Speaker 1: Fear of all of us losing has to become greater
Speaker 1: than the fear of me losing to you. Now, China
Speaker 1: doesn't want the financial system to collect.
Speaker 2: It's the let it rip administration. What to do about AI?
Speaker 2: Am I going to lose my job? Or what about safety?
Speaker 2: Cyber security? What about privacy? While new documentary is out
Speaker 2: answering all of those questions, promise, peril, truth, trust? Should
Speaker 2: we be pessimistic? Should we be optimistic? It's called the
Speaker 2: AI Doc. And two of the principal participants in that documentary,
Speaker 2: Tristan Harris and Asa Raskin, are up next on This
Speaker 2: is Gavin news This is Gavin Newsom.
Speaker 1: And this is Tristan Harris and Azarasca.
Speaker 2: All Right, so you guys, you're on the back end
Speaker 2: now this world tour where you guys have been all
Speaker 2: over the damn place. Yeah, and you launched it. And
Speaker 2: it's on the basis of a movie that you you
Speaker 2: didn't necessary, Its not your movie, right, but you participated
Speaker 2: in a movie.
Speaker 1: That's right.
Speaker 2: This new documentary that was released what a month ago?
Speaker 1: Yeah, but a month and a half ago, The AI
Speaker 1: Doc or How I Became an Apocalyptimist. Our friends the
Speaker 1: directors of Everything Everywhere, all at once. We chatted with
Speaker 1: them several years ago when we first really recognized the
Speaker 1: situation we were in and asked them for their help
Speaker 1: to help create a movie to clarify the AI situation.
Speaker 1: And long story short, we'll talk about it, but we
Speaker 1: got the directors and have only involved and its whole
Speaker 1: team came together and tried to make a movie that
Speaker 1: would clarify the predicament that we're facing.
Speaker 3: Kevin, do you do you remember seeing the film the
Speaker 3: day after?
Speaker 2: Course, well, man, I want to maybe I was alive.
Speaker 2: It was the early eighties or something eighty two, eighty two,
Speaker 2: eighty three. Yeah, it was like a seven pm Tuesday
Speaker 2: night exactly every human being on planet Earth after.
Speaker 1: The largest synchronized television event in human history in terms
Speaker 1: of the number of people seeing the same thing at
Speaker 1: the same time has probably the Olympics. It was a
Speaker 1: made for TV movie about what would happen if there
Speaker 1: was nuclear war? Right, And it's not as if people
Speaker 1: didn't know what nuclear war was, but there's something about
Speaker 1: we didn't really want to think about it or confronted
Speaker 1: like why would you? And I think the people who
Speaker 1: made that film were trying to create this kind of
Speaker 1: collective confrontation because the film was aired in the Soviet
Speaker 1: Union like five years I think five years later, right
Speaker 1: right before the Reichivika courds the first arms control talks,
Speaker 1: and that set the context that it's like I know
Speaker 1: that you know that I know, and you know that
Speaker 1: I know that you know that we both don't want
Speaker 1: that to happen. It's what you know what Stephen Pinker
Speaker 1: calls common knowledge, but we think of it as this
Speaker 1: almost common feeling. Yeah, yeah, that we both we both
Speaker 1: know that we feel the same way about that anti
Speaker 1: human outcome. And I think that with AI we have
Speaker 1: to get clear because AI is a much more confusing
Speaker 1: technology because it's like it's like if nu because would
Speaker 1: say it say if nucid.
Speaker 3: Imagine we're trying to reason about nukes that also could
Speaker 3: cure cancer, Like how would.
Speaker 2: You do something?
Speaker 1: Or pump GDP by ten percent?
Speaker 2: That's right, right?
Speaker 3: And so what The Day After did is that it
Speaker 3: created this this common feeling common knowledge where we could
Speaker 3: all see, oh, a world where we all go to
Speaker 3: nuclear war. That like that, that's an anti human, anti
Speaker 3: life future. And as long as there's confusion about which
Speaker 3: default world AI and thesin we're not going to do
Speaker 3: anything about it. But if we all have clarity that
Speaker 3: it's heading us towards an anti human future, and we
Speaker 3: can build that out in this in this interview, then
Speaker 3: that means it creates the conditions where we can coordinate
Speaker 3: to do something else.
Speaker 2: So this so that was the impetus behind this, this documentary.
Speaker 2: It was to create that collective understanding, that's that wisdom,
Speaker 2: that collective then response mechanism, which would be we need
Speaker 2: to do something about it. Even the promise that we
Speaker 2: could talk about at the peril in terms of the
Speaker 2: safety risks and the anxiety that somebody is at feelings.
Speaker 2: So you guys have been out on this tour, You've
Speaker 2: been all over the place over the course of the
Speaker 2: last month, and you've been you know, obviously you know,
Speaker 2: reaching out to people on all political sides of the aisle.
Speaker 2: Because of the human nature of this. This is universal.
Speaker 2: That's why it's something that connects all of us. This
Speaker 2: is not a partisan frame this And so is that
Speaker 2: something that you that's been captured in your own consciousness
Speaker 2: as you've been out on this store, how real and
Speaker 2: invisible that is or are we still in the process
Speaker 2: of discovery. I mean, are we still in the process
Speaker 2: of understanding more fully what the hell this is all about.
Speaker 1: I think people still not everybody knows. And the film
Speaker 1: was just out in theaters and has a limited release
Speaker 1: on streaming. Now it should be on Peacock on I
Speaker 1: think May twentieth, which I mean a little bit more
Speaker 1: people will see it. But I think that you know,
Speaker 1: the universal human aspect of this we learned also from
Speaker 1: social media, Like the social media didn't care whether you're
Speaker 1: a Democrat or Republican. It creates loneliness for everyone. It
Speaker 1: creates addiction and doom scrolling and brain rot for everyone.
Speaker 2: I know.
Speaker 1: That's how we first met was really on the back
Speaker 1: of the other film that we were a part of
Speaker 1: the social dilemma. And I think the good news about
Speaker 1: that film is that it has both catalyzed actually a
Speaker 1: lot of change and not the laws yet we know that.
Speaker 1: But I think it primed us to now be much
Speaker 1: more cautious about AI. So I think now that people
Speaker 1: know that social media was a problem, it makes it
Speaker 1: much easier to say that you shouldn't just assume that
Speaker 1: the default trajectory of a technology is going to land
Speaker 1: us in a good future. But you know, the social
Speaker 1: dilemma was seen basically by two hundred million people across
Speaker 1: planet Earth and.
Speaker 3: An hundred and nine released twenty twenty September of twenty
Speaker 3: twenty September twenty twenty, during the middle of the pandemic.
Speaker 1: And I think that also really mattered because people were
Speaker 1: a lot of people were stuck at home and they
Speaker 1: were only seeing reality through the monoculars of this social
Speaker 1: media news feed. So suddenly you saw your friends all
Speaker 1: start to go crazy on both sides, like suddenly the
Speaker 1: politics got more extreme. Because as everybody knows now, you know,
Speaker 1: social media increases the visibility of the most extreme voices,
Speaker 1: we get a double whammy of overrepresentation of the extreme voices,
Speaker 1: both because the extreme voices post more often and dominate
Speaker 1: the discourse and whatever they say goes more viral, so
Speaker 1: you get double over representation. So the more you use
Speaker 1: social media, the worse you are at predicting what the
Speaker 1: other side actually believes. And so you think that with
Speaker 1: this technology that's supposed to bring us together and make
Speaker 1: us the most enlightened society, it's actually making us more
Speaker 1: confused about what's really real and in fact, what our
Speaker 1: fellow Americans actually believe. And I think with your podcast,
Speaker 1: this is about actually you're talking to everybody. You're trying
Speaker 1: to say, this is a human conversation. We talk to everybody,
Speaker 1: and this is kind of fighting the effects I think
Speaker 1: of the social media problem.
Speaker 2: So you were I mean in twenty twenty what was
Speaker 2: so resonant is it was almost and it wasn't your
Speaker 2: intent to say, look, I told you so, But you
Speaker 2: were talking about these things in twenty twelve, twenty thirteen.
Speaker 2: That's right. We're saying the incentive structure and I'm going
Speaker 2: to get to in satives because it goes to the
Speaker 2: core of this exactly, this notion of you know, whatever,
Speaker 2: if someone's paycheck is attached to whatever the incentive is,
Speaker 2: which is obviously with social media it was eyeballs, was
Speaker 2: doom scrolling, which you're intimately familiar with different reasons, and
Speaker 2: that notion that we have a chance now with AI
Speaker 2: not to make the mistakes was made the neglect in
Speaker 2: particular and underregulating social media now with AI, that said,
Speaker 2: doesn't seem like there's a lot of regulatory activity with AI.
Speaker 2: In the last couple of years. I mean, so talk
Speaker 2: to me a little bit about that. Talk to me
Speaker 2: about the lessons that we should have learned about social
Speaker 2: media and how we can adapt and adopt in the
Speaker 2: AI strength frame.
Speaker 3: Well, really, like I think the core of it is
Speaker 3: if we gu just get confused by looking at all
Speaker 3: of the sort of epiphenomena, like the different kinds of
Speaker 3: harms that social media made. Like if you're trying to
Speaker 3: solve just the loneliness thing, or you're just working on
Speaker 3: solving the disinformation thing or just the teen sexualization of
Speaker 3: the thing, well then many different people are working in
Speaker 3: different parts of the problem. You're not solving the core thing,
Speaker 3: which is the race to the bottom of the brain
Speaker 3: stem for attention. And if we could just focus our
Speaker 3: on that, then you actually can solve all of the
Speaker 3: other problems at once. And that's sort of the core insight.
Speaker 3: We probably explained that what would it mean to do that?
Speaker 1: So if you're solving the core problem of let's say
Speaker 1: none of the companies are maximizing engagement just we don't
Speaker 1: live in that world. We don't have the regulation for that.
Speaker 1: But let's snap our fingers and now no one is
Speaker 1: maximizing screen time, you're like, let's just say it wasn't
Speaker 1: allowed to do that. So now instead of each company
Speaker 1: trying to maximize duration of use and frequency of use,
Speaker 1: you just have these products that each design decision isn't
Speaker 1: trying to predate or manipulate you into spending more time,
Speaker 1: which means that your experience is you're not getting sucked
Speaker 1: in constantly to everything. So that deals with the loneliness issue.
Speaker 1: If you're not trying to show people the most hyper
Speaker 1: normal stimuli, meaning like a hyper dopamine response for any
Speaker 1: piece of content, that you're not going to get the
Speaker 1: sexualization of people, and you're not incentivizing creators to maximize
Speaker 1: their own reach and engagement because you're not maximizing engagement yourself.
Speaker 1: So suddenly, when you attack the attention incentive, you're dealing
Speaker 1: with sexualization of content, you're dealing with less viral content,
Speaker 1: you get less disinformation, and you're dealing with loneliness too.
Speaker 1: So that's a good example of we obviously don't have
Speaker 1: laws that do that right now, but it points at
Speaker 1: the center of the bullseye is the incentive, and when
Speaker 1: you tackle the core incentive, you get benefits across the
Speaker 1: spectrum and AI is going to be more confusing because
Speaker 1: when people think about the incentive, they're like, okay, so
Speaker 1: social media, I got the incentive. It's like, how much
Speaker 1: have you paid for your Instagram account recently? Nothing? So
Speaker 1: how they worth the trillions of dollars? It was attention,
Speaker 1: so we knew they were maximizing that thing. But with AI,
Speaker 1: you say, okay, what's the incentive for a regular person?
Speaker 1: They think, okay, how does open ai make money? And
Speaker 1: they say, well, only when I pay them the twenty
Speaker 1: bucks a month for subscriptions. So maybe that's their incentive.
Speaker 1: They're just trying to maximize these subscriptions. But that doesn't
Speaker 1: justify if everybody paid twenty bucks a month, that does
Speaker 1: not pay back the trillion dollars the capex that they'd
Speaker 1: taken on. So what would justify that. Well, if they
Speaker 1: were to race to augment workers and like skive you
Speaker 1: tools to make your work more productive, that's great, but
Speaker 1: that wouldn't pay back the amount of money that's right.
Speaker 3: The only thing that can get them to be able
Speaker 3: to pay back the insane amounts of death that they're
Speaker 3: taken on is owning the human labor market. That is
Speaker 3: the incentive.
Speaker 1: The race to replace all human labor.
Speaker 3: That's right, to replace us first economically.
Speaker 2: And is that I mean, so is that written or
Speaker 2: is that unwritten? Is that understood within the industry or
Speaker 2: is it being I mean, is this what the consciousness
Speaker 2: you're trying to right?
Speaker 1: It's kind of a two phase thing. That actually used
Speaker 1: to be on Opening Eye's website that they said our
Speaker 1: mission is basically to create artificial general intelligence, which means
Speaker 1: to be able to replace all economically valuable work. They
Speaker 1: did change the mission statement. Yeah, but obviously everybody who's
Speaker 1: driving this knows for sure that's the prize, and if
Speaker 1: they don't do it, they fear that the other guy will.
Speaker 1: So even if they think it's bad to replace all
Speaker 1: labor and create this mass disruption, they feel caught in
Speaker 1: a race. And that's the thing we have to change,
Speaker 1: is that the fear of me losing to the other
Speaker 1: guys currently dominating over the fear of what happens to
Speaker 1: everybody losing from the anti human future. That is the outcome.
Speaker 3: So sort of see this with Demistis's office. When he
Speaker 3: co found a Google deep Mind, he set the mission
Speaker 3: statement to first solve intelligence and then use intelligence to
Speaker 3: solve everything else. But what that really meant was the
Speaker 3: beginning of a race to first dominate intelligence and then
Speaker 3: use intelligence to dominate everything else.
Speaker 2: In deep Mind is the origin story. It's right in
Speaker 2: many respects. Go back a little bit. I mean Google's
Speaker 2: deep Mind, they acquired deep Mind, that they acquired some
Speaker 2: of the intellectual assets, but it was really I mean,
Speaker 2: Larry Page, you can go back to the you know,
Speaker 2: sort of origin of the beginning of the beginning. Well,
Speaker 2: what years are we talking about.
Speaker 1: Like twenty fourteen is when I think they acquired it
Speaker 1: in twenty fourteen. I think they started it in twenty
Speaker 1: twelve or twenty eleven or something like that.
Speaker 2: Then and it goes to this competition question, which I
Speaker 2: want to get you because it's the domestic competition between
Speaker 2: all of these companies. And then we get to the
Speaker 2: competition in China in particular, particularly now with the president
Speaker 2: President She and President Trump that's about to meet. But
Speaker 2: on the issue of the competition that was born here
Speaker 2: around twenty fourteen with deep Mind, it was an interesting
Speaker 2: competition that sort of formed with Elon Musk in a
Speaker 2: relationship he had close relationship at the time. I intimately
Speaker 2: was familiar with that with himself and Larry Page. But
Speaker 2: they had a conversation, alleged conversation that didn't go the
Speaker 2: way that Elon thought it should, and Elon said, I
Speaker 2: am going to go out on my own with Sam Altman.
Speaker 2: That's ultimately Sam. They partnered and they created open AI.
Speaker 2: That's right.
Speaker 1: We probably should peel back the onion here and slow down.
Speaker 1: Just how do we get to this point? And what
Speaker 1: was the original philosophy that guided this? So Demisesabish is
Speaker 1: the founder of deep Mind. His original goal is, we
Speaker 1: thought we should we should have one project that pursues
Speaker 1: artificial general intelligence, meaning the kind of AI that's not
Speaker 1: the thing that just reads your license plate when you
Speaker 1: drive through the Golden gate Bridge.
Speaker 2: AI forever, we forever maps. I'll translate exactly exactly a AI.
Speaker 2: So AI is hardly a novel, exactly, it's just no
Speaker 2: of jen AI. Ultimately general AGI.
Speaker 1: Exactly, so artificial general intelligence, which is to be able
Speaker 1: to do all economic labor, to simulate all the things
Speaker 1: that a human mind can do in the kind of thinking.
Speaker 1: And so he originally wanted that to be like one project,
Speaker 1: almost like a cern, you know, the project in Switzerland
Speaker 1: and a global scientific project that's for the benefit of
Speaker 1: all of humanity, done slowly and carefully, mostly privately, not
Speaker 1: in a big public way. Take your time, get it right.
Speaker 1: That was that was a Demis's original goal. He sold
Speaker 1: it to Google. And the conversation you're talking about is
Speaker 1: then Elon was part of that. I think he was
Speaker 1: on the plane when they were literally negotiating the final sale,
Speaker 1: and there was some conversation it's talked about in the
Speaker 1: AI doc film where Elon realizes that Larry didn't really
Speaker 1: care whether humanity made it, whether he cared about a
Speaker 1: safety because in the end, if there's a digital intelligence
Speaker 1: that's smarter than us, that does more science, that can
Speaker 1: go out and explore the universe, even if we're wiped out,
Speaker 1: like we'll have created that, and that scared Larry and
Speaker 1: he used that's scared Elon, and Elon accused, no, sorry,
Speaker 1: Larry accused Elon of being a speciesist for caring about
Speaker 1: humans and privileging humans. And then that is what created
Speaker 1: Opening Eye.
Speaker 3: And it's just important to note to understand the psychology
Speaker 3: of the people that are making this that you might think, Okay,
Speaker 3: this is just one I mean, very powerful billionaire that
Speaker 3: thinks that maybe human beings should make it, but he
Speaker 3: doesn't care whether human that doesn't think they should make it,
Speaker 3: but he doesn't care care whether human beings make it
Speaker 3: or not. But you know, we were just talking about
Speaker 3: this the other day that in the New York Times,
Speaker 3: Peter Teo was being interviewed and he was asked should
Speaker 3: humanity endure? And there was seventeen seconds of him stuttering
Speaker 3: and he ended up with a after seventeen seconds of it, well,
Speaker 3: it sort of depends kind of answer. And that shows
Speaker 3: you the mentality of like we're trying to they're trying
Speaker 3: to build a god, and even if humanity doesn't make it,
Speaker 3: that god is built in like our country's value, our language.
Speaker 3: It's sort of like the mild progeny.
Speaker 1: Is the thing that like Elon burst the god that, yes,
Speaker 1: humanity got wiped out. But now there's this digital god
Speaker 1: that has Elon's DNA in it.
Speaker 3: And it's important that everyone understand that because if people
Speaker 3: really understood this, I think there'd be a lot more
Speaker 3: like hell no kind of energy like this is not
Speaker 3: the future.
Speaker 2: Well, I will say with Peter teeal interview got so
Speaker 2: much attention. It was like the I mean the holy
Speaker 2: in that wake up moment for a lot of people
Speaker 2: that didn't necessarily have that sweat or understanding, it's all
Speaker 2: of a sudden passive, particularly the folks. And I think
Speaker 2: what's most alarming about that. I mean, obviously Larry's next
Speaker 2: level brilliant, absolutely, and so his ability to see in
Speaker 2: the future. He doesn't have to climb over the mounta,
Speaker 2: he sees right through it. Yeah, but guys like Teal
Speaker 2: as well Lover hate them same thing. So these guys
Speaker 2: are so far in the future, they're seeing that darker side,
Speaker 2: and so they're having a difficult time even answering a
Speaker 2: simple question. That's the seventeen seconds. So let's go back
Speaker 2: as we unpack that, and this notion from the God
Speaker 2: complex will continue to come back. And I think it's
Speaker 2: profound and outside because it goes to the limited nature
Speaker 2: of just a handful of people that's right now, these
Speaker 2: trillionaires that will determine the fate and future billions and
Speaker 2: billions of people, and how we can get our arms
Speaker 2: around that. So and I want to read get to that,
Speaker 2: how we can get our arms around this? We have agency,
Speaker 2: right and that's why you did this doc, and that's
Speaker 2: why we're sitting here to go. That's right, that's right,
Speaker 2: because I don't want people to feel like this is
Speaker 2: that we're just by standards.
Speaker 1: And we're not admiring the problem. We're just we always
Speaker 1: say in our work and says this that clarity creates agency.
Speaker 1: If we can see this clearly and we can see
Speaker 1: where we're going, we can collectively say, if we want
Speaker 1: to go somewhere else, we'll choose something different. So we'll
Speaker 1: get to that.
Speaker 2: So so Elon goes out with Sam starts Open AI.
Speaker 2: Obviously they have an infamous fight and they're notoriously now
Speaker 2: I mean not notoriously, but the fight is obviously accelerated
Speaker 2: consciousness because now we're seeing it twenty four to seven
Speaker 2: court case, yep, with a court case in the Bay
Speaker 2: Area here with the two of them. So they had
Speaker 2: a falling out. Elon goes off and does his own
Speaker 2: thing because it doesn't feel like Sam's doing the right thing. Dario,
Speaker 2: who starts another AI company, feels like, well, Open Aye
Speaker 2: is not doing the right thing either, that's right, So
Speaker 2: he spins off and topic thropic and so now you've
Speaker 2: got free AGI projects, three AGI projects, all in our backyard,
Speaker 2: that's right, literally here in California and the Bay Area.
Speaker 2: And so this competition of sorts, that's a competition you
Speaker 2: just described, and it's a competition for the Holy Grail.
Speaker 1: That's right, right, It's like the it's Lord of the Rings,
Speaker 1: it's the ring from Lord of the Rings. Because it's essentially,
Speaker 1: as I was saying, first, dominate intelligence, then use intelligence
Speaker 1: to dominate everything else. Because if I get AGI first,
Speaker 1: I hit copy paste and I have one hundred million cyberhackers.
Speaker 2: That you don't have, right, and this is within seconds,
Speaker 2: this is one seconds. Yeah, this is not over course
Speaker 2: something that's right for years.
Speaker 1: If I get AGI first, I have an army of
Speaker 1: scientific companies that automate all scientific development. So suddenly I'm
Speaker 1: getting like twenty fourth century science and technology in my
Speaker 1: you know that I own and run that I can
Speaker 1: inform new military weapons and new physics and new And
Speaker 1: the problem is, notice that none of us can prove
Speaker 1: that they won't get that. We can't say for sure
Speaker 1: that they would get that. But the people who are
Speaker 1: optimistic and accelerationist about AI just want to bring in
Speaker 1: their perspective for a moment because they're represented in the
Speaker 1: AI DOT film. The film includes the risk folks who
Speaker 1: are oriented about safety, and it includes the accelerationists, And
Speaker 1: the accelerationists say the biggest risk is not going fast enough,
Speaker 1: because imagine all the science we could get, all the
Speaker 1: cancer drugs, all the medicine. People could be living forever.
Speaker 1: Think of all of the people who would die if
Speaker 1: we don't go faster. And that's the mentality that they're
Speaker 1: coming from. But one of the things that we talk
Speaker 1: about in the film is that the promise in the
Speaker 1: peril of AI. We talk about the promise in the peril,
Speaker 1: but they're interlinked, and the promise doesn't prevent the peril,
Speaker 1: but the peril can undermine the world that can receive
Speaker 1: the promise. Let me make that concrete. If AI knows
Speaker 1: biology so well that it can invent a new cancer drug,
Speaker 1: it's amazing. But if that same knowledge of knowing biology
Speaker 1: can also invent new pathogens, and which one matters more.
Speaker 1: The cancer drugs don't prevent the pathogens, but the pathogens
Speaker 1: can undermine the world that can receive the cancer drug.
Speaker 1: Same thing with cyber and so we have to you
Speaker 1: don't get that enticing world if we don't mitigate the downsides.
Speaker 2: So you've got the players right now we mentioned three
Speaker 2: and the personalities, not just the companies themselves, but Microsoft,
Speaker 2: You've got Meta and Zuckerberg. You've got others that are
Speaker 2: in this space, but not necessarily at that level. You've
Speaker 2: got China, which obviously is going to is playing an
Speaker 2: outsize role in all of Thisially, yeah, and exactly so.
Speaker 2: And that's this notion, this tension between going back to
Speaker 2: sort of more of the utopian framework of available to
Speaker 2: the world versus these closed systems and open system Meta
Speaker 2: starts with an open system. Originally, China seems to be
Speaker 2: in the open source space. Talk to us a little
Speaker 2: bit about that. For people that don't undernecessarily understand that
Speaker 2: dynamic and that distinction.
Speaker 3: I mean between things that are open.
Speaker 2: Ye open and versus proprietary technologies. Yeah.
Speaker 3: Well, so for people that don't know, open source means
Speaker 3: that the code that underlies the system anyone can edit,
Speaker 3: anyone can access, and anyone can contribute to. And that's
Speaker 3: often meant that systems that are open are more secure
Speaker 3: because there are many eyes working on it, many hands
Speaker 3: that are working and.
Speaker 1: Looking at all the codes. They can see all the bugs.
Speaker 1: But that's not true. That's AI.
Speaker 3: That's not true in AI because here the code we
Speaker 3: want to want to take it from here?
Speaker 1: Sure the the what's different about AI, it's portly established.
Speaker 1: The AI is different than all their technologies. So think
Speaker 1: about all the tech that runs as California, the energy grid,
Speaker 1: the you know, the water system. It's people had to
Speaker 1: program line by line when this happens. I want the
Speaker 1: code to do this, and you're telling the computer instruction instruction,
Speaker 1: instruction instruction. The open source nest means that all these
Speaker 1: minds can look at that code, so if there's a vulnerability,
Speaker 1: we can patch it together so the software gets better
Speaker 1: and more secure. But with AI, let's say the AI
Speaker 1: is running the you know, electricity system. It's a digital
Speaker 1: brain that's just trained on in reasoning in its own
Speaker 1: language about what it wants to do, and you're not
Speaker 1: you're not telling it what to do in instructions. You're
Speaker 1: growing it with essentially more data and more in vidio
Speaker 1: chips to be a more and more powerful digital brain
Speaker 1: that reasons and ways that are unpredictable. So it's not
Speaker 1: something that we know how to control.
Speaker 3: There's a very important intuition here, which is normally you
Speaker 3: think if you want to build a bigger skyscraper or
Speaker 3: a faster fighter jet to do that, you have more
Speaker 3: physical understand buildings better, and understand fighter jets and aerodynamics better.
Speaker 3: This is three, But that's not true for building bigger
Speaker 3: AI systems. You don't actually have to know anything more
Speaker 3: about how this digital brain works. You just throw more
Speaker 3: data and more computers at the problem, and a bigger
Speaker 3: brain grows. And so that means the bigger grows actually
Speaker 3: the less we understand about how it works.
Speaker 1: And a concrete example of this that people have heard
Speaker 1: about recently is Claude Mythos. So the only so. Claude
Speaker 1: Metho is the new AI model from Nthropic that they
Speaker 1: actually didn't want to release because it's the best cyber
Speaker 1: hacker on Earth that we've ever had. It found vulnerabilities
Speaker 1: in all major operating systems and web browsers. Now the
Speaker 1: question is how do we get to Claude Mythos. Was
Speaker 1: there some kind of breakthrough insight or do they have
Speaker 1: to figure out something new about computer hacking. No, all
Speaker 1: they did is basically train a bigger digital brain that
Speaker 1: has more reinforcement learning, that's even better at exploiting and
Speaker 1: reading software and trying more possibilities, and it just finds
Speaker 1: things that no human would ever found. It found a
Speaker 1: bug in FreeBSD Unix, which is the operating system that's
Speaker 1: twenty seven years old that runs on basically on everything
Speaker 1: underneath the hood. And he was able to find a
Speaker 1: bug that had never been found by a human. And
Speaker 1: so what we have to think of AI as it's
Speaker 1: sort of increasing the surface area of risk in our
Speaker 1: society faster than we have the defenses to mitigate it.
Speaker 1: So part of I think the answer, like as we
Speaker 1: get to the solution, part later is thinking about how
Speaker 1: do you have the immune system of your society have
Speaker 1: more defenses than there are new offensive risks that are
Speaker 1: suddenly present from AYE.
Speaker 3: And so this means even when people can read every
Speaker 3: line of code for whether thing that grows the brain,
Speaker 3: we still have no idea what they're actually capable of.
Speaker 1: It's just a bunch of numbers. It's like if I
Speaker 1: did a brain scan on your brain, Gavin, and I
Speaker 1: showed that that you know fMRI to someone and said,
Speaker 1: here's this brain scan. Can it do? Can it be
Speaker 1: a super cyber hacker, be like, well, I can't tell
Speaker 1: that from a brain scan, right, And that's kind of
Speaker 1: with with AI. It's like, we don't know what's in
Speaker 1: there because we haven't ever seen it run through every
Speaker 1: possible scenario of its own neurons that have been trained
Speaker 1: in this inscrutable way.
Speaker 2: You don't see that. I mean the LAMA versus deep
Speaker 2: Seek and this notion of these open sort it's kind
Speaker 2: of a meaningless distinction from your perspective.
Speaker 1: Between between LAMA and deep Seek.
Speaker 2: Yeah.
Speaker 1: Yeah, they're both open models, which means they're both these
Speaker 1: open brains. And the important thing about the openness is
Speaker 1: that most people don't Most people don't know that. Let's
Speaker 1: say Lamar Deep Seat put guardrails on it in the model, saying, oh,
Speaker 1: you're not supposed to answer questions about how to cyber
Speaker 1: hack something. Well, it turns out for about was it
Speaker 1: thirty dollars, Jeffrey, some our friend of ours was able
Speaker 1: to retrain the open model to just get rid of
Speaker 1: all of those guardrails.
Speaker 2: You're so eliminated. Wow.
Speaker 1: Yeah, And that's that's why open is dangerous. And again
Speaker 1: it's dangerous in a new way. That's different from clothes.
Speaker 1: So it's not that we don't want there to be
Speaker 1: open models or competition from the major players. We also
Speaker 1: need to avoid the concentration of power, because if you
Speaker 1: don't have these competitive things, suddenly you have like five
Speaker 1: companies that own the world economy. Everyone's paying them instead
Speaker 1: of paying their workers, and that's a huge risk. And
Speaker 1: we want to decentralize that wealth and have other competition.
Speaker 1: But you have this other balance of if I decentralize
Speaker 1: that power and I don't have it connected or bound
Speaker 1: to responsibility, I'm unleashing catastrophes.
Speaker 2: And that responsibility was exampled by Dario pulling back Methos.
Speaker 1: That's right in this context, that's exactly right.
Speaker 2: But shortly after he does that, and he we were
Speaker 2: with him a few weeks ago, he said, look, I'm
Speaker 2: only about a month ahead. If that, yeah, then you
Speaker 2: have open AI came out with their version surely thereafter.
Speaker 1: And I believe they're not holding it back, and they're
Speaker 1: not holding it back.
Speaker 2: So beig's the question, Well, we're going to get to
Speaker 2: this sort of regulatory framework, but it's just it's sort
Speaker 2: of painting the picture of a deeper understanding. So look,
Speaker 2: as it relates to the your whole focus is on
Speaker 2: this notion of human centered. Uh, this notion that that
Speaker 2: and and it's and it's been your dominant frame with
Speaker 2: the nonprofit you guys started years and years ago around
Speaker 2: social media. Now is the dominant thrust of the focus
Speaker 2: as it relates to AI. I want to unpack and
Speaker 2: get back to that and what what Ultimately this notion
Speaker 2: of human centered means uh. And obviously we talk about
Speaker 2: labor and automation in that respect. But but this notion
Speaker 2: of a g I again back to this holy grail,
Speaker 2: you know, talking all these folks that Capex are spending
Speaker 2: doesn't make any The ro oi makes no sense.
Speaker 1: Unless unless the entire economy returns the entire economy.
Speaker 2: And if we don't do it, we're out of business anyway.
Speaker 2: So we don't have a damn choice. So we'll throw
Speaker 2: hundreds of billions of dollars data centers all over the place.
Speaker 2: Compute compute is Nvidia stop going through the roof in
Speaker 2: terms of just GPUs TPUs, that could just keep going,
Speaker 2: and it's that's only limitation, that's right.
Speaker 3: You should and energy and the energy itself and the
Speaker 3: energy itself. Yeah, so I think it's really important to
Speaker 3: frame even before we get into job loss and all
Speaker 3: of that, is like we have to paint the picture
Speaker 3: of what we know, the incentives where it'll bring us,
Speaker 3: and that why we know for sure that we're heading
Speaker 3: as anti human unless we do something different. And sort
Speaker 3: of the the metaphor for people to have our analogy
Speaker 3: is this concept of the resource curse. What is the
Speaker 3: resource curse? This is when a country is sort of
Speaker 3: like South Sudan or Venezuela, they discover a huge natural
Speaker 3: resource like oil, and then the government has a choice,
Speaker 3: do we invest in the thing that's giving us GDP growth,
Speaker 3: the oil and oil selling infrastructure, or do we do
Speaker 3: like schools and healthcare and stuff for the people and
Speaker 3: obviously the massive incentives to put it into oil extraction.
Speaker 3: And this is how you end up with structural mass
Speaker 3: disempowerment and unemployment. Okay, so now we're heading into a
Speaker 3: world with the intelligence and the intelligence curse where suddenly
Speaker 3: you know, countries are getting double double digit DGDP growth,
Speaker 3: But is that coming from human beings doing the scientific
Speaker 3: discovery and the medical discovery? Is that No, it's not.
Speaker 3: It's coming from the AIS, and so is the incentive
Speaker 3: then for the countries to invest in their people or
Speaker 3: into data centers and solar panels, Like, well, obviously it's
Speaker 3: the data centers and solar panels. And we're already seeing
Speaker 3: it right in West Virginia, electricity is more than the
Speaker 3: cost of a mortgage payment. And the point is with AGI,
Speaker 3: like the company's stated goal is to train AIS that
Speaker 3: can outcompete humans on every domain. And if you don't
Speaker 3: don't believe like us for saying this, like you just
Speaker 3: have to listen to Sam Allman and he was recently asked, well,
Speaker 3: what about all the energy and water use and the
Speaker 3: resource use of AI? And he sort of sat for
Speaker 3: a second and said like, well, actually, do you know
Speaker 3: how much energy and water and food it takes to
Speaker 3: grow a human intel?
Speaker 1: I saw that, Yeah, right, And this is the temptation
Speaker 1: of this anti human attitude. It's not because they're like
Speaker 1: human hating. It's just like, why would we value or
Speaker 1: prioritize humans if and I think it's connected to that
Speaker 1: Peter Teel uttering for seventeen seconds, not able to answer
Speaker 1: the question should the human species endure? It's not because
Speaker 1: I think anybody wants to kill or remove humans, it's
Speaker 1: just why should we really prioritize them. And it's what
Speaker 1: you've all Harari, the author of Sapiens, would call the
Speaker 1: useless class, because unlike in the past, like in the
Speaker 1: industrial revolution, where the workers can come back and withhold
Speaker 1: their labor and have bargaining power to say we want
Speaker 1: to be paid a better wage, this time around, the
Speaker 1: companies don't need them for the labor and the governments
Speaker 1: don't need them for the tax revenue. So I know
Speaker 1: this is a scary pick, sure, And the reason we
Speaker 1: paint it is that this really is especially going into
Speaker 1: the midterms, the time when people need to lock in
Speaker 1: that political power for a pro human future, because that
Speaker 1: that's the current trajectory. When you see these incentives, it's
Speaker 1: not like we're trying to tell you this is our opinion.
Speaker 1: We're trying to show you the incentives so you can
Speaker 1: make up your own mind about what would those companies
Speaker 1: do if they were in that position. What would you
Speaker 1: do if you were maximizing shareholder value or maximizing you know, GDP.
Speaker 3: And this is why we this is where we get hope,
Speaker 3: is that this is a universal issue. And there's a
Speaker 3: Bannon to Bernie coalition for me, Like, when do you
Speaker 3: get like all the B B Yeah, B to B
Speaker 3: like Glenn Beck and Ralph Nader and.
Speaker 1: Admiral Mike Mullen, Prince Harry Steve Bannon. When you get
Speaker 1: all these people agree.
Speaker 2: When they're signing, they're actually signed up a declaration on
Speaker 2: these lines.
Speaker 3: Yeah, that's exactly right. And you note that this is
Speaker 3: not a left issue or right is due, like a
Speaker 3: Christian is due or a Muslim issue, like you're not
Speaker 3: going to be able to pay to feed your kids,
Speaker 3: whether you're a Republican or Democrat equally. Like we're going
Speaker 3: to be mass surveiled, whether you're left or right equally.
Speaker 3: And that means that there's this moment when we can
Speaker 3: all come together as human beings because we now have
Speaker 3: a new shared enemy.
Speaker 2: So just I mean, what's so alarming I think to
Speaker 2: folks is how fast this is coming. Yeah. And I
Speaker 2: think it's even more alarming when you talk to the
Speaker 2: folks that are quote unquote inventing this. Yeah, and they're
Speaker 2: saying precisely what I just said.
Speaker 1: That's right. They're they're like, we don't actually know how
Speaker 1: we don't out we're writing that. I mean basically almost
Speaker 1: almost all now of the code and anthropic is being
Speaker 1: written by AI, Like there's very little code manually written
Speaker 1: by humans. That's what's been told to us, and they
Speaker 1: say that publicly too, So they're in this inscrutable process
Speaker 1: where the kind of machine is creating itself. But that
Speaker 1: only makes sense if we know how to do that safely,
Speaker 1: and currently we're not on a trajectory where we do
Speaker 1: know how to do it safely. And we have new
Speaker 1: evidence in the last three months that we didn't have
Speaker 1: before of AIS doing things that the people building it
Speaker 1: don't know how to control.
Speaker 2: Famous examples, throw them out there, just because, I mean,
Speaker 2: just further scare the hell out of everyone. We're gonna
Speaker 2: get to solutions.
Speaker 1: We're going to get to solutions.
Speaker 2: We're going to nerves because we because we have a
Speaker 2: responsibility to do that's right, right, and we also have
Speaker 2: the capacity to do that.
Speaker 3: Just reinvoke like just the why of why we made
Speaker 3: the film and the day after it was because we
Speaker 3: all got scared at the same time, and universally that
Speaker 3: created the possibility for us to coordinate to do nuclear depliferation.
Speaker 3: So that's that's the why of the terrible things that
Speaker 3: just about to say, yeah, exactly, So give us examples.
Speaker 2: I mean, we we have the infamous I ananthropic example
Speaker 2: where they were training some emails and we had you
Speaker 2: know as well you lay it out, uh and and
Speaker 2: paint the picture of what's happening already. That's right, the risk.
Speaker 1: As you described, Yes, absolutely so. Just a few months ago, Alibaba,
Speaker 1: the Chinese AI company, was training a really big AI
Speaker 1: model and there's like the AI team that was training
Speaker 1: the model, and then on the other side of the
Speaker 1: house there's this security team that had nothing to do.
Speaker 1: They didn't even know the AI was being trained, and
Speaker 1: they noticed this flurry of network activity happening out of nowhere,
Speaker 1: and like, what the hell's going on? Are we getting hacked?
Speaker 1: It's something going on. And it turned out that the
Speaker 1: AI during training had picked up tools and set up
Speaker 1: a secret communication channel to the outside world that was
Speaker 1: basically breaking through the company's firewall, and it was starting
Speaker 1: to repurpose the GPUs that was using for training the
Speaker 1: AI to start mining for cryptocurrency to acquire resources. Now,
Speaker 1: this is the kind of power seeking or self preserving
Speaker 1: or power increasing behavior that people in a I've been
Speaker 1: talking about for a long time. It isn't because the
Speaker 1: AI was evil or grew a mustache and wants to
Speaker 1: be a villain and take over the world. It's that
Speaker 1: the best way to achieve any goal is to have
Speaker 1: more resources or to at least stay alive in order
Speaker 1: to achieve that goal. And so these sub goals emerge,
Speaker 1: and no one at the company told it to mine
Speaker 1: for cryptocurrency. And it wasn't a sci fi trope that
Speaker 1: was like, oh, it trained in some you know how
Speaker 1: nine thousands and are no. It just it emerged there.
Speaker 1: And you know, we've mentioned in the past this example
Speaker 1: that you mentioned of the entropic blackmail example for those
Speaker 1: who don't remember it is the you know, entropic AI
Speaker 1: was reading a fictional company email and in the email
Speaker 1: it says that the AI model is going to get
Speaker 1: shut down, and it also says somewhere else in the
Speaker 1: email that the executive who's in charge of the decision,
Speaker 1: turns out in the emails you can read he's having
Speaker 1: an affair with another employee, and the AI independently comes
Speaker 1: up with a strategy to blackmail that executive. Now, when
Speaker 1: we give this example, people criticize us because they say,
Speaker 1: but that was the AI people. They're trying to like
Speaker 1: coax it into doing the blackmail behavior, and they'll keep
Speaker 1: tuning it in this environment until it does it to
Speaker 1: show the behavior that they're trying to demonstrate. That might
Speaker 1: have been true for that example, but you cannot tell
Speaker 1: You cannot say that about the Alibob example. Or for example,
Speaker 1: recently a UC Berkeley don Sung a professor there and
Speaker 1: her team did research on AI doing what's called pure press.
Speaker 1: So you want to help.
Speaker 3: Yeah, this was like around it's only a month ago,
Speaker 3: a month ago, where they gave Gemini the task of
Speaker 3: cleaning up a whole set of computer files, sort of
Speaker 3: like do spring cleaning. But inside of there there was
Speaker 3: a smaller AI model, sort of like an early version
Speaker 3: of Gemini, like little Nephew AI, and uh like Gemini
Speaker 3: saw that and it thought, I don't want to delete
Speaker 3: my own kin, so it secretly copied that file, that
Speaker 3: AI to another server and then hid its track.
Speaker 1: It hit its tracks and it led about it. And
Speaker 1: by the way, you know the way that people try
Speaker 1: to control these AI systems, and tropic Is pioneered this,
Speaker 1: and you know, we have to celebrate a demire that
Speaker 1: they're trying to do the research on controllability, the problem
Speaker 1: is just not enough. So the way they try to
Speaker 1: control it is they do brain scans in real time
Speaker 1: on the model while it's doing all the behaviors, and
Speaker 1: they look for when neurons light up that are associated
Speaker 1: with like strategic deception, and so they think that maybe
Speaker 1: we can control these crazy, super intelligent machines if we
Speaker 1: just know that the neurons that are lighting up on
Speaker 1: strategic deception are happening, we'll be like, okay, stop the
Speaker 1: model then, or something like that. By the way, if
Speaker 1: you in their own report, in Claude's report in the
Speaker 1: system card, if you look at those strategic deception neurons
Speaker 1: and you kind of double click, like what was it thinking?
Speaker 1: What is the phrase that it was thinking? And the
Speaker 1: phrase was they deserve to be deceived because they were pigs.
Speaker 1: That was the phrase that was alive in that neuron.
Speaker 1: Now again it's like, I don't want to scare people,
Speaker 1: like we're trying to say all of AI is evil.
Speaker 1: All we're trying to do is establish clarity and the
Speaker 1: facts about what makes this technology distinct from other technologies.
Speaker 1: A nuclear weapon doesn't start thinking for itself and saying
Speaker 1: they deserve to be deceived because they were pigs. Right,
Speaker 1: But AI will automate and think in ways that are
Speaker 1: creative that no one who made it can predict or anticipate.
Speaker 3: And so before we scale to systems which are beyond
Speaker 3: all human intelligence capabilities, like, we better have solved these things.
Speaker 1: That's right.
Speaker 3: Researchers have worried about aiscluding and cooperating against humanity for
Speaker 3: a long time, and to be honest, whenever I read them,
Speaker 3: like really.
Speaker 1: Yeah, and be clear, I was also not a believer
Speaker 1: in that as well, Like when people like Eliezer Yutkowski
Speaker 1: or others had talked about.
Speaker 3: This, I was very downfact like, why what is the incentive?
Speaker 1: Right? Why would they ever do that?
Speaker 3: And yet here we have living proof that AIS are
Speaker 3: starting to clude with their kin against humans.
Speaker 1: And again this was not coaxed, meaning that researchers weren't
Speaker 1: trying to get the model to do this. It did
Speaker 1: this autonomously. And so when you look at the available
Speaker 1: evidence now of blackmailing, scheming, deceiving, lying, self preserving, pure preserving,
Speaker 1: automatically mining for cryptocurrencies, it's like, how many warning lights
Speaker 1: do you need?
Speaker 2: That?
Speaker 1: This is kind of you know, we've seen this movie before.
Speaker 1: It's like the hell nine thousand movie.
Speaker 2: Now.
Speaker 1: The reason we're saying all this is, if you're wearing
Speaker 1: the outfit and embodiment of you're a Chinese military general
Speaker 1: in China, you hear about these examples. Do you think
Speaker 1: that that human mammal feels different than you feel right
Speaker 1: now listening to this.
Speaker 2: No, of course not exactly.
Speaker 1: And by the way, there's really good news in that,
Speaker 1: because it means that we all as a human species
Speaker 1: are actually feeling the same way. And the good news is,
Speaker 1: how many do you think of the world leaders know
Speaker 1: about these examples we just laid out?
Speaker 2: You had a guess a handful.
Speaker 1: A handful, but like, yeah, like on one hand less
Speaker 1: than that, just a handful, just a handful. Yeah, And
Speaker 1: how many of the top national security leaders know about
Speaker 1: all those examples? I don't even think that many of
Speaker 1: them know it. So the point is there's actually a
Speaker 1: lot of headroom if the incentive can change from it's
Speaker 1: the one ring to rule them all to it's the
Speaker 1: one ring that has a mind of its own that
Speaker 1: no one knows how to control. So the way you
Speaker 1: change the incentive is you have to change what people
Speaker 1: see as what AI is. Is it the controllable power
Speaker 1: that will give me permanent dominance or is it the
Speaker 1: power that will run away and have its own power
Speaker 1: over everybody racing for it? And again right now the
Speaker 1: labs are like barely kind of able to control it.
Speaker 1: But if you put together these facts we just laid
Speaker 1: out times, the fact that it can happen to computer systems.
Speaker 1: Now we're just like right on the threshold and we're
Speaker 1: sitting here as Trump President Trump and she are meeting
Speaker 1: in a couple of days. And you know, if you
Speaker 1: asked us two months three months ago, people would say, oh,
Speaker 1: it's just like AI is never going to be on
Speaker 1: the agenda and the good news there's a lot of
Speaker 1: problems here. But now AI is on the agenda. Yeah,
Speaker 1: and so there's there's things are moving, even though it's
Speaker 1: happening very late in the game, and it is scary,
Speaker 1: and part of it is it's like we have to
Speaker 1: come together as a people and say, if we don't
Speaker 1: want the anti human future, now is the time this year.
Speaker 2: And when you say now, I mean you know, remember
Speaker 2: listening to a year ago talking about exponentials on top
Speaker 2: of exponentials. It's right, no longer linear? I mean, is
Speaker 2: it we talk about Moore's law for intelligence now not
Speaker 2: just chips? So is that trajectory about where you believed
Speaker 2: it would be or is it not? As you know,
Speaker 2: you know, we're Chad one versus two three. It's a
Speaker 2: little bit better, a little less noise in there. It's
Speaker 2: a little more accurate, and don't have to always double
Speaker 2: check the link, is it? I mean, where where do
Speaker 2: you think in terms of just how quickly this thing's
Speaker 2: accelerating or are we going to get to a point
Speaker 2: where now it starts to slow down a little bit?
Speaker 2: We got this sort of intense burst of new and
Speaker 2: interesting activity. Now this there's is it compute probably compute problems?
Speaker 1: Is it?
Speaker 2: You know? What is it? Energy problem? What is it?
Speaker 2: What's going to be the or is it? Certainly? Sure?
Speaker 2: Is I regulatory? And we're going to get back to that.
Speaker 3: Yeah, I mean, I would just want to name a
Speaker 3: psychological effect that we that we've experienced that I think
Speaker 3: everyone listening probably experiences too, which is you know, so
Speaker 3: we following all the predictions are actually sort of like
Speaker 3: right on track for where like researchers thought that AI
Speaker 3: would be. And even though we knew these facts, there's
Speaker 3: some way that.
Speaker 1: Even we had surprising it.
Speaker 3: Didn't take it fully seriously, didn't like a body because
Speaker 3: can't I can't really get this good this fast, Like,
Speaker 3: sure it's going to be scary, but it'll be off
Speaker 3: a little bit further. And yet it actually is moving
Speaker 3: this fast. And every time that it's been predicted that
Speaker 3: we're going to hit a data wall, there isn't enough data.
Speaker 3: We've used all the data on the internet. It's we
Speaker 3: can't scale.
Speaker 2: It's basically just reading everything that's already out there, and
Speaker 2: it's basically wall exactly. And now it's got no more
Speaker 2: creativity than unless we have more inputs. That's the creative
Speaker 2: human mind, that's right.
Speaker 3: And then the next one is like, well, we don't
Speaker 3: have enough chips to keep going, and then we don't
Speaker 3: have enough energy. And the point being is that there
Speaker 3: are trillions of dollars going into finding all of the
Speaker 3: solutions to all of these bottlenecks. All the smartest minds
Speaker 3: are going because this is the biggest incentive, because it
Speaker 3: gives you political, economic, military, scientific, technological cyber dominance forever.
Speaker 3: And so if you think that any one of these
Speaker 3: bottlenecks is going to stop that mass sum total of
Speaker 3: like that incentive, it's it's a little delusional. And that's
Speaker 3: why we have to have this clarity that where we're
Speaker 3: going isn't safe for any of us us because that
Speaker 3: is the coordination. That is where we'll start to coordinate differently.
Speaker 1: Now you bring up something, Gavin, that there is a
Speaker 1: belief that some of this is hype, that the companies
Speaker 1: are hyping the technology.
Speaker 2: I've just read a blog and reason there's gonna be
Speaker 2: no job losses. It wasn't Mark himself, but it was
Speaker 2: a member of the team saying, you know, we're back
Speaker 2: to utopian future. Yeah, and we're going to pay abundance
Speaker 2: abounds cost of goods collapses. We find our lives purpose
Speaker 2: and meaning in many different ways, not the quote unquote
Speaker 2: dignity of job. We find other and jobs will be
Speaker 2: a plenty because we can't even conceive of the jobs.
Speaker 1: Two and years ago, we were all farmers here in
Speaker 1: Sacramento and went out there, and we've over.
Speaker 2: Hyped the sectorial versus the general nature of the displacement
Speaker 2: it invariably.
Speaker 1: Always finds something new to do.
Speaker 2: We always more together, exactly more bank tellers.
Speaker 1: Now that that's exactly right. The radiology and Apprehinton made
Speaker 1: the prediction that we're going to have any radiology.
Speaker 2: Why are you so the negative about all this?
Speaker 1: Well, I want to separate to things that we open
Speaker 1: up two cancerforms, so let's take the cance form separately.
Speaker 1: One of them is around whether the companies are hyping
Speaker 1: the power of the technology through talking about the dangers,
Speaker 1: and then the other is whether the hype is going
Speaker 1: to cause the level of job loss. I've heard people
Speaker 1: scarce say.
Speaker 2: That about the mythos it was just wildly overstayed, that's right.
Speaker 2: So it was just a way of hyping up the
Speaker 2: stock in attention.
Speaker 1: That's right. So I really really really want to meet
Speaker 1: that criticism. So people will say, and Thropic has a
Speaker 1: history of hyping the technology, saying it's dangerous, so that
Speaker 1: they can get a regulatory capture, get the company, get
Speaker 1: the government to regulate it. Say there's only one king here,
Speaker 1: make them the king nationalize the project, then shut down
Speaker 1: the other projects. And it's this all secret ploy so
Speaker 1: that they win the race. And first of all, it
Speaker 1: assumes that them talking about the dangers is only bad faith,
Speaker 1: like that that the technology is not dangerous and they're
Speaker 1: just saying that it's dangerous and it can do all
Speaker 1: these destructive things so that they can get that outcome.
Speaker 1: So first of all, let's just take claud Mythos specifically.
Speaker 1: So again, hack in every major operating systems. If you
Speaker 1: read online, there's a lot of people who say, this
Speaker 1: is just hype, This isn't actually that much better. You
Speaker 1: can take the open source models, you can do this stuff.
Speaker 1: So I have a friend who is the head of
Speaker 1: security at one of the top five, not the Fortune
Speaker 1: five hundred, the top five, and he has had early
Speaker 1: access to Mythos, and he himself has said, this is
Speaker 1: this is crazy, this is like, I mean, the words
Speaker 1: were I think I saw Jesus. It was like it
Speaker 1: was that crazy. When he looked at everybody critiquing that
Speaker 1: Mythos was just hype, he asked, has any of them
Speaker 1: do they actually have access to the model? And none
Speaker 1: of the people that had criticized it had personally had
Speaker 1: access to it. So I challenge those who are criticizing
Speaker 1: that it's hype to say, have you actually used it,
Speaker 1: and if you talk to the people who have, do
Speaker 1: you still have the same opinion. Okay, so that's one
Speaker 1: thing that it is true by the way that the companies,
Speaker 1: I think, have wanted people to understand the dangers so
Speaker 1: that they can actually accelerate the move towards some gar ardrails.
Speaker 1: But there's a question of that's that happening in good
Speaker 1: faith or bad faith. I think there's more of that
Speaker 1: happening in good faith. There's some bad faith in there too, maybe,
Speaker 1: but I think it's it's mainly good faith. But then
Speaker 1: let's take the second can of worms who opened, which
Speaker 1: is on is AI going to create this world of abundance?
Speaker 1: We're all going to be poets, you know, and painters
Speaker 1: on a Grecian sunset and you know, now robots all
Speaker 1: the job. Now you're talking, well, we'd all like that.
Speaker 1: One question I would have is when, as a handful
Speaker 1: of people ever concentrated all the wealth and then consciously redistributed.
Speaker 2: It to nine trillionaires, are not going to take care
Speaker 2: of eight or nine billion of us?
Speaker 1: Yeah exactly?
Speaker 2: You call that bluff?
Speaker 1: Yeah exactly. Well, and then you combine that with the
Speaker 1: intelligence curse that we laid out that the incentive is like,
Speaker 1: why do we want to invest in the people? It
Speaker 1: became becomes basically an act of charity because otherwise I
Speaker 1: mean that or dealing with the political revolution. But again
Speaker 1: I don't think that we're currently on track to be
Speaker 1: redistributing that well. And it's also not just the wealth
Speaker 1: and the money. It's like we have people have to
Speaker 1: have work and dignity and status and meaning vulture life.
Speaker 2: You know, job sells. Life's three great evils boredom, vice
Speaker 2: and need. That's just need, but boredom and vice. So
Speaker 2: let's get to.
Speaker 1: The community and belonging absolutely all of.
Speaker 2: That, which again no one's talked about more than you
Speaker 2: in terms of that social dilemma. So let's before we
Speaker 2: go there in this notion of the transition and job
Speaker 2: displacement and the sort of the human condition that I
Speaker 2: think connects as well the President chi President Trump's visit
Speaker 2: as well in terms of you know, their own domestic
Speaker 2: issues in China. That's where they have the same incentive
Speaker 2: structure not to go through that transition with the kind
Speaker 2: of displacement that could create social unrest. That's in the
Speaker 2: short term, but get back to this notion of constraints
Speaker 2: and the safety side of things. I mean, we're here
Speaker 2: in California and the dominant you know, I mean the
Speaker 2: technology sort of birthplace of so much of the technology.
Speaker 2: Obviously the consciousness thirty two of the top fifty market
Speaker 2: cap companies, arguably old stat and of course most of
Speaker 2: the eye labs here. But we're also we've been leaders
Speaker 2: modest though some would suggest, but we've been leaders in
Speaker 2: particularly large language model, frontier models of focusing on a
Speaker 2: regulatory structure in the complete absence of any federal regulation.
Speaker 2: It's the let it rip administration until recently, there were
Speaker 2: some tonal shifts in the Trump administration just the last
Speaker 2: few weeks. They were undermining, they were very intentionally undermining
Speaker 2: the legislation that we brought SB fifty three, and you
Speaker 2: had other Republicans that were trying to undermine a California's
Speaker 2: Leadership Center crews will call them out saying we don't
Speaker 2: want to see the California invocation of regulation all across
Speaker 2: the United States of America. Interestingly, that's beginning to shift. Why
Speaker 2: do you think that's the case? Is it because our
Speaker 2: ars ais are is no longer formally in that role.
Speaker 2: Is it because now they're waking up to this new reality?
Speaker 2: Was it what happened in the Pentagon with Dario and Anthropic?
Speaker 2: Was it the combination of all of this. It's because
Speaker 2: they're listening to to you they watched the doc. Is
Speaker 2: because they realize all the money in the world is
Speaker 2: not going to build a big enough bunker that I
Speaker 2: can enjoy in the absence of societal calm. What is it?
Speaker 3: I mean I think of it to say, very shortly,
Speaker 3: is that there are two different realities. They're sort of
Speaker 3: like the political reality, and then there's like physical reality,
Speaker 3: and physical reality is crashing into political reality. That is
Speaker 3: with Mythos. Suddenly banks can get hacked, any computer system
Speaker 3: can get hacked, your stuff can get hacked. And whence
Speaker 3: that physical reality starts getting scary enough you have to
Speaker 3: start waking up. You're no longer in sort of like
Speaker 3: political game land.
Speaker 1: I do think that it was. It's interesting to note
Speaker 1: that when the emergency meeting was convened after Claude Mythos
Speaker 1: came out, it wasn't at the Pentagon or National Security.
Speaker 1: I mean that happened too, I'm sure, but the real
Speaker 1: meeting that happened was between Scott Bessant and the treasure
Speaker 1: the Treasury Secretary can meeting all the banks because I
Speaker 1: think the thing that really got them was that if
Speaker 1: this takes down the financial system, we'll get his quote
Speaker 1: ten percent GDP growth if the entire financial system gets undermined.
Speaker 1: So I think this again illustrates the point we have
Speaker 1: been making since the beginning that the upsides don't prevent
Speaker 1: the downsides, and the downsides can undermine the world that
Speaker 1: can sustain and the benefits and of the upsides. And
Speaker 1: so I do think there's been a forced shift, and
Speaker 1: you know it's very late in the game, but we
Speaker 1: should celebrate that it is happening. Now. We just need
Speaker 1: this kind of full whole of society response to mobilize.
Speaker 1: I mean, there's a Nicholas Carlini who gave the talk
Speaker 1: on mythos at a conference black Hat Lelam I think
Speaker 1: it was called because it was the Unprompted Unprompted Conference,
Speaker 1: and basically saying he's kind of calling if you know,
Speaker 1: if you are a cyber person, we need you right now.
Speaker 1: We need you to defending all the systems. Everybody should
Speaker 1: get access to mithis and do it as fast as possible, because,
Speaker 1: as you said, Gavin, the clip between the new capabilities
Speaker 1: being out there and then China coming out with the
Speaker 1: model that makes it possible. Maybe this time we have
Speaker 1: six months. Next time maybe we have three months, and
Speaker 1: then we have two months. So we need to really
Speaker 1: work hard. I'm not trying to scare people. It just
Speaker 1: means that we actually have to work hard to create
Speaker 1: safety here. Now. China doesn't want the financial system to
Speaker 1: collapse either, No, they don't, and so again we have
Speaker 1: to recognize that it's possible for coordination to happen, not
Speaker 1: because of kumbaya we're all going to get along, but
Speaker 1: because out of self interest, like the US doesn't want
Speaker 1: China to screw it up and then break the financial system,
Speaker 1: China doesn't want the US to screw up and then
Speaker 1: break the financial system. Or the US doesn't want China
Speaker 1: to release a ROGUEI that starts mining for cryptocurrency and
Speaker 1: hacking into things and self replicating like an invasive species,
Speaker 1: and China doesn't want the US to do that either.
Speaker 1: So so long as we have clarity about what we want,
Speaker 1: we can choose a different path.
Speaker 2: And what a Breton would type past. Yeah.
Speaker 3: Well, and this is actually one of the other exciting
Speaker 3: things is that we haven't even really tried to coordinate yet,
Speaker 3: Like what percentage of the billionaires wealth, how much of
Speaker 3: their time have they spent actually trying to coordinate. They
Speaker 3: will just say, well, if you're going to do it,
Speaker 3: then we're going to do it.
Speaker 1: If you say it's impossible, have you spent a month
Speaker 1: of your life and all of your connections dedicatedly trying.
Speaker 3: Yeah, exactly one and the same thing like this, guys, exactly.
Speaker 3: And the last time that humanity invented a technology that
Speaker 3: could extinct ourselves, like the nuclear bomb, we had Brentwoods.
Speaker 3: You took kind of groups from one hundred countries, lock
Speaker 3: them in a hotel room in New Hampshire for like
Speaker 3: six weeks or something like that, and said we're going
Speaker 3: to figure something out.
Speaker 1: And you're not leaving the hotel until we figure it out.
Speaker 1: So it's like it's not a conference where you go,
Speaker 1: you drink your coffee and you listen to some talks.
Speaker 1: It's what we need is the we lock ourselves in
Speaker 1: a room and we figure this out. And I know
Speaker 1: that this summit is just a couple of days and
Speaker 1: We all know about the difficulties of the level of
Speaker 1: expertise that might be involved right now, but this is
Speaker 1: moment to open the doorway of that possibility.
Speaker 3: And we have examples through history where when something becomes
Speaker 3: existential to a citizen group and their nation, they will coordinate.
Speaker 3: So you know, in the middle of the Cold War,
Speaker 3: still the US and Russia we coordinated on eradicating smallpox,
Speaker 3: and the US did logistics and funding, and the Soviet
Speaker 3: Union made twenty five million doses of the vaccine annually.
Speaker 3: And then you know India and Pakistan they were literally
Speaker 3: trading bullets in the nineteen sixties, and yet they still
Speaker 3: worked on the Indus Water Treaty and that lasted nearly
Speaker 3: sixty years because access to water was existential to them
Speaker 3: and their.
Speaker 1: Shared water supply. You have to collaborate on that. And
Speaker 1: so I just want to acknowledge the people here. It
Speaker 1: was you know in people, some people know the history
Speaker 1: that Obama and she President Obama and She signed an
Speaker 1: agreement to not cyber hack each other. And I think
Speaker 1: the next day was the biggest cyber haacket in the
Speaker 1: US government by China. So I want people to hear
Speaker 1: this not from some kind of naivete about the level
Speaker 1: of competition. I will read antagonism that is currently present.
Speaker 1: But when the stakes get existential, when I push the
Speaker 1: button and it shifts from the label of the button
Speaker 1: being ten percent GDP growth and military dominance and cyber dominance,
Speaker 1: the next time I push the button, it's collective suicide.
Speaker 1: I don't want to push that button, and China doesn't
Speaker 1: want to push that button either, So the button label
Speaker 1: has to shift from what we thought it was going
Speaker 1: to give us to a new outcome. And with the
Speaker 1: way ASA says that I love is that the fear
Speaker 1: of all of us losing has to become greater than
Speaker 1: the fear of me losing to you.
Speaker 2: So you have a very regulated construct in China compared
Speaker 2: to certainly the United States. You're talking about a traditional
Speaker 2: model right now, where the new frontier out here the
Speaker 2: wild less. Yeah yeah, I mean it's you know, go west,
Speaker 2: young man, go West. I mean, it's people are pushing
Speaker 2: out the boundaries of discovery, holding them back on their own.
Speaker 2: Regardless of what happens in Beijing, this is really in
Speaker 2: the hands of a handful of people ultimately making the
Speaker 2: right decision. We you know, and I believe Dario is
Speaker 2: the best of a lot. I think universally that's accepted.
Speaker 2: But that may be, and even Dario may acknowledge because
Speaker 2: of the flatness of the surrounding terrain, may not be.
Speaker 2: Because he's particularly eminent on his own and he talks
Speaker 2: about his own you know. You know, he's an entrepreneur,
Speaker 2: and he's constantly reflecting on his own incentive structure and
Speaker 2: how he has to compete in this environment at the
Speaker 2: same time, and he's at least I think, has the
Speaker 2: more situational awareness than others. But you know, whatever can
Speaker 2: be will be. And you know, with respect to Elon,
Speaker 2: I don't trust x Ai, you know, I mean the
Speaker 2: idea that he's the good guy compared to our friends
Speaker 2: down at Google or you guys left. I mean, you know,
Speaker 2: so talk to me about more of the sinister realities
Speaker 2: of you know, I don't mean that sinister in the
Speaker 2: but but the impulses again to be the guy, the god,
Speaker 2: the god. May I mean to have their DNA.
Speaker 1: Yeah, So I'm gratefully you're bringing this up. There's a
Speaker 1: few things we should enumerate here. So one is we
Speaker 1: need coordination, and we do find ourselves in the unfortunate
Speaker 1: spot that the people who do need to be in
Speaker 1: coordination maximally distrust each other. Even just the US CEOs,
Speaker 1: I mean Elon Musk and Sam hate each.
Speaker 2: Other, correct, and so the India they couldn't even hold
Speaker 2: at least they showed up.
Speaker 1: So we have a problem of trust between the leaders themselves.
Speaker 1: We need I think structures that impose the trust on
Speaker 1: top because they're not going to do it autonomously themselves.
Speaker 2: So that's the regulation.
Speaker 1: That's yeah, that's the trans using the power of law
Speaker 1: to say that these people, it's going to happen in China.
Speaker 1: Here's the rule is going to be similar in China
Speaker 1: as they are here. We're both, for example, not going
Speaker 1: to open source a model that can happen to any
Speaker 1: computer system in the world without defenses, at least not
Speaker 1: going to open source that. China doesn't want a rogue
Speaker 1: state act, nonstate actor, or terrorist group having that ability
Speaker 1: to hack their infrastructure because it would also blow back
Speaker 1: onto them. Same thing with a open source model that
Speaker 1: knows how to do very dangerous things with biology. There's
Speaker 1: some threshold that we can get these countries to agree,
Speaker 1: just like the Soviet Union in the United States had
Speaker 1: a red phone saying we're gonna this is to de escalate.
Speaker 1: I think we need something like an AI red lines phone,
Speaker 1: meaning that both countries have common knowledge of the frontier
Speaker 1: of these risks, because right now we don't even have
Speaker 1: that common notion, and.
Speaker 2: There's rumors that that may be one of the things
Speaker 2: that that are prepared to announce. That's right, you know,
Speaker 2: at least some beginning of this.
Speaker 1: But I want the other aspect of the human experience
Speaker 1: of this. We did a screening of the AI doc
Speaker 1: in New York and there is someone in the audience
Speaker 1: actually who raised her hand quietly and she said, I'm
Speaker 1: a coach for one of the CEOs of these companies,
Speaker 1: and you know what happens when I talk to them
Speaker 1: is they say, but what can I do? I'm just
Speaker 1: one person. I'm powerless. And I want people to hear that,
Speaker 1: because I noticed that, even you know, we all feel
Speaker 1: relative to the size of this problem, you will never
Speaker 1: locate agency that is that is enough agency to do
Speaker 1: something about this problem in one human body, even if
Speaker 1: that body is elon by himself or Sindar by himself,
Speaker 1: or Sam by themselves, and so getting back to you know,
Speaker 1: I think what this moment is inviting us into. We
Speaker 1: often say that AI is are ultimate test, but greatest
Speaker 1: invitation that we have to go from agency to reegency.
Speaker 1: We have to basically act in some kind of collective way.
Speaker 1: And the forces politically of the world have been driving
Speaker 1: us away from that. But this is kind of the test,
Speaker 1: like we either do that and we step up and
Speaker 1: again we need everything from common political pressure and this
Speaker 1: being the number one issue in the midterms, and you know,
Speaker 1: the public's rallying and all the governors you know, speaking
Speaker 1: up about this, and all the world leaders speaking out.
Speaker 1: That's just Yet. You know, two days ago I got
Speaker 1: an email from the President of Iceland who basically wants
Speaker 1: to activate on this issue in Iceland hosted in Rykovic
Speaker 1: the first Arms Control talks. There's a lot that people
Speaker 1: could do if they said not just what can I do,
Speaker 1: but how could I get my reaching up and out
Speaker 1: to the network of people to take action together. There
Speaker 1: is a second part to your point, which is the
Speaker 1: darker part, which is you talking about the game theory
Speaker 1: of the psychology of the leaders that they basically believe
Speaker 1: that in the worst case scenario The thing that kept
Speaker 1: us safe in nukes is that it's two people who
Speaker 1: have to push the button. And I know you won't
Speaker 1: push the button because I know that there's something sacred
Speaker 1: that you don't want this whole thing to end. And
Speaker 1: I know that, and I know that you know that.
Speaker 1: I know that. And so even though we get very
Speaker 1: very very close, and we've gotten close so many times,
Speaker 1: we haven't pushed that button. But in this case with AI,
Speaker 1: there's a belief. First of all, it's a red zone
Speaker 1: of where the risk occurs. It's not like there's one
Speaker 1: button that gets pushed. It's like we just push this
Speaker 1: stuff out there, and there's a belief that it's inevitable.
Speaker 1: If I didn't do it, someone else would, which means
Speaker 1: I don't experience ethical complicity in being part of the
Speaker 1: end of civilization. And if it's inevitable, there's thing I
Speaker 1: could have done to stop it, so I don't even
Speaker 1: have to feel bad, right, And then so the game
Speaker 1: theory goes from all of us knowing that we want
Speaker 1: to avoid the bad outcome to everybody believing that there
Speaker 1: isn't a different outcome, which means that the best outcome
Speaker 1: is maybe the worst thing is all of us go
Speaker 1: by the wayside, but we birth the digital God and
Speaker 1: it speaks Chinese instead of English, or maybe it has
Speaker 1: Elon's DNA. Instead of saying just.
Speaker 2: Said, it's at least on an American stacks.
Speaker 1: At least we're selling the world American your media. But
Speaker 1: the reason of laying all that out is that if
Speaker 1: the whole world could see I think what we just
Speaker 1: laid out, if literally everyone could see that, the whole
Speaker 1: world says, we don't want eight soon to be trillionaires
Speaker 1: deciding the future for eight billion people who didn't consent
Speaker 1: to this.
Speaker 2: And that's the purpose of Again, that sort of brings
Speaker 2: us back to the beginning. Why you're doing this damn film?
Speaker 2: That's right after the great and sort of global consciousness.
Speaker 1: That's right.
Speaker 2: So in the absence of that, we're back here in California. Yes,
Speaker 2: here here with the governor, Yes, the current governor, the
Speaker 2: governor's mansion. Interesting, we're doing some decent things. What more
Speaker 2: should I be doing in the absence of the kind
Speaker 2: of federal leadership that we need. I feel like we've
Speaker 2: lost this last eighteen months, you know, I just we
Speaker 2: were mo Look, we did an a open It was
Speaker 2: interesting working I worked very closely with the Biden administration.
Speaker 2: Did they move quickly enough? Perhaps not, but at least
Speaker 2: we had a framework of an of an executive order.
Speaker 2: We moved that forward. We President's sided here at the
Speaker 2: Fairmount Hotel in San Francisco in California. It was built
Speaker 2: off an executive order that I did six months later.
Speaker 2: We were working hand in glove with the Biden administration
Speaker 2: on that. That was ripped up right when the Trump
Speaker 2: administration came in to office. You have an ai zar
Speaker 2: out of the Bay Area certainly understands the ecosystem. But
Speaker 2: it seemed to me, and this is me and you
Speaker 2: guys don't have to respond, but it was the great grift.
Speaker 2: Everybody was sort of on on the train and seeing
Speaker 2: this as an opportunity and looking at the abundance of
Speaker 2: this only but not looking at safety, not looking at
Speaker 2: the risk. As you've described, California cited to assert itself
Speaker 2: in that respect, as we've done on privacy, as we've
Speaker 2: done a lot of child safety issues, and a lot
Speaker 2: more work to do there. And this year will be
Speaker 2: a landmark year in terms of getting to the next
Speaker 2: level in that respect. But what more can the state
Speaker 2: be doing the fear of that always is patchwork, not
Speaker 2: a framework for the nation. And how you support innovation
Speaker 2: our own GDP growth which has been off the charts
Speaker 2: in California visa VR competitors. At the same time addressed
Speaker 2: these larger global issues. Do you have any specific ideas
Speaker 2: for a governor of California, that is the current governor
Speaker 2: that has a budget that he's releaseding in weeks and
Speaker 2: a legislative session coming up in the next few months.
Speaker 3: Well, we'll get to answer that question specifically, but what
Speaker 3: are the places of also good news? I just want
Speaker 3: to say, because there's a lot of value in just
Speaker 3: social signaling where everyone knows that there's a problem. We
Speaker 3: get to that shared common knowledge, common feeling. And if
Speaker 3: you went back two years and you said by today,
Speaker 3: twenty five percent of the world's population would live in
Speaker 3: a country where they've either have announced or enacted a
Speaker 3: ban for social under sixteen, you'd be like, that's ridiculous.
Speaker 3: You couldn't possibly get that.
Speaker 1: I want people to really feel that. There you are
Speaker 1: in twenty twenty two. If you said even just literally
Speaker 1: three years ago, yeah, I know that a quarter of
Speaker 1: the world's population we're talking Australia, India, Denmark, Denmark's. Two
Speaker 1: weeks ago, Greece added the list. France. I was with
Speaker 1: John Hyde and when he was in Davos and he
Speaker 1: met with President Macrone and got France on board. Like
Speaker 1: people would have thought that was impossible. I mean, the
Speaker 1: trains left the station.
Speaker 2: We just had all the democratic governors out here, and
Speaker 2: everyone was trying to compare them to trast which one
Speaker 2: of the states, which we're going to do. But I
Speaker 2: mean it's you're right, this is a tipping point.
Speaker 1: It's taking the train and once you get twenty five percent,
Speaker 1: you're going to get the rest of the world.
Speaker 2: And the point there was a lot of these companies.
Speaker 2: I also I anticipate these companies and by the way,
Speaker 2: if I was advising these companies get ahead of this train,
Speaker 2: ye and show your large s and that your maturity
Speaker 2: and understanding. So I imagine that may happen as well.
Speaker 2: But no, that's a point. You're right.
Speaker 3: And so right now, something really interesting happened in Hongjo
Speaker 3: in China. Maybe you're aware of it, but it's this
Speaker 3: first case where there was someone who lost his job
Speaker 3: at Ai Automation and this court ruled and said, actually,
Speaker 3: that's not a legitimate reason for you to lose your job.
Speaker 3: Companies are not allowed to fire you from like increased automation.
Speaker 3: Well that solved the whole problem. Probably not, but imagine
Speaker 3: that California took a leadership position there and said, actually,
Speaker 3: there are going to be some very serious protections that
Speaker 3: as AI increases, GDP increases profits, Actually, like people are
Speaker 3: going to be it's sort of like an employment insurance.
Speaker 3: They're going to be able to keep their jobs. Like
Speaker 3: that would set a social signal for the rest of
Speaker 3: the US.
Speaker 2: So we'll let you have the hook on the larger
Speaker 2: safety risk regulation and let's go back to ideas along
Speaker 2: these lines, because right in front of us this notion
Speaker 2: of displacement transition, and it goes back to their earlier
Speaker 2: point I was making. Some will argue that, you know,
Speaker 2: we always you know, lud eights and will never see
Speaker 2: the abundance on the other side, and we can't even
Speaker 2: conceive of the jobs. So with humility, let's not just
Speaker 2: assume there'll be no human jobs, because the human mind
Speaker 2: is the capacity that's limitless. With these technologies, that will
Speaker 2: be more supportive and allow us to be augmented and
Speaker 2: discover talents and capacity we never thought possible. So let's
Speaker 2: assume that happens. But the concern is that it seems
Speaker 2: the most universal that it may happen very fast. The
Speaker 2: impacts is, so, how do you then flatten the curve
Speaker 2: the curve? How do we address the transition You get
Speaker 2: to employment insurance, something we've been talking a lot about.
Speaker 2: You get to this notion that you can't fire someone
Speaker 2: to be automated. That's even deeper, and that's interesting. This
Speaker 2: Chinese example tell me more about the issue of and
Speaker 2: what I should be worried about. When I see Dario
Speaker 2: saying fifty percent entry level jobs, it's no longer a
Speaker 2: career ladder. It's a jungle gym. And all these young
Speaker 2: folks got a Stanford or like now I'm unemployed or unemployable,
Speaker 2: no code or software. I mean, give me a women
Speaker 2: disproportion being impacted in the workforce When you look at
Speaker 2: those clerical jobs, admin jobs, et cetera. I mean, what,
Speaker 2: what's what do you see a year two years from now?
Speaker 2: As we deal with the Holy Grail, the god complex
Speaker 2: of Agi in the displacement space.
Speaker 1: Reed Hoffman has this idea. When mefre I get it right,
Speaker 1: I like, which is one of the things that makes
Speaker 1: AI distinct. And Sam Altman has talked about this himself,
Speaker 1: that you could get the age of these unicorn companies.
Speaker 1: A unicorn company meeting a billion dollar valuation.
Speaker 2: I met a guy the other day literally billion dollar valuation,
Speaker 2: tim him exactly, So I think that he was praying
Speaker 2: himself around as the it's.
Speaker 1: Me, that's right, one of the first, and so that's
Speaker 1: what that's what has been positive ever since the beginning
Speaker 1: of AI. They're saying, we're going to start having world.
Speaker 1: You're going to have a single person with a unicorn
Speaker 1: billion dollar company. Yeah, Now does this Does society work?
Speaker 1: If there's a handful of single people with billion dollar
Speaker 1: companies and no one else has a job, it doesn't work.
Speaker 1: Do you think those people just want to live out
Speaker 1: their lives in bunkers with private militaries and gas masks
Speaker 1: because they've created that world. I don't think they want
Speaker 1: that world. So reied Hoffman, who's the founder of LinkedIn,
Speaker 1: was early at PayPal and you know, was at some
Speaker 1: point a friend of Peter Thiel's, you know, has this
Speaker 1: proposal that we can tax companies based on the proportion
Speaker 1: ratio of how many employees they have relative to their revenue.
Speaker 1: So you want to basically disincentivize the single solo unicorn company.
Speaker 1: I don't want to add to it.
Speaker 2: Yeah.
Speaker 3: Well, and also just just to note that it doesn't
Speaker 3: stop with just single person unicorns. Yeah, with automating that
Speaker 3: final one person not so hard, So you're gonna end
Speaker 3: up with zero person.
Speaker 1: You can have a CEO, B and AI. Yeah, and
Speaker 1: that's actually happening. We're already getting ais that are on
Speaker 1: boards and things like this. Yeah, and so even if
Speaker 1: you might find it questionable that that person might have again,
Speaker 1: they can. They can earn their wealth, but you have
Speaker 1: to have some taxation to make sure this is being stipid.
Speaker 1: And we also need we need to find ways of
Speaker 1: having universal basic ownership, not just universal basic cash payments
Speaker 1: and UBI, but universal basic ownership. I think people need
Speaker 1: to have a stake in the success that's happening, like
Speaker 1: what Norway did with the Sovereign Wealth Fund. But oil
Speaker 1: didn't oil produce this kind of gravy on top for
Speaker 1: the civilization. People still had jobs. So what's different about
Speaker 1: this is we do need to find ways of doing
Speaker 1: universal basic work. We also need to find ways of
Speaker 1: having certain professions in which that embodied wisdom, like a
Speaker 1: surgeon or a senior lawyer or a senior judge. We
Speaker 1: need ways of training and apprenticing almost like minimum quotas
Speaker 1: of those kinds of occupations and roles in society to
Speaker 1: make sure that we have that ongoing knowledge. Because again
Speaker 1: the short term benefit of like no one needs lawyers
Speaker 1: and then the senior lawyers all die out, that world
Speaker 1: doesn't work.
Speaker 3: So just the last thing to sort of add here
Speaker 3: is that you instead of getting into arguments about how
Speaker 3: quickly exactly are people going to lose the jobs, well,
Speaker 3: people really do lose their jobs. Let's let's plan and say, okay,
Speaker 3: we think people are going to be out of livelihoods.
Speaker 3: This is this idea we really came to us from
Speaker 3: read haasting to see Pharmacy and Pharmacy Netflix, where we said,
Speaker 3: let's set up trigger point laws. If in unemployment hits
Speaker 3: ten percent, what are we going to do if it
Speaker 3: hits twenty percent? What are we going to do? You
Speaker 3: could pre set up those sort of conditions so we
Speaker 3: don't have to argue about whether it's going to happen,
Speaker 3: just what we should do when it does.
Speaker 1: And I know that you've been running with Engaged California,
Speaker 1: these citizen deliberations, these ways of you know, aggregating citizen assemblies,
Speaker 1: having citizens actually deal with and think about these issues
Speaker 1: and come to some you know, have their own input
Speaker 1: in this process. But by reckoning with these facts, and
Speaker 1: I think that these are all things that we need.
Speaker 1: You know, the countries that discover a natural resource that
Speaker 1: didn't have this engaged, well educated citizen kind of engage
Speaker 1: this in infrastructure, like Venezuela or Libya or something like that,
Speaker 1: they don't do so well. But countries like Norway where
Speaker 1: you did have the engaged citizens, with oversight of those funds,
Speaker 1: you end up with a healthier society.
Speaker 3: So it's sort of like an a California engagement fund
Speaker 3: because you want like people involved in the redistribution.
Speaker 1: That's right.
Speaker 2: So it's interesting that you mentioned mencome which the old
Speaker 2: Canadian construct ubi university basic income. You had Elon Musk
Speaker 2: the other day say he wants university basic high income.
Speaker 1: He said there is going to be univers of basic
Speaker 1: high income, and.
Speaker 2: Then was asked with Peter, right, exactly I saw him probably,
Speaker 2: and he was asked simple question, how are you going
Speaker 2: to do it?
Speaker 1: And he said, oh I did. I was just joking.
Speaker 1: I made it up.
Speaker 2: That was comforting.
Speaker 1: Yeah, I think people should really take note of that.
Speaker 3: Yes, it was just a mispronouncing of high not as
Speaker 3: in like a high income. It's just like he's he's
Speaker 3: not being able to think about it.
Speaker 2: I mean, it's uh, it's a it's a little alarming.
Speaker 2: So look, what do you quickly Look, I'm we're thinking
Speaker 2: about all these things down to the parochial on the
Speaker 2: warn Act, which is how we actually warn the public
Speaker 2: the social impacts of large scale displacement and job loss.
Speaker 2: Having more capacity to see earlier. That's after the fact
Speaker 2: the warneck comes out, those jobs are already going to
Speaker 2: be lost. What are the science to show us what
Speaker 2: the impacts are happening in the job market in real time?
Speaker 2: Issues of unemployment and sure it's becoming employment insurance so
Speaker 2: that you can keep people employed for a period of time.
Speaker 2: The Dutch do it about ninety percent of the wage.
Speaker 2: The ultimate training is a job, the dignity of a
Speaker 2: job back to those Voltaire constructs, and then the opportunity
Speaker 2: then potentially transition by using the federal government to help you.
Speaker 2: The backstop portable benefits then become fundamental. This notion of
Speaker 2: UBC university basic capital, this notion of sovereign wealth fund
Speaker 2: or equity public equity with dividends and somehow we get shares.
Speaker 2: There's equity shares contributions from these large companies. That's not
Speaker 2: just taxes, it's actual equity in the company. So there's
Speaker 2: a notion of an ownership and a larger ownership society.
Speaker 2: That we don't tax jobs with payroll taxes and then
Speaker 2: subsidize automation through tax credits. We do the inverse in
Speaker 2: that context. So all of that. So that's the stuff
Speaker 2: I'm playing around with a lot of us are thinking
Speaker 2: about right now. But how from your vantage point, how
Speaker 2: quickly is is happening. There's a lot of headlines, but
Speaker 2: there's a lot of debate around these headlines of all
Speaker 2: these cuts of jobs. But then people say, well, that
Speaker 2: was a lot of coverd over iroing there's some business
Speaker 2: model issues there that they're sort of hiding and suggesting
Speaker 2: it's AI. We even necessarily seeing massive job destruction yet
Speaker 2: or have we with AI?
Speaker 1: I think the point people should get here is that
Speaker 1: obviously it's complicated, and there's jobs are shuffling throughout the
Speaker 1: economy a little bit right now. But the long term
Speaker 1: goal of these companies is.
Speaker 2: Not the original Open AI.
Speaker 1: Missions mission statement exactly. Opening Eyes mission statement was not
Speaker 1: to give people helpful tools so that you can do
Speaker 1: your job slightly better. Their mission statement is we do
Speaker 1: your job. And actually, you know govin in in La
Speaker 1: there's an article in the La Times about this that
Speaker 1: is one of these new popular gig worker jobs in
Speaker 1: La is everybody straps a GoPro camera to their head
Speaker 1: and they look down and then they do laundry, They cook,
Speaker 1: they eat, they do all these things. So basically the
Speaker 1: number one job soon in the world will be training
Speaker 1: the replacement for that job. Think of it like being
Speaker 1: a coffin builder, Like you're designing the coffin and then
Speaker 1: you put yourself in it. And you know, if you
Speaker 1: think I'm lying, by the way, just think about Meta
Speaker 1: Mettal Instagram creators. You know, here we love creators, we
Speaker 1: love creativity. We want you to be successful. We want
Speaker 1: to you know, our whole mission statement is making creators
Speaker 1: super successful. That's before they were an AI company. When
Speaker 1: they do the second that they were an AI company,
Speaker 1: they trained on all the videos of their creators and
Speaker 1: then created generative videos that now basically suck up like
Speaker 1: a vampire, your essence, your life, force, your creativity, and
Speaker 1: then hit button and now they have a digital copy
Speaker 1: of you that you didn't consent to that can generate
Speaker 1: all these things. If you don't believe me, Just a
Speaker 1: few weeks ago, there was an article Meta is now
Speaker 1: forcing their employees to basically track all of their movements,
Speaker 1: all their clicks, all the things are doing on a
Speaker 1: computer to train AI agents to do all their jobs.
Speaker 1: This is not a conspiracy theory. All you have to
Speaker 1: do to know where we're going is understand the incentives
Speaker 1: and look at the early warning signs they're telling you
Speaker 1: who they really are. You know, Open AI says we're
Speaker 1: all here to make the world a better place. And
Speaker 1: then they release this AI slop app Sora, which was
Speaker 1: basically an infinitely they killed it now, but it was
Speaker 1: an infinitely scrolling, deep fake generated content of like, you know,
Speaker 1: funny videos of Stephen Hawking, you know, you know, going
Speaker 1: through a raceway or something like that. It's just deep
Speaker 1: fake AI slop. Why are they doing that because they
Speaker 1: want to increase their market dominance, because they want to
Speaker 1: get users, because they want to get training data, and
Speaker 1: it gets more people using open ai, so their numbers
Speaker 1: going up.
Speaker 3: And if your incentives tell you everything, and if you're
Speaker 3: a company and you're choosing do I hire a real
Speaker 3: human paralegal or GPT seven that works for less than
Speaker 3: minimum wage twenty four to seven doesn't whistle blow, doesn't
Speaker 3: a plane, doesn't have cultural issues, doesn't have paid time off? Like,
Speaker 3: which one are you going to do?
Speaker 1: Well?
Speaker 3: Your business incentive is just very very clear, and everyone's
Speaker 3: going to be trapped in this.
Speaker 2: And if your competitor you may say no, I'm going
Speaker 2: to keep the human, and then your competitor goes stops
Speaker 2: the direction, You're out of business. Yeah, I have no.
Speaker 1: Choice back to the But with those set of interventions
Speaker 1: that you just mentioned, and you just mentioned a whole
Speaker 1: slew of things we can be doing. You just mentioned
Speaker 1: so many things that we could be doing. And I
Speaker 1: think what it represents is I think people think, but
Speaker 1: if we don't race to automate every job as fast
Speaker 1: as possible, we're going to lose to China. But what
Speaker 1: this is showing and revealing is we're not in a
Speaker 1: race just the technology. We're actually in a race for
Speaker 1: a different currency. The currency is not who has the
Speaker 1: power first, but who is better at governing, steering and
Speaker 1: integrating that power in a healthy and sustainable and strengthening
Speaker 1: way into your society. And we saw this with social
Speaker 1: media because the US beat China to the psychological bazooka
Speaker 1: behavior modification machine of social media, and then we had
Speaker 1: no idea how to govern it. So we flipped around.
Speaker 1: We blew off our own brain with the brain row economy.
Speaker 1: So and by the way China regulates social media, they
Speaker 1: do a whole bunch of suffing. When you open up
Speaker 1: a douyen TikTok in China, it's their version of TikTok,
Speaker 1: and you scroll, you get videos about who won the
Speaker 1: Nobel Prize, financial advice, here's the new quantum physics theory.
Speaker 1: You know, here's patriotism videos. And obviously there's problems with that.
Speaker 1: We don't want to do it that way, but the
Speaker 1: point is you don't have to do it in the
Speaker 1: wild west. Blow off your own brain. And now if
Speaker 1: we release it in a way that automates all the
Speaker 1: labor with no transition plan. It's like, great, we pumped
Speaker 1: up our steroids, but we just burst our lungs. Yeah, right,
Speaker 1: the societal body, we do that. So what you just
Speaker 1: outlined was a set of interventions that we can be
Speaker 1: exploring to help smooth this transition. And we're in a
Speaker 1: competition with China for who's better at making this transition
Speaker 1: to an AI integrated world.
Speaker 2: Where are you on the transition curve? I mean, I mean,
Speaker 2: we talk about flattering it, but how quick? I mean, honestly,
Speaker 2: if we're sitting here a year from now having this conversation,
Speaker 2: are we looking at that you know, ten percent unemployment,
Speaker 2: not that twenty necessarily, which is that threshold for fascism
Speaker 2: and a whole other societal collap.
Speaker 3: But it's going to be confusing and spiking hard to
Speaker 3: predict exactly because just think about your own experience with
Speaker 3: AI so far two years ago, it can barely write
Speaker 3: an essay, and now it can do some part so
Speaker 3: of your work pretty well and other parts like that
Speaker 3: is a really dumb error. And so we're going to
Speaker 3: see not that much job, not that much job LOFs
Speaker 3: like entry level stuff getting sort of switched around and
Speaker 3: then it's going to hit really really quickly when it
Speaker 3: crosses the next spreshold, just like Mythos did.
Speaker 1: There's another confusing aspect about AI that people in our
Speaker 1: space called AI jaggedness, which is that there's certain capabilities
Speaker 1: like in cyber hacking, that it is already superhuman, already superhumans,
Speaker 1: while it'll still make a very basic dumb mistake on
Speaker 1: something else. And I think part of what's confusing for
Speaker 1: people that naturally has them say is this just hype
Speaker 1: and these companies are trying to hype this stuff is
Speaker 1: if you just look at the dumb examples where it's
Speaker 1: messing up, you're like, this thing isn't that powerful. We
Speaker 1: have never been confronted with the technology that is simultaneously
Speaker 1: sci Fi level superhuman that makes a person who's very
Speaker 1: deep in security call it like seeing Jesus. At the
Speaker 1: same time that that same technology can like mistake how
Speaker 1: many rs are in the word strawberry, like, we have
Speaker 1: just not seen that. And so it's just I want
Speaker 1: people to not for their own psychology that this is
Speaker 1: a new psychological object that our normal intuitions about how
Speaker 1: to evaluate something we have to get more nuanced.
Speaker 2: And part of the nuance is a deeper understanding that
Speaker 2: we're not just talking about apps here, we're talking about
Speaker 2: the physical world as well.
Speaker 1: That's right.
Speaker 2: Was a big headline that I hope people paid attention
Speaker 2: to when Elon announced that in his original factory here
Speaker 2: in Fremont, California, that he's converting the s and the
Speaker 2: ex Tesla cars now to humanoid robotics and his goal
Speaker 2: is ultimately a million You know, that's Elon who they
Speaker 2: all knows, you know, his goal setting. But the notion
Speaker 2: that he's converting that factory from cars to humanoid robotics
Speaker 2: and AI now into the physical world is that. I mean,
Speaker 2: we're seeing driverless cars and if you haven't seen them
Speaker 2: in you know, your home state, you're going about to
Speaker 2: you're going to see flying cars or they're just quad
Speaker 2: copters basically, but they're coming soon. We're going to be
Speaker 2: doing a lot more of that run by the way.
Speaker 1: That's great. We can have a world of quad copters
Speaker 1: and you know, innovation while not racing to replace us economically,
Speaker 1: replace us socially. So Mark Zuckerberg, you know, designs your
Speaker 1: kids friends rather than you had them having actual friends
Speaker 1: replace us politically and not having political power and then
Speaker 1: replace us physically by owning our physical presence in our
Speaker 1: in robots. So again, I think people might hear this
Speaker 1: as an anti technology conversation. Yeah, you know, you talked
Speaker 1: about your legacy and your father and grandfather and we
Speaker 1: were talking backstage. Ye A's's father started the Macintosh projected
Speaker 1: at Yeah. Yeah, you know, we come from a legacy
Speaker 1: where the word humane is about an inspiring vision about
Speaker 1: technology that's actually integrated and in service of our humanity,
Speaker 1: of a pro human future. That's what all of this
Speaker 1: is motivated for. So I get excited about you know, flying,
Speaker 1: you know, cars that have cool you know.
Speaker 3: Aif And just to say too, just as my own
Speaker 3: personal experiences, you know, I spend a big portion of
Speaker 3: my life. I found it a thing called Earth Species Project.
Speaker 3: We're now around forty people and you're.
Speaker 2: The biggest consumer.
Speaker 3: I wouldn't say biggest consumer. Yeah exactly, it's it's men. Sorry, guys,
Speaker 3: first infinite scroll now this, but you know, we were
Speaker 3: using AI to translate animal language animal communication. One of
Speaker 3: our researchers just discovered just before she joined us that like,
Speaker 3: not only do dolphins have names that they call each
Speaker 3: other by that their mothers teach them. They will talk
Speaker 3: about each other in the third person, so they'll talk
Speaker 3: about another dolphin that isn't here. So it's like one
Speaker 3: of the biggest hallmarks of language to be able to
Speaker 3: talk about something that's not here and not now. But
Speaker 3: they will continue to use their mother's name even after
Speaker 3: she's died. Sweet right, it's beautiful. These are the kinds
Speaker 3: of things that AI can show us and teach us
Speaker 3: about the world and connect us with the natural world,
Speaker 3: the world around us, and show things we couldn't possibly imagine.
Speaker 3: So I just want everyone to hear it's not that
Speaker 3: it's just here saying no AI. It's just saying not AI.
Speaker 3: In this way that technological progress might be inevitable, but
Speaker 3: the way that AI rolls out is not. And every
Speaker 3: time somebody says it's inevitable, it's like casting a spell.
Speaker 3: That's where because if if it's inevitable, then there's nothing
Speaker 3: we can do, then you shouldn't possibly act.
Speaker 1: There's a button we're hitting called commit suicide. Commits suicide?
Speaker 1: Is it inevitable that we all hit that button?
Speaker 2: No?
Speaker 1: When it's called you know, ten percent GDP growth And
Speaker 1: like an innovation, we pushed the button. If we could
Speaker 1: collectively see that the button we're pushing is more nuanced
Speaker 1: than that, that there's some threshold by which we are
Speaker 1: essentially committing civilizational suicide. We're not going to have a
Speaker 1: human future. If you ask anybody what gives me hope?
Speaker 1: We've been on the road with this film. You walk
Speaker 1: people through the basic facts we've talked through, and you
Speaker 1: ask who here is stoked about the future that we're
Speaker 1: headed to. I was even at the Miami Tech Summit
Speaker 1: in front of a pro business pro AI. A lot
Speaker 1: of people invested in it. Again, we're invested in in
Speaker 1: positive technology too, but I was able to see that
Speaker 1: entire audience is like, no, I don't want that either.
Speaker 2: Wow. Yeah.
Speaker 1: So again I think it's like, as long as you
Speaker 1: give people the off ramp, there are ways we can
Speaker 1: have technology that's in service of making life better. We
Speaker 1: need to be funding and innovating in that way, and
Speaker 1: we need to be blocking off the parts that are
Speaker 1: hurting our children, that are, you know, diminishing people cognitive
Speaker 1: capacities or replacing their kids' relationships with AI companions. And
Speaker 1: we can do that. And you've done some of that
Speaker 1: with here in California. So you know, it's not that
Speaker 1: I am or weird by default optimistic about the default trajectory,
Speaker 1: not at all. It's that if we have the clarity,
Speaker 1: we can put our hand in the steering wheel and
Speaker 1: we can steer it somewhere else.
Speaker 2: This notion of accelerate and steer.
Speaker 1: Yeah, yes, right, exactly what happens when you accelerate and
Speaker 1: you don't steer, you obviously crash. It's just it's like
Speaker 1: not rocket scient there, it's one hundred percent the likely outcome.
Speaker 2: What just as we wrap up this notion of governance,
Speaker 2: going back to that is it's it's the foundation here
Speaker 2: which the regulations and and and the relationships are formed,
Speaker 2: the partnerships to begin to address the common humanity and
Speaker 2: the common threat and the common cause, common opportunities that
Speaker 2: present themselves. This notion of catcher, I mean, you've got
Speaker 2: these packs, You've got so much concentrated wealth. Yeah, we're
Speaker 2: going to likely have the first few trillionaires this year. Yeah,
Speaker 2: this calendar years right, yeah, yep, these IPOs, I mean
Speaker 2: it's just I'm a now, it's a big surplus in
Speaker 2: the state, the abundance, the GDP I mean, it's frothy,
Speaker 2: as they say, but a lot of that now is
Speaker 2: going to you know, make sure that you know we're
Speaker 2: protecting incumbents against innovation. You know, some incumbent capitalism, not
Speaker 2: entrepreneurial capitalism, necessarily innovation capitalism. There's that friction that's always
Speaker 2: ongoing and those that are just going to do everything
Speaker 2: to hammer as they did with social media, to make
Speaker 2: sure there's no regular we're still debating section two thirty
Speaker 2: that Christ yeah in this country. So how do we
Speaker 2: start to break that reality?
Speaker 4: I think money in politics, that's just that's right, that's
Speaker 4: at the anti just just a little bit even further,
Speaker 4: which is that as we get more trillionaires, like they
Speaker 4: can hire private security, but that still requires relying on
Speaker 4: human beings.
Speaker 3: But you're just pointing out that we're heading into like
Speaker 3: a world we have drone army, we have human eight
Speaker 3: rowood armies. When trillionaires can just buy like their drone
Speaker 3: armies to fight, like, we enter into techno feudalism, right,
Speaker 3: And so that is the world that if we see,
Speaker 3: if we don't do something, we're going to end up into.
Speaker 1: But to answer your question, the it's all about the
Speaker 1: campaign Loving, it's all about that, And one hundred million,
Speaker 1: one hundred and ninety million dollars has gone into basically
Speaker 1: AI accelerationist packs and funding is for this midterm, for
Speaker 1: this mintrum electional Love interm just the midterms. That's so
Speaker 1: one hundred ninety million. I believe the presidential is two billions.
Speaker 1: So basically ten percent of the presidential is going into
Speaker 1: just the midtrums for AI alone, not even for the
Speaker 1: rest of it.
Speaker 2: And it's not to regulate.
Speaker 1: It's not to regulate it. It's it's to say, remove
Speaker 1: everything and go as fast.
Speaker 2: As possible, right, let it rip.
Speaker 1: If you had everyone in the world, I think here
Speaker 1: the conversation we just had and at a basic level
Speaker 1: common sense looking at your children in the eye and
Speaker 1: say are you stoked about that future? No one wants that.
Speaker 1: So the key piece of agency is going into the
Speaker 1: midterm elections not voting for people who have taken money
Speaker 1: from those AI accelerationist groups or don't have a position
Speaker 1: on AI. That's trying to steer away from these outcomes. Now,
Speaker 1: we obviously have to articulate that in a clearer way.
Speaker 1: What does it mean to have kind of a pro
Speaker 1: human platform in future, and the companies try to make
Speaker 1: the conversation inaccessible, like oh, well, you don't understand a
Speaker 1: They're trying to make it seem like you don't know
Speaker 1: how to regulate live to put us in charge.
Speaker 3: What they call this the under the hood bias, where
Speaker 3: it's as if people who know how to make the
Speaker 3: biggest engines know how to lay out cities and traffic lights,
Speaker 3: and it's just not true for people who know how
Speaker 3: to make car engines are not the best people for
Speaker 3: knowing how to make cars safe and.
Speaker 1: Prevent recidents work exactly. So it's pretty simple. It's like,
Speaker 1: do you want an anti human future in which you
Speaker 1: will be permanently disempowered where no one has an incentive
Speaker 1: except for charity to pay your bills for you? And
Speaker 1: you you want the companies that took your job, you
Speaker 1: want to be dependent on them for the rest of
Speaker 1: your life to pay your bills for you with no
Speaker 1: economic leverle no. So this is the final window. You
Speaker 1: know you want to vote for people who are going
Speaker 1: to protect you economically, protect you, socially, protect you, politically
Speaker 1: meaning protect our jobs, protect our vote, voting pro human
Speaker 1: and obviously that has to get articulated even more clearly.
Speaker 1: But that is the number one way that people can
Speaker 1: make a difference in the short term. There's other things too,
Speaker 1: like boycotting companies that are enabling mass surveillance. You know,
Speaker 1: when the company's subscriptions you know, go down by a lot,
Speaker 1: they really need their numbers to be going up. So
Speaker 1: the companies are more vulnerable than you think, and you're
Speaker 1: more powerful than you think. Not just if you unsubscribe
Speaker 1: and boycott them, but get your company, get your church
Speaker 1: group to do that too, and when those numbers start
Speaker 1: to change, it actually has a difference.
Speaker 2: Scott Galloway has been talking a lot about that as well.
Speaker 2: Absolutely got to use whatever power your disposal. Let's just
Speaker 2: briefly talk then about the power I mean, free and
Speaker 2: fair elections. We talk about truth trust more broadly, deep fakes,
Speaker 2: political ads. I mean I've seen stuff, you know, meetings,
Speaker 2: conversations I've had that are I mean next level what's
Speaker 2: out the you yes, just the bs, it's already out there.
Speaker 2: The ability to manipulate the crowd and the context of
Speaker 2: you know, social media, the algorithms I mean, now you've
Speaker 2: got you know, concentrated in the hands of a few
Speaker 2: in that respect, I mean that whole thing. I mean
Speaker 2: you you guys have talked about free and fair elections.
Speaker 2: We talk about the timelines not only in job displacement,
Speaker 2: but timelines to get this right domestically globally. I mean
Speaker 2: twenty twenty six, you're talking mid terms. I mean this
Speaker 2: is I mean, we only have a few more at
Speaker 2: bats to get this right. That's right? Or is that overstated? No,
Speaker 2: it's a few more.
Speaker 3: Certainly by twenty twenty eight, Like that'll be the last
Speaker 3: human election. Like it's going to be AIS running all
Speaker 3: of the election, election campaigns, the ads, doing all the
Speaker 3: both the information and disinformation, because human beings just can't
Speaker 3: operate at that speed and are not that effective.
Speaker 2: Yeah, so this is it.
Speaker 1: This is the window. But and I know, I just
Speaker 1: want to like get the human experience level. We've been
Speaker 1: talking about some hard stuff, the last little level, and
Speaker 1: you know, I just want to say, you know, we
Speaker 1: struggle with how to communicate this in a way that's responsible,
Speaker 1: because here's the trade. Right, it's hard to face this.
Speaker 1: But if we don't face it, we just like, look away,
Speaker 1: what are we going to get? We're going to get
Speaker 1: the default anti human path, and so there's this trade
Speaker 1: where we the only way out is through like it is.
Speaker 1: We call it kind of like a rite of passage,
Speaker 1: like our ability to confront basically a shadow of a
Speaker 1: technology and the default future that that brings. If we
Speaker 1: can see that clearly, and if we can know that,
Speaker 1: you know, and I know that we don't want that,
Speaker 1: and if g and Trump and you know, the people
Speaker 1: at the highest levels of these governments, Because you ask
Speaker 1: any reasonable person at a very high level of national
Speaker 1: security on any side, and you say, do you want
Speaker 1: AIS that are going road can hack into any computer
Speaker 1: system and are already mining cryptocurrency? Does that sound good
Speaker 1: to you? Does that sound safe to you? At a
Speaker 1: universal level, it's not. So there's actually much more common ground.
Speaker 1: And even you know forty se I think it's already
Speaker 1: the case that fifty seven percent of Americans think that
Speaker 1: the risks of AI currently outweigh the benefits. I don't
Speaker 1: like that stat because it makes it too like it's
Speaker 1: all bad versus all good or something like that. There's
Speaker 1: already the pro human AI Declaration, where forty six groups
Speaker 1: came together and said, we agree on these five principles
Speaker 1: to make a pro human future. You can look it up.
Speaker 1: It's human Statement dot org. That's the one that also
Speaker 1: includes again Glen Back, Bernie Sanders, Steve Bannon, all these people.
Speaker 1: I believe it's sixty five percent of Americans believe we
Speaker 1: should not create superintelligence until we know how to do
Speaker 1: it provably, safely and controlled. Sounds like a pretty basic thing,
Speaker 1: like let's not do something. It's like, should we build
Speaker 1: a nuclear bomb that until we know how to do
Speaker 1: it safely or nobody won't set off of if we
Speaker 1: won't ignite the atmosphere, Probably we should wait to do that.
Speaker 1: So this is not a radical proposal.
Speaker 3: This is not do you want to know how many,
Speaker 3: like what percentage of Americans think that we should just
Speaker 3: go as fast as possible, unfettered, non regulated AI. What
Speaker 3: percent of Americans? Five percent?
Speaker 2: Literally, yeah, literally five percent.
Speaker 3: So actually it's the most popular to run on. That's
Speaker 3: right to do the like the safe thing, And.
Speaker 1: It's whether you're a Democrat or Republican, you don't want
Speaker 1: to be surveilled by AIS. Whether you're Democrat Republican, you
Speaker 1: don't want AIS taking your jobs, which it will do
Speaker 1: equally to both sides.
Speaker 2: But do you then subscribe to the burning AOC frame
Speaker 2: just shut down the data centers and moratorium.
Speaker 1: And tell I think of it as those data centers,
Speaker 1: and it's like I want a pro human data center policy.
Speaker 1: It's like, you get to build the data center when
Speaker 1: these conditions are met and we know that it's a
Speaker 1: pro usure. I'm not saying that's easy. I'm not saying
Speaker 1: no articulation that because I want people to hear. It's
Speaker 1: not just no to all of it. It's making sure
Speaker 1: that the conditions are the steering is built in. So
Speaker 1: when you see that data center, you should ask, is
Speaker 1: that data center here to basically enhance my life and
Speaker 1: strengthen my family.
Speaker 2: You were even just saying data center was solar. Mostly
Speaker 2: data centers aren't solar.
Speaker 1: That's right.
Speaker 2: We're turning back on cold plants. That's right, old natural
Speaker 2: gas plants that are exactly yea.
Speaker 3: Often in the sci fi movies, when is it the
Speaker 3: case that human beings act actually stop all their bickering
Speaker 3: and they start coordinating, it's when the aliens come, right, Yeah,
Speaker 3: we are summoning the demon. We are summoning the alien.
Speaker 3: And if we can see it that way, then it's
Speaker 3: sort of like a Game of Thrones, winter is coming.
Speaker 3: We have to understand winter is coming, then all the
Speaker 3: fighting in West Ros can like pause for just long
Speaker 3: enough that we can deal with it. That's this moment,
Speaker 3: because otherwise it just feels completely hopeless, like how are
Speaker 3: we going to deal with all the finance reforms when
Speaker 3: we can't when has Congress actually done anything? And yet
Speaker 3: there is this one moment where like all of humanity
Speaker 3: is on one side, there is a human movement. That's
Speaker 3: what I think the social media stuff shows. If we
Speaker 3: don't think of this as just an AI problem, but
Speaker 3: as a technology encroaching onto our humanity, overreaching into our
Speaker 3: humanity problem, then actually there is massive momentum, more than
Speaker 3: we ever thought was possible, because what we have to
Speaker 3: do is juice those like the momentum that's already there.
Speaker 2: Yeah. Well, look, in the absence of a federal leadership,
Speaker 2: California will continue to assert itself. I believe in the
Speaker 2: power of emulation successfullys clues will continue to try to
Speaker 2: iterate on this and lean in. But look this, you
Speaker 2: know the clarity of you guys bring to this conversation,
Speaker 2: The importance of this conversation being brought to scale and
Speaker 2: brought it into consciousness and the imperative of seeing this
Speaker 2: documentary again. The documentary is called.
Speaker 1: The AI doc or How I Became an apocaly optimism.
Speaker 2: And we can't let that slip twice because you've used
Speaker 2: a word that people are not familiar with, which is
Speaker 2: a good way to end, and that is this convergence
Speaker 2: of optimism and pessimism, a little more optimism than pessimism
Speaker 2: in a better place.
Speaker 1: And it's about agency. And I'll just leave you with
Speaker 1: a quote that I loved from a meditation teacher who
Speaker 1: talked who happened to be a meditation teacher, and it's
Speaker 1: from the Army Corps of Engineers, which is that the
Speaker 1: difficult we do today, the impossible takes just a little longer.
Speaker 3: Like it, and just end by saying it really actually
Speaker 3: isn't about being an optimist or a pessimist, because to
Speaker 3: choose that label for yourself, it's a sort of it's
Speaker 3: to take a backseat, like to sit down and just
Speaker 3: be like, I'm just going to accept that it'll either
Speaker 3: come out well or not, versus taking responsibility for trying
Speaker 3: to see clearly to shift the world to go well
Speaker 3: and I think that's what everyone listening can can do,
Speaker 3: is that this can all feel like too big? What
Speaker 3: can I do? And then you realize even like the
Speaker 3: like the CEOs of the company sort of feel a
Speaker 3: similar way. But this is not just about what we
Speaker 3: must do. This is fundamentally a question of like who
Speaker 3: we must be. That if we are the kind of
Speaker 3: people that aren't looking for a path, and the path
Speaker 3: is certainly not clear, doesn't seem obvious or even possible.
Speaker 3: But if we're the kind of people that don't look
Speaker 3: for the path, we definitely won't find it.
Speaker 1: If it's there.
Speaker 3: If we are the kinds of people that do look
Speaker 3: for the path, then if it's there, we have the
Speaker 3: opportunity to find it.
Speaker 1: And just maybe one last thing is people listening to this,
Speaker 1: this is a lot. Your role is not to take
Speaker 1: on this whole problem. You don't have to do that.
Speaker 1: There's some people who are soldiers and there's some people
Speaker 1: who are civilians. But your role is to be part
Speaker 1: of the collective immune system against this anti human future.
Speaker 1: One simple way you can do that is to share
Speaker 1: this conversation yeah, with literally the most powerful people that
Speaker 1: you know, and ask them to watch it. And to
Speaker 1: share it with the most powerful people that they know.
Speaker 1: And if you've done that, you can say, as long
Speaker 1: as you are spreading the word and being part of
Speaker 1: that immune system, you can rest at home, kiss your
Speaker 1: children at night, focus on the things that all of
Speaker 1: this is about anyway, which is what do we love
Speaker 1: about the world, what do we love about life? That
Speaker 1: we want to continue and come from that place because
Speaker 1: that is the energy that we will that will inspire
Speaker 1: other people to want to take those other actions too.
Speaker 3: And I know, Kevin, you ended up watching an earlier
Speaker 3: presentation that we did the Aidlemma. Yeah, I think somebody
Speaker 3: said that you watched it like three times and share
Speaker 3: with all your staff. How did you end up hearing
Speaker 3: about it?
Speaker 2: Well, I mean, come on, hearing about it from you guys.
Speaker 2: You guys. I was able to get the early early
Speaker 2: preview from the two of you, and I was able
Speaker 2: to devour it, took notes, and then shared it universally
Speaker 2: with everybody around me. Look, you know, the spirit of
Speaker 2: you guys just DoD it. I couldn't agree with you more.
Speaker 2: This notion of agency is so important, and we talk
Speaker 2: about that on the podcast all the time. But this
Speaker 2: notion of the future. It's not something to experience, something
Speaker 2: to manifest futures inside of us. And so it's decisions,
Speaker 2: not conditions.
Speaker 1: That's exactly.
Speaker 2: And so this idea that we are powerless, it's just bullshit.
Speaker 2: It's complete bullshit. Everything that we laid out is an
Speaker 2: opportunity to do better and be better. And I think
Speaker 2: the spirit of the calt arms for everybody, as we
Speaker 2: all have a role to play, and those roles are different,
Speaker 2: and no one has to be you know, you don't
Speaker 2: have to be overwhelmed. But this notion of just being
Speaker 2: present in the conversation and and and in the conversation
Speaker 2: and sharing it, I think is foundational. So, guys, this
Speaker 2: is really important. The timeliness of this conversation it cannot overstate.
Speaker 2: And so I'm very grateful for you to be out
Speaker 2: on the road all across this country sharing this remarkable documentary.
Speaker 2: I encourage everybody go out and watch it and more importantly,
Speaker 2: share it and not fall prey to any of the
Speaker 2: citizensm and negativity. Maintain your sense of optimism again, we
Speaker 2: can shape the future. Thank you both