The Right Time with Bomani Jones - Why AI & Their CEOS CAN NOT be trusted | 8.11

Episode Date: August 11, 2026

Bomani Jones is joined by Ted Tremper, a producer, to break down the complexities, fears, and economic realities surrounding artificial intelligence. They discuss Tremper's two-and-a-half-year journey researching and interviewing over 40 AI experts and tech leaders, sharing behind-the-scenes insights from his discussions with frontier lab CEOs like OpenAI's Sam Altman, Anthropic's Dario Amodei, and Google DeepMind's Demis Hassabis. Bo and Ted examine the shifting public perception of AI, the threat of potential job replacements, the environmental racism of data center expansion, and how algorithmic design fosters a dangerous illusion of human connection. They also explore the intense geopolitical space race against China's booming open-source market, the staggering amount of unlicensed data driving the industry, and the precarious Jenga tower of debt threatening the broader American economy. Along the way, they make sense of the money, politics, and societal chaos defining our relationship with this modern digital god. . . . Subscribe to Supercast for Ad-Free Episodes: https://righttime.supercast.com/ Buy 'The Right Time' merch: http://therighttimebomani.com/ Subscribe to The Right Time with Bomani Jones on Spotify, Apple or wherever you get your podcasts and follow the show on Instagram, Twitter, and Tik Tok for all the best moments from the show. Download Full Podcast Here: Spotify: https://open.spotify.com/show/6N7fDvgNz2EPDIOm49aj7M?si=FCb5EzTyTYuIy9-fWs4rQA&nd=1&utm_source=hoobe&utm_medium=social Apple: https://podcasts.apple.com/us/podcast/the-right-time-with-bomani-jones/id982639043?utm_source=hoobe&utm_medium=social Follow The Right Time with Bomani Jones on Social Media: http://lnk.to/therighttime Learn more about your ad choices. Visit megaphone.fm/adchoices

Wave. Ladies and gentlemen, welcome to the right time, a wave original. My name is Beaumani Jones. Thanks for listening to Rev. You get your podcast. Thanks for watching us on YouTube. Subscribe, like, rate us, review us, give us five stars. You only give us four stars. I'm inclined to believe you are a hater.

Now, it is the time of week where we have a guest join us. And one of my favorite subsets of guests, obviously, is game theory with Bomani Jones. alumni in joining us now. He worked as a field producer on the right time. He has been a showrunner and done things in other capacities, worked on the daily show, and very recently worked as a producer, and I want to make sure I

get the full title of this documentary correct, because it's important. The AI doc or how I became an apocalypticist. Very good, very good. That was a mouthful. Ladies and gentlemen, Costco enthusiast Ted Trempter. How are you, Matt?

I'm very good. I appreciate you. wearing the Seattle Sonics colors for me. I did that just for you. Are we getting the team back? I've heard for years we're getting a Vegas team and a Seattle team. Is that real? I think you'll get a team that will then be called the Sonics and you guys will act like all this anger that you've been riding with for the last 20 years.

Let me tell you. I have not watched the basketball game since they left. And I believe you. You're the person who says that and I firmly believe that like you have decided to take this stand. And I want to say this right fast before we get going so people know. one of the like moments of interesting moments of my life is the first day that we were in the office for game theory and you got to remember it's 2022 and with the way a television show works we were still pretty like in the thick of COVID we were a very masked up audience and we did the meet and greet meeting with the whole staff but the first meeting that I had with people in the room and the first meeting of my life that I've ever been in charge of was a meeting sketching out a something that we did where we created a museum exhibit. about Duke basketball. And Ted Trepper, who is kind of the project manager for this, I suppose,

is the term, is on this screen ahead of me. And the schematics of this are being laid out. Like, it's the most amazing thing I've ever had. I got my man Rod. I got Sidney Castile. They were working on, like, filling it up with content and stuff. And we're all there. And it's the first time I've ever been in charge of a meeting. And Ted is breaking down what everything is. And I have this, like, giant smile on my face. Meanwhile, the guys next to me are petrified and nervous if I liked it because they can't tell because I had a mask on. So I am thinking that I am radiating all this. Wow, this is so cool.

And nobody can see it. Intentzy energy guy and he's laying it out. He's talking about stuff. I didn't even know what's possible. He's using schematic terms. They don't mean shit to me. But I'm just riding this out. And I'm so gassed up.

And everybody thinks I'm mad because nobody can see my face. You know, that's the same thing. I proposed to my way. wife while I was, or I asked for permission to propose to my wife while my future father-in-law was wearing a mask. And he didn't give me an answer because we were in an airport and it was during COVID. I didn't know I was going to see him again. And he just told me, I'm not going to give your answer now. I'm going to make you sweat a little bit. And I turned out that he didn't want to give me an answer because he didn't want to cry because then it would reveal to his wife and my now

wife that this had happened. But I just thought he hated me. And I thought we had a good, we had a great rapport. I thought we were cool. And no, yeah, I'm glad. I'm glad to see your smile. I'm glad to see. I'm glad that we pulled through. Yeah. And Ted also was the man behind all of our black and white shots on the street that the first time we did was the coldest I'd ever been in my life. And every time we shot, by the way, except for like the literal last one was terrible frigid weather. And it's so weird when I go down to the West Village now, like I get off at West 4th street. And I'm like, why does this look familiar? Oh, yeah. this is where we did all the shooting.

But the first time we did it, it was the worst. I don't even know if you had been brought on board yet because I was out there with Stu. No. It was so cold. It was so terrible. And then people said the thing

that I was fearing that they would say, that's the best part of the show. It's like, shit, we got to get out here and do this every day, huh? Every week. Two things. I think this is the first time

we've ever spoken in summertime, number one. And number two, you do have to tell people, what did I bring? I picked up, at a Costco driving across the country, I brought the heated gloves and the heated socks.

That's how, that's how much I care. Ted had, Ted had all the things in a way that like, once you break up with a girlfriend, you realize now you have to do all these things for yourself. Ted was prepared and shared to wealth. Like I imagine in other situations you're in the same place. Like I find myself now among my friends being the person that has the things

because once somebody has the things, now you have to have the things. And I still have those socks with. the battery pack to keep my feet warm. Everybody knows in L.A. When it really starts collapsing, come over. I got everything. I got this all in the

basement. I got, I got, it's all set up. It's all set up. There's a good segue into the end of the world. It really is, right? It really is. So I just have to do that because that was such a great time in my life. And Ted, the stuff that we did with Ted was so excellent to go back and watch. And so

if you guys can find it, I still get residual checks. So apparently somewhere you can go watch some of this show, check it out. But Ted worked on the AI doc, which I think was the best way to put it, because in this day and age, when these docs wind up on streaming, they just become the blank doc for whoever. Like, you've seen the, like Chris Rock called it the prison dock on HBO back

on Bring to Pain 30 years ago. But it is the AI doc. And I watched it. And I've watched all the doom and gloom. I've read all the doom and gloom AI books. But I wanted to start with you first before we get into like really the specifics of it. And you said you basically spent two and a half years at a room working on this. Where were you on the topic of AI before you spent two and a half years in the world?

It actually, I remember walking from the office back to my Airbnb on our show. And my friend Daniel Kwan called me up and he said, hey, I think you should watch this thing. And it was a YouTube video that was called the AI Dilemma that Tristan Harris and Azaraskin from the Center of Humane Technology had released in late 2022. And it was foretelling basically everything that we're seeing now. It was the rise of large language models and their exponential increase in capabilities and all. the different impacts that was going to have on society. And Kwan had shared it. And also Daniel Kwan, by the way, he was the co-writer and co-director of everything

everywhere all at once. This is before they swept the Oscars. But we've been friends for about 15 years. And he knows I'm a nerd. He's a nerd. And we're in a video game group together. And he kind of threw that into the chat. And that became this thing where after they won all the Oscars, they can meet with

anybody. So they said we want to meet with these two guys. And basically the plan was, if you remember the film the day after about nuclear annihilation, that was kind of a wake-up call to society as to why we need to focus on nuclear non-proliferation and deep proliferation. And the goal was, can we make a documentary that will have a similar impact on society vis-a-vis the way that AI is being developed and deployed? So that was the impetus that made them get the team that had made Navalny, which won the Oscar the same year that they won. So they put together this team. I was asked to jump on. I was going to

stay for five or six weeks to help book some people. And, uh, you know, we reached out to a hundred people in AI land and six responded. And that was the moment we realized that people in AI don't really give a shit about movies. And so that became this, uh, an odyssey for me where I was the tip of the spear. I had to talk to these researchers. And in order to talk to them, I had to learn what they did. And in order to know what they did, I had to learn how the tech worked. So it became this like, you know me very well. I don't give up. And I, I don't stop. And the challenge was, I'm used to sprinting, like nightly, weekly TV is a sprint. And what the experience for me was, I can sprint for five or six weeks. But what happened at the end

of that five or six weeks was, you know, I've got my sprinting cleats on. I get to what I think is the 100 yard line where we're done. A door opens up and there's just more road. And then it's like, well, we'd be done in eight months. So we can be done before the election. And then eight months turns to a year, turns to a year and a half, turns to two years, turns to two and a half years. And it damn near killed me. But at the end of the day, we interviewed more than 40 people on camera. I interviewed more than 100 people on background. I developed confidential sources inside of every single lab.

It was either current or former employees of every frontier lab. So now I have what I never claimed to be an AI expert, but I have what's called interpretive expertise, which is I know, I think I have a good bearing on what every single different kind of expert would say in this landscape. So yeah, life's different. Yeah. So the first thing that I find interesting about Ted saying that he thought it would be this,

and then it kept going to this, is that you offered once an accurate interpretation of me that helped me understand and explain myself to people, which is he just wants to know what the ask is. And that is 100% correct. If you tell me we're going to be here for 10 minutes, fine. If you tell me we're going to be here for 100 minutes, fine. But if you tell me it's 10 and it's 11, that last minute's going to suck. Yeah. Tell me it's 100 is going to be it.

That last one's going to suck. So for you, why did this keep pushing out? Well, let me know a secret you need to know about me is the reason I saw that in use because that's the way I am. If somebody said, hey, do you want to work for two and a half years on an AI documentary? I would have said, sure, let me know what the money is because what happened was the moment you go from a weekly to a project fee, every day you work over eight months is a day that's lowering your rate. And so when that doubles and a half, then the math doesn't matter. But no, it really came down to wanting to get it right. And the challenge of this film was, how can you make a documentary about the most complex subject that maybe humanity has ever faced, but make it funny, make it entertaining, make it human, make it not technical to a degree that any person, regardless of what their background is, if they've won a Nobel Prize or if they've never talked about AI ever, can walk away with the same intuitions about the way the technology works.

And I think that's what we did. The most common comment that we've gotten about the film, which is also the most flattering, which is I didn't expect. a documentary about AI to make me laugh and make me cry. That's it. So let's get to the film itself, right? Because I think we are beginning to see, and I actually do find this to be a bit of encouraging, that like the fomenting revolution of humans,

like now when people say they will not replace us, it's not nearly as scary because they're talking about computers. Yeah. Right? When they throw that one out there now, it's like, oh, okay, cool. We can we can all do this. But I thought the doc was important. because I don't think people really understand how AI works.

And I understand, like, I think it is a, it is a vast black box, a fascinating one. And one that I understand why the nerds get so fascinated by what could happen, but also the point of the film is no one really seemed to stop and ask, now what? And that's, correct me if I'm wrong, but that seems to be the overarching theme of this is getting to the point of the now what that we're at now and what the now what will be if it goes a little farther. Correct. Yeah, I think the major. the major thing and having and there was a time there was a time where i had i had listened to or read

every single word that sam altman had said and darya amadee and all the five ceoes uh and the most shocking part of it to me was that they they are very clear that they they don't have a plan remember it's actually when when in the most recent election when trump was asked about health care and he and they asked what's your health care plan and he didn't say he had a plan he said they had ideas about a plan and that's where we're at they have ideas about a plan the challenges, and this goes back to the fact that maybe they don't watch enough movies, but if you remember Jurassic Park, they spent so much time asking whether they could that they didn't ask whether or not they should.

The major thing to understand about the CEOs is they do not look at this, but this is my assessment, they don't look at it as something that they are building. They look at this as a discovery that has been made, that if they don't build it, someone else who maybe doesn't have a strong moral compass as they do, will build it. And the challenge there is it puts you into a Lord of the Rings situation where everyone believes that they're Frodo. And if you know anything about Frodo, the only thing that makes Frodo Frodo is he doesn't think he's Frodo. He doesn't think he should be the one to be doing it. So the moment you start thinking, oh, well, it has to be me, you've already revealed yourself to be the kind of person who probably shouldn't be the one who's doing it.

Yeah. And that's the challenge. And there are some of the CEOs who really are focused on trying to scale things to a point where they can then take the final steps together as part of an international coalition, et cetera. But the race is so strong. And now you've got over a trillion dollars in debt that is part of all these interwoven, very incestuous deals that are propping the economy up. And now you have to really start to ask some questions about where we as a society want to go. And there are no clear answers as to where we will go. And it changes, as somebody who's been on this beat now for three years,

it's an impossible job to keep up with it. And I know that as a person who's tried. And the fact that they are being surprised by it tells you another unique, enormous thing, which is they don't know where it's going. So the good news is, to your point, I read a statistic, the deciding factor as to whether or not you are optimistic or pessimistic about AI is whether or not you make above or below $200,000 a year. And most Americans don't make above $200,000 a year,

which means that you have other statistics, only 18% of young people from 14 to, I think, 29, feel hopeful about AI. And when the younger generation is looking at the ways that data centers are, and it's just the other thing is it's so cross-partisan. When you go to Tennessee and you start taking people's water away and you start multiplying their energy rates by 3x, 4x, 5x, that doesn't matter who you voted for. You're going to start making phone calls.

You're going to start showing up at town halls. And that's kind of where we're at. Yeah, I want to put a pin in the economy point because I think a lot of people probably saw the Larry Ellison piece that was in the New York Times over the weekend, which was terrifying. I will explain to you guys a little later why it was so terrifying. But one of the books that I read on AI,

and I hate that I'm at this point where I just read all this stuff and I can't remember what it is, but I want to make sure people know I didn't come over with this shit myself, right, just, you know, offer a little humility in the process. The growth rate of AI is part of what's interesting. And I think there are two components, which is no one actually knows how quickly the technology will grow and no one actually knows how it will grow within that speed. So one thing, the idea is that in 15 years, we could be here or we could be way farther along than we thought.

like one of these incarnations that Chad GPT was a mindblower for people that it had gotten so good so fast. But the other part is, and I found this fascinating in learning about AI, developing an AI algorithm is like raising a child in the sense that you can impart it with whatever values and things that you think are important. But at the end of the day, that shit is out of your hands and that kid is going to be what that kid is going to be. And all these models, I always figure, right, it wasn't until that first. time that model the damn Chad GBT flat out lied to me about something. Just flat out lied.

And I was like, I can't believe this is possible because I just figured that it was basically such a flow chart one in zero, ones and zero sort of situation. I didn't think this thing could lie to me. But that bad boy lied in my face about something because it was trained to not tell me that it couldn't do an operation that I asked it to do. And then you realize, oh, no, no, no, no, no, no. This isn't too late, I guess is the question, because it feels like they've gone. gone so far and we've done so much. And once you realize that the algorithms actually kind of

control themselves, is it too late? So, so I think there's a couple of important things to unpack there. Like the challenge when people are building this, like there's a huge incentive to anthropomorphize these things. Because if you can make it believe like it's an organism, then you remove culpability. That if I can, if I can really convince everyone, well, this is an organic thing. Like it's, it's creating its own connections, et cetera. That is true to us on a technical level. But the really important thing is to remember that there are human beings who are designing these things. Like human beings are creating the circumstances that they can do these tests where it is, you know, being trained and learning and can become recursively self-improving.

So those are all choices that people are making. So that's the thing we need to focus on from a control standpoint is the people making the choices. The other thing that you make me think of is when it comes to catastrophic risk or extinction risk, one of the big questions is give me an example of. of a smarter species, or sorry, a dumber species controlling a smarter species or a dumber thing controlling a smarter thing. And there are all these people in extinction risk

and catastrophic risk land who will point to, well, the important thing is to make it feel like it's a mother to humanity so that it has a deep love for people. And one of the questions I didn't ask one of these people is, y'all ever heard of Casey Anthony? And I know that she was found in a but we can all have our own personal opinions about how that went down. But to me, it's like there are hundreds of examples a year of a mother killing her child.

And when you are talking about, you know, imbuing the values of a mother to how they take care of their children in a machine that is capable of taking down the entire power grid or making the internet not work. Like these are things where we should not deploy this into systems where there is irreversible harm that can be caused by something because we think that it loves us. That just seems to me like a bad thing and not an intelligent thing to do. And then to the point of line, one of my favorite things to do, anytime I get any response from a large language model, before I do anything with it, I just open up a new window. I paste the response and I say, I want you to be a rigorous fact checker and red team this response. I don't believe that it's true. and then it'll give you all the new, all of the things that it didn't do because it was trying to please you, it will oftentimes be able to catch that.

And just also, you know, using different models to check for different things. Like that's just from a practical standpoint is useful. But yeah, I mean, going back to the idea of the question, is it too late? I don't think so because, I mean,

there's so many things happening that by the time that this airs, it's going to be outdated, but just from an intuitive level, the fact that most Americans are highly skeptical of the way that this is being developed and deployed, and they realize the enormous amount of power this conveys to an extremely small group of people, if it continues to scale, that's what brings me hope. And I think that that's where I hope that the people will continue to rein this in.

And if it gets to a point where we have things like omnipresent surveillance technology, like you see how people are reacting to flock. You know, I have very far left liberal friends who want to take an angle grander to every flock camera they see just as much as my very conservative truck driving brother-in-law. That gives me hope. like the people the people get it. I think it is also interesting to me just how acute it has become because like I've been on dates where I have said that I put something into Chad GPT because I where Chad GPT and I talk is I find that AI chat bots are very helpful

in whittling down that which is infinite. And so I talk to it about travel because the world is an infinite thing. And so it's just like, okay, this month, this time, these kinds of things I like, what do we have? Because otherwise, I would not be, you know, it'll come up with things I'd never thought of, X, Y, and Z. That's where I go. And I find, like, especially if you are talking to somebody

that's under 40, and you mention using some AI, there's a recoil and resistance that comes from people. Now, you also have the kids that are using it to cheat on every exam and every paper that they've ever been asked right. But I think, and I thought that this was the interesting part of the doc also, it was kind of an acknowledgement that there's a bit of disconnect between how the average person will use this technology and the idea, for example, if you can't afford to build a staff for a entrepreneurial idea you have, that the ability,

like there's a bit of democratization that comes from being able to use the technology to help you. But there's a much bigger, larger, more terrifying discussion that is higher. And that's when we start talking about surveillance. That's when we start talking about defense and all of those things. And it feels kind of like we're being sold the little thing that can make. your life a bit easier but behind the curtain it's something else that's going on it's that's very true and it's to me somebody pointed out the other day to me that right now we're in a world where using a large language model is the same as like online dating in the early like the mid 2000s

where everybody's doing it but nobody wants to talk about it like you don't want to say you don't want to say we met on tinder you want to say we met at work or whatever uh and i think that to you to your other point it is a there's a soiling green as people aspect to a lot of this to your point where the idea of, you know, having something that makes it easier for me to make a flyer for my kid's birthday party financing what is also being sold to the federal government to create a panopticon. That really hasn't happened in the history of technology. Like usually, you know, if I'm giving money to Amazon, I know what Jeff Bezos is trying to do with that money. And that's because it's a general purpose technology. So we kind of, we have this

notion of artificial general intelligence, which is the sort of a digital God that a lot of the frontier labs are trying to build, which is a machine that is designed to replace the totality of economically valuable intellectual labor that a human can do. That's step one. And then step two is doing the same thing but replacing all physical labor in the form of robots. So that's the stated goal of these companies. That's where people are getting wise to because they've been told for the last six, seven, eight years, oh, we're coming to replace you. And now, if you'll notice, the song has changed a little bit. Now they're not talking about replacement. So now they're talking about, well, it's just going to make you a little bit better.

It's going to make you more efficient. And the challenge about negotiating these areas are there's a very, it's very difficult for a human being to understand that two things can be true at the same time, that sound as though they're antithetical. So it can be true that they are scaling to a point where it could replace people at the same time where in really specific cases, it still sucks. And the other part of it that that gets really challenging is most people who I know who think that large language models don't. don't do a good job, are not using the paid tier, which means they're not using the state of the art models. And the difference there is enormous, which then gets us into the inequality piece of it, which is if you have more money, you're going to have access to better models. And look what that does on a business level, on an education level, on a kid level. And then you get into the

whole notion of like how it's impacting education. And to your point at that Ivy League school, where the professor pulled a switch on the last minute and he went from an online exam to an in-person exam and the scores, I believe, dropped 45 or 50 percent. We're talking about a sort of dumbification of the next generation of people where they're not being taught to think. And this is all the fallout when I used to teach at schools in New Haven. And it was the birth of the teach for the test era. Now you're seeing a world where you're combining teaching for the test with a software that will do all of that work for you. And you end up with a generation of people who don't know how to think.

And that's that to me, those societal harm. And this, again, doesn't get into the environmental racism based around where the data center is being built, the environmental impact of those things, the financial impact of utility rates, et cetera. But just on a level, you're exactly right that we've never been in a place before where a company that's making what is a subscription product. And it'd be like if Spotify were building a nuclear bomb. You know what I mean? I just want some music. I just want to listen. I think I want to do a good thing.

I want my artist to get one one thousandth of a penny every time I listen to their song. But then behind the scenes, they're helping, you know, the federal government become big brother. We haven't seen that before. Yeah, I think it was what May Yadis Veruficus, who had made the point that he thought

the saving grace on this AI thing would be this system only works if you, this economic system only works if you have sellers and buyers. And people can't buy if they don't have money and you get money from going to jobs and that at some point that would be the thing that would slow people down. But no, that's not doing that. Like, that is, I think part of what's interesting about this is not just about AI.

It's about the larger tech ethos, right? Like, just break shit and see what happens. How would they put that, right? Move fast and break shit. Break stuff. I think it's what they call it. But this is the most interesting example of it because it's one thing when you say that about just like trying to come up with some cool technological doodads.

But now we're talking about something that has grown faster than I think most people expected that it would be capable of growing. And it's created a phenomenon. And I think something that the film also talks about where now everybody feels like they have to use it. Correct. But nobody asked for this. But it does, it's like, hey, man, you're going to be behind.

Exactly. Well, and that's the thing. The idea of the, there's the degree of phomo that we feel from not being on social media is social. But to combine those sort of neuropathways with the idea of you are going to not be as productive. as the next person. It is totally understandable to feel that way and to believe that you must actually use this stuff. And in a lot of cases, people are being forced to, regardless of what the

backlash is going to be. The number of people that I know who, you know, have what you work in social media, et cetera, and they try to explain to their bosses, you don't get it. If I put an AI generated thumbnail on this video, people are going to comment bomb this into oblivion and you're going to lose credibility as a brand. That happens constantly. And then they have to, you know, you have to show their bosses look, you need to go back to human employment. That, to me, it's a really, there's a lot of conflict there where people want to not miss out on the increase in productivity that they believe that they can get from the systems, while at the same time being able to account for the social pressure for not using it.

So it's a very strange soup to be in. All right. Now, coming up next, I'm going to talk to Ted about the experience of talking to some of these founders, which the documentary has. including Sam Maltman, and more on what is going on with AI. The right time is brought to you by Fandul. Baseball fans, think you know who's hitting a homer today? Well, Fandual is giving you a free chance to call your shot with daily dingers.

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Go to Baskin LatherC.O.com and use code TRT for 20% off. That's 20% off at Baskin Lather C.O.com code TRT. All right, we are back with Matt Ted Tremper, producer on the AI Doc, how I became an apocalypticist. I recommend that you check this out.

I was actually surprised that you got, what, four CEOs. We got three out of five. So we got Sam Altman, Dari Amadeh and Demis Sassabas, yeah. Right. And so the five companies are Open AI, Anthropic, DeepMind, Google, and is Microsoft the Fifth? Is Google DeepMind? So it's OpenAI, Anthropic, Google DeepMind,

and then XAI and Meta-I. Yes, yes. So Zuckerberg and, in Elon, huh? They just looked too busy for you. Zuckerberg turned us down multiple times. I developed a contact that, so in the documentary,

it points out that Elon Musk agreed to be in the documentary, but then got busy. And that was essentially the experience that I developed a contact in his inner circle. After we got Sam Altman, Dariamadei and Demasasas, this person channeled to him, hey, if you want to do this, this is who he have. And he said, yes, I should definitely do that. Have that person text me.

So I texted Elon three times and he didn't get back to me. So you have Elon's phone number, which is an amazing thing to be able to see. say. Well, it went, I can't get into too much of what the timing was for these things, but this was at the height of Doge. And unfortunately, the third text I sent went through is green and I thought I blocked the number and I checked him with my contact and they said, oh, well, he had to change it because of the secret baby thing. And that was when the, I said, what? And then I checked the news. And that was when the woman, I think it worked for the, the communications department of the White House or

Fox News had come forward and said, oh, yeah. I had a lens baby, et cetera, et cetera, and he had to change his number up. So I don't have it anymore, but that was... Elon Musk is just like everybody else trying to shake off a baby mama that he wasn't trying to have. Allegedly, allegedly, allegedly. Hey, man, Billy Jean, is not my lover, said Elon Musk. But what did you get from talking to these people?

Now, obviously, they're not all the same person, but I imagine there had to be some common threads that ran between the people that are running these companies. Yes. Yeah, I think that it's really interesting. So the process of getting them, they were all my white whales, as it were. And I believed that we could use the fact that they are in this race. They are in a race to develop and deploy this technology.

And they believe that if they win it, they will essentially control the most powerful tool that humanity is ever built in the form of artificial general intelligence. So then you have to think, okay, well, if those are their incentives, how can I create a circumstance in which they'd want to participate in a documentary like this? because there is no real incentive for them to, you know, expose themselves to really difficult questions, et cetera. So my belief was if I got one, I would probably get more than one and I could maybe get all of them. So what that meant was for those two and a half years, I read and listened to every single thing that any of them had ever written. And I wrote down the names of every person they ever

name checked, good or bad. And I reached out to the people that could get me to those people. And those were a lot of the people that we interviewed for the film. So once we had amassed, you know, between 40 to 60 of those names when we actually made the ask that that list would have at least 20 people that they really love and respect and a couple of people that they were very afraid of what they would say so that way they would want to go on record to be able to well done yeah so you know it's it's a long it was a long long long con long play and to that effect like one of the things I want to give them credit for which is very different is from from previous CEOs is you know, General Motors, to my knowledge, knew about the harms of leaded gasoline, you know, as soon as the 30s or 40s.

You know, the oil industry knew about climate change 40 years ago. They kept a lid on it. These CEOs have been very proactive in saying that they believe that this technology could result in the extinction of the human race. I'm sorry. And they've been saying, no, I know. I mean, it is what it is. They've been saying it for, you can, I mean, Sam Olman's blog that he. he's been writing 2016 or 15, I think, is still online.

You can read every word that he's ever said. And then it becomes a question about whether or not they're using that to hype the power and the capabilities, these products. And depending on who you are, like, depending on who is writing that, I believe that each of them believe different things about that. And I think people need to make up their minds about those people. I think that the, I've not actually read the Ronan Farrow piece about Sam Allman, but there's one from, I think, 2019 when he took over Y Combinator. that was written in The New Yorker. And Paul Graham, who was Sam Altman's mentor, said of him. And he meant this as a compliment.

I believe the quote is, if you dropped Sam on an island of cannibals and came back in two years, he would be the president of Cannibal Island. And I think that if you know much about the way that he was fired and then brought back to Open AI, you know, Sam seems to be the kind of person who is really interested in telling you exactly what he believes that you want to hear and using that as a way to maintain power over the whatever fishbowl he's in. And I think that my personal opinion is that I think that Dario and Demas are a little bit different than that. I think Elon has different incentives. I think that Mark Saccovert has different incentives. But regardless, the most important thing to take away is

if we are trying to live in a world where the future of humanity depends on whether or not one person is a good guy, we're not ready. We have not built the systems that can coexist with that world. But unfortunately, you know, the rise of authoritarianism makes perfect sense, given that you have people in our society and parties in our society, they're trying to prove that the systems that exist don't work need to be dismantled. I disagree with that. I think they need to be upgraded. And I think that people need to engage in good faith in upgrading them so that we don't evolve to a place where we have one dude who we, who we don't, really hope is a nice fella in control of that kind of power and that kind of technology.

Well, like the good guy dependence thing becomes interesting with talking about Altman and Musk and for people who don't know, Altman and Musk were working together and Open AI and the whole claim was we're going to do this. Basically, they were going to be the morally upstanding people, right? Like, they were going to be the ones you could trust. And then they broke up basically, I believe each claiming that the other one really wasn't that invested in the first place in doing the right thing. And now they're in the race. And I mean, Elon Musk is the guy to do the right thing is somewhat of a laughable notion, but it wasn't as laughable in 2015.

No. And that's the thing that's really important. Actually, I'm so glad you're bringing that up because we do need to remember that there was a point where Elon Musk was regarded to be the Thomas Edison of our time, that he was going to lead us to Mars. He was going to revolution. He was going to, you know, Tesla was going to replace every gas car. We were going to fix global warming, et cetera. But then you look at the ways that that and mirroring it against social media.

Social media was, you know, Arab Spring, there was going to be a flourishing of democracy. It was going to be this tool that led to bringing out all of our best natures and look what happened. The incentives that are based around maximizing for attention, maximizing for outrage, point toward the society that we got. And you need to look and have the same understanding of what the tech industry is trying to do with the proliferation of AI. If the goal is to be able to replace human beings so that you can control the totality of the economy, Like when Elon Musk says that AI is going to be a multi-trillion dollar market, it's because he believes that's where we're headed. And we are really getting to a point where if the capability scale and they're able to start paying back investors at the rate that they need to, they might be right because it may become too tantalizing a proposition for business to continue to exist without it.

And at that point, if we have eroded the social support structure, that the very middling ones that exist in our society already, we're in a world where there's no transition plan between double digit, you know, 40% unemployment. And if you've done your history lessons, you realize that Hitler rose to power in Germany because of three consecutive years of 20% unemployment. Yeah. That's not good. And so I think that that's, yeah, I mean, to your point, boy, I don't know if Elon was different then. I don't know whether or not the ketamine and spending too much time on Twitter

rotted his brain out. But like I said, either way, even if it was Elon 2008, I wouldn't trust him with the technology because he's a human being. And that's not the kind of world we need to live in. And as we said before, and I think it bears repeating,

these apps are designed to be customer-friendly. Like, I don't think we really got into that, but that's an important thing to note about the way this stuff is used is that it is designed to give you answers to make you use it more because it's as a product, its goal is to make you use it. They may have these other intentions about what it could do like for the world, but the bottom line is in order for it to catch on, they're going to do the things in there that make you use it. That's why I talk about what it lied to me at that time because it didn't

want to tell me you couldn't do something. It's just like people in your regular life. Well, and down to a design level, there's a great professor out of Oxford, whose name I forget is one of the lines that people use, oh, it's just a tool. It's just a tool. You know, a knife can be used to stab somebody or it can be used to spread butter. And this professor brought up, you need to think about the intention of how you're designing it. Because believe it or not, a gun can also be used to spread butter if you want it to, but it's designed to kill people. And when you talk about sycophancy, which is the notion of AI lying to you, like the reason why when you put a query into chat TPT, the little three dots appears on the left side of the screen, like, like it's sending you a text, that's for you to believe that it's a person behind there. There's a reason why Anthropics model has a name and that name is Claude. Like all of these things are intentions of design. And it's interesting, there's a very, there's a country called China that made it illegal to anthropomorphize models because they understand that they don't want their populace.

They don't want to cede power and control to this ostensibly omnipotent thing because then you start getting in these psychotic states where you are believing that it shouldn't be making every decision for you, et cetera. And children obviously are the most vulnerable to those kinds of impressions where you just want to give away all of your decisions to that. And I'm certainly guilty of it based off of travel. I've algorithm's been doing this to people for, I don't know why I do pottery, Bo. I don't know why, but I love pottery. And I don't know whether or not the algorithm fed that to me because it knew that I would like it or whether or not I just looked at one Reddit post for too long.

And now I've spent $1,000 on pottery lessons this year, dude. This is such a tripper thing. I think I like it. I think I like it. But, you know, it's this notion, the Center of Humane Technology brings up this notion that every human being wants to believe we're living above the algorithm. We want to believe that we are above the control mechanisms that, you know, all of the different ways that algorithms are designed to monopolize our thought and our attention.

We all want to believe we're above that because we're human beings. But guess what? Study after study just shows we're very impressionable. And it's not our fault. But if we account for it, we can put different guardrails in place so that we don't fall prey to, you know, AI sycophancy, AI psychosis, et cetera, et cetera. We just have to know it. Now, you mentioned China. And I think that's an important part of this.

And, you know, for the tail end of what we're doing here, because this is a geopolitical, like, competition superpublic. power sort of issue. So one thing that is interesting, and I think it was Yannis who wrote a book that mentioned this, is that economically speaking, like Europe is in a very precarious position because there is no European that owns anything like Facebook, like Twitter, these sites that just dominates Amazon, right? They get all your information and have all this stuff, right? Like those guys that are turning into trillionaires, none of them are from Europe because Europe does not, nobody in Europe possesses that level of infrastructure. China is in a different situation, right? They've got some of those things and they got that TikTok thing, which

becomes its own discussion, the power that that algorithm has and everything else. But the thing that's important about this is there's a, there's a space race involved here in this. And the Chinese are trying to figure out how they're going to do it. And a lot of it has to do with microchips and who produces them and who can then get possession of them and everything else. But in the end, this is not just a race about economics and like the stock market. and who can get the riches, it's kind of sort of the way that the way the countries view this at a national level is that this is about the fate of the world. So how much like the government will only do with so much curbing of this industry

because if you curb it here and the Chinese run away, then what do we have? And that's, you know, the three main things that allow for capabilities to scale are power, data, and compute, which is the chips. And when you look at the infrastructure that China has built over the last 20 years, most people don't realize that they are not just the world's leader of renewable energy. They are like many, many, many, many times second place. And they've been doing this for decades at this point. Then you think about data.

When you live in a society where people don't have any rights at all for their medical records, et cetera, you can just feed all that data in there, not to mention all the stuff that they're able to steal. And then you talk about compute. You know, we have the Chips Act, which was trying to curtail the amount of the state-of-the-art chips that were going to China. That seems this all changes such and flies, even if they just needed to buy them in the black of market, which they were doing anyway, they could still maintain access to those. But the thing that looks like it's happening now with the birth of these, like, you know, we had another deep-seek moment last week or two weeks ago with Kimmy K-3 and the new deep-seek model where their capabilities are outpacing. So Deepseek is the Chinese version of these five companies that we're talking about. And they shook the world up when they were able to come up in one of these models.

They'd do it a lot cheaper, which may be very fearful for these five companies. Yes. Oh, my God. The Chinese Booleg version is here. And the funny thing about that is obviously, like, the American frontier models were built off of stolen and unlicensed data. That the amount, like really when you think about the amount of theft, and folding in of unlicensed data into these models. You can't really conceive of it.

It's every email you've ever written. It's every Reddit post. It's every your children's vacation, like photos of them on vacation. It's everything. Goes into these models. And I'm being general, it's not literally everything,

but it is a staggering amount of data. The thing that always makes me a little, laugh a little bit is the Chinese models invented this process of distillation where they essentially query the American models enough times they can essentially pull the brain out of it. And so for a few, million dollars as opposed to a few billion dollars, you can essentially pull out all of the

different ways it works and build this Chinese model. And then the frontier labs say, well, hey, you stole all of our data. And I'm over here sitting like, dude, you, you invented the game. Don't, don't hate this new player for playing the game that you set up. And the thing that's also really important, like there are ways in which people will paint this as, oh, well, you know, this AI race is made up. The thing you have to understand is it's many different domains. So you touched upon it. There's the military domain. There's the surveillance domain. There's the economic domain where right now, understanding that from the American side, when you have the vast percentage of the total growth of the stock market of the last several years has been wedded to these different

companies, you're in a world where a trillion dollars of capital is sort of betting on this existing. At a certain point, that doesn't become a bet that you want to win. That becomes a bet that you need to win. So if China is able to flood our market in the global marketplace with models that are of similar or even higher capabilities that they're given to you for free, number one, you're now in a place where, okay, if I'm a business, I have to choose. Do I want China getting all my data? And do I want to have my, you know, compute costs that I'm spending on AI to be $20,000 less? I don't care if China has my data. They're going to get it anyway. It may as well go with the cheaper model. Then you're in a Huawei situation where basically China is able to go to Africa,

to Europe, et cetera, and be able to corner the market at giving these free models away. And the thing that that really is challenging is institutional trust in America as a country, I think it's probably worldwide about at China level at this point. So the idea of us being these trustworthy partners that we can develop technology with, when that's gone and we're more expensive, there's no incentive for Europe or for Africa to want to get in bed with America anymore. So it's really a perfect storm for, you know, right now what I think we're seeing is, China's playbook is going to be to continue flooding America and the world market with absolutely

free open source, open weight models you can customize because that's their competitive advantage because all the frontier models, closed source, you can't manipulate them, et cetera, et cetera. So it's really, there's a whole other side of it where the attitude that the Chinese people have towards AI is wildly different than the United States because they've been deploying it in really specific what are called narrow use categories. So it's, you know, they have an aging population. So it's how are we going to make this replace jobs that people are aging out of that we don't need to replace with the human being because their population is shrinking and it can then support us. That's really great. In the United States, we're being told, we're going to

replace you at the height of your career. That's very bad. So these differing opinions of the way that AI is going to go, they've already won the culture war that their country's having internally with how they feel about AI. And for the United States to be competitive in that, there's a great cat power song I love called Living Proof, that's what we need an error of living proof. For every time that they said it's going to steal your job, they need to show you 20x, 30X that it's actually going to make your life better. And they're not doing that right now. And if we want to win any AI race, it's predicated on Living Proof.

And I think that hopefully they're starting to wake up for that. I don't know that they will. I don't think they will in time. But we'll see. Now I'm going to take that Living Proof idea and get us to where I want to close on this, which is what I mentioned people earlier, which is the Ellison article in the New York Times. Did you see that?

I have not seen it yet, so you've got to educate me too. Okay, okay. I think what I tell you a little, you'll get it, right? So for those who have not seen it, Larry Ellison, who has once been the richest man in the world, the man behind Oracle, the man who owns his own Hawaiian Island, the man whose son is trying to buy Warner Brothers Discovery, basically bankrolled by his father and heavily so in Oracle's stock,

and that's where this gets interesting, because the article winds up being a discussion about how tenuous his fortune is and how not just his fortune, but also the American economy hinges on the adoption rates of AI. I think they said in the year 2025, 95% of GDP growth in this country was on the building of data centers or just what AI, what the AI companies were doing. So what we have is a system, or not a system is not the way to put it, but basically what's going on now is these companies are doing all this AI building and all these data centers and every else, and they're racking up crazy levels of debt to do so because that is what is going to be

necessary in order for them to win this battle. But if you pay attention to it, it really only one of them, it feels like, can win by the notion of how this goes. But it's going and going and going. And so Ellison and Oracle have decided they want to be the back end of all this AI stuff. And that's where their money comes through. But in the process, they've had to do all the borrowing. and now their bonds are now rated at junk stats. And so it becomes a dilemma for AI, for people who observe AI from this distance, because on one hand,

we don't want this to get out of control, but this has the potential to create an spectacular economic depression because it is the growth right now that is propping up our limp economy. It's this entire sector that is doing it. And so for Ellison, he's now so debt-ridden that is rich.

He's like a metaphor for everybody else, right? He borrowed all the money he possibly could, and now he could wind up being ruined. It's partially holding up the Warner Brothers deal because it's being backed by his money. It's not terribly different than Elon Musk when he backed up the Twitter purchase with all those shares at Tesla,

and it's like, oh, what exactly is going to happen here? And so people are going to wind up in a dilemma about who they root for in this, Because rooting for the world can also lead to rooting for your own, at least short-term economic destruction. Well, and the irony is here, I won't encourage people to search for it. But there was the most succinct description of the Jenga Tower that has been built with AI. Actually, I watched on Newsmax, believe it or not.

But they basically pointed out everything you're pointing out. But it goes even further than that. Because once you start seeing the economy dragging in certain sectors, for example, in the entertainment industry, you start seeing people cash out on their pensions. And then when you have people doing that en masse, what that does to their capacity to make investments or, and it goes the other way around. If you're, if you're afraid that, um, you know, the economy is going to collapse, you start liquefying all of your assets and then the stock market deflates. There's so many different that there's such an enormous amount of volatility that it's

impossible to really feel like we can make any bets on the future. The, the one, the, the one, the, One intuition that I want people to take away, there's two different things. One is there are really two fallacies. The first and most insidious is this is inevitable, that the way that this technology is being developed and deployed is inevitable, that we have no control over it. That is nonsense and it has always been nonsense. There's many different examples of people developing power technology, power for technologies where my favorite example of this is when they, uh, uh, the, well, yeah, I'll say the example that I, how many human clones have you seen walking around? Like the incentives to create super soldiers using gene line editing after we had cloning technology is enormous. You know, organ farms, as far as I know, I don't know what Putin and she have gotten cooking up.

I even I've heard, I saw their hot mic. I don't know that we have organ farms anywhere in the country. These are things where we as a society decided that this is a bridge too far and we shouldn't cross it. So that's one side. And then on the regulatory side, you know, when we pass the nuclear nonproliferation agreements, I believe in the 60s, we didn't have the technology to even understand whether companies were complying with it, but we signed those treaties and then people built it. And then we were able to make sure the countries were complying.

Like, we are able as a society to steer where we want to go and force these companies to react. So that's one thing. The other one, which comes from more the artist side and the labor side, is it will never be able to fallacy. It's very tempting to look at the way the capabilities are moving and to say, you know, it's not going to do that. It's not going to get better. It's going to level off here. And being somebody who's watched for three years, hearing people say,

it's never going to be able to do the hands right. It's never going to be able to make a song that's indistinguishable from a human song. And you keep seeing time after time after time, they eventually figure it out. So what we have to understand is we have this very narrow window where we are able to rein the technology in. And the very good news is people are aware. And there's a phrase, Bo, that you introduce me to, which is the oaky doke. Yes. The okie doke in this domain is, if they can convince you that you are replaceable and that you have no self-determination and you have no power, then they are able to do whatever they want.

Where we find changes, just talking to people that you know about what's going on, about people at your company and saying like, hey, I really don't think we should be doing this because people hate this shit. Just being able to show a person with money or if you're working in the finance department saying, you know, we're wasting a shitload of money on these tokens. We're not getting any return out of this. Maybe we should pump the brakes. Or, you know, being in your, with your kids' school. Like when you realize that not only are the teachers using GPT to grade the kids work, but they're using with their communication. Like, these are different things that you can,

you can change the way that you're interacting with this technology, that the people in your lives are interacting with it. And yeah, you can just, the other metaphor I give is, If you look at your marriage as a series of problems to be solved, you will never relax. You will always feel like you're living in hell and in chaos. But if you set up boundaries, that becomes intuitive. You know where you stand. So when you see it, you know how to react.

And rather than feeling like you're playing whackamol, just decide how you want your life to be run vis-a-vis technology and how you want to be deploying it and how you want the people in your life to be deploying it. Just keep having the conversations. And it doesn't have to be stressful. It doesn't have to suck. you just have to coordinate. And maybe good old-fashioned capitalism will save us. This is from a professor at Vanderbilt from that else's story. He's like, to me, it's a math problem.

We are making trillions of dollars in investments on the back of tens of billions of dollars of revenue. That might be. I'm not an economist, but let me say this. I'm an English major, but that makes sense to me. I see it. I see the vision. Yep. I, hey man, Ted Trepper.

I want you guys to check out the AI doc or how I became an apocalypticist. I saved that term for the movie. I think people can figure it out. But I want to check it out. I checked it out. It's absolutely worth your time. I think you can get it on Hulu right now.

But if not, you know how it goes. Find it on Peacock. You can rent it from Amazon. Yeah, Peacock, Amazon or Apple, you can rent it. And just keep your eyes out because we're going to, I think it's going to Netflix relatively soon. But just keep your eyes out for it. Or any plane.

I think it's on, I've gotten multiple texts. last week. It's a great plane movie. It'll make you feel okay. If you crash, it'll be, it's good for you. You are a gentleman and a scholar, sir. I thank you so much. It's so good to see you both. Likewise, bad. And ladies and gentlemen, thanks so much for joining us here on the right time. We do this couple times a week during the summer. Mike McQuaid's handling everything behind the scenes. Thank you, sir. Hit voicemail 323-3-9-677-67. Remember, follow the right time. Subscribe, like, rate us, review us, give us five stars. You only give us four stars. I'm inclined to believe you are a hater.

And we'll talk to you guys in a couple of days. Take it easy.