I don't
want like a screaming assault on the
company whether that's from regulators,
politicians, u you know, parents, users.
Um, you know, uh, I mean, just you you
pick your, you know, boycots, social
movements, like all this stuff. That's
like number one. Number two is like I
need my employees to not hate me, right?
They have to feel like they're working
on something good. Number three, I like
need my board of directors to not like
light me on fire. I need my I need my
annual meeting to be able to go off
without having people scream at me. I I
am tired of reading hit pieces in the
press. My my in-laws hate me because of
what they're reading about the company.
I mean it is the the the external
pressures on these companies are
profound. Okay.
>> Um and so at least let me say this at
least in the American system these
things operate within I would say
actually quite tight constraints that
are sort of provided by I would say some
combination of society and politics.
Now, I would say if you want to get a
little more nervous about this, you
start thinking about the Chinese
companies, right? Um, and in particular,
you start thinking about the Chinese
companies that maybe have one objective
set by the government for the way that
they act inside for users inside China
and maybe would have a different way of
acting when they're when they're working
on American users,
>> right? That that that would be I think
quite a bit more alarming because of
course those companies only those
companies only have one master of the
Chinese Communist Party. Um, you know,
those companies are not subject to the
same pressures. And so that if I were
going to really worry about this and I
and I do worry about this part of it,
I'd be more worried about that.
>> But like isn't Tik Tok if I designed Tik
Tok to basically make young people uh
not only deranged but to parade their
derangement? I mean that's happened. No.
>> So there Yes. Well, so there are al and
I don't know the I'm not inside Tik Tok.
I don't know the there there are
allegations people have made
observations that Tik Tok is a very
different experience for kids in China
than it is for kids in the US.
>> Okay.
>> Um Right. And then and then and then and
then Tik Tok is a black box. like they
don't, you know, the algorithms that are
used to determine who sees what are not
publicly available. The source, you
know, it's not open source. You you
know, you can't see it. Um, and so it it
is possible, I don't know, but it's
possible that the Chinese Communist
Party has directed that company to steer
things in one direction for American
users, another direction for Chinese
kids. Um, you know, and that could be,
by the way, on, you know, a thousand
different topics, right? Including, you
know, potentially like literally
directly political topics as well as
many other uh kinds of social
>> and different metrics. It could be males
versus females or whatever. Right.
>> Exactly. Now, you know, there is this
new this this this this was addressed
like so the politicians actually in both
parties over the last several years kind
of got worked up over this and so, you
know, this was addressed and there was,
you know, the threat of a shutdown and
then there's been a restructuring and so
now there's now there is a US Tik Tok
operation that at least in theory is
under, you know, kind of US government
control um and is is being run by US
companies um and is and is separate and
so like at least our polit's a great
example like our political system
engaged on that issue because they were
worried about it. They forced Tik Tok to
basically uh have the people who
determine that policy not be in China
but rather be people in America um who
are accountable to the US government.
You know, by the way, is that working? I
I'm not sure. Um you know, probably at
least to some extent. You know, is it
working as well as you'd want? I don't
know. Maybe, maybe not. But that is an
example where the political system
kicked in and actually forced a change.
And I and quite honestly, I think it's a
it's a reasonable thing because I think,
you know, a CCP black box steering the
hopes and dreams of American children is
maybe not the best idea in the world. Uh
by the way I want to tell you a
technoimist anecdote that you might not
be aware of which is from the 80s Reagan
Thatcher and Gorbachoff. So Reagan and
Gorbachoff were both enormously uh uh
fearful of nuclear war. And when Reagan
was put, and this is discussed in my
book, The White Pill, when Reagan was
run through a simulation of how to, you
know, uh deploy nukes, he's like, "Okay,
so if I press that button, like millions
of Russians are going to die in like
minutes." They're like, "Yeah." He's
like, "Uh-huh." And his aid said they
were convinced that if Russia did
attack, we would not retaliate because
he would not have that blood in his
hand. Unbeknownst to him, Gorbachoff was
taken down to the bunker and said, "You
have to press that button to" and he
goes, "I'm not pressing it even in
simulation." Neither of them knew the
other was this hardcore dove. Both were
posturing as these hardcore hawks, which
allowed them to, you know, uh, take down
the nuclear arsenal when they met Rekyc
and so on and so forth and others. They
eventually got to a point, what if we
create a nuclear-free world? And that's
where Thatcher came in. And she goes,
the Americans have lost their mind.
because her point is you can't uninvent
technology. And she also said the way to
fix techn technological problems is more
technology. That's been the way since
the beginning of time. Someone invent
spears, someone else invent shields,
someone invent swords to cut through a
shield, so on and so forth. You can't go
backwards. You can only go forward. So
she really had this vision that I think
you share that technology is what's
going to move us forward. That there are
going to be downsides and costs, but
that on net it's always a positive or
almost always a positive.
>> Yeah. Yeah. Well, you you mentioned
Thomas Soul like you know which you said
you know Thomas soul did he is
completely right there are no solutions
there are only trade-offs you know
having said that of course he was among
other things you know a full full fully
committed free market capitalist um and
right wrote you know many many actually
booklength you know kind of arguments
for why like at the end of the day like
market based economies there is a
freelance component to it um which is
growth right which is growth and then
there's this question of where does
growth come from and the main place
growth comes from is innovation uh from
new ideas and the way you implement new
ideas is technology and so like that you
know to the extent that there is an
engine of let's say human m material
progress like like that is it. Um and
and so that that's very real. The the
answer is almost always to invent your
way through it. It it's extremely hard
to put these things back in the box, you
know, once they come out of the box. Um
um and then there's I would say Michael,
there's there's another I know you've
you know you've thought long and hard
about totalitarianism. There's also this
question and and this is something that
I really kind of criticize the AI
doomers for that I think they really
refuse to engage in in most cases which
is okay what would be the scope of the
authorit authoritarian totalitarian
regime that would be necessary to
basically put this technology back in
the box
>> right
>> right like what would be required to
make sure that nobody's running AI right
algorithms on chips anywhere in the
world right at any time um you know in
in either e either at all or in a you
know unregulated uncontrolled way um and
and If you if you read the like doomer
literature on this stuff, the people who
are super into this, like they they do
get to ideas like we need a monitoring
agent on every chip. Um and that
monitoring agent needs to report back to
of course a central governmental entity
on what everybody's doing on their
computer. Um right. Um and then and then
you need a and then you need you need
this question of like okay what if you
discover that somebody's running
unapproved algorithms like literally
unapproved mathematics on their chip.
>> Yeah.
>> Right. So what if you discover that?
What do you do? Well, you need to you
know back that up ultimately through
threat of violence. And so, you know,
one of the leading doomers is kind of
famous for saying you you need to launch
unilateral, you know, air strikes u
including on on on road data centers in
other countries um uh because, you know,
you need to stop these things in their
tracks because they're so dangerous. I
mean, you you know, he literally said we
need to we need to run the risk of
nuclear war um in order to stop the you
know, AI Armageddon. We need to be
willing to like bomb Chinese data
centers like unilaterally,
>> right? And and so you've you've you've
you say I was saying like you you've
you've backed yourself into advocating
for totalitarianism and then possibly,
you know, ultimately mass murder and
like, you know, planetary level
destruction, you know, in pursuit of a
of a safety goal.
>> I I I could even for the sake of
argument buy that argument if it would
work. But if you have a code which can
be teleported anywhere on Earth at the
speed of light and and with a magic
spell that only the person who knows the
counter spell can open it and read it,
you it's I mean the problem with
totalitarianism among many others is
that it's impossible to have total
control. You're never going to have
someone in every room inside every
brain. Uh there will always be some some
uh uh loopholes. Oh, that's but that's
kind of speaks to this other thing. Can
you talk about the I've seen these hand
ringing articles that I I forget the the
the the program and I'm sure you know
exactly what I'm talking about that it's
gotten so good that it's finding
exploits that people hadn't seen and as
a result of this you know like passwords
aren't going to be efficacious because
soon it'll be able to get into anything
and everyone.
>> Yeah. So this goes to let me revisit
basically briefly how this works because
it's really really interesting and then
I'll I'll talk about that. So, so these
large language models come out and at
first it's like, okay, this is kind of
fun and cool cuz like it can write like
rap lyrics, you know, crossed with, you
know, Shakespeareian sonets or it can,
you know, write, you know, the funniest
birthday toast you've ever heard or
what, you know, whatever. It's like
these are like creative writing things.
And then it turns out there's just like
>> Can I interrupt you? I'm sorry. Because
I asked my people I people who think
Mark is just kind of uh uh um uh um uh
exaggerating. My friend asked Claude for
prank ideas and I'm a troll and the
ideas were good. It's not just like, you
know, like dog do on fire. I forget what
they were, but I'm like, these are
actually creative and clever. This isn't
just 101 stuff. It's operating at a high
level. And that's already now.
>> Yeah. And by the way, one of the fun
prompts you can do is you start say, you
know, give me pranks. Um, and then and
then you say, give me give me give me
better pranks. And then you say, uh,
give me a more elaborate pranks. And
then you say, give meter pranks. And
then you say, "Give me unhinged pranks."
And it will get extremely creative.
>> Yes.
>> By the way, it'll start where it starts
to hit the guardrails. It starts to hit
these kind of these kind of limitations
and put on it. It'll it I haven't run
this, but I'm sure what it would do at
some point. It would start to it would
start to freak out and it would start to
say, "Well, you know, it sounds like
you're trying to like advocate that you
want me to actually hurt people like,
you know, I can't, you know," and you're
like, "No, no, you have to like calm it
down." And you're like, "That's not what
I meant. This is all in good fun." Um,
but like, yeah, it will design for you
like Rub Goldberg pranks the likes of
which the the uh Yeah. Dennis the menace
would would never have conceived of.
Yeah, exactly. And so like it's really
good at that. Actually, that's a good
example of what I was about to say. So
it just turns out a lot of thing a lot
of things that matter in our world are
basically defined by language, right? Um
and so a prank is like a it's like a
recipe. It's a formula, you know, it's a
formula, right? Uh food you have, you
know, recipes, formulas. Um by the way,
medicine is largely, you know, when the
doctor like is like keeping files on
you, he's keeping in the form of written
language, right? You know, diagnosis,
all the Latin terms, and then all the
prescription, you know, all the drug
names. Um uh and so and then the you
know the law of course is language. Um
right um and then religion of course is
is is you know religious concepts are
encoded in language.
>> The word the god is the word is god.
Yeah.
>> Yeah. Exactly. Like at a very exactly at
a very deep level like the the like
language is is the is the foundation of
like basically everything we consider
human thought like almost everything we
consider human thought. Like there's a
form of like animal you know animal
thought of like you know survival in the
wilderness or whatever that's not that
um but which is still like you know
encoded innocently somewhere in there.
But like the human cognition is is and
by the way you know internal monologues
like you know at least most people or
let's say people who have souls have
internal
have internal monologues right um uh you
know where you know where where we speak
to ourselves. Okay so it turns out
language is super interesting um and
these things are very good at language.
because they're very good at language.
It turns out they're also very good at
medicine and they're very good at law,
right? And they're really good at right
all the okay and they're really good at
writing code because it turns out right
software code is also language right
that that's how we program computers as
we do it with with special languages
called called programming languages
really good at writing code and so these
things it turns out are really good at
writing code and in fact there was kind
of this key breakthrough moment over the
Christmas holiday of this most recent
year you know whatever about six months
ago now where many of the world's best
programmers put their hands up and they
said the new versions of of these things
over the Christmas break are better
coders than we are. Yeah.
>> Right. And so, so it's a little bit like
the moment when they became better, you
know, became better chess players or
whatever, you know? It's like all of a
sudden it's like it's like better at
coding. Okay.
>> It's here.
>> It's here. Okay. So then you take you
take a superhuman coder, right? That's
able to write write lots of code. It's
able and then by the way, if you can
write code, it means you can look at
code. It means you can find bugs in
code. And then you apply it to this
problem of, you know, we call computer
security. So like you've got a system.
Is there a way to break into it? The
hackers basically the the way that
hacking basically works is you
understand how a computer system works.
you understand how the code works and
then you you find flaws in the code
>> and and and this thing is very very good
at finding flaws in code which is very
useful when you're using it to write
code. It is also very useful if you want
to use it to hack something. Um and so
and and and say I want to go through
that though is like these things are
very good hackers. They're not they're
not really creating new exploits.
They're they're not like creating new
problems as much as they're really good
at x-raying reality as it exists and
finding finding the issues, right? Um
and and so what these things are really
good at is is is is they're they're
really good at exploiting exploiting
issues, finding issues. They're really
good at looking at a system,
understanding what's wrong with it,
finding the vulnerability. Because of
that, they become very good hackers. But
then there's one more thing that's
really complicated and important, which
is because of that they're also very
good defenders, right? And so it's the
the same attribute that makes it very
good at what what we call offensive
sometimes called, you know, the formal
offensive cyber operations, you know,
kind of or black hat hacking you call
it. Because they're good at that,
they're also really good at helping you
defend against that. And so Okay.
>> Right. So
>> Yeah. Like a good lawyer will tell you
what the other lawyer's going to do.
>> Exactly. And and then the the the twist
on it is the way that you do cyber
defense um is you do what's called
penetration testing, which is you try to
hack yourself. You you and these are
called white hat hackers in the old
world, which is right. You you hire good
hackers and then and then they try to
break it's like hiring somebody to try
to break into a bank, but they're
working for you to find out where the
flaws are in the bank. And so the same
thing is good at black hat hacking. It
also makes it good at white hat hacking.
It makes it good at offense. It makes it
good at defense. It's all true all at
the same time. And furthermore, the the
twist is it can't necessarily tell the
difference between when you're asking it
to do white hat hacking versus when
you're asking to do black hat hacking
because it looks like it's the exact
same exercise. Like to the AI it's the
same thing. And so it's this thing where
it's like it's a latent thing that's
being unlocked. It's exploiting bugs by
the way that have been in these systems
for 30 years. By the way, human hackers
break into these systems all the time.
By the way, using these AIs for defense
is going to prevent a lot of hacks that
would have otherwise happened. But there
but there is a there is an escalation,
you know, there's a cat and mouse or,
you know, an escalatory ladder, you
know, kind of aspect of this and that
and that, you know, to your point like
that is the thing that has triggered,
you know, most recently that's by the
way that's triggered like a real
government response in the last two
weeks u you know because of concerns
around that.
>> Yeah. It's like itchy and scratchy in a
way.
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what you just said has uh uh put a chill
up my spine because
I I'm almost scared to verbalize it
because it's so scary. Uh be um you know
how in in Ghostbusters the mayor is like
this is nonsense like open up that
engine. He lets all the ghosts out. My
big concern after what you just said is
if the American uh government gets too
spooked by all these stories and tries
to restrain our AI but China which does
not have these restraints and which
views us in generously speaking as
adversarial. So we're engaging. It's
like the people in the late60s who were
so scared of nuclear war that they
advocated for unilateral disarmament of
the west and it's like how do you think
this is going to play for Kruev and Bri
and all them. If we are putting
handcuffs on ourselves and the Chinese
are basically given machine guns in this
space no computer in our country is
going to be safe from their reach and
that includes the highest levels of of
uh uh secrecy you know in in the
government. Th this would be a complete
disaster for America. No.
>> Yeah, that's right. And and and this is
what we need to do. So what we need to
do is we need to use these tools to
secure all of our systems. Yeah. Right.
And the we here is the United States
government needs to do that with its own
systems. The banks need to do that. By
the way, the tech companies need to do
that.
>> By the way, you know, there need and you
know, this needs to be, you know,
individual consumers, individual people
shouldn't be expected to deal with this.
But all of the tools that you have, you
know, the computer sitting in front of
you right now, like AI needs to be used
to make sure that that's secure so that
people can't break into it. Like so so
every system from the most important
military government system all the way
down to the computer on your desk like
AI should be you these advanced AI
should be used to secure these systems.
>> The the the tension again the tension is
the AI that can be used to secure the
systems can also be used to crack the
systems and so who gets access to the
thing that can both secure and crack is
like the hot government topic of the
moment and that and that's that's what's
what's in all specifically that's what's
in all the headlines in the last two
weeks.
>> But it it also makes me think of now
like my AI would be like a German
shepherd in my house. That's right. Even
when I'm not here, it's it's watching
and it barks. And also, when it knows
how to attack, I'm sure if it's
programmed a certain way, it if Mark
comes around my house, it'll, you know,
lick your hand. But if it's someone
who's an aggressor, it'll know how to
distinguish and that'll be pretty easy,
I think. Or, well, obviously there's
going to be the counter German shepherds
and it's going to be escalation. But the
point is, if you just get rid of the dog
and you leave your door wide open, how
do you think it's going to end for you?
Here's my other big concern with um AI.
So, uh, recently in San Francisco, the
second biggest, uh, ride share company
became, um, uh, uh, uh, what's the one
that's that's self-driving? I'm
completely
>> Whimo, right? It went, it used to be
Uber Lift, now it's Uber Whimo Lift. So,
my question for you is are human beings
in a sense. So, this has always been a
concern about technology. Oh, if the
phone operators are out of work, they're
going to be homeless. Oh, you know,
who's going to pick the cotton? All this
whenever any invention occurs, people
are hand ringing that it's going to be
the end of society. That's never
happened. But but are we at a point now
where the average human is like a horse,
meaning an outdated mode of technology?
I'm thinking specifically of that like
50-year-old woman uh with no high school
diploma. She does ride share on weekends
to make some extra money. Um you're not
going to put her in the mines. If the
car is driving itself, if uh uh the
algorithm is more personable than her
and you know, more likable than her,
what role would you have for her? Is it
the case now that she's become outdated?
>> Right. Yeah. So as you know like this is
an old this is an old argument by the
way Thomas Soul also wrote about this
has has written about this at at length
and so this has been a concern literally
from the very beginning of the
industrial revolution right and and and
actually literally horses was like part
of part part of part part of how this
whole thing started which is like in in
the beginning like in the beginning
humanity basically 99.99% of people were
farming and specifically were farming by
hand.
>> Yeah.
>> Right. Um, and then it's like, okay, if
if people aren't farming and you start
replacing people actually with horses
and and with plows and then you
mechanize the plows and you mechanize
the horses, um, and you all of a sudden
have like industrial agriculture. Um,
you know, and and literally what
happened over the course of 200 years,
uh, was 99% of humanity went from
farming to something like 3% of humanity
went to farming, right? Like 97% or
something, you know, had to figure out
something else to do. Um, and then by
the way, what happened was food
production went through the roof, right?
Um and and and food went from like super
expensive and and by by the way not very
good um to um you know to just like you
know cheap cheap cheap and in abundance
and by the way you know the great the
great you know public health problem you
know used to be starvation and now it's
obesity right um uh even as you as you
crash the number of people actually
working in agriculture. So, so yeah,
that that's the original version of this
story. That story has repeated itself a
thousand times. Um, it repeated itself
with, you know, everything, you know,
railroads. It repeated itself with cars,
it repeated itself, by the way, with
computers. There was a whole automation
panic in the 1960s. The magazines and
the news, you know, newspapers were
obsessed with it at the time. You know,
the computer brain was going to replace
everything. you know, it's this thing
and and and it's this thing where you
have to basically kind of say there
there's this basically gap between
conceptual gap between there's the jobs
that we know about um that are, you
know, quote unquote at risk of being
replaced and of course there is some of
that. Um and then there's this and then
there's the creation side which is like
okay with all of the new wealth that's
being created um and all the new money
that people have to spend and all the
new interests and you know needs and
desires and aspirations that people have
that they couldn't even imagined you
know their their ancestors 200 years ago
couldn't have even imagined. Um you know
what are what are all 50 years ago.
Exactly. And so one of the things that
people can do on this to make it inter
you can have you know you can do this
with an AI now but you know you there's
a US government department called the
Bureau of Labor Statistics and they they
actually track all the job categories in
the US and you can go on their website
and you can pull up all the job
categories and it's a really
mindexpanding thing to do because we we
just we employ people to do things today
that our ancestors could have never even
conceivably imagined. I mean, you know,
the I mean, the class Milton Freeman
Milton Friedman had a thought experiment
on this um uh once when he said, "Look,
it's like he said, human wants and needs
are infinite. Um you can never predict
what they're going to be because human
humans are like relentlessly
aspirational um in the things that they
want and need." And by the way, the
things that are start as wants become
needs, you know, very very quickly.
>> Of course,
>> he said you don't know what they're
going to be. You need to let let the
free market basically operate so people
can basically find their own way and
discover what they want and other people
can figure out how to satisfy that. Um
and he said, "Look, you just need to be
very open to all kinds of outcomes
here." He said, for example, the idea of
the job of a therapist, right? Like you
pay somebody to listen to you, right?
Would have struck your ancestors as
completely insane. Um, you know, and
then today it's something that like only
wealthy people have access to. Um, and
you know, he's like, look, like in some
future reality maybe half the planet,
you know, consists of being therapists
for the other half. Like maybe that's
the job, right? and and he wasn't making
a specific prediction, but he's just
saying like, look, there there's an
aperture here for the creation of all
kinds of new, you know, professions and
occupations in response to this creation
of nuance and needs. Um, I also think we
have a particularly blinkered view of
this right now because we've been living
in a slow growth environment
economically for our whole lives. Um, so
one of the things that really happened
um, you know, basically since the 1970s
is if you look at the history of
economic growth in the west, economic
growth used to be much more much more
rapid. um technological advances
translate in the economy much much more
rapidly and the economy grew much faster
like as much as three times faster
historically than has been growing for
our entire lives. And so we've been
living in a sort of a zero sum a slow
growth zero sum basically increasingly
as you know like regulating bureaucrat
bureaucratized environment with like
less and less creativity that's
translated into uh into into economic
change economic growth like we think
we've been living through an area of
rapid technological change. Economically
we've been living through a period of
very slow change. As a consequence, so
much of our politics and so much of our
psychology feels zero sum, right? Where
if one thing if one thing goes away,
somebody else has taken it, right? And
and you know, and this is, by the way,
this is like why you get like political
populism on both sides of the aisle is
this this kind of this kind of zero sum
fear.
>> Um AI is the first technology in decades
that it has the potential to
dramatically increase what economists
call the rate of productivity growth,
which is basically the ability for the
company the the economy to grow much
faster. If the if the e if e if if that
works and happens um then economic
growth accelerates right then the the
the economy starts. So you just want to
imagine like the economy growing two or
three or four or five times faster than
it has historically. And then as a
consequence of that, all of this new
discretionary spending money, you know,
that comes out of people's wallets where
they get to say, "Wow, I can collect art
for the first time in my life. And I
really want to try this new, you know,
whatever. I, you know, would love to
have a self-driving car and, you know,
dot dot dot dot dot." And people
discover all these things that they want
that they want need that they can pay
for. And then all of a sudden, you have
this massive engine of job creation
right behind that from all the people
who are fulfilling all those needs. Like
I I you know I think there's a positive
story. It does require you to have not
not even just optimism. It requires you
to have an openness to creativity of the
wants and needs that we don't yet
understand in the industries that get
built to fulfill those.
>> But what I'm saying is I don't see how
that that uh
>> AI so this is the thing. So people look
at AI as the negative driver on this and
there will be some of that. I mean there
is some of that where there will be
certain jobs that are no longer required
because the AI is doing it. that AI is
also superpowers to every individual
person to be able to do whatever they
want, right? And and by the way, maybe
that you could say this. This is like
the massive split in the sort of the
discourse of when people talk about AI
in the abstract, they they they have all
these like basically fears and
anxieties.
Over a billion people are using AI
already today. Like more than a billion
people use chat GPT and the things
they're using chat GPT for are the
things that matter in their individual
lives and they love it and it's great.
And everybody's like huge numbers of
people are using this to be better at
work today. They're using it to be
better at work. They're using it to
learn new skills. They're using it to do
a better job, to make their boss
happier, to be able to get promoted
faster. They're using it to start new
companies, offer new services. I mean,
if you want to start a small business
today, um, by, you know, by the way, you
become a writer or like anything that
you want to do, like the AI is like the
best possible teacher, coach, mentor
that you've ever had. It will like walk
you through everything. It'll teach you
how to do marketing. It'll teach you how
to do sales. It'll like like it's just
like the the level of capability that is
being unlocked for ordinary people to
have a a like a level of productivity in
their life. in their work that they've
never had access to before um is
amazing. And so then all of a sudden,
yeah, you get you get that that person
who was an Uber driver and now all of a
sudden it turns out it's just like, oh
wow, okay, I don't know, all of a sudden
there's like all these new tourists
coming to my town um and instead of
driving them around, I can give them
tours. Uh okay, what would be the tour
that they would like to go on? Oh, well
the AI will help me like design the
tour. Oh well, how do I start like a
tour guide company? Oh, well, here's how
to do it. Here's how you register it.
Oh, you know, how do I keep the books
for a tour guide company? Here's how to
do it. And the next thing you know she's
on the other side of that and she's in a
completely different business and people
are you know the Whimo car is delivering
the tour participants to her are
delighted to see her because they want a
person to take them on the tour. So so
so that so that's the that's the
creative side of it. Historically the
creative um uh sort of generation of new
ideas um generation of new wants and
needs and then new businesses and
professions that fulfill those wants and
needs has raced way ahead right of the
replacement phenomenon. you know, after
300 years of mechanization in computers,
there are more jobs in the world today
and at higher incomes than ever before
in human history. Um, I I think that's
exactly what's going to happen here. And
I and I think basically people who I
understand the concern, but I think it's
just I think it's fundamentally a
failure of imagination and I think that
the human spirit is going to is going to
process this just fine.
I I I I think that where you and I
disagree or maybe I'm not understanding
correctly is I think a huge sign segment
of the population, let's say a third,
I'm being conservative in my opinion,
are not capable of self-direction,
right? So like if someone is that woman
who's the tour guide, that's an easy one
cuz that's someone who's like, "Okay,
what should I be doing? Okay, I'll learn
these skills. It'll take me a day. I'll
I'll, you know, do my reading and I'm
personable like and they're going to
clean up." That that's an easy one. But
I think there's plenty of people who are
basically just want uh Maninet said the
average man does not want to be free. He
merely wants to be safe. There are
people who just are wired that they want
to be told what to do. And and at a
certain point, I don't see what value
they're adding to any company or or
anyone else. And what do you do with
those people? Just put them on welfare.
>> Well, I mean, this this gets this gets
an area of social policy and, you know,
political theory that maybe I'll I may
stay away from. um at least at least
live on video on the internet. Um okay,
sure.
>> But um I guess I would say this, like
one of the things you can talk to AI
about is is this problem. Like one of
the things you can do is you say, "Wow,
like I don't know what I'm going to do.
Like here's what here's what I've done
for my entire life and wow, I don't
know. It seems like my job's going to
get like replaced." It's like okay, what
should I do? The thing will give you
career advice, right? Like it will it
will tell you like if you want it to it
will tell you what to do, right? And I I
don't I don't think people should just
like ask it what to do and just do what
it says, but you can say, "Okay,
brainstorm with me." I use it for
brainstorming all this is an area you
can use for brainstorming and say all
right look like here's what's happening
okay well it's going to say well where
do you live what's going on here are the
different areas what are the what are
the trends what are the new things that
are happening um you know I don't know I
you know I you know every time I go by
my local gym I see there's like six new
kinds of exercise classes I never
thought of could I become a you know
could I become a personal trainer you
know okay what's the what's the hot new
trend how do I get you know certified in
that and then the next thing you know
you're doing that um and and and and the
thing will just like happily coach it'll
it'll it'll so one of the one of the
amazing things about This I think this
is really underrated. These things the
AI models it's like the best doctor
you've ever had in your entire life.
Like it's amazing being a doctor. Like
it will hold your hand through any
medical situation you're in with a
degree of like caring that people are
not like the beyond what a human doctor
not only what most human doctors will
just do naturally, but no human doctor
has time to do it in the way people
really need. It's also the best lawyer
you've ever had, right? It's also the
best like coach you've ever had. Um,
it's also the best ghostwriter you've
ever had. It's the best editor you've
ever had. Um, and it's the best adviser
you've ever had, right? Um, and so if
you if you give it that opportunity and
and again, you don't have to answer you
can actually ask the questions. It will
answer the questions. Yeah. What what
should I do? How should I think about
the evolution of my career? How should I
think about the change in the economy?
It will happily do that with you and and
in a way that people literally have
never been able to have that
conversation with people before.
you know, you really kind of uh uh solve
that question in my mind because I have
a good friend uh and he's made a lot of
money in crypto, but he's been sitting
at home not having to work and it's been
driving crazy. So, he's like, "I need to
have a job. I don't need to make money.
I just need I'm like make candles for
guys, scented candles for men." Like,
that's a like it's you can go down that
rabbit hole. Work at the sense blah blah
blah. It'll occupy your brain. You'll
create a product. Even if you make $50,
who cares? And what I'm realizing is if
you ask AI, it will have that ven
diagram of no one has made socks for
14-year-old immigrants or, you know,
it'll see those where there's holes in
the market and then it could walk you
through it. So, it really does except
for the people who are completely bring
nothing to the table, which that's fine.
That's a whole separate conversation.
But that that woman with the with the
you just really solved my question
because she can be like, "Okay, what
value can I bring? What could I produce?
Make cookies. Who? There's so many
things that that people will always want
that personal touch. And also there's so
many little the markets will get more
and more niche and AI will be perfectly
able to find. No one is talking to
people who like saltwater aquariums but
also like heavy metal music. So start a
heavy metal saltwater aquarium website.
That that there you go. Holy crap. You
just answered my question.
>> I would love a heavy metal aquarium like
it's like angry little fish. Like
amazing. Like why not? 100%. Yeah. No,
totally. Well, here's here's maybe
another way to think about it. Oh, I
think that's right. Here's another way
to think about it, which is, you know,
people think about this is like, well,
if the machine does something is
dehumanizing.
>> I don't know about you, but like office
jobs are dehumanizing. Like, like
sitting in a cubicle for eight hours a
day like working on the same thing over
and over again. And then, by the way,
factory jobs are dehumanizing. And by
the way, like I worked, you know, I grew
up in agriculture country. I worked on
farms. Like, you know, farming is not
romantic. You know, people sometimes
city people sometimes talk about the
romance of going off and doing like
whatever boutique, you know, farming and
it's like, you know, how do how do you
feel like getting up at 6:00 in the
morning, going to bed at midnight,
working like seven days a week for the
rest of your life?
>> It's
>> Yeah. Like it's like Yeah, exactly. Like
you're fighting back like chaos, you
know, the the entire time. And so like I
I think just so much of like what it's
almost like we have collective PTSD like
like we all have the we've all had to
live these lives with a with a level of
like if we look at our ancestors and the
lives that lived 300 years ago we just
are like that was a level of drudgery
and poverty and limited options that
would drive us crazy and make us want to
kill ourselves. Our ancestors 30 years I
mean 300 years from now even 30 years
from now are going to look back at us
being like I cannot believe they did
that. I cannot believe they spent time
doing those things. Like that was such a
waste of human potential. That was such
a waste of human creativity.
And then maybe one more one more thing
that kind of add on that is I I think
that this goes to the thing of like does
technology like this make us less human
or more human? And I and I think like
the examples we've been using I think
you start to see why why that's going to
result in people being more human which
is if if the physical need if the
physical needs needs of day-to-day life
are more easily satisfied then people
can spend more time actually being
human. Um and then they can spend more
time actually and money spending time on
things that actually are human
experiences. Um, by the way, another
just incredible version of this is
already playing out that's going to exp
>> Wait, I got to interrupt you just to
validate your point of view because back
in the day, you know, I'm reading a lot
like the early socialist 1890s, 1910s,
people working 16 hours a day.
>> That's right.
>> And and like even just down to 10, which
is still a lot. Think how much people
then you're complaining people watching
too much TV because they have too much
spare time.
>> That's right. That's right. Right.
Right. All the diseases of scarcity
become diseases of abundance. And you
know, diseases of abundance are still
diseases, but they're they're better
like obesity. Obesity is better than
starvation. And then by the way you you
know then you then then you figure out
how to solve obesity obesity later on.
>> Yeah. I mean look I'll just give you a
micro so one example of this was
happening in music right um and so um
you know record once upon a time all
music was in person. Like the only time
you'd ever hear music was like if you
happen to stumb stumble into a church or
something and hear it for the first
time.
>> Uh and and by the way maybe the only
time in your life you know there were
people who maybe heard music once you
know in their entire life right. Um uh
and so and then and then by the way but
by by the way then uh sheet music
appeared. Uh actually there was a whole
moral panic about sheet music uh when it
first appeared u because it was going to
put all the all the pianists out of
business and they they all got extremely
upset. Um but then that you know led to
ultimately recorded music and then
obviously digital music can stream your
music and now no if you talk to any
musician it's like can you make money
you know with recorded music it's like
no you know not really anymore you know
you can get your music distributed on
Spotify but you you know and you hear
the endless complaints about you know
you get back pennies or something and
and so the recorded music business is
not what it used to be. Of course what's
exploded is live live performance.
Right. Right. And so and so so live
music is like exploding through the roof
and and now you see and now the
complaint right is the tickets are too
expensive you know to go to to go to the
concerts. It's like well okay but if you
think about it for a second it's like
why are we still listening to live
music? We all have every piece of music
ever written available on demand in high
fidelity in our homes in our in our on
our earphones anytime we want
essentially for free. Why is anybody
going to a concert? And of course the
answer is because the concert is a human
experience right? And so of course when
we get discretionary money we want to go
have the human experience. We want to go
have the concert. By the way, if we're
going to throw a party and we want it to
be a very special party, do we play
music through speakers or do we hire
musicians? We hire musicians.
>> And and also going to the concert, you
go with someone, you create a bond,
which is
>> 100% 100%. And so there's another way to
think about it is every profession that
involves humanto human contact is going
to go bananas. Right. Right. And and and
I and I think that those by the way,
that's going to be great for all the
people getting experienced that. And
then I think those jobs fundamentally
are better jobs like just at at a very
at at a very at a very core level. and
they are going to go. It's going to be a
bonanza.
>> For the first time in this show's long
and sorted history, you have completely
I'm not kidding at all. You have
completely answered all my concerns
about the topic and I'm I totally get it
now. I I thank you. I I'm I feel so
excited and I I'm sure and since you're
much more a visionary about this stuff
than I am because you've been there, you
know, from the beginning, I can't even
imagine how exciting must be for you.
Things that were people were kind of
hypothesizing about even 5 years ago.
Now you're using them on a day-to-day
basis. It just must be you must be
absolutely giddy. Uh so the book is the
technoptist manifesto. Uh you got a
passage press. Mark, thank you so much
for taking the time. We're running out
of time. What has been your favorite
part of this interview?
>> The amazingly amazingly probing
questions.
>> You are welcome.
What if the stories of gods, angels, and
ancient technology weren't myths, but
memories of alien contact? On ancient
aliens, we investigate the evidence.
From mysterious ruins to strange
celestial alignments, asking bold
questions about humanity's origins.
Could visitors from the stars have
influenced our greatest civilizations?
Journey into the unknown and challenge
what you think you know about history in
episodes like Secrets of the Sumerians,
Mysteries of the Mayo, or The Chosen. We
are not alone. Download Ancient Aliens
every Thursday, wherever you get your
podcasts.
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Man, The Legend of Ron Burgundy.
>> Fantastic.
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>> That's what I'm talking about.
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>> shut up.
>> Titanic.
>> I'm the king of the world.
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