Latest / INSPIRE STORY / #062_ STORY INSPIRE: Is America in Decline? The Warning Everyone Should Hear

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#062_ STORY INSPIRE: Is America in Decline? The Warning Everyone Should Hear · INSPIRE STORY

• 0:00
  Speaker 1: It's inevitable that socialism will happen in America. But I
• 0:02
  Speaker 1: don't want to lose my agency, my liberty, my freedom.
• 0:04
  Speaker 2: Do you think the US as an empire is in decline?
• 0:06
  Speaker 1: The answer is yes. I was appointed to President Trump's
• 0:09
  Speaker 1: Council of Advisors in Science and Technology. And one of
• 0:12
  Speaker 1: the great lies is that the government will save you.
• 0:14
  Speaker 1: But the more government has tried to create services for
• 0:18
  Speaker 1: people and help bring them up the ladder, the more
• 0:20
  Speaker 1: expensive those things get. 63% of Americans live paycheck to paycheck.
• 0:24
  Speaker 1: People can't afford to pay their bills, and it needs
• 0:26
  Speaker 1: to be fixed.
• 0:27
  Speaker 2: What will ultimately happen?
• 0:29
  Speaker 1: So all my politician friends are about to chop my
• 0:31
  Speaker 1: head off about this, but.
• 0:33
  Speaker 2: David Friberg, what is the most important subject of our time?
• 0:37
  Speaker 1: And I don't buy into the narrative that Dario, Elon,
• 0:41
  Speaker 1: and Sam end up having all the value in AI.
• 0:43
  Speaker 1: Because in the next 10 years, there will be a
• 0:45
  Speaker 1: billionaire that will emerge that has zero net worth today,
• 0:48
  Speaker 1: downloaded open-sourced AI, and built a company that made them
• 0:50
  Speaker 1: a billionaire. And they're going to be someone that's going
• 0:52
  Speaker 1: to come from nowhere. And there's going to be a
• 0:54
  Speaker 1: lot of these sorts of stories.
• 0:55
  Speaker 2: But this narrative that AI will take jobs away, you
• 0:57
  Speaker 2: don't believe it.
• 0:58
  Speaker 1: So from data, from evidence, over all periods of technological
• 1:01
  Speaker 1: revolution like this, we've never seen jobs decline. And the
• 1:04
  Speaker 1: average person doesn't see it. But, oh my God, the
• 1:06
  Speaker 1: stuff we can do is unbelievable. Right now we have
• 1:08
  Speaker 1: a billion people in the world that are starving. We
• 1:10
  Speaker 1: have hundreds of millions dying from curable disease. These are
• 1:12
  Speaker 1: the sorts of things that are going to get resolved.
• 1:15
  Speaker 1: Because AI unleashes this capacity for human advancement. And it's
• 1:19
  Speaker 1: transforming every aspect of biology and our understanding of life sciences.
• 1:23
  Speaker 2: So I wanted to ask you, do you think we're
• 1:24
  Speaker 2: going to be able to live forever soon?
• 1:26
  Speaker 1: The truth is....
• 1:31
  Speaker 2: This is super interesting to me. My team gave me
• 1:32
  Speaker 2: this report to show me how many of you that
• 1:34
  Speaker 2: watch this show subscribe. And some of you have told us,
• 1:36
  Speaker 2: according to this, that you are unsubscribed from the channel randomly. So,
• 1:40
  Speaker 2: favour to ask all of you. please could you check
• 1:42
  Speaker 2: right now if you've hit the subscribe button if you
• 1:44
  Speaker 2: are a regular viewer of the show and you like
• 1:45
  Speaker 2: what we do here we're approaching quite a significant landmark
• 1:48
  Speaker 2: on this show in terms of a subscriber number so
• 1:50
  Speaker 2: if there was one simple free thing that you could
• 1:53
  Speaker 2: do to help us my team everyone here to keep
• 1:55
  Speaker 2: this show free to keep it improving year over year
• 1:58
  Speaker 2: and week over week it is just to hit that
• 2:00
  Speaker 2: subscribe button and to double check if you've hit it
• 2:02
  Speaker 2: only thing I'll ever ask of you do we have
• 2:04
  Speaker 2: a deal if you do it I'll tell you what
• 2:05
  Speaker 2: I'll do I'll make sure Every single week, every single month,
• 2:09
  Speaker 2: we fight harder and harder and harder and harder to
• 2:11
  Speaker 2: bring you the guests and conversations that you want to hear.
• 2:13
  Speaker 2: I've stayed true to that promise since the very beginning
• 2:15
  Speaker 2: of the Diary of a CEO, and I will not
• 2:17
  Speaker 2: let you down. Please help us. Really appreciate it. Let's
• 2:20
  Speaker 2: get on with the show. David Freeburg, you're someone that
• 2:26
  Speaker 2: graces lots of different subjects. If you were to sort
• 2:29
  Speaker 2: of self-define who you are and what you do, now
• 2:33
  Speaker 2: this is difficult because you've got to kind of put
• 2:35
  Speaker 2: yourself on a label here. What would that label be?
• 2:37
  Speaker 2: How would you self-categorize yourself?
• 2:39
  Speaker 1: I would say I'm deeply curious about the world and
• 2:43
  Speaker 1: the universe and how it works and why it works
• 2:45
  Speaker 1: the way it does. And I'm a big believer in
• 2:47
  Speaker 1: human agency to affect the universe around us. And that's
• 2:51
  Speaker 1: kind of my core kind of driving motivation. A lot
• 2:54
  Speaker 1: of the other stuff ancillary is about how do you
• 2:56
  Speaker 1: enable that? And I think that that's sort of probably
• 2:59
  Speaker 1: where I also spend some time is in the enablement
• 3:02
  Speaker 1: of those things.
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  Speaker 2: Got a nice cute photo here of that. kid that
• 3:06
  Speaker 2: wanted to be Einstein.
• 3:07
  Speaker 1: Yeah.
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  Speaker 2: And then as it relates to how that manifested into
• 3:09
  Speaker 2: like a professional journey, what's your professional journey been for
• 3:12
  Speaker 2: anyone that might not know?
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  Speaker 1: I started in college majoring in math and physics, and
• 3:16
  Speaker 1: then I changed my major to astrophysics. And it was
• 3:19
  Speaker 1: during the time I was in college is when the
• 3:21
  Speaker 1: dot-com boom happened. In the heart of Silicon Valley, there
• 3:23
  Speaker 1: was a kid in my dorm room who started a
• 3:26
  Speaker 1: website selling DVDs online, and he sold it for a
• 3:29
  Speaker 1: million dollars in our junior year of college. That was
• 3:31
  Speaker 1: like an unbelievable, unfathomable amount of money. And so There
• 3:35
  Speaker 1: was this change that was happening in the world, and
• 3:37
  Speaker 1: I got enamored with this idea of businesses and how
• 3:40
  Speaker 1: do you use businesses to change the world, not just
• 3:43
  Speaker 1: use scientific discovery as a method to change the world.
• 3:45
  Speaker 1: So I decided to go work in Silicon Valley. I
• 3:48
  Speaker 1: interviewed for jobs. I didn't get a lot of offers,
• 3:51
  Speaker 1: but I played a lot of poker during my college days.
• 3:54
  Speaker 1: That's how I was able to make money. I read
• 3:56
  Speaker 1: all the strategy books on playing poker. I actually spent
• 3:59
  Speaker 1: a year working in a pool hall, and the manager
• 4:01
  Speaker 1: of the pool hall and the bookie invited me to
• 4:03
  Speaker 1: their home poker game, took all my money that I
• 4:05
  Speaker 1: made at the pool hall. I was making $ 4 an hour, $ 4. 25
• 4:07
  Speaker 1: an hour. And so I was like, I'm going to
• 4:09
  Speaker 1: learn poker. So I learned it. That's how I made money.
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  Speaker 1: And I put that on my resume when I applied
• 4:12
  Speaker 1: for jobs after college. And I got interviews with investment banks.
• 4:15
  Speaker 1: And the investment banks were like, oh, we want to
• 4:17
  Speaker 1: talk to a kid that knows how to play poker.
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  Speaker 1: Because this was before internet poker, before ESPN poker. So
• 4:22
  Speaker 1: it was like an interesting thing. And so I ended
• 4:24
  Speaker 1: up getting a job working in investment banking and then
• 4:26
  Speaker 1: worked on tech companies. So then I got to learn business, finance, accounting,
• 4:30
  Speaker 1: mergers and acquisitions, all this sort of stuff. And then
• 4:33
  Speaker 1: I ended up working at Google. I worked at Google
• 4:34
  Speaker 1: when it was started when it was just under a
• 4:36
  Speaker 1: thousand employees. And I left a couple of years later,
• 4:39
  Speaker 1: started a business called the Climate Corporation. And so I've
• 4:42
  Speaker 1: been in Silicon Valley my whole career.
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  Speaker 2: And that company you end up starting does pretty well.
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  Speaker 1: The Climate Corporation?
• 4:49
  Speaker 2: The Climate Corporation.
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  Speaker 1: That one we sold in 2013. So we sold it
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  Speaker 1: for a little over a billion dollars, which was a
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  Speaker 1: great outcome for investors and shareholders. And today, you know,
• 4:59
  Speaker 1: it's software for farmers. And today that software is now
• 5:02
  Speaker 1: owned by Bayer, which is the big kind of pharma
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  Speaker 1: slash ag company. It's used across 200 million acres every year.
• 5:10
  Speaker 1: That's a pretty sizable amount of farmland that uses that
• 5:12
  Speaker 1: software still. So yeah, it's done fairly well.
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  Speaker 2: So I'm 33 now. You were 33 when you sold that?
• 5:18
  Speaker 1: I was 33.
• 5:19
  Speaker 2: 33. A lot of money, $ 1. 1 billion. And you've done
• 5:22
  Speaker 2: lots of other things since then, which we can go into.
• 5:24
  Speaker 2: But you've also, I think from March this year, you
• 5:27
  Speaker 2: were appointed as an advisor to Donald Trump.
• 5:29
  Speaker 1: Yeah, I was appointed to President Trump's Council of Advisors
• 5:32
  Speaker 1: in Science and Technology.
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  Speaker 2: What does that mean in reality?
• 5:35
  Speaker 1: So if you look back in the last couple administrations,
• 5:39
  Speaker 1: there have been different themes over time on who is
• 5:42
  Speaker 1: appointed to PCAST. In historical context, like Bill Clinton had
• 5:46
  Speaker 1: a PCAST that was set up just for the internet.
• 5:48
  Speaker 2: PCAST.
• 5:49
  Speaker 1: President's Council of Advisors in Science and Technology. And so
• 5:52
  Speaker 1: he set one up focused on the internet. And this
• 5:55
  Speaker 1: current PCAST under this administration is heavy in AI. So
• 5:58
  Speaker 1: it's like Mark Zuckerberg, Mark Andreessen, Sergey Brin. That's kind
• 6:02
  Speaker 1: of the cohort that's on this advisory council. But it's
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  Speaker 1: always included folks that are involved in things like biotechnology, sciences,
• 6:09
  Speaker 1: and to help guide science policy for the administration. So
• 6:13
  Speaker 1: it involves having conversations with people in the administration on
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  Speaker 1: things that are happening in industry, things that are happening
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  Speaker 1: on the frontiers of science and technology to help guide
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  Speaker 1: some of the policy decisions that the administration is trying
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  Speaker 1: to create or enforce.
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  Speaker 2: And what is the most important subject of our time?
• 6:28
  Speaker 1: AI. And right now, the big question in the United
• 6:33
  Speaker 1: States from a policy perspective seems to be the regulation
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  Speaker 1: of AI. What role should the government play in determining
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  Speaker 1: policy where AI goes, how it gets built, how it
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  Speaker 1: gets deployed, who gets to use it, who owns it,
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  Speaker 1: where the value lies. A lot of these factions that
• 6:51
  Speaker 1: emerge inside a government, even today on the same political party,
• 6:54
  Speaker 1: on whether or not, for example, to allow Chinese open
• 6:57
  Speaker 1: source models to be used by American businesses. These Chinese
• 7:01
  Speaker 1: models are as good as, or in many cases, better
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  Speaker 1: than private American models of And because they're open weights,
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  Speaker 1: you can download them and run them on any computer
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  Speaker 1: you want that works. A lot of companies want to
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  Speaker 1: use those because they're cheap. You can pay effectively 50
• 7:15
  Speaker 1: cents for a million tokens of output, which is a
• 7:18
  Speaker 1: measure of how productive the model is. A token is
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  Speaker 1: kind of like a word versus $ 50 from Anthropic, which
• 7:25
  Speaker 1: is a private model. So the question is, do we
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  Speaker 1: allow these Chinese models to kind of become ubiquitous in
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  Speaker 1: industry and And if so, what does that do to
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  Speaker 1: American AI? What does that do to our capacity to compete?
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  Speaker 1: Is there security risk? So there's a lot of this
• 7:44
  Speaker 1: kind of debate underway. And that, I think, is probably
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  Speaker 1: the hot topic du jour. I don't know if it's
• 7:49
  Speaker 1: the hot topic tomorrow, but today that's kind of the
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  Speaker 1: big thing. But all of this administration, I think, from
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  Speaker 1: a science and technology policy perspective, will probably be viewed as,
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  Speaker 1: on the one hand, what's the enablement acceleration, regulation of AI.
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  Speaker 1: And on the other hand, you know, there's this question
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  Speaker 1: still on what is science today? In an era of AI,
• 8:11
  Speaker 1: science is also changing. And so there's this kind of,
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  Speaker 1: I think, big shift underway.
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  Speaker 2: We'll go into those subjects, specifically the subjects on AI
• 8:18
  Speaker 2: and everything that it interfaces with. But I think it's
• 8:21
  Speaker 2: important also to get kind of like a backdrop of
• 8:24
  Speaker 2: the economic state and like the social state of the nation,
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  Speaker 2: because all of these things feed into these big questions
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  Speaker 2: on AI. And they also inform everyone's biases on the subject.
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  Speaker 2: Because if you're at a different sort of socioeconomic position,
• 8:37
  Speaker 2: or if you're feeling a different thing, your perspective on
• 8:39
  Speaker 2: AI is going to be radically different. So if we
• 8:41
  Speaker 2: started then first on like, if we just focus on
• 8:43
  Speaker 2: the United States, which in some respects is a little
• 8:46
  Speaker 2: bit of a proxy for the rest of the Western world,
• 8:48
  Speaker 2: where is the United States at this moment in time
• 8:51
  Speaker 2: in terms of, is it on the rise, inequality? What
• 8:54
  Speaker 2: are the sort of pertinent factors here that help us
• 8:57
  Speaker 2: understand the backdrop of this nation?
• 8:59
  Speaker 1: The biggest driver is, for this nation at the moment
• 9:02
  Speaker 1: in terms of what public policy and private markets will
• 9:05
  Speaker 1: do is number one, the unaffordability crisis. What does that mean?
• 9:10
  Speaker 1: 63% of Americans live paycheck to paycheck. They don't have
• 9:13
  Speaker 1: enough savings to pay for a fiscal emergency in their household.
• 9:17
  Speaker 1: 63% of Americans. And the cost of things is rising
• 9:20
  Speaker 1: faster than wages are increasing. So things feel less affordable
• 9:25
  Speaker 1: to most Americans. And then there's this wealth inequality crisis concern,
• 9:31
  Speaker 1: which I would say is both kind of a perception issue.
• 9:35
  Speaker 1: There's definitely policy issues that has allowed it to happen.
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  Speaker 1: And we can talk about those. But I think America
• 9:41
  Speaker 1: is in this kind of crisis of classism, this crisis
• 9:45
  Speaker 1: of us versus them. And it manifests in a lot
• 9:49
  Speaker 1: of different ways. So, you know, you had Ray Dalio on.
• 9:52
  Speaker 1: And if you think about Ray Dalio's kind of like
• 9:54
  Speaker 1: cycle of empires, you know, this is this idea that
• 9:57
  Speaker 1: there's been six empires in the last 500 years. And
• 9:58
  Speaker 1: the United States is on the decline and China's on
• 10:01
  Speaker 1: the rise. And it can be measured across a number
• 10:04
  Speaker 1: of different dimensions, one of which is this crisis of
• 10:07
  Speaker 1: internal struggle, which manifests often with external struggle, the Iran war. Like,
• 10:12
  Speaker 1: why can't we stop having external wars? Well, you know,
• 10:15
  Speaker 1: a nation that's happy with itself generally doesn't go to war.
• 10:18
  Speaker 1: A nation that's not happy generally dies. does go to war.
• 10:21
  Speaker 1: And so a lot of this stuff gets tied up,
• 10:24
  Speaker 1: I think, in this economic distress that the United States
• 10:27
  Speaker 1: is feeling. My contention, which may not be very popular,
• 10:32
  Speaker 1: is that the more government has tried to create services
• 10:36
  Speaker 1: for people and help bring them up the ladder, the
• 10:39
  Speaker 1: more expensive those things get.
• 10:41
  Speaker 2: Are you socialism?
• 10:42
  Speaker 1: Policy in the United States, and this is one of
• 10:45
  Speaker 1: the great lies, and I think there's a in U.S.
• 10:49
  Speaker 1: policy over the last half century. But one of the
• 10:52
  Speaker 1: great lies is that the government will save you. The
• 10:55
  Speaker 1: government will help you by giving you these essential services
• 10:59
  Speaker 1: that you want more of. Education, healthcare, housing. And as
• 11:04
  Speaker 1: the government has entered into those markets, because remember, there
• 11:07
  Speaker 1: are people making those things, offering those services, and there's
• 11:09
  Speaker 1: someone paying for it. So as the government enables more
• 11:12
  Speaker 1: money to flow into those markets, the cost of those
• 11:14
  Speaker 1: things has just gone up. And you can see how
• 11:16
  Speaker 1: this plays out, for example, in education. So higher education.
• 11:20
  Speaker 1: If you want to go to college in the United States,
• 11:22
  Speaker 1: and I'll just give you a statistic, 30 years ago,
• 11:24
  Speaker 1: administrative staff were like 10% of colleges. Today, they're like
• 11:28
  Speaker 1: 60% in just 30 years. Give me a rational reason
• 11:31
  Speaker 1: why we should have 6x the administrative staffing at colleges
• 11:33
  Speaker 1: and universities. There isn't a good reason why. The real
• 11:37
  Speaker 1: reason is that because the federal student loan program doesn't
• 11:40
  Speaker 1: discriminate against the university on how well they do with
• 11:43
  Speaker 1: their graduating students or the degree or the individual that's
• 11:46
  Speaker 1: taking out the loan, The federal student loan program has
• 11:48
  Speaker 1: just allowed more money to flow in to universities. Now,
• 11:51
  Speaker 1: if you're a university administrator, there's no constraint on how
• 11:54
  Speaker 1: much you can charge for tuition. So, hey, we'll raise
• 11:56
  Speaker 1: tuition 5% this year. We'll raise it 8%. We'll raise
• 11:59
  Speaker 1: it 10%. And we'll hire more people. And if people
• 12:01
  Speaker 1: hire more people, they get a higher salary. If you
• 12:04
  Speaker 1: think about the individual, I don't get to make more
• 12:05
  Speaker 1: salary until I'm a manager. Now I want to be
• 12:07
  Speaker 1: a director. Now I want to be a senior director.
• 12:09
  Speaker 1: And the organization grows. That's very natural for any organization,
• 12:13
  Speaker 1: whether it's a nonprofit, a university, or a private company.
• 12:16
  Speaker 1: You want to grow and people want to make more
• 12:17
  Speaker 1: money year after year. So they, because they can collect
• 12:20
  Speaker 1: more money, can charge more for tuition. There isn't a
• 12:23
  Speaker 1: natural market force that says your tuition is too high
• 12:26
  Speaker 1: now because the government has provided unlimited funding to higher
• 12:30
  Speaker 1: education through the federal student loan program. So as a result,
• 12:33
  Speaker 1: education has gotten so vastly expensive that everyone now looks
• 12:36
  Speaker 1: at it and says, we got to do something about this.
• 12:38
  Speaker 1: And both parties seem to say, well, here's what the
• 12:40
  Speaker 1: government's going to do to do more. And it's like
• 12:42
  Speaker 1: putting fuel on the fire. So the challenge right now
• 12:44
  Speaker 1: is people are feeling left behind. There's massive wealth inequality.
• 12:48
  Speaker 1: Things are extremely unaffordable. And the solution that's being embraced
• 12:53
  Speaker 1: is for the government to do more, which de facto
• 12:55
  Speaker 1: leads to socialism. What is wrong with socialism? I would
• 13:00
  Speaker 1: argue that the key measure of a country's success is
• 13:04
  Speaker 1: how many people are transitioning from labor to capital each year.
• 13:08
  Speaker 2: What does that mean?
• 13:08
  Speaker 1: That means every year I'm working paycheck to paycheck. I'm
• 13:11
  Speaker 1: collecting checks. I graduated college. I had $ 19, 000 in debt.
• 13:15
  Speaker 1: I went and worked. I got paid. I saved up.
• 13:18
  Speaker 1: I paid down my debt. I was able to get
• 13:20
  Speaker 1: out of it. Then I worked at Google. We had
• 13:22
  Speaker 1: an IPO. Suddenly I had assets. I had stuff. I
• 13:25
  Speaker 1: had money in the bank account. And it was like
• 13:28
  Speaker 1: an incredible moment for me. And I said, I could
• 13:30
  Speaker 1: live off that money. I don't need to live off
• 13:32
  Speaker 1: a paycheck every month. I now have savings. I have assets.
• 13:36
  Speaker 1: That is capital. And everyone talks about capital versus labor.
• 13:41
  Speaker 1: But the real advantage of America is enabling people to
• 13:44
  Speaker 1: go from labor to capital. Every individual that works, saves, invests,
• 13:50
  Speaker 1: does whatever they need to do to accumulate enough capital
• 13:52
  Speaker 1: ends up in the capital bucket. And then you're no
• 13:54
  Speaker 1: longer stuck needing to go paycheck to paycheck to pay
• 13:58
  Speaker 1: your bills. That's the dream. That's the real American dream.
• 14:00
  Speaker 1: It's not just about owning a house. If you own
• 14:02
  Speaker 1: a house and you have a bunch of debt and
• 14:04
  Speaker 1: you got insurance payments to make and you still got
• 14:06
  Speaker 1: to work every month to make those payments, you're not
• 14:08
  Speaker 1: necessarily living the American dream yet. The American dream is
• 14:11
  Speaker 1: being freed of that burden.
• 14:13
  Speaker 2: Because you can live off the interest of your assets.
• 14:16
  Speaker 1: That's right. And so you're earning income. Let's say you
• 14:19
  Speaker 1: have $ 100, 000 saved and you can make 10% a year
• 14:22
  Speaker 1: on that. That's $ 10, 000. Suddenly, if you get to a
• 14:24
  Speaker 1: million dollars saved, you can make $ 100, 000 a year and
• 14:27
  Speaker 1: you can live on that. That's economic security. That's financial security.
• 14:31
  Speaker 1: That's what we should give to every American is the
• 14:33
  Speaker 1: ability to own assets that give them freedom to choose
• 14:36
  Speaker 1: what they want to do in their life rather than
• 14:37
  Speaker 1: be stuck in work. And the problem with socialism is
• 14:40
  Speaker 1: it takes away that transition moment. It eliminates it because
• 14:43
  Speaker 1: it says everyone has to be labor all the time
• 14:45
  Speaker 1: for the rest of their lives. And then no one
• 14:47
  Speaker 1: has freedom. And that's what America was founded on was
• 14:48
  Speaker 1: this ability to find through freedom of choice, through agency,
• 14:52
  Speaker 1: the ability to transition from labor to capital. And I
• 14:56
  Speaker 1: think our goal as a country should be get 2%
• 14:59
  Speaker 1: of Americans across that line every year. Then I think
• 15:02
  Speaker 1: we'll be successful going forward. But if everything's all about
• 15:05
  Speaker 1: like give people more stuff and have the government do it,
• 15:08
  Speaker 1: We're just going to keep raising the debt, making things
• 15:10
  Speaker 1: more expensive, inflating the cost away. And it's inevitable that
• 15:13
  Speaker 1: socialism will happen in America. It's absolutely inevitable.
• 15:16
  Speaker 2: Do you think the US as an empire is in decline?
• 15:19
  Speaker 1: In terms of the power of the dollar, in terms
• 15:23
  Speaker 1: of prosperity of Americans, the average American, a majority of Americans,
• 15:26
  Speaker 1: the answer is yes. But the potential hasn't been deleted.
• 15:32
  Speaker 1: Meaning decline is not inevitable. To be very clear, like
• 15:36
  Speaker 1: we are not yet at a point where it's a
• 15:39
  Speaker 1: runaway train. In the history of democracies, there's never been
• 15:42
  Speaker 1: a place like America, where an individual like myself, you know,
• 15:45
  Speaker 1: moving here from South Africa, going to public college, graduating
• 15:49
  Speaker 1: with debt, and then being able to work my way
• 15:51
  Speaker 1: out of the debt and find myself in the position
• 15:53
  Speaker 1: I'm in today, with no nepotism, with no handouts with,
• 15:56
  Speaker 1: I mean, you could argue about privilege and all these
• 15:58
  Speaker 1: other sorts of things that I was vested over my life.
• 16:00
  Speaker 1: But It's an amazing place that that sort of story
• 16:03
  Speaker 1: can be told a million times over, that there's not
• 16:05
  Speaker 1: just one or two people that this has happened to,
• 16:07
  Speaker 1: but there's millions of people. The problem is it's all
• 16:10
  Speaker 1: the other hundreds of millions that didn't get to live
• 16:12
  Speaker 1: that opportunity. And if we can fix that, America is
• 16:15
  Speaker 1: not in decline. America is a prosperous nation and has
• 16:19
  Speaker 1: centuries ahead of it.
• 16:20
  Speaker 2: When you look at this, you're talking about runaway trains.
• 16:22
  Speaker 2: When you look at the national debt, though, it does
• 16:24
  Speaker 2: look very much like a runaway train.
• 16:25
  Speaker 1: That's inflation. Want to know where inflation comes from? That's
• 16:27
  Speaker 1: where inflation comes from. By printing more dollars to pay
• 16:30
  Speaker 1: for that debt, which is what happens, the Federal Reserve
• 16:32
  Speaker 1: buys the debt and they issue dollars to the bank
• 16:35
  Speaker 1: system to buy the debt from the government. Remember, the
• 16:38
  Speaker 1: Federal Reserve is separate from the government. The Federal Reserve
• 16:40
  Speaker 1: can print dollars. They can send dollars to banks and
• 16:43
  Speaker 1: now the banks can loan money out and it makes
• 16:45
  Speaker 1: its way into the economy. Now there's more dollars in
• 16:47
  Speaker 1: the economy. And that money was... you know, owed back
• 16:51
  Speaker 1: to the government at some point, but the Federal Reserve
• 16:53
  Speaker 1: may never get paid back. They may just keep adding
• 16:55
  Speaker 1: and adding and adding and adding. And they're just printing
• 16:57
  Speaker 1: more and more dollars.
• 16:58
  Speaker 2: Is that sustainable?
• 16:59
  Speaker 1: No.
• 17:00
  Speaker 2: So I don't understand the force that's going to intervene
• 17:02
  Speaker 2: to stop this sort of compounding debt.
• 17:05
  Speaker 1: The outcome of this is socialism. That's the moment we're
• 17:07
  Speaker 1: in right now. That's why we're seeing this wave of socialism.
• 17:09
  Speaker 1: I've been saying for five years, we're going to face
• 17:12
  Speaker 1: a wave of socialism. And after Donald Trump was elected,
• 17:15
  Speaker 1: My prediction for the next year was that the next
• 17:17
  Speaker 1: wave in politics in America will be socialism, and people
• 17:20
  Speaker 1: thought I was crazy. And I'm like, it is absolutely
• 17:22
  Speaker 1: inevitable if you look at this. This is where we're headed.
• 17:25
  Speaker 1: It is de facto socialism when the government employs roughly
• 17:29
  Speaker 1: one half of the people of the United States. Right now,
• 17:32
  Speaker 1: if you look at all the federal, state, local agencies,
• 17:35
  Speaker 1: so the people that are employed, the people that are
• 17:37
  Speaker 1: contractors of those agencies, and then the people that live
• 17:41
  Speaker 1: off of some sort of government pension or social security system,
• 17:44
  Speaker 1: the total amount is close to 50% of Americans. So
• 17:47
  Speaker 1: we're getting to a point where people are like, the
• 17:49
  Speaker 1: only place I can go is more money from the government.
• 17:51
  Speaker 1: And then eventually the government becomes the whole economy.
• 17:54
  Speaker 2: If the outcome is socialism, was the cause capitalism?
• 17:56
  Speaker 1: That's a great question. I think it was capitalism plus policies.
• 17:59
  Speaker 1: Let's say you have a million dollars.
• 18:00
  Speaker 2: Yeah.
• 18:01
  Speaker 1: You're making, say, 10% a year. Next year, you have 1.1 million.
• 18:07
  Speaker 1: The next year, you have $ 1. 21 million or whatever, and
• 18:10
  Speaker 1: you keep adding it up. That's called compounding. After a
• 18:14
  Speaker 1: couple of years, your million dollars turns into $ 10 million.
• 18:16
  Speaker 1: And you never have to sell shares along the way.
• 18:19
  Speaker 1: You can just own the shares and whatever's going up.
• 18:21
  Speaker 1: Your value just keeps going up. You've never paid taxes
• 18:23
  Speaker 1: along the way. Boom, boom, boom, boom, boom. And suddenly,
• 18:25
  Speaker 1: fast forward a couple of years, instead of having a million,
• 18:27
  Speaker 1: you've now got 10. That's capital compounding over time. Meanwhile,
• 18:33
  Speaker 1: if you're working, every paycheck, taxes are taken out. Every
• 18:37
  Speaker 1: time you get a check, every time you get more money,
• 18:39
  Speaker 1: more capital, taxes are taken out. So if you don't
• 18:42
  Speaker 1: get capital, if you don't get enough savings to allow
• 18:45
  Speaker 1: you to compound, you are never going to get there.
• 18:48
  Speaker 1: So from a tax policy perspective, labor working for your
• 18:52
  Speaker 1: money should have never been taxed higher than earning returns
• 18:56
  Speaker 1: on your capital.
• 18:57
  Speaker 2: So you're saying tax the rich?
• 18:59
  Speaker 1: I'm saying tax capital at a rate that's equivalent to labor.
• 19:03
  Speaker 2: Wealth taxes?
• 19:05
  Speaker 1: Wealth taxes are asset seizures. Definitely no. So One of
• 19:08
  Speaker 1: the principles of the United States and the principle of
• 19:10
  Speaker 1: what this country was founded on is private property rights.
• 19:14
  Speaker 1: If you go back to England, right, like 500 years,
• 19:18
  Speaker 1: or let's just talk Europe broadly. There were very few
• 19:21
  Speaker 1: places where you as an individual citizen had rights to
• 19:25
  Speaker 1: own private property. There were very few places where you
• 19:27
  Speaker 1: could say, I have this thing and it doesn't belong
• 19:29
  Speaker 1: to the king or it doesn't belong to whatever the
• 19:32
  Speaker 1: local lord is. Everything was the property of the lords,
• 19:37
  Speaker 1: of the higher class, of the upper class. It was
• 19:39
  Speaker 1: endowed to them, it was vested to them by birthright
• 19:41
  Speaker 1: for centuries. Same in Asia, same in the Middle East,
• 19:44
  Speaker 1: same in Africa. I mean, like every nation started out
• 19:47
  Speaker 1: with the system where people didn't have rights to private property.
• 19:51
  Speaker 1: Those who had kind of these systems above could decide
• 19:53
  Speaker 1: who got what. So the United States was founded on
• 19:56
  Speaker 1: one of the principles of private property for an individual that,
• 19:58
  Speaker 1: you know, I think when they were drafting the Declaration
• 20:01
  Speaker 1: of Independence, it was about life, liberty, and the pursuit
• 20:03
  Speaker 1: of property. And they later changed it to pursuit of happiness.
• 20:06
  Speaker 1: And the pursuit of property was really the measure of
• 20:09
  Speaker 1: what you've accumulated as an individual. You now have a
• 20:11
  Speaker 1: right to accumulate things. You now have a right to
• 20:13
  Speaker 1: build value, to build wealth, to build a house and
• 20:16
  Speaker 1: have your family in your house and have all these things.
• 20:19
  Speaker 1: That was a principle of the United States. I'm all
• 20:21
  Speaker 1: for taxes when people transact, when they turn their stock
• 20:25
  Speaker 1: that they've held for a couple of years into cash
• 20:27
  Speaker 1: and buy something with it. Boom, tax. You get taxed
• 20:29
  Speaker 1: on that. If that's the right model, that's when you
• 20:31
  Speaker 1: should get taxed. Right then, when you're able to turn
• 20:33
  Speaker 1: that asset that you own into another asset. So that's
• 20:36
  Speaker 1: what we do today. That's an income tax or a
• 20:39
  Speaker 1: capital gains tax, like when you realize that gain. But
• 20:41
  Speaker 1: if I go into your shares and I'm like, hey,
• 20:43
  Speaker 1: I'm going to take 5% of your shares, what are
• 20:45
  Speaker 1: you losing? Well, you can't use those shares to buy
• 20:48
  Speaker 1: anything because as soon as you try and buy something,
• 20:50
  Speaker 1: you owe tax on those shares. So by taking away
• 20:53
  Speaker 1: your shares before you've actually transacted with them, before you've
• 20:55
  Speaker 1: actually sold them, or taking away your private property, your home,
• 20:58
  Speaker 1: or giving the government the right to come in your
• 21:00
  Speaker 1: garage and audit everything you own and say, hey, this
• 21:02
  Speaker 1: year we're doing a 2% tax. That is antithetical to
• 21:05
  Speaker 1: what the United States was founded on, which was a
• 21:07
  Speaker 1: founding principle of private property. Now, if your property goes
• 21:10
  Speaker 1: up in value, and then you eventually turn it into
• 21:12
  Speaker 1: some other property, that's a transaction, and that's when you
• 21:15
  Speaker 1: get taxed. That's how the system's set up. So if
• 21:18
  Speaker 1: we have an issue with people having too much wealth,
• 21:20
  Speaker 1: that's the moment to increase the tax rate. That's capital
• 21:23
  Speaker 1: gains tax, income tax on high earners. Those two things
• 21:26
  Speaker 1: can get you 97% of the way there, and you're
• 21:28
  Speaker 1: not really gonna gain much. Separately, we can kind of
• 21:31
  Speaker 1: talk about the numbers on this, but like tax the rich,
• 21:34
  Speaker 1: all for it, but tax the rich when they transact,
• 21:37
  Speaker 1: when they sell, when they have a capital gain, if
• 21:39
  Speaker 1: they borrow against their assets. This is another thing that's
• 21:42
  Speaker 1: wrong about our system today. If I'm very wealthy, I
• 21:45
  Speaker 1: own a bunch of stock and I've never sold any
• 21:47
  Speaker 1: of the stock. If I borrow against my stock to
• 21:50
  Speaker 1: go buy a yacht, I don't pay taxes. That should
• 21:54
  Speaker 1: be a taxable event. We should fix that. That's an
• 21:57
  Speaker 1: easy fix in the tax system. I'm not taking away
• 21:59
  Speaker 1: your private property, but as soon as you borrow against that,
• 22:02
  Speaker 1: it's effectively like transacting on that property and So that's
• 22:05
  Speaker 1: a moment to pay a tax. And if we think
• 22:07
  Speaker 1: that the rich aren't paying enough taxes, you can raise
• 22:09
  Speaker 1: income tax or capital gains taxes to get them to
• 22:11
  Speaker 1: pay more.
• 22:12
  Speaker 2: This is what I was going to say, but you
• 22:14
  Speaker 2: arrived at it, was most people that own stock in
• 22:17
  Speaker 2: big companies will just borrow against their stock and they
• 22:20
  Speaker 2: never pay a tax. I didn't know this until I was,
• 22:22
  Speaker 2: I'm going to say 26. And my company had gone
• 22:25
  Speaker 2: public and this bank in Europe approached me and said,
• 22:28
  Speaker 2: by the way, we'll give you 20% of whatever the
• 22:32
  Speaker 2: value of the stock you have in my company called
• 22:34
  Speaker 2: Social Chain AG is a tax-free loan. I was like,
• 22:38
  Speaker 2: explain this to me. So you'll just send me millions
• 22:41
  Speaker 2: of pounds and I don't have to pay tax.
• 22:42
  Speaker 1: You don't have to sell your shares.
• 22:43
  Speaker 2: I don't have to sell anything. I said, well, look
• 22:45
  Speaker 2: at the rest of my portfolio. And I had some
• 22:47
  Speaker 2: Facebook stock at the time. They're like, well, we'll give
• 22:49
  Speaker 2: you 50% to 60% loan to value on that, i.e.
• 22:52
  Speaker 2: if you have A million dollars of Facebook stock. We
• 22:54
  Speaker 2: will transfer you today 700 grand tax-free. And I can
• 22:58
  Speaker 2: do with that whatever I want. And I thought, fucking hell,
• 23:00
  Speaker 2: this is what the rich do.
• 23:01
  Speaker 1: That's exactly right. And the truth is that no one
• 23:04
  Speaker 1: talks about behind closed doors. Everyone knows that it needs
• 23:07
  Speaker 1: to change.
• 23:08
  Speaker 2: But no one wants to say it because... I'm saying it. Yeah.
• 23:11
  Speaker 1: Gotta change.
• 23:12
  Speaker 2: What's interesting about that is say that I have 10
• 23:14
  Speaker 2: million of Facebook stock and I take a loan and
• 23:16
  Speaker 2: they give me 5 million in cash. What a rich
• 23:18
  Speaker 2: person then does is they take that 5 million and
• 23:20
  Speaker 2: they go and buy other assets.
• 23:21
  Speaker 1: Exactly right.
• 23:22
  Speaker 2: And then they start acquiring more and more assets.
• 23:24
  Speaker 1: That's what's unfair about the system because then when you
• 23:26
  Speaker 1: have capital, you're accumulating more capital while labor, if you
• 23:30
  Speaker 1: haven't made that cross that chasm from labor to capital,
• 23:33
  Speaker 1: you're still here grinding every month, grinding every week, trying
• 23:35
  Speaker 1: to pay your frigging bills. And then these guys have
• 23:37
  Speaker 1: all these shenanigans that are going on.
• 23:39
  Speaker 2: Yeah.
• 23:39
  Speaker 1: It is wrong and it needs to be fixed. The
• 23:42
  Speaker 1: answer though is not taking private property.
• 23:45
  Speaker 2: Yeah.
• 23:45
  Speaker 1: As soon as you start taking private property, those gates
• 23:48
  Speaker 1: are open. By the way, it's not even going to
• 23:49
  Speaker 1: be constitutional in the United States. The fifth amendment, has
• 23:51
  Speaker 1: this taker clause. It's legally not going to win in
• 23:54
  Speaker 1: federal court. It could work in some states. There are
• 23:58
  Speaker 1: seven states that actually have a constitutional ban on private
• 24:01
  Speaker 1: property tax like this. There's 43 states where it's game on,
• 24:06
  Speaker 1: and we'll see how they play out in the courts
• 24:07
  Speaker 1: as they try to pass these wealth taxes as well.
• 24:09
  Speaker 1: But these are asset seizure taxes. You can have a
• 24:12
  Speaker 1: wealth tax by raising capital gains make high income or
• 24:15
  Speaker 1: high asset people pay more taxes or whatever when they
• 24:18
  Speaker 1: sell stuff or when they buy stuff. There's a lot
• 24:20
  Speaker 1: of ways to tax wealth. But taking assets from people
• 24:25
  Speaker 1: after they've paid their taxes or before they've paid their
• 24:27
  Speaker 1: taxes is not the right way to do it.
• 24:30
  Speaker 2: What will ultimately happen?
• 24:31
  Speaker 1: So the ultimate outcome will be that 51% of people
• 24:35
  Speaker 1: will say, hey, give me all the stuff that the
• 24:36
  Speaker 1: 49% have. What would stop them from doing that? Because
• 24:40
  Speaker 1: ultimately you can take as much as you want from
• 24:43
  Speaker 1: a minority of people and distribute it to the majority.
• 24:46
  Speaker 1: And that minority starts out with a few billionaires, then
• 24:48
  Speaker 1: a couple more 50 millionaires, then a couple more 10 millionaires,
• 24:51
  Speaker 1: then millionaires, then 100,000aires. And there's no limit to where
• 24:54
  Speaker 1: this thing goes. And that is socialism.
• 24:56
  Speaker 2: And what does that do in terms of how talent
• 25:00
  Speaker 2: moves and how people move to different places?
• 25:04
  Speaker 1: I know billionaires.
• 25:07
  Speaker 2: Yeah.
• 25:07
  Speaker 1: Many of them have moved or are planning to move
• 25:09
  Speaker 1: out of California, just on the threat of this. And
• 25:12
  Speaker 1: people say... F them, good riddance, get rid of them.
• 25:15
  Speaker 1: You know, the top 1% of taxpayers in California pay
• 25:18
  Speaker 1: the majority of taxes in the state. I think it's probably,
• 25:22
  Speaker 1: it's definitely north of 40%, but it's probably the majority.
• 25:25
  Speaker 2: The top 1% of earners pay 40 to 50% of
• 25:28
  Speaker 2: California's total personal income tax, depending on stock market capital
• 25:31
  Speaker 2: gains performance.
• 25:32
  Speaker 1: There you go. So that 1% are the people I'm
• 25:35
  Speaker 1: talking about that are leaving the state because they see
• 25:37
  Speaker 1: where this is headed. I don't think California wants that.
• 25:41
  Speaker 1: Those are very productive people for the state. They're people
• 25:44
  Speaker 1: that create companies, that hire people, that pay well, go
• 25:48
  Speaker 1: to fancy restaurants, pay for cars. I mean, they support
• 25:51
  Speaker 1: the economy. It's not just the taxes, but they're a
• 25:53
  Speaker 1: big part of capital flowing through the economy. We saw
• 25:56
  Speaker 1: this happen in France. You know, France had this wealth
• 25:58
  Speaker 1: tax and then their total tax revenue declined by more
• 26:01
  Speaker 1: than they were making on the wealth tax because everyone
• 26:03
  Speaker 1: left France. Then they stopped doing the wealth tax and
• 26:06
  Speaker 1: everyone came back and the income came back. So this
• 26:08
  Speaker 1: is a well-studied kind of case. So I don't think
• 26:10
  Speaker 1: that a wealth tax or an asset seizure tax is
• 26:13
  Speaker 1: the solution. I think we've got to fix all the
• 26:14
  Speaker 1: other stuff that we've talked about, and we've got to
• 26:16
  Speaker 1: fix the government spending problem. And if we can do
• 26:19
  Speaker 1: those two things, then I think we can bring inflation down,
• 26:21
  Speaker 1: we can bring the wealth inequality down, and give more
• 26:24
  Speaker 1: people the ability to make that transition. But I do
• 26:26
  Speaker 1: think every politician should be talking about the focus on
• 26:28
  Speaker 1: what percent of people in the United States every year
• 26:31
  Speaker 1: are moving from labor to capital. How many people can say, hey,
• 26:34
  Speaker 1: I've got enough cash to retire if I wanted to,
• 26:36
  Speaker 1: That's what we want to try and get everyone towards,
• 26:38
  Speaker 1: not just convincing people. And this is one of the
• 26:40
  Speaker 1: great lies, convincing everyone that the great American dream is
• 26:43
  Speaker 1: to own a house. When owning a house for a
• 26:45
  Speaker 1: lot of Americans ends up putting all your capital in
• 26:48
  Speaker 1: one asset, and you've got to basically get the price
• 26:50
  Speaker 1: of housing to go up every year to keep everyone
• 26:52
  Speaker 1: moving up the ladder. So now, fast forward 30, 40,
• 26:55
  Speaker 1: 50 years, young people can't afford to buy a house
• 26:57
  Speaker 1: anymore because we've pushed the asset value up so much
• 27:00
  Speaker 1: to try and make sure that everyone's got good household wealth.
• 27:03
  Speaker 2: We are told that. I mean, that's the sort of
• 27:05
  Speaker 2: central idea once you leave university is to figure out
• 27:07
  Speaker 2: how quickly you can get a mortgage or buy a house.
• 27:09
  Speaker 1: Great lie. It's one of the great lies. And there's
• 27:11
  Speaker 1: a lot of countries where people have been able to
• 27:13
  Speaker 1: accumulate capital and jump that ravine from labor to capital
• 27:17
  Speaker 1: much more quickly when they don't buy a house because
• 27:19
  Speaker 1: they can invest in stuff. They can buy, you know,
• 27:21
  Speaker 1: the S & P 500, which you can just buy
• 27:23
  Speaker 1: on an E-Trade or Robinhood account and you can just
• 27:25
  Speaker 1: own it, on average will make you 10, 11% a year.
• 27:28
  Speaker 1: You just put your money in that, you're making 10,
• 27:29
  Speaker 1: 11% a year and it can go up every year.
• 27:31
  Speaker 1: You don't have to pay taxes. You don't have to
• 27:32
  Speaker 1: pay property tax. You don't have to pay insurance. You
• 27:34
  Speaker 1: don't have to deal with repairs and maintenance, all that
• 27:36
  Speaker 1: sort of stuff. So a lot of people would have
• 27:38
  Speaker 1: been better off depending on the markets that they're in.
• 27:40
  Speaker 1: There are some markets that ballooned, but a lot of
• 27:42
  Speaker 1: people would have been better off over the last 30
• 27:44
  Speaker 1: years actually owning the S & P 500 than owning
• 27:47
  Speaker 1: their home and paying for the rent on a home.
• 27:49
  Speaker 2: One of the things I see in the comment section
• 27:50
  Speaker 2: whenever someone makes that point is you'll have someone who
• 27:53
  Speaker 2: bought a house 20 years ago saying, well, listen, I
• 27:56
  Speaker 2: bought a house 20 years ago for this amount. And
• 28:00
  Speaker 2: now it's worth this. And this is every single time
• 28:02
  Speaker 2: that I see this, this argument being made from financial
• 28:05
  Speaker 2: advisors or investors, that is always the top comment is, well,
• 28:10
  Speaker 2: I bought one and I did good. Yep.
• 28:12
  Speaker 1: It actually indicates a problem, which is if your house
• 28:15
  Speaker 1: went up in price so much, that house is much
• 28:17
  Speaker 1: less affordable to a young person that's going to buy
• 28:19
  Speaker 1: it next. And that's what we fundamentally done with this
• 28:23
  Speaker 1: asset class, residential real estate. We've created a system whereby
• 28:27
  Speaker 1: residential real estate prices go up so much, and there's
• 28:30
  Speaker 1: a whole bunch of policies around making this happen.
• 28:33
  Speaker 2: I've got a graph here showing all the things that
• 28:35
  Speaker 2: have gone up, and you can see housing is one
• 28:37
  Speaker 2: of them.
• 28:37
  Speaker 1: Yeah, the stuff on the bottom, the government doesn't touch.
• 28:39
  Speaker 1: The stuff on the top, the government touches. And so
• 28:41
  Speaker 1: the more the government's involved, the more expensive these things get.
• 28:44
  Speaker 1: But all of the policy around residential real estate has
• 28:47
  Speaker 1: allowed the middle class in America, which has the majority
• 28:50
  Speaker 1: of wealth, and I'll give you the statistics in a minute,
• 28:52
  Speaker 1: to grow their asset base, to accumulate more assets, to
• 28:55
  Speaker 1: become wealthier. All the boomers, they're so wealthy because they
• 28:59
  Speaker 1: owned all these houses. And now young people graduating college
• 29:02
  Speaker 1: can't afford a house. It is a bad fact that
• 29:06
  Speaker 1: a lot of people got very wealthy by owning a
• 29:08
  Speaker 1: home because it means that the next generation is going
• 29:10
  Speaker 1: to say, I want socialism because I can't afford a home.
• 29:13
  Speaker 1: That's the moment we're in. 40 million Americans graduated from
• 29:17
  Speaker 1: colleges in the United States in the last 10 years.
• 29:18
  Speaker 1: 45 million. So if you do the math on this,
• 29:22
  Speaker 1: That's a large number of people that are now on
• 29:25
  Speaker 1: average encumbered with some amount of student debt facing a
• 29:30
  Speaker 1: challenging job market. And then the only way to buy
• 29:33
  Speaker 1: a home is you got to come up with a
• 29:34
  Speaker 1: million bucks. And, you know, it leads to this problem
• 29:37
  Speaker 1: where everyone's like, man, I need mom Donnie.
• 29:39
  Speaker 2: So, what would you say then to people that are
• 29:42
  Speaker 2: in that 62 percent was it 63 63 percent of people.
• 29:45
  Speaker 1: And that statistic changes year to year but that's roughly
• 29:47
  Speaker 1: the number 63 percent of americans you know less than
• 29:50
  Speaker 1: 500 of savings and working paycheck to paycheck and can't
• 29:54
  Speaker 1: pay for a fiscal emergency.
• 29:56
  Speaker 2: So for those people, the 63% who you're telling them
• 30:00
  Speaker 2: that buying a house is now like unaffordable, it's potentially
• 30:03
  Speaker 2: not a good investment. If they're trying to sort of
• 30:05
  Speaker 2: cross that cousin and get over to the side where
• 30:07
  Speaker 2: they have assets, what would your prescription be for them?
• 30:11
  Speaker 2: What should they do?
• 30:12
  Speaker 1: Man, that's a great question. People will challenge it, but
• 30:16
  Speaker 1: I would have never thought that podcasting would be such
• 30:20
  Speaker 1: a massive business. I would have never thought that being
• 30:24
  Speaker 1: an Instagram influencer would be such a massive business or
• 30:26
  Speaker 1: a TikTok influencer. I would have never thought that individual
• 30:30
  Speaker 1: artists could publish online and make money without getting a
• 30:33
  Speaker 1: record deal. I would have never thought that individual artists
• 30:36
  Speaker 1: would be able to sell their work and make a
• 30:38
  Speaker 1: living on eBay and Etsy. I would have never thought
• 30:41
  Speaker 1: that craftspeople would be able to find jobs through the internet.
• 30:45
  Speaker 1: I think the internet has been this incredible enabler of
• 30:47
  Speaker 1: millions of new ways to work, of new ways to
• 30:51
  Speaker 1: earn an income. And a lot of people will roll
• 30:53
  Speaker 1: their eyes and say, but that's not what the system
• 30:55
  Speaker 1: was supposed to have set me up for. The system
• 30:56
  Speaker 1: failed us. Maybe the system did fail you. And maybe
• 30:59
  Speaker 1: the government solution wasn't the right solution, but human agency
• 31:02
  Speaker 1: is what got all these people there. They all got
• 31:04
  Speaker 1: to this place. Did the government give you your job
• 31:07
  Speaker 1: as a podcaster? Did the government teach you how to
• 31:09
  Speaker 1: podcast and build this incredible media empire that you've built?
• 31:12
  Speaker 1: I don't know if the government played much of a
• 31:14
  Speaker 1: role in it. I think you played the role in it.
• 31:16
  Speaker 1: I don't know. You tell me if I'm wrong. But
• 31:19
  Speaker 1: I think that this is really important for a lot
• 31:20
  Speaker 1: of people to observe firstly, which is the government isn't
• 31:23
  Speaker 1: going to save individuals. The government's going to make things
• 31:26
  Speaker 1: harder for individuals to find their path. If I have
• 31:29
  Speaker 1: to go and start a barber shop, I got to
• 31:31
  Speaker 1: go get all these cosmetology licenses. I got to go
• 31:34
  Speaker 1: figure out a way to go to school, pay thousands
• 31:37
  Speaker 1: of dollars, get health inspections done. There's a lot of
• 31:39
  Speaker 1: government layers that stop me from doing that work. There's
• 31:42
  Speaker 1: a lot of ways that the government actually inhibits people's
• 31:44
  Speaker 1: agency and makes it harder for them to do the
• 31:47
  Speaker 1: things that they want to do and progress. I think
• 31:48
  Speaker 1: that's just fundamental for me, one of the observable truths.
• 31:52
  Speaker 1: But I think the second thing is I never discount
• 31:54
  Speaker 1: human agency. There was this great podcast done years ago
• 31:59
  Speaker 1: by those guys at the Hoover Institute where they talked
• 32:02
  Speaker 1: about the success of China. And a lot of people,
• 32:05
  Speaker 1: you know, where China grew GDP per capita from like 3,000
• 32:08
  Speaker 1: to 30,000 or whatever it was. And they're like, man,
• 32:11
  Speaker 1: Chinese central planning is brilliant. They're so good at this.
• 32:14
  Speaker 1: And these guys made the argument, which I discounted at
• 32:16
  Speaker 1: the time, But I often think about nowadays that it
• 32:19
  Speaker 1: was actually the agency of the individual choice, the entrepreneurship,
• 32:25
  Speaker 1: the drive, the motivation of the population, of the individuals
• 32:29
  Speaker 1: in China, not central planning. But basically, the government enabled
• 32:33
  Speaker 1: free markets. They allowed people to work. They allowed people
• 32:35
  Speaker 1: to trade. They allowed people to create value for each other,
• 32:38
  Speaker 1: to do something that someone else might want. They looked
• 32:40
  Speaker 1: around and they said, I think you want this, and
• 32:42
  Speaker 1: they started making it. And when the government loosened the
• 32:45
  Speaker 1: shackles on individuals... that population grew the economy. And the
• 32:49
  Speaker 1: government still has a big role in central planning in China.
• 32:52
  Speaker 1: But it was a really important point. If you think
• 32:54
  Speaker 1: about all the success that's come from the United States,
• 32:56
  Speaker 1: it's not a central message that the government said, let's
• 32:58
  Speaker 1: do this, and then we're going to do this, and
• 32:59
  Speaker 1: we're going to do this. It's individuals making their own choices.
• 33:02
  Speaker 1: You've seen what people want to learn, what people want
• 33:04
  Speaker 1: to watch, what they're interested in, and you give it
• 33:06
  Speaker 1: to them. You create value for them. You deliver that value,
• 33:09
  Speaker 1: and you've earned something from that. People are willing to
• 33:12
  Speaker 1: pay for that. And I think that that's core to
• 33:15
  Speaker 1: kind of where we can go from here And I
• 33:17
  Speaker 1: don't think we teach it in schools. I don't think
• 33:19
  Speaker 1: we teach it as a value. We've lost that value
• 33:22
  Speaker 1: of agency, the importance of the individual taking their own action.
• 33:26
  Speaker 1: Every conversation we have in every frigging context is all
• 33:30
  Speaker 1: about the frigging government. Government this, do this, do this,
• 33:33
  Speaker 1: do this, do this for me. What individuals can do
• 33:36
  Speaker 1: is limitless. And that's where I think we fall short.
• 33:39
  Speaker 1: Every day someone should ask themselves, I tell my kids this,
• 33:41
  Speaker 1: but what did you do today that someone else valued?
• 33:45
  Speaker 1: And if you focus on figuring out something that you
• 33:47
  Speaker 1: can do, that someone else can value, and you do
• 33:51
  Speaker 1: that over and over again, rinse and repeat, I think
• 33:54
  Speaker 1: there's paths for people.
• 33:55
  Speaker 2: So a couple of counter arguments here.
• 33:57
  Speaker 1: Yeah.
• 33:57
  Speaker 2: So we can stress test this thinking. You pointed at
• 34:00
  Speaker 2: me and said, I was, you know, I started podcasts,
• 34:01
  Speaker 2: I started businesses, those businesses grew. And it was, you know,
• 34:05
  Speaker 2: you were very generous in giving me probably more credit
• 34:07
  Speaker 2: than I deserve there. But if I was to, if
• 34:10
  Speaker 2: I was to rebuttal that, I would say I was
• 34:12
  Speaker 2: born in Africa and Would that have been possible in Africa?
• 34:15
  Speaker 2: Would that have been possible in like Nigeria where my
• 34:17
  Speaker 2: mother's from or would it have been possible in Botswana
• 34:20
  Speaker 2: where I was born? Is it the fact that I
• 34:23
  Speaker 2: moved to the UK where I had this sort of
• 34:25
  Speaker 2: foundation of stability because of the government where school was
• 34:28
  Speaker 2: free for us, healthcare is taken care of. So I
• 34:30
  Speaker 2: never had to think about those things, which allowed me
• 34:33
  Speaker 2: at 18 years old to like not go to university,
• 34:37
  Speaker 2: take a risk, drop out, be in that room. No,
• 34:39
  Speaker 2: when I was sat in that room in Manchester, I
• 34:41
  Speaker 2: actually at one point printed off the job seekers allowance forms,
• 34:44
  Speaker 2: which are basically the government will give me free money
• 34:47
  Speaker 2: if I get to the point where my shoplifting of
• 34:49
  Speaker 2: pizzas is no longer a reliable way to feed myself.
• 34:52
  Speaker 2: But I had that form on my desk and it
• 34:54
  Speaker 2: was there. And there's maybe something psychological about knowing that
• 34:57
  Speaker 2: I had this sort of like underlying safety net where
• 34:59
  Speaker 2: I could rush back a 300 mile round trip to
• 35:02
  Speaker 2: my parents in Plymouth and I could like live in
• 35:04
  Speaker 2: the house or I could fill out this form, this
• 35:07
  Speaker 2: job seekers allowance form, and they would like pay me money.
• 35:10
  Speaker 2: That allowed me maybe at some deeper level to go
• 35:13
  Speaker 2: and take that risk. And I never even realized the
• 35:15
  Speaker 2: privilege of like, oh, there's like healthcare and there's laws
• 35:18
  Speaker 2: and there's roads and there's like this wifi thing that
• 35:21
  Speaker 2: allows me with this laptop in my room to like
• 35:23
  Speaker 2: build this website that I built. So that's the government's
• 35:26
  Speaker 2: involvement in my success. They gave me this great foundation
• 35:28
  Speaker 2: of stability and infrastructure.
• 35:30
  Speaker 1: Great, great role for government to play.
• 35:32
  Speaker 2: But the problem is that's a slippery slope, right?
• 35:34
  Speaker 1: That's right.
• 35:35
  Speaker 2: And so there's balance here. There's nuance of like personal agency,
• 35:37
  Speaker 2: but then also the government do need to give me
• 35:39
  Speaker 2: a good foundation.
• 35:40
  Speaker 1: That's right. But the government shouldn't employ you. And that's
• 35:45
  Speaker 1: the slippery slope that we end up on. And that's
• 35:47
  Speaker 1: where I worry about our ability to come back from that.
• 35:50
  Speaker 1: Because if you do end up with 40, 50% of
• 35:51
  Speaker 1: Americans getting paid some check from the government, it becomes
• 35:55
  Speaker 1: very hard to get off of that check. And then
• 35:56
  Speaker 1: people vote for that check to get bigger and bigger.
• 35:59
  Speaker 2: The other point I wanted to point out of maybe
• 36:01
  Speaker 2: a counterpoint is just like, and you know this because
• 36:03
  Speaker 2: I've heard you say this before, but like there is
• 36:04
  Speaker 2: a privilege that we both have in terms of our
• 36:07
  Speaker 2: just nature. Yeah. Nature, nurture, whatever it might be. Yeah.
• 36:11
  Speaker 2: And I said nature because upbringing implies that our parents
• 36:15
  Speaker 2: were great to us and that's what made us whatever.
• 36:17
  Speaker 2: But also the opposite can be true. If you think
• 36:19
  Speaker 2: about someone like Elon Musk, you go, his dad wasn't
• 36:21
  Speaker 2: that nice to him. So not necessarily a lovely upbringing,
• 36:24
  Speaker 2: but the circumstances.
• 36:25
  Speaker 1: Well, he was never without a meal and neither was I.
• 36:27
  Speaker 1: And I mean, you know, those are important facts of privilege.
• 36:31
  Speaker 2: The circumstances of our upbringing and maybe our nature, maybe
• 36:34
  Speaker 2: our biology, maybe. set us up to be the certain
• 36:37
  Speaker 2: type of person where agency, however that's defined. And again,
• 36:41
  Speaker 2: I pause there.
• 36:42
  Speaker 1: I think you're exactly right. And I think that that's
• 36:44
  Speaker 1: what education should be teaching that value. That's where I
• 36:48
  Speaker 1: think this role of like, what's the role of a
• 36:50
  Speaker 1: public school? What's the role of this infrastructure that government's
• 36:54
  Speaker 1: building around us? If it's teaching you that your next
• 36:57
  Speaker 1: job is to come and work for the city or
• 36:59
  Speaker 1: come and work for the state, it's not teaching you
• 37:01
  Speaker 1: that you have agency. It's not telling you, if it's
• 37:04
  Speaker 1: telling you that the only path you're going to have
• 37:06
  Speaker 1: coming out of this rural school is to go work
• 37:08
  Speaker 1: in the military, it's not teaching you about your agency.
• 37:10
  Speaker 1: And I'm not saying it's wrong to do civil service
• 37:12
  Speaker 1: or to do military service. I think those are very
• 37:14
  Speaker 1: important parts of what all of us should strive to
• 37:16
  Speaker 1: do is to support the government that makes our society possible.
• 37:20
  Speaker 1: But I think that this idea that we should all
• 37:23
  Speaker 1: be proposed as like the government role, the government path,
• 37:26
  Speaker 1: the government work is what we should all be stuck
• 37:28
  Speaker 1: doing for the rest of our lives is the wrong setup.
• 37:31
  Speaker 2: The opposite is the also probably the wrong setup, which
• 37:35
  Speaker 2: is that we should all start a business or become
• 37:36
  Speaker 2: a creator.
• 37:37
  Speaker 1: I think that's a mistake too. But I think that
• 37:39
  Speaker 1: this idea that you can find a path where you
• 37:41
  Speaker 1: can provide value to someone as part of an organization,
• 37:44
  Speaker 1: as an individual, as a leader, you can choose your path.
• 37:48
  Speaker 1: But the idea that you should be accessing your capacity,
• 37:50
  Speaker 1: that you can create value for someone else should be
• 37:52
  Speaker 1: the objective.
• 37:53
  Speaker 2: Do you think there's always going to be inequality?
• 37:56
  Speaker 1: Yes. I mean, it's either inequality or it's lack of progress.
• 38:02
  Speaker 1: I think those are the That's the dance. That's the dance.
• 38:04
  Speaker 1: So China's very good at this. If you watch their policy,
• 38:07
  Speaker 1: they just recently shifted to a free market policy. They
• 38:10
  Speaker 1: literally just have like a throttle. I always vision Xi
• 38:13
  Speaker 1: has this lever in his big room where he goes
• 38:16
  Speaker 1: like free market, not free market. Like he's just kind
• 38:19
  Speaker 1: of like rolling it back and forth. When you have
• 38:22
  Speaker 1: a free market, people push the frontier. They discover new things.
• 38:25
  Speaker 1: They make new things that have never been done before.
• 38:27
  Speaker 1: They create new value and the economy grows exponentially. The
• 38:31
  Speaker 1: problem is it doesn't grow evenly initially. So like, let's
• 38:34
  Speaker 1: say that you came up with a goose that lays
• 38:36
  Speaker 1: golden eggs and AI, and you've got this technology and
• 38:41
  Speaker 1: this technology is making golden eggs and you're getting very
• 38:44
  Speaker 1: wealthy with these golden eggs. And then that goose makes
• 38:46
  Speaker 1: two geese and three geese and four, it starts breeding
• 38:49
  Speaker 1: and he starts selling the goose. And it takes a
• 38:51
  Speaker 1: number of years before everyone has a golden goose. During
• 38:54
  Speaker 1: that time, you've raced ahead because you've got now dozens
• 38:57
  Speaker 1: of geese making lots of golden eggs for you. And
• 39:00
  Speaker 1: a lot of people are like, I want a golden goose.
• 39:01
  Speaker 1: By the time they get a golden goose, you've now
• 39:03
  Speaker 1: got a million golden geese. And it feels like inequality.
• 39:07
  Speaker 1: But the truth is now everyone here has a golden goose.
• 39:09
  Speaker 1: And if you told them 30 years ago, you would
• 39:11
  Speaker 1: have a golden goose, they'd be like, no way, that'd
• 39:12
  Speaker 1: be amazing. So every day they're making the golden goose,
• 39:15
  Speaker 1: they're printing the money, they're buying stuff with it. That's
• 39:18
  Speaker 1: the problem with progress. Whether it's medicine, you know, a
• 39:21
  Speaker 1: lot of medicines today are a million dollars a dose
• 39:22
  Speaker 1: for like CAR T therapies, for example. These can save
• 39:25
  Speaker 1: you from cancer. Only 50,000 people in the US can
• 39:27
  Speaker 1: get them every year. And there's hundreds of thousands of
• 39:29
  Speaker 1: people that die. because they don't have access to these therapies.
• 39:32
  Speaker 1: So it's limited in terms of its availability. There's technology
• 39:36
  Speaker 1: like AI. Not everyone has access to it. Not everyone
• 39:38
  Speaker 1: owns a piece of a model, etc. Not everyone's using it.
• 39:41
  Speaker 1: And the people that are using it are getting ahead
• 39:43
  Speaker 1: faster than the people behind.
• 39:44
  Speaker 2: In your golden goose analogy, by the time that the
• 39:47
  Speaker 2: golden goose geese get down to the sort of lower
• 39:50
  Speaker 2: end of the socioeconomic ladder or.
• 39:53
  Speaker 1: I would i would use the word diffuse yeah yeah.
• 39:55
  Speaker 2: Those those golden eggs or whatever buy less because something
• 39:59
  Speaker 2: happens along the way.
• 40:00
  Speaker 1: That's right so along the way the government says let's
• 40:02
  Speaker 1: give everyone that let's give everyone access to more stuff
• 40:05
  Speaker 1: to make up for that difference and then things get
• 40:07
  Speaker 1: more expensive.
• 40:08
  Speaker 2: Is this in part because when the nation becomes prosperous
• 40:11
  Speaker 2: because the gdp is high uh when you have four-year
• 40:14
  Speaker 2: election cycles politicians get in by offering you lots of
• 40:17
  Speaker 2: free stuff And that is the nature of the four-year
• 40:20
  Speaker 2: election cycle.
• 40:21
  Speaker 1: I always said the kid that got elected president in
• 40:23
  Speaker 1: middle school was the kid who said he's going to
• 40:25
  Speaker 1: make the vending machines free. That's always going to be
• 40:27
  Speaker 1: true in any election. And at the end of the day,
• 40:30
  Speaker 1: that's how the system grows.
• 40:31
  Speaker 2: We don't talk about this four-year election thing enough as
• 40:34
  Speaker 2: maybe it's being a bit of a causal factor that's
• 40:36
  Speaker 2: causing short-termism amongst these leaders where they're all just spending
• 40:40
  Speaker 2: more money to.
• 40:41
  Speaker 1: I cannot tell you how much it drives me nuts
• 40:43
  Speaker 1: when I go to Washington, D.C. And I go to Washington, D.C.
• 40:47
  Speaker 1: every couple of weeks or whatever.
• 40:48
  Speaker 2: And I.
• 40:49
  Speaker 1: meet with Congress people, senators and representatives, literally all of
• 40:54
  Speaker 1: them just talk about getting stuff for their constituents.
• 40:56
  Speaker 2: Yeah.
• 40:57
  Speaker 1: That's all that they're there to do. Just get stuff
• 41:00
  Speaker 1: for their people. That's their job. And that's how they
• 41:03
  Speaker 1: get elected. And the incentive is I'm going to get
• 41:06
  Speaker 1: you something vote for me. Now the founding fathers kind
• 41:10
  Speaker 1: of had this idea that they would rotate into public
• 41:13
  Speaker 1: service and rotate out and go back to private life.
• 41:15
  Speaker 1: There's a lot of writings about this, you know, in
• 41:17
  Speaker 1: the early days of the formation of this republic. And
• 41:20
  Speaker 1: it was like, we should all go do our tour
• 41:21
  Speaker 1: of duty. We should go in. There was never this
• 41:24
  Speaker 1: belief that America would evolve to a world where you
• 41:26
  Speaker 1: have career politicians, people that are just constantly trying to
• 41:29
  Speaker 1: get elected. And their job is to be a politician.
• 41:32
  Speaker 1: It's just such a mind-numbingly crazy idea to think about.
• 41:34
  Speaker 1: And all my politician friends are about to chop my
• 41:37
  Speaker 1: head off about this. But I think it's nuts. I
• 41:39
  Speaker 1: don't think a person should be a politician. I don't
• 41:42
  Speaker 1: think that job title should exist. And I'm sorry to
• 41:45
  Speaker 1: all the politicians out there. I think the people that
• 41:47
  Speaker 1: represent the people should have the best long-term interests of
• 41:50
  Speaker 1: the people in mind because they should be constrained to
• 41:53
  Speaker 1: serving for a limited period of time, and then they
• 41:55
  Speaker 1: go back to private life. That means that we should
• 41:57
  Speaker 1: have term limits. So you should never be able to
• 42:00
  Speaker 1: be elected more than two terms as a senator or
• 42:04
  Speaker 1: four terms as a representative or whatever it is. And
• 42:07
  Speaker 1: it should be the case that if you're in one
• 42:09
  Speaker 1: public office, maybe you shouldn't go transition to other public
• 42:11
  Speaker 1: offices under those same limits. Because at the end of
• 42:14
  Speaker 1: the day, you have created a system whereby you've proven
• 42:16
  Speaker 1: that you can get stuff for people and your job
• 42:18
  Speaker 1: is to go get stuff for people. And that causes
• 42:20
  Speaker 1: the government to inflate, be mismanaged, you know, and then
• 42:25
  Speaker 1: there's all the waste, fraud and abuse stuff that happens
• 42:27
  Speaker 1: along the way.
• 42:28
  Speaker 2: Everything is a trade-off, right? Even in that example, if
• 42:30
  Speaker 2: some people did eight years in government and they know
• 42:34
  Speaker 2: they're going back to private life, they could be dealing
• 42:37
  Speaker 2: their friends. I'm going to do eight years in government.
• 42:39
  Speaker 2: I'm going to run the transportation division. I'm going to
• 42:42
  Speaker 2: serve some nice benefits to my friend who runs Boeing.
• 42:45
  Speaker 2: And then when I step back in, I'm going to
• 42:46
  Speaker 2: step in as the chair.
• 42:47
  Speaker 1: That's a law to make sure that doesn't happen. And
• 42:49
  Speaker 1: he goes to jail if that happens. That's a pretty
• 42:51
  Speaker 1: easy fix. You can't buy stocks. You can't own stuff.
• 42:53
  Speaker 1: You can't trade. I mean, there's just so many obvious things.
• 42:56
  Speaker 1: If you're going to go serve in government, you can't
• 42:58
  Speaker 1: do stuff that you can do as a private citizen.
• 43:01
  Speaker 1: And you shouldn't be able to enrich yourself as a
• 43:02
  Speaker 1: private citizen. And if you do, you should go to jail.
• 43:04
  Speaker 1: But we should also make sure that the incentive structure
• 43:06
  Speaker 1: is set up right so that good people come and
• 43:07
  Speaker 1: work in government and that we have good rotation between
• 43:10
  Speaker 1: public and private life.
• 43:12
  Speaker 2: It's a hard problem, though, this problem of how you
• 43:14
  Speaker 2: fix this incentive structure so that you don't just get,
• 43:18
  Speaker 2: I mean, this stuff inevitably happens because we hand out
• 43:20
  Speaker 2: lots of free things and we don't think about the
• 43:22
  Speaker 2: long-term consequences. Has anyone fixed it globally? Is there any
• 43:25
  Speaker 2: nation you look at as a model for a better?
• 43:27
  Speaker 1: A lot of people will point to Denmark. They'll point
• 43:30
  Speaker 1: to places like that and say, hey, these guys do
• 43:32
  Speaker 1: a great job. And, you know, there's a lot of
• 43:34
  Speaker 1: public services and people pay high taxes. But, you know,
• 43:37
  Speaker 1: there's not a lot of great progress. There's no entrepreneurial
• 43:40
  Speaker 1: success coming out of those places. What happens in America,
• 43:44
  Speaker 1: the freedoms that were afforded, the individual agency and liberty
• 43:47
  Speaker 1: and rights to private property, creates an incentive structure that says,
• 43:51
  Speaker 1: go try and do crazy stuff that could work. And
• 43:54
  Speaker 1: if it works, there's tremendous return, so it's worth taking
• 43:57
  Speaker 1: the risk. And that level of risk is what pushes
• 44:00
  Speaker 1: the boundaries. It's what discovered CAR-T therapy, what discovered gene
• 44:04
  Speaker 1: editing that can lead to curing human diseases. It's what's
• 44:07
  Speaker 1: discovered new advances in agriculture, new physics, new engineering, A.I.,
• 44:12
  Speaker 1: All of these things came from this risk-taking system that
• 44:15
  Speaker 1: we've set up in the United States that's built around
• 44:17
  Speaker 1: these individual incentives. And it works. So you can have
• 44:21
  Speaker 1: great comfort for a great many people in Denmark. And
• 44:26
  Speaker 1: people will be very happy living there. And they will
• 44:28
  Speaker 1: have a good life. But you will not have progress
• 44:30
  Speaker 1: like you have in the United States. And we push
• 44:32
  Speaker 1: the frontier because we create this incentive structure. And that's
• 44:35
  Speaker 1: where progress comes from.
• 44:36
  Speaker 2: Would you say the vast majority would choose to live
• 44:38
  Speaker 2: in a place like Denmark if it, you know, I'm
• 44:42
  Speaker 2: looking at some of the stats here. They have higher
• 44:45
  Speaker 2: societal trust in government, police institutions and strangers. They have
• 44:49
  Speaker 2: standard 37 hour work weeks, five to six weeks of
• 44:53
  Speaker 2: paid vacation and cultural emphasis on balance. They have lower
• 44:56
  Speaker 2: ceiling of extreme wealth, but a higher floor, so less
• 44:59
  Speaker 2: poverty and financial ruin. And according to global happiness metrics,
• 45:02
  Speaker 2: Denmark consistently ranks significantly higher than the United States. Most
• 45:05
  Speaker 2: people would choose that, right? Absolutely. So central planning, it
• 45:09
  Speaker 2: might stop a few, you know, very high agency, ambitious people,
• 45:13
  Speaker 2: but the vast majority would theoretically be happier with a
• 45:16
  Speaker 2: Denmark model.
• 45:17
  Speaker 1: The vast majority may be.
• 45:18
  Speaker 2: And do you think the vast majority in this country
• 45:19
  Speaker 2: actually would, if there was two buttons and they had
• 45:22
  Speaker 2: to press, they'd press Denmark?
• 45:24
  Speaker 1: One of the things that I think makes American culture
• 45:26
  Speaker 1: different from Denmark is this idea of individual progress. So
• 45:31
  Speaker 1: I think if you ask the majority of people, you
• 45:33
  Speaker 1: can have that. but you don't get to progress. Meaning
• 45:37
  Speaker 1: you don't get to earn more next year and you
• 45:38
  Speaker 1: don't get to earn more next year. You don't have
• 45:40
  Speaker 1: a shot at becoming a millionaire. You don't have a
• 45:42
  Speaker 1: shot at building something great. You don't have a shot
• 45:45
  Speaker 1: at buying a second home. You're limited, but you get that.
• 45:49
  Speaker 1: Over here, you don't get anything guaranteed here. You get
• 45:52
  Speaker 1: some stuff guaranteed to you, but you don't get much
• 45:53
  Speaker 1: more guaranteed to you. But you could have the world.
• 45:58
  Speaker 1: You could make a million dollars. You could own a
• 46:00
  Speaker 1: second home. You could buy a second car. You could
• 46:02
  Speaker 1: pay off your kid's college tuition debt. if you earn well.
• 46:07
  Speaker 1: There's more options here. There's more guaranteed here.
• 46:10
  Speaker 2: You think the 63% would pick?
• 46:13
  Speaker 1: I think even within the 63%, there would be some
• 46:16
  Speaker 1: percent that would say this. But I do think this
• 46:18
  Speaker 1: is why we're headed the way we're headed in the
• 46:20
  Speaker 1: United States. People want more of a guarantee. The question is,
• 46:23
  Speaker 1: do you want to maximize the number of people that
• 46:25
  Speaker 1: are happy? Or do you want to maximize the number
• 46:28
  Speaker 1: of people that are truly free? And by being truly free,
• 46:33
  Speaker 1: increases the rate of progress across the whole population. And
• 46:36
  Speaker 1: that rate of progress may be asymmetric, it may be diffuse,
• 46:38
  Speaker 1: starts with some, makes its way to others over time.
• 46:43
  Speaker 1: I think that that's what America's chosen to be for
• 46:45
  Speaker 1: the last 250 years. I'm not sure we're choosing to
• 46:47
  Speaker 1: be that for the next 250 based on what's going
• 46:49
  Speaker 1: on across the country right now.
• 46:50
  Speaker 2: Maybe because people aren't happy. And actually, maybe that was
• 46:53
  Speaker 2: always the more important thing versus progress.
• 46:56
  Speaker 1: Important in an aggregate way. Again, I'll come back to
• 46:59
  Speaker 1: the individual. We choose to live in a society because
• 47:02
  Speaker 1: it gives us that foundation that you described, that ability
• 47:05
  Speaker 1: to have the safety, the security to take risk, to
• 47:09
  Speaker 1: make our own decisions and potentially build a media empire
• 47:13
  Speaker 1: as you have done. And maybe you would have been
• 47:15
  Speaker 1: happy in the other context where you didn't have that,
• 47:18
  Speaker 1: but would you have reached your potential as a human?
• 47:21
  Speaker 2: I'll be honest. I'm not sure I would have been
• 47:22
  Speaker 2: happy because again, that goes back to my own nature.
• 47:25
  Speaker 2: It's just the way that I am. If you put
• 47:26
  Speaker 2: me in a room, I'll try and create something and
• 47:28
  Speaker 2: build something. But I've come to learn with time that
• 47:31
  Speaker 2: not everybody has that bias or those desires. Not everybody
• 47:34
  Speaker 2: has that lower T trauma from their childhood of being
• 47:36
  Speaker 2: the only black kid in all white area and thinking
• 47:38
  Speaker 2: money was really important and it was freedom and it
• 47:39
  Speaker 2: was self-assertive. Not everybody has that. So I realized that
• 47:44
  Speaker 2: when I designed solutions, they shouldn't probably be designed for me.
• 47:46
  Speaker 2: It's taken me a long time to get to that
• 47:48
  Speaker 2: place because I was very much.
• 47:50
  Speaker 1: The challenge with America in this moment is can you
• 47:54
  Speaker 1: give what you're describing, the Denmark answer... to enough Americans
• 47:58
  Speaker 1: without taking away the liberty that the Americans that want
• 48:01
  Speaker 1: to have that liberty have today? And I'm not sure
• 48:04
  Speaker 1: the answer is yes. As soon as you start taking
• 48:06
  Speaker 1: private property from these people, the ones that are successful
• 48:09
  Speaker 1: in this bucket, then you're sort of taking away the
• 48:11
  Speaker 1: incentive for them to be in this bucket in America.
• 48:14
  Speaker 1: And I'm seeing that. I see people want to leave.
• 48:16
  Speaker 1: And so you're not going to solve for everyone. But
• 48:19
  Speaker 1: if you solve for this Denmark solution, I think you
• 48:22
  Speaker 1: lose a lot of this.
• 48:23
  Speaker 2: Well, the UK is quite an interesting example here for
• 48:26
  Speaker 2: this very reason. I mean, one of the big subjects
• 48:28
  Speaker 2: of conversation in the UK is that the millionaires are
• 48:31
  Speaker 2: all leaving, or at least in high volume, and they're
• 48:33
  Speaker 2: coming to other places. If you look at the millionaire
• 48:35
  Speaker 2: exists maps that they publish often, they're going to Dubai
• 48:38
  Speaker 2: or they're coming to America. A lot of my friends
• 48:40
  Speaker 2: that are building technical companies in particular have come over
• 48:43
  Speaker 2: to America.
• 48:44
  Speaker 1: Yeah.
• 48:44
  Speaker 2: For this reason.
• 48:45
  Speaker 3: Yeah.
• 48:46
  Speaker 2: And I do think we might have a little bit
• 48:48
  Speaker 2: of a, we have a bit of a spending problem,
• 48:49
  Speaker 2: it seems, but also I think we might have a
• 48:50
  Speaker 2: bit of a productivity problem.
• 48:52
  Speaker 1: In the UK.
• 48:53
  Speaker 2: In the UK. Yeah.
• 48:54
  Speaker 1: Well, do you think the productivity problem is related to
• 48:56
  Speaker 1: the spending problem?
• 48:58
  Speaker 2: Oh, yes, of course. Right.
• 48:59
  Speaker 1: If you're collecting checks or getting services provided to you,
• 49:03
  Speaker 1: the incentive to be more productive as an individual goes away.
• 49:07
  Speaker 1: But also as a system, it becomes a lot harder
• 49:10
  Speaker 1: to create economic incentives for productivity gains when tax rates
• 49:13
  Speaker 1: are very high and you don't actually get to reap
• 49:15
  Speaker 1: the benefits of the risk you take and and so
• 49:17
  Speaker 1: on that's the economic argument.
• 49:19
  Speaker 2: Listen i've been catfished by furniture my whole life where
• 49:22
  Speaker 2: something has looked fantastic in the picture whether it's a
• 49:24
  Speaker 2: sofa whatever it might be and i order it and
• 49:27
  Speaker 2: i get so excited and then it comes and it's
• 49:29
  Speaker 2: something entirely different the quality was significantly different to what
• 49:33
  Speaker 2: it said or looks like online or the the texture
• 49:36
  Speaker 2: was different or or it didn't hold up in the
• 49:39
  Speaker 2: same way. And so one of the things that I
• 49:41
  Speaker 2: love about our sponsor Wayfair, who have helped us fit
• 49:44
  Speaker 2: out our green room, which is in the room behind me,
• 49:46
  Speaker 2: is they have this system called Wayfair Verified. Wayfair Verified
• 49:50
  Speaker 2: takes away all of that second guessing. Products are hand
• 49:52
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• 49:56
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• 49:59
  Speaker 2: So if you're looking for furniture for your house, whatever
• 50:01
  Speaker 2: it might be, any room of your house, Go to wayfair.com
• 50:05
  Speaker 2: to start your home refresh today and make sure you
• 50:07
  Speaker 2: use Wayfair Verified. It is amazing. Hello, I wasn't able
• 50:12
  Speaker 2: to make that finance meeting. Can you tell me what
• 50:14
  Speaker 2: I missed? What I have in front of me is
• 50:16
  Speaker 2: Whisperflow's new note taker. And for me, it's been an
• 50:19
  Speaker 2: absolute game changer. I spend most of my life sat
• 50:21
  Speaker 2: in very, very long meetings with lots of different teams
• 50:23
  Speaker 2: and lots of different departments. In any given week, I
• 50:25
  Speaker 2: could have 40, 50 meetings and sometimes more. But also
• 50:29
  Speaker 2: I sit in podcasts where lots of very interesting things
• 50:31
  Speaker 2: get said. I need to focus on the conversation. What
• 50:34
  Speaker 2: Whisperflow's notetaker does for me is it captures the entire
• 50:37
  Speaker 2: context of everything that's happened throughout my entire week. It
• 50:40
  Speaker 2: labels who the people are that said what. And I
• 50:43
  Speaker 2: can ask it for things that I might have forgotten,
• 50:46
  Speaker 2: for actions, things that I said I would do that
• 50:48
  Speaker 2: I haven't yet done. It's building this sort of broader
• 50:51
  Speaker 2: context of everything that's happening in my life. And it's
• 50:54
  Speaker 2: an incredible, incredible superpower. I love the fact that so
• 50:56
  Speaker 2: many of you come up to me in the street
• 50:57
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• 50:59
  Speaker 2: me how much it's changed your life. It is the
• 51:01
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• 51:04
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• 51:08
  Speaker 2: it right now and give it a try. And once
• 51:09
  Speaker 2: you try it, I think you'll realize why we let
• 51:11
  Speaker 2: them sponsor this podcast. It's amazing. I mean, this kind
• 51:14
  Speaker 2: of does tie into the subject of artificial intelligence and
• 51:18
  Speaker 2: where it all fits, in part because the narrative of
• 51:21
  Speaker 2: artificial intelligence is that it's about to take our jobs.
• 51:24
  Speaker 2: And you think about that. That's why I wanted to
• 51:25
  Speaker 2: start with the backdrop. Think about that backdrop of I'm
• 51:28
  Speaker 2: already struggling. I'm in the 63%. And now you're telling
• 51:31
  Speaker 2: me I'm going to lose this fucking job that's paying me?
• 51:33
  Speaker 2: And I'm already living hand to mouth. And what's the offer?
• 51:36
  Speaker 2: We might get UBI. We might be sent checks in
• 51:39
  Speaker 2: the post at some point. Well, actually, I like my job.
• 51:41
  Speaker 2: It's a community, a sense of purpose. It gives me
• 51:43
  Speaker 2: something to do. And that's the narrative.
• 51:46
  Speaker 1: Yes, that is the narrative.
• 51:48
  Speaker 2: You don't believe the narrative.
• 51:50
  Speaker 1: I believe what everyone's feeling.
• 51:53
  Speaker 2: But this narrative that AI will take jobs away, you
• 51:56
  Speaker 2: don't believe it.
• 51:57
  Speaker 1: I recently pulled up and you guys can go to archive.org.
• 52:00
  Speaker 1: There's a Newsweek article about computers will take all the
• 52:03
  Speaker 1: jobs from 1963. So the mainframes are what got put
• 52:07
  Speaker 1: in the basement in the 60s. And everyone like had
• 52:09
  Speaker 1: to walk past the scary mainframe on the right. It's
• 52:12
  Speaker 1: like blinking lights and buzzing and making sounds. And it's
• 52:15
  Speaker 1: like the mainframe is going to destroy all the accountant jobs,
• 52:18
  Speaker 1: all the typing jobs, all these things that we all
• 52:20
  Speaker 1: do that we get paid to do. And I like
• 52:23
  Speaker 1: working in my office. I like my colleagues. I like
• 52:25
  Speaker 1: coming in every day, having lunch. That's a good life.
• 52:27
  Speaker 1: This mainframe is going to ruin my life. And so
• 52:29
  Speaker 1: there was this effort to legislate against these things at
• 52:32
  Speaker 1: the time that didn't get through in Congress. And then
• 52:34
  Speaker 1: in the 80s, there was another wave on computing where
• 52:37
  Speaker 1: it was like, hey, now we're all getting desktop computers.
• 52:39
  Speaker 1: It's going to replace the workers and it's going to
• 52:40
  Speaker 1: be a desktop computer and a worker and like 50
• 52:42
  Speaker 1: people disappear out of the workforce. So empirically, meaning from data,
• 52:46
  Speaker 1: from evidence, over all periods of technological revolution like this,
• 52:50
  Speaker 1: we've never seen jobs decline. We've always seen jobs go up.
• 52:55
  Speaker 1: And we've seen demand go up and therefore incomes rise
• 52:58
  Speaker 1: when new technology enters the workforce. That's because the new
• 53:01
  Speaker 1: technology makes an individual more productive so they can do
• 53:04
  Speaker 1: more per hour with their time. And as a result,
• 53:06
  Speaker 1: they can get paid more for doing that work. So
• 53:09
  Speaker 1: imagine instead of having a painter painting a wall, what
• 53:11
  Speaker 1: if he was in charge of the five robots that
• 53:13
  Speaker 1: are painting the wall? Okay, great. Now he's going to
• 53:15
  Speaker 1: get paid more because you can get so many more
• 53:18
  Speaker 1: homes painted in a day. He's going to get paid
• 53:20
  Speaker 1: more to do that work. People are going to be like, well,
• 53:22
  Speaker 1: there's only so many homes. That's always the argument is
• 53:23
  Speaker 1: you always think about The fixed pie argument that the
• 53:26
  Speaker 1: pie doesn't grow. But what always happens is that the
• 53:29
  Speaker 1: pie grows. The economy grows is the way to think
• 53:32
  Speaker 1: about it. And so as automation or technology is used
• 53:37
  Speaker 1: to give individuals more leverage to do more things with
• 53:40
  Speaker 1: their time, then more things get done. People come up
• 53:42
  Speaker 1: with these new product ideas. Hey, we've got excess capital.
• 53:46
  Speaker 1: Let's build new homes. Let's build a building.
• 53:48
  Speaker 2: But who gets, who benefits from the expansion of that pie?
• 53:50
  Speaker 1: In all cases, it's been, there's been deep economic value
• 53:54
  Speaker 1: created for the entire workforce all the way down to
• 53:56
  Speaker 1: the lowest level. It doesn't happen overnight. And that's where
• 54:00
  Speaker 1: during that period of time, when you see the new technologies, oh,
• 54:02
  Speaker 1: the mainframes in the basement or the desktop computers on
• 54:07
  Speaker 1: my colleague's desk. And you're like, oh my God, I'm
• 54:08
  Speaker 1: going to lose my job to the time that your
• 54:11
  Speaker 1: company is growing considerably their revenue and giving everyone raises
• 54:15
  Speaker 1: and everyone bonuses and adding more product lines and doing
• 54:18
  Speaker 1: more stuff you're like oh man okay I feel better
• 54:22
  Speaker 1: and I think that would be the argument from the
• 54:23
  Speaker 1: 60s and 80s and even back in the Industrial Revolution
• 54:26
  Speaker 1: but the question today is how does work change because
• 54:29
  Speaker 1: remember in the Industrial Revolution people moved from farms 60%
• 54:33
  Speaker 1: of labor was in farming today it's like 2% into
• 54:35
  Speaker 1: factories and And they got paid a lot more and
• 54:39
  Speaker 1: they lived a better life. They actually were able to
• 54:41
  Speaker 1: afford healthcare, yada, yada, yada. And the transition in any
• 54:45
  Speaker 1: sort of like technological revolution is net beneficial for all
• 54:50
  Speaker 1: parties involved, but there is a transition. So what's it
• 54:52
  Speaker 1: going to look like? Are we all going to lose
• 54:54
  Speaker 1: our jobs? AI is definitely different, but I don't think
• 54:59
  Speaker 1: that AI is this world where humans are going to
• 55:02
  Speaker 1: look around and be like, none of us have anything
• 55:04
  Speaker 1: to do anymore. Like, I don't believe in that narrative.
• 55:07
  Speaker 1: And the reason is I already see extraordinary creative things
• 55:11
  Speaker 1: being done with AI that were not possible years ago.
• 55:14
  Speaker 1: People are creating TV shows, one person, that they would
• 55:18
  Speaker 1: have needed a staff of 20 people to do. And
• 55:20
  Speaker 1: they can use AI to create AI-generated content and put
• 55:22
  Speaker 1: these shows out on YouTube or TikTok or Instagram. I mean, look,
• 55:26
  Speaker 1: you may not like how it looks today. There may
• 55:28
  Speaker 1: be a lot of AI slop out there. But as
• 55:29
  Speaker 1: this stuff gets better and better, the creative output of
• 55:32
  Speaker 1: people using AI on creative channels, where we're all consuming media,
• 55:36
  Speaker 1: It's only going to go up and people are going
• 55:38
  Speaker 1: to make money that they weren't able to make before
• 55:40
  Speaker 1: from that output as other people consume it. My ability
• 55:43
  Speaker 1: to do work, I don't have to, you know, think
• 55:45
  Speaker 1: about my, you know, four hours a day that I'm
• 55:48
  Speaker 1: writing documents today. I can get all that work done
• 55:50
  Speaker 1: in 10 minutes or 15 minutes. And then I can
• 55:52
  Speaker 1: spend the other three and a half hours doing other
• 55:54
  Speaker 1: things that create new value for my company.
• 55:56
  Speaker 2: If we go back to the top of this, the
• 55:58
  Speaker 2: robot painter analogy.
• 55:59
  Speaker 1: Yes.
• 56:00
  Speaker 2: You said a guy might have had five people painting.
• 56:02
  Speaker 2: Now they can have five robots painting.
• 56:04
  Speaker 1: No, I was saying the guy, instead of painting on
• 56:06
  Speaker 1: his own, he can now have five robots painting.
• 56:08
  Speaker 2: Yeah.
• 56:09
  Speaker 1: And then he can now produce five times as much
• 56:11
  Speaker 1: with his time. Think about what we saw with the
• 56:13
  Speaker 1: desktop computer revolution, right? Adobe Photoshop came around and everyone
• 56:16
  Speaker 1: was like, oh my God, like photographers are out of
• 56:19
  Speaker 1: work because a big part of being a photographer was
• 56:22
  Speaker 1: all the post editing and cleaning up and airbrushing and
• 56:24
  Speaker 1: all this sort of stuff. And they're like, that whole
• 56:25
  Speaker 1: industry is destroyed with Photoshop. What ended up happening is
• 56:28
  Speaker 1: a ton more media was created and print media was
• 56:30
  Speaker 1: created because Photoshop created leverage to create many more beautiful images.
• 56:34
  Speaker 1: And then all these magazines took off. And like, if
• 56:36
  Speaker 1: you look at magazine circulation, they grew considerably as Photoshop
• 56:39
  Speaker 1: came out, because it allowed much more production on, you know,
• 56:42
  Speaker 1: high value photography.
• 56:44
  Speaker 2: I think the reason why it feels different is because that's,
• 56:47
  Speaker 2: I mean, the industrial revolution example is kind of like
• 56:49
  Speaker 2: physical work moving to cognitive work. That was cognitive work
• 56:53
  Speaker 2: creating a new type of cognitive work, the Adobe analogy.
• 56:56
  Speaker 2: If AI takes the cognitive work, and from what you
• 56:58
  Speaker 2: said about robotics, robotics takes a lot of the physical work.
• 57:01
  Speaker 2: What is this third type of work?
• 57:03
  Speaker 1: I think it's cognitive and physical. It's no different than
• 57:06
  Speaker 1: what we've seen in the past, but it doesn't mean
• 57:08
  Speaker 1: that there isn't an individual who's going to program the
• 57:11
  Speaker 1: robot on what rooms to paint, how to paint them,
• 57:13
  Speaker 1: how to do the detailing correct. The homeowner doesn't have
• 57:16
  Speaker 1: the level of skill that the painter does, right? So
• 57:18
  Speaker 1: the painter- And AI couldn't do that. Maybe at some point.
• 57:21
  Speaker 1: I mean, you could make this argument on a continuum
• 57:23
  Speaker 1: where eventually everything, nothing exists. But along the way, there
• 57:27
  Speaker 1: are new things that are emerging. Think about going back
• 57:29
  Speaker 1: 50 years. There was no yoga instructor. There was no
• 57:33
  Speaker 1: dog walker. There was no Instagram influencer. There was no podcaster.
• 57:36
  Speaker 1: I mean, there's a million versions of new work that
• 57:39
  Speaker 1: emerged along the way as the internet took hold and
• 57:42
  Speaker 1: people could start to spend their time or market themselves
• 57:44
  Speaker 1: or market their capabilities in other ways. So I think
• 57:47
  Speaker 1: it's a pessimistic view to assume that robots replace all
• 57:51
  Speaker 1: humans and then humans have no logic, no agency, no
• 57:53
  Speaker 1: capacity for creative work anymore. I have an optimistic view
• 57:56
  Speaker 1: on this, which is that AI and robotics enables individuals
• 58:00
  Speaker 1: to to do far more things than they ever could
• 58:03
  Speaker 1: have contemplated. And that's going to give everyone much more
• 58:06
  Speaker 1: ability to realize their potential with their agency.
• 58:08
  Speaker 2: I mean, even the podcast, I think game is going
• 58:11
  Speaker 2: to be significantly disrupted in some part. We ran a
• 58:15
  Speaker 2: test a couple of years ago to figure out if
• 58:17
  Speaker 2: a synthesized voice of me could have the same average
• 58:19
  Speaker 2: view duration as me. And it was just me reading
• 58:24
  Speaker 2: out the stories of founders through history. So I did
• 58:26
  Speaker 2: like a Steve Jobs episode where it was my voice,
• 58:28
  Speaker 2: AI had written the script, AI had synthesized my voice,
• 58:30
  Speaker 2: so I had no involvement. And the amount of people
• 58:32
  Speaker 2: that got to the end was 40 to 50% of
• 58:34
  Speaker 2: an hour. And they knew it was AI because it
• 58:37
  Speaker 2: said at the top, this is an AI podcast. And
• 58:38
  Speaker 2: so I thought, okay, there is a lot of informational
• 58:40
  Speaker 2: part of what me and you do, where we're sharing
• 58:43
  Speaker 2: just in pure play information that will be taken away. However,
• 58:46
  Speaker 2: what I hear through listening to your answer about creators
• 58:49
  Speaker 2: and art is, You're saying that there will be this human,
• 58:51
  Speaker 2: sort of irreplaceably human component, yoga teachers. Yoga teachers aren't
• 58:55
  Speaker 2: telling you yoga. It's also community and gathering in real
• 58:57
  Speaker 2: life and being there amongst other people.
• 58:59
  Speaker 1: I think the IRL job world is going to explode.
• 59:03
  Speaker 1: And I think it's going to be extremely valuable. I
• 59:05
  Speaker 1: always had this view like, oh, coffee shops will be automated.
• 59:07
  Speaker 1: But I actually think the opposite is probably true. I
• 59:10
  Speaker 1: think there will be a premium on coffee shops. I'll
• 59:12
  Speaker 1: pay $ 40 for a latte because that human is making
• 59:16
  Speaker 1: the latte, and I get to go be with other humans.
• 59:19
  Speaker 1: I get to go to a workout class with humans.
• 59:21
  Speaker 1: I get to go spend time at a concert. I
• 59:23
  Speaker 1: get to go spend time at dinners. I think this event,
• 59:26
  Speaker 1: live space, experiential part of our world that we kind
• 59:29
  Speaker 1: of think about as luxury today, maybe it becomes more core.
• 59:33
  Speaker 1: Maybe it becomes more of how we spend our time.
• 59:36
  Speaker 1: Maybe we spend 30, 40% of our time in these
• 59:39
  Speaker 1: sorts of spaces and automation is generating income for us
• 59:42
  Speaker 1: and supporting us in whatever pursuit we're interested in in work.
• 59:47
  Speaker 1: And we spend far less time doing work and far
• 59:49
  Speaker 1: more time paying a premium in the economy, in the
• 59:51
  Speaker 1: live space economy.
• 59:52
  Speaker 2: It's hard, isn't it? Because we don't know what these
• 59:54
  Speaker 2: jobs are.
• 59:54
  Speaker 1: We just don't. And that's, I mean, imagine telling someone
• 59:57
  Speaker 1: that worked in a factory in 1923, that fast forward
• 1:00:02
  Speaker 1: a hundred years, there's going to be people making X
• 1:00:05
  Speaker 1: dollars as personal trainers, or there's someone that has a
• 1:00:09
  Speaker 1: job dog walking in their neighborhood. I don't know if
• 1:00:12
  Speaker 1: that would have been like grok fully.
• 1:00:14
  Speaker 2: But the pace of disruption here seems to be different
• 1:00:17
  Speaker 2: than like the industrial revolution is targeting cognitive work. It's
• 1:00:20
  Speaker 2: built on this platform called the internet, which has this.
• 1:00:22
  Speaker 1: I'm telling you, I just don't see it. I like
• 1:00:24
  Speaker 1: at my work, everyone's using AI and everyone's just doing more.
• 1:00:28
  Speaker 1: And then they ask for more employees. You can kind
• 1:00:30
  Speaker 1: of think about a business having two sides, revenue and costs.
• 1:00:34
  Speaker 1: Revenue is I'm making stuff and people are paying me
• 1:00:37
  Speaker 1: for the things I'm making or doing. Cost is how
• 1:00:40
  Speaker 1: am I operating the business? Like what am I spending?
• 1:00:42
  Speaker 1: And the argument has always been like, okay, you're going
• 1:00:45
  Speaker 1: to lose customer service reps. You're going to lose all
• 1:00:48
  Speaker 1: the cost side of the equation. No one ever says
• 1:00:50
  Speaker 1: you're going to lose the revenue side. The truth is
• 1:00:52
  Speaker 1: on the revenue side, what ends up happening is is
• 1:00:54
  Speaker 1: you create new products that you couldn't create before because
• 1:00:57
  Speaker 1: of AI. The technology enables so much advancement in your business.
• 1:01:00
  Speaker 1: Let's say you're a material science company. This is totally esoteric,
• 1:01:03
  Speaker 1: but like, let's say your job as a company is
• 1:01:06
  Speaker 1: to discover new materials, new synthetics that can be used
• 1:01:09
  Speaker 1: to make microchips or be used for computing or be
• 1:01:13
  Speaker 1: used for travel or for airplanes. The material science world
• 1:01:17
  Speaker 1: has been challenged by its experimental cycle. You got to
• 1:01:19
  Speaker 1: create an experiment, make a product, test it, do it
• 1:01:22
  Speaker 1: all manually. It's all creative ideas. It's all human potential.
• 1:01:25
  Speaker 1: AI can now screen through millions of material science ideas
• 1:01:29
  Speaker 1: in a computer, print them out, test them, and you
• 1:01:32
  Speaker 1: can automate that throughput. Therefore, that materials company can now
• 1:01:35
  Speaker 1: have more revenue. They can make more products.
• 1:01:37
  Speaker 2: Do you not think that maybe there's a possibility that
• 1:01:39
  Speaker 2: people like me and you exist in this particular band where,
• 1:01:43
  Speaker 2: because we're both founders and we have capital and we're
• 1:01:46
  Speaker 2: thinking about how to really push intelligence to create new
• 1:01:49
  Speaker 2: things and that maybe we, because what you're saying, I
• 1:01:52
  Speaker 2: can relate to. I can relate to the fact that
• 1:01:54
  Speaker 2: AI has made me actually quite, it's probably made me
• 1:01:56
  Speaker 2: more ambitious about hiring, especially in the near term. I
• 1:01:59
  Speaker 2: would caveat it by saying that there's a certain type
• 1:02:01
  Speaker 2: of role that I'm now hiring much less. And as,
• 1:02:07
  Speaker 2: especially when you think about entry-level roles, I have to
• 1:02:09
  Speaker 2: pause a lot more now because a lot of the
• 1:02:12
  Speaker 2: agents and some tooling can do some of those things
• 1:02:14
  Speaker 2: that I would have otherwise hired for. But generally, I
• 1:02:16
  Speaker 2: feel like I'm hiring as fast as I possibly can.
• 1:02:19
  Speaker 2: But would you not say that for like the 21-year-old
• 1:02:22
  Speaker 2: that's graduated from university or the DoorDash driver or those
• 1:02:26
  Speaker 2: types of individuals, whether the leap from where they currently
• 1:02:30
  Speaker 2: are on a factory floor assembling a part or flipping packages,
• 1:02:36
  Speaker 2: the leap from where they are to this new world
• 1:02:39
  Speaker 2: is so great that there's going to be this messy middle.
• 1:02:42
  Speaker 1: Yeah, what I'm saying is as new products are created,
• 1:02:44
  Speaker 1: new revenue comes in, you don't cut costs, you grow costs.
• 1:02:48
  Speaker 1: and you hire more people, and you up-level, and you
• 1:02:50
  Speaker 1: train people. That is what I'm seeing on the ground.
• 1:02:53
  Speaker 1: You know, we just published, I think, one of the
• 1:02:55
  Speaker 1: lowest unemployment rates in the U.S., and I think that
• 1:02:57
  Speaker 1: this idea that your current job is going to get
• 1:03:01
  Speaker 1: disrupted and you're going to lose your job, I don't
• 1:03:04
  Speaker 1: think is how the enterprise transitions. The enterprise transitions, meaning companies,
• 1:03:09
  Speaker 1: by doing more things and bringing people up the ladder,
• 1:03:13
  Speaker 1: hiring more people, and that's just what I'm seeing on
• 1:03:15
  Speaker 1: the ground. I think that there's a media narrative on like,
• 1:03:18
  Speaker 1: oh my God, there was a layoff at so-and-so company
• 1:03:20
  Speaker 1: because it underlines what they've been promoting to everyone, which
• 1:03:23
  Speaker 1: is AI is going to cause job loss.
• 1:03:25
  Speaker 2: The interesting thing is it didn't come from the media.
• 1:03:27
  Speaker 1: It came from the AI guys. Yeah.
• 1:03:29
  Speaker 2: Yeah. This is the biggest. I listen to it all
• 1:03:31
  Speaker 2: in podcasts. By the way, it's one of my favorite podcasts.
• 1:03:34
  Speaker 2: I don't think I've ever missed an episode. So I
• 1:03:35
  Speaker 2: very much understand your perspective and all of your.
• 1:03:37
  Speaker 1: I had no idea you were a fan.
• 1:03:38
  Speaker 2: No, no, I do. I've listened to it.
• 1:03:39
  Speaker 1: I've gone on people's shows where they're like, I don't
• 1:03:41
  Speaker 1: know who you are. And I'm like, it's good to
• 1:03:43
  Speaker 1: meet you.
• 1:03:44
  Speaker 2: No, no, no. I don't think I've ever missed an
• 1:03:45
  Speaker 2: episode since the beginning. So I understand your perspective.
• 1:03:48
  Speaker 1: You've heard all this.
• 1:03:49
  Speaker 2: I've heard all of this. And I've heard Jason's opinion. Weirdly,
• 1:03:52
  Speaker 2: I tend to side a little bit more with Jason
• 1:03:54
  Speaker 2: on this. Because I think Jason... I don't know why
• 1:03:57
  Speaker 2: his arguments seem to present the most nuance. And also,
• 1:04:00
  Speaker 2: I would say, when we think about different people's incentives... Yeah,
• 1:04:03
  Speaker 2: you're right. Often on that show... It's framed as a
• 1:04:07
  Speaker 2: media narrative, whereas it's actually all your friends.
• 1:04:10
  Speaker 1: Yeah.
• 1:04:10
  Speaker 2: No.
• 1:04:10
  Speaker 1: So first of all, none of them are my friends.
• 1:04:13
  Speaker 2: Elon's your friend. Okay.
• 1:04:14
  Speaker 1: So what I will say, like I've said this on
• 1:04:17
  Speaker 1: the show, I'll say it again. I think there is
• 1:04:19
  Speaker 1: a deep arrogance in making these sorts of proclamations.
• 1:04:24
  Speaker 2: Which proclamations?
• 1:04:25
  Speaker 1: That we're not going to work anymore. It effectively discounts
• 1:04:28
  Speaker 1: the human. It's like what you do today is your limit.
• 1:04:33
  Speaker 1: But I think that this idea that like these jobs
• 1:04:35
  Speaker 1: will go away is sourced by people that are seeing
• 1:04:38
  Speaker 1: the crazy stuff that they're doing. And they're like, oh,
• 1:04:40
  Speaker 1: my God, this is amazing. I'm responsible for this. We
• 1:04:45
  Speaker 1: are going to change the world. We are going to
• 1:04:46
  Speaker 1: take all jobs and they're all going to sit in
• 1:04:47
  Speaker 1: my computer. I don't think that that's what happens because
• 1:04:51
  Speaker 1: I think that humans have a profound capacity for doing
• 1:04:55
  Speaker 1: things that, you know, these technologists don't necessarily see. The
• 1:04:59
  Speaker 1: great technologists see technology. They don't see people. I think
• 1:05:04
  Speaker 1: you have to see people, meaning the potential of people,
• 1:05:08
  Speaker 1: of individuals. And you have to believe in that. They
• 1:05:11
  Speaker 1: believe in technology, they engineer technology. But I am not
• 1:05:14
  Speaker 1: going to be pessimistic about people. I think that people
• 1:05:18
  Speaker 1: have capacity in any environment. I mean, the amazing thing
• 1:05:22
  Speaker 1: about humans is our adaptability. We can live in any climate.
• 1:05:24
  Speaker 1: We can eat any kind of food. I mean, we
• 1:05:26
  Speaker 1: can work all these different jobs. I Arguably, many humans
• 1:05:33
  Speaker 1: have been limited in their potential. And I think that
• 1:05:35
  Speaker 1: AI enables more capacity for those individuals to realize more
• 1:05:39
  Speaker 1: of their potential.
• 1:05:40
  Speaker 2: Much of the conversation we've had about the US economy
• 1:05:42
  Speaker 2: has centered around incentive structures leading to inevitable outcomes. You know,
• 1:05:46
  Speaker 2: the older I've gotten, the more I just try and
• 1:05:47
  Speaker 2: look at incentives to figure out behavior and also to
• 1:05:50
  Speaker 2: figure out who to trust. So when I look at
• 1:05:53
  Speaker 2: the incentives of the people that are building the AI companies,
• 1:05:56
  Speaker 2: Andy Jassy has said that there's going to be fewer
• 1:05:59
  Speaker 2: people doing some of the jobs that are being done today.
• 1:06:03
  Speaker 2: Then they cut, you know, tens of thousands of jobs.
• 1:06:04
  Speaker 2: Mark Benioff, who I know has been on your show,
• 1:06:06
  Speaker 2: cut 4,000 jobs and said, I need less heads because
• 1:06:09
  Speaker 2: of AI. And I was like, okay, maybe they're saying
• 1:06:11
  Speaker 2: that because they want their share price to go up
• 1:06:13
  Speaker 2: because it's a good, you know, we're going to reduce
• 1:06:14
  Speaker 2: costs as a good narrative. But then I look at
• 1:06:16
  Speaker 2: the other, the AI CEOs, Dario, Elon, Sam Altman, and
• 1:06:21
  Speaker 2: I go, their incentives, I'd say other than the exception
• 1:06:25
  Speaker 2: of Elon, have just kind of changed with whatever's good
• 1:06:28
  Speaker 2: for them at that moment, oftentimes. I actually, I think
• 1:06:31
  Speaker 2: Dario might be the exception a little bit, because he
• 1:06:34
  Speaker 2: seems to be a bit more nuanced. If I go
• 1:06:37
  Speaker 2: back through the quotes of these individuals, you have Sal
• 1:06:41
  Speaker 2: Montman in February 2015 saying, development of super machine intelligence
• 1:06:44
  Speaker 2: is probably the greatest threat to the continued existence of humanity.
• 1:06:48
  Speaker 2: You have Elon in 2014 saying, with artificial intelligence, we
• 1:06:51
  Speaker 2: are summoning the demon. It's far more dangerous than nukes.
• 1:06:56
  Speaker 2: mitigating the risk of extinction from AI should be a
• 1:06:58
  Speaker 2: global priority alongside societal scale risks, such as pandemics and
• 1:07:02
  Speaker 2: nuclear wars. And that was signed by Sam Altman, Demis, Dario,
• 1:07:06
  Speaker 2: Bill Gates, amongst many hundreds of others. Sam Altman in
• 1:07:10
  Speaker 2: the Senate in 2023. I think if this technology goes wrong,
• 1:07:13
  Speaker 2: it can go very wrong. OpenAI, super intelligence letter they wrote.
• 1:07:18
  Speaker 2: The disempowerment of humanity or even human extinction could be
• 1:07:22
  Speaker 2: caused by super intelligence. Again, in the athletic Sam Altman.
• 1:07:25
  Speaker 2: Jobs are definitely going to go away. Full stop. Barry Armaday,
• 1:07:31
  Speaker 2: May 2025, he predicted a white-collar bloodbath, half of entry-level
• 1:07:35
  Speaker 2: white-collar jobs gone, unemployment at 10% to 20% within one
• 1:07:38
  Speaker 2: to five years.
• 1:07:39
  Speaker 1: 10% to 20% unemployment in one to five years. It's
• 1:07:43
  Speaker 1: pretty high.
• 1:07:44
  Speaker 2: And Altman at the Federal Reserve in July 2025 said,
• 1:07:47
  Speaker 2: whole job categories will disappear, customer support first. That one is, quote, totally,
• 1:07:51
  Speaker 2: totally gone. And then suddenly the message changed. Before his
• 1:07:55
  Speaker 2: sort of pre-IPO discussions, he said things could go pretty wrong.
• 1:07:57
  Speaker 2: And then he says that he now has changed his
• 1:08:00
  Speaker 2: mind and he's delighted that he feels like he was wrong.
• 1:08:03
  Speaker 2: And suddenly he's talking about how OpenAI and ChatGPT will
• 1:08:06
  Speaker 2: benefit all of humanity.
• 1:08:07
  Speaker 1: And that's their goal.
• 1:08:08
  Speaker 2: Should we trust the same people that told us to
• 1:08:10
  Speaker 2: be scared when they say don't be scared?
• 1:08:13
  Speaker 1: First of all, I think there was a bunch of
• 1:08:15
  Speaker 1: companies that said early on, That they were like cutting
• 1:08:20
  Speaker 1: all their customer service reps. Which was the big company?
• 1:08:22
  Speaker 1: Starts with a K.
• 1:08:23
  Speaker 2: Klana. But I did call the founder.
• 1:08:25
  Speaker 1: And what'd you find out?
• 1:08:27
  Speaker 2: He said that he's been misinterpreted in the press. I
• 1:08:28
  Speaker 2: heard you guys talk about this in the All In podcast,
• 1:08:30
  Speaker 2: but I've actually called him live on this show.
• 1:08:32
  Speaker 1: And did he re-hire or like, what did he do?
• 1:08:34
  Speaker 2: He said that the media just completely misconstrued what he said.
• 1:08:37
  Speaker 1: Initially or later?
• 1:08:37
  Speaker 2: He said he had 7,000 employees. By the end of
• 1:08:40
  Speaker 2: last summer, he said he'd be on 3,000. But the
• 1:08:42
  Speaker 2: media framed it as, I had 7,000 employees... And then
• 1:08:45
  Speaker 2: I tried to cut some, I realized I couldn't and
• 1:08:47
  Speaker 2: I went back. That's not what happened. And it's just,
• 1:08:49
  Speaker 2: I see it on all these podcasts and just repeating it.
• 1:08:51
  Speaker 2: I heard it repeat on your show.
• 1:08:52
  Speaker 1: Like, but he said we are cutting because of AI. Yeah.
• 1:08:55
  Speaker 1: And he's confirmed that he's doing that.
• 1:08:57
  Speaker 2: He's DM'd me on X.
• 1:08:58
  Speaker 1: I've got the DM.
• 1:08:59
  Speaker 2: And live on this show, he confirmed it to all
• 1:09:01
  Speaker 2: of our listeners.
• 1:09:01
  Speaker 1: And is his business still growing?
• 1:09:03
  Speaker 2: The business is growing. What he did say, and this
• 1:09:05
  Speaker 2: is a point of nuance, is with the cost savings,
• 1:09:08
  Speaker 2: he's able to offer better white glove services to his
• 1:09:10
  Speaker 2: highest ticket clients.
• 1:09:11
  Speaker 1: Right.
• 1:09:12
  Speaker 2: Which makes a lot of sense.
• 1:09:13
  Speaker 1: Yes. And you could think about that analogy being in
• 1:09:16
  Speaker 1: another business where they would take that capital, invest in
• 1:09:19
  Speaker 1: offering new products, new services, but then you need employees
• 1:09:22
  Speaker 1: to offer those new products and new services. And so
• 1:09:25
  Speaker 1: you do actually hire up. And I think that is
• 1:09:27
  Speaker 1: what I am actually seeing on the ground. And while
• 1:09:29
  Speaker 1: he may have this acute restructuring he's doing, on the ground,
• 1:09:33
  Speaker 1: I just see people hiring more because they can do
• 1:09:36
  Speaker 1: more with AI. It's counterintuitive, but if you're a business manager,
• 1:09:40
  Speaker 1: you can invest $ 10 and make one product a year,
• 1:09:44
  Speaker 1: or you can invest $ 20 and make five products a year.
• 1:09:47
  Speaker 1: You're going to invest the $ 20 to make five products
• 1:09:49
  Speaker 1: a year. You're going to spend more. And I think
• 1:09:51
  Speaker 1: that's what AI does. As soon as you have the
• 1:09:53
  Speaker 1: ability to get leverage on how much more productive people are,
• 1:09:57
  Speaker 1: you'll put more capital towards hiring more people and scale up.
• 1:10:00
  Speaker 1: That's just what I'm seeing. And look, I could be
• 1:10:02
  Speaker 1: wrong and all jobs go away in five years and
• 1:10:04
  Speaker 1: we have 20% unemployment. I don't think that that's the case.
• 1:10:08
  Speaker 1: I think that, again, we can go back to this
• 1:10:11
  Speaker 1: where people are going to be spending their time. I
• 1:10:13
  Speaker 1: do think that there's going to be a big growth
• 1:10:15
  Speaker 1: in media. I think there's going to be a big
• 1:10:17
  Speaker 1: growth in media encompassing everything, digital content creation, et cetera.
• 1:10:21
  Speaker 1: I think there's going to be a big growth in entrepreneurship,
• 1:10:24
  Speaker 1: and I think there's going to be a big growth
• 1:10:25
  Speaker 1: in IRL stuff.
• 1:10:27
  Speaker 2: I'll play this interviews, and Klan has always mentioned, because
• 1:10:30
  Speaker 2: I think the media has said that you double down
• 1:10:32
  Speaker 2: on AI, then you reverse because it didn't work out.
• 1:10:35
  Speaker 2: So I know I spoke to you a while ago,
• 1:10:36
  Speaker 2: and we exchanged a couple of DMs about it, but
• 1:10:38
  Speaker 2: that was almost a year ago now. So I just
• 1:10:41
  Speaker 2: wanted to get an update on Klarna's business, AI agents,
• 1:10:44
  Speaker 2: and all of that, if possible. This was five months ago.
• 1:10:47
  Speaker 1: First and foremost, we.
• 1:10:47
  Speaker 3: Were early on released AI to support our customer service,
• 1:10:52
  Speaker 3: which had that initial benefit of more calls being dealt
• 1:10:58
  Speaker 3: with by AI, which customers liked because those calls or
• 1:11:01
  Speaker 3: chat messages were much, much better. faster and more qualitative.
• 1:11:05
  Speaker 3: Then since then, that has actually expanded slightly. What we did, however,
• 1:11:09
  Speaker 3: try to communicate as well is that we believed in
• 1:11:12
  Speaker 3: a world where AI is cheap and available, the value
• 1:11:16
  Speaker 3: of human interaction will be regarded as higher. So the
• 1:11:20
  Speaker 3: future of customer service VIP is a human. We have
• 1:11:24
  Speaker 3: then hence doubled down on providing more of that. But
• 1:11:27
  Speaker 3: at the same time, the efficiency gains within the company
• 1:11:31
  Speaker 3: has continued. I mean, we used to be about 6,000 people,
• 1:11:35
  Speaker 3: and now we are less than 3,000, which is two,
• 1:11:38
  Speaker 3: three years since we stopped recruiting. And at the same time,
• 1:11:42
  Speaker 3: our revenue has doubled, right?
• 1:11:44
  Speaker 1: No. This is a startup, just to be clear. I
• 1:11:48
  Speaker 1: don't know if we can, and again, I'm not going
• 1:11:51
  Speaker 1: to sit here and concede or argue jobs aren't going
• 1:11:53
  Speaker 1: to change, but a startup that grew very quickly and
• 1:11:56
  Speaker 1: then cut heads is a pretty common phenomenon. So I
• 1:12:00
  Speaker 1: don't know how much restructuring he was doing in his
• 1:12:03
  Speaker 1: AI-ification of his business. That's totally fine and totally fair.
• 1:12:07
  Speaker 1: But the question is, what are the people that were
• 1:12:09
  Speaker 1: doing customer service calls and sitting, you know, how many
• 1:12:12
  Speaker 1: of them were actually fully occupied on the phone? I
• 1:12:14
  Speaker 1: don't know. Like, were they on the phone for four
• 1:12:16
  Speaker 1: hours a day, two hours a day, or eight hours
• 1:12:18
  Speaker 1: a day? Were they actually fully employed? Really? Were they
• 1:12:21
  Speaker 1: truly fully employed? I don't know.
• 1:12:23
  Speaker 2: And what are they doing now? And is whatever they're
• 1:12:25
  Speaker 2: doing now, is that defensible again from this spread of
• 1:12:29
  Speaker 2: intelligence yeah because they could be door dash I don't
• 1:12:31
  Speaker 2: know they could be lawyers but they could also be
• 1:12:33
  Speaker 2: doing door dash and Dara sat here and said that
• 1:12:35
  Speaker 2: the 9,000 people that are riders won't have jobs.
• 1:12:39
  Speaker 1: The ones that are driving food around yeah and drivers
• 1:12:41
  Speaker 1: yeah yeah.
• 1:12:42
  Speaker 2: That's obviously all their big investments I was with him
• 1:12:43
  Speaker 2: the other day and he was talking about their autonomous
• 1:12:46
  Speaker 2: vehicle investments yeah and how I mean that's the big
• 1:12:49
  Speaker 2: what does he think He thinks that those drivers will
• 1:12:52
  Speaker 2: have to go, will do something else.
• 1:12:53
  Speaker 1: What does he think that something else is?
• 1:12:55
  Speaker 2: He loosely hypothesized. Well, it might be, it could be
• 1:12:58
  Speaker 2: data labeling.
• 1:12:59
  Speaker 1: Now, let me just go back because your whole point
• 1:13:02
  Speaker 1: about like AI is going to destroy us all. And
• 1:13:03
  Speaker 1: these guys were making all these claims and then they
• 1:13:05
  Speaker 1: all kind of backtracked. I think there's an important question
• 1:13:07
  Speaker 1: to ask, which is like, should we stop AI development?
• 1:13:10
  Speaker 1: And can we? Meaning, can we really affect what China does?
• 1:13:14
  Speaker 1: Can we really affect what Europe does? Can we really
• 1:13:15
  Speaker 1: affect what some lab in Indonesia does if they get
• 1:13:18
  Speaker 1: a group of people together? There are moments in human
• 1:13:21
  Speaker 1: history when technology advances and it's not like you can
• 1:13:24
  Speaker 1: just put the catapult away and be like, no one
• 1:13:26
  Speaker 1: can develop the catapult anymore. Once the catapult's out there,
• 1:13:29
  Speaker 1: the catapult's out there. We're just there. So the question is,
• 1:13:35
  Speaker 1: what is going to enable the most kind of productive
• 1:13:38
  Speaker 1: path forward for U.S. policy for U.S. citizens? And China's
• 1:13:43
  Speaker 1: asking themselves the same question. What's the most productive path forward?
• 1:13:46
  Speaker 1: China policy for China citizens. China's answer, I think, is
• 1:13:50
  Speaker 1: to make models free and ubiquitous, which, by the way,
• 1:13:53
  Speaker 1: benefits a large part of the global economy. But it
• 1:13:56
  Speaker 1: doesn't do very well with Sam Altman, Dario, Google, or
• 1:14:00
  Speaker 1: others that have invested billions or hundreds of billions of
• 1:14:02
  Speaker 1: dollars in model development. And now those investments that they've
• 1:14:05
  Speaker 1: made have been reduced to rubble because China's got a
• 1:14:09
  Speaker 1: model that's as good or cheaper. So I think the
• 1:14:11
  Speaker 1: more important question is, is, like, what does the U.S.
• 1:14:14
  Speaker 1: do to navigate? If we stop data centers, those data
• 1:14:16
  Speaker 1: centers are going to be built somewhere else. They'll be
• 1:14:18
  Speaker 1: built in Iceland. They'll be built in China. They'll be
• 1:14:21
  Speaker 1: built in Indonesia. They'll be built in places where you
• 1:14:23
  Speaker 1: can get access to energy and plug them into the Internet,
• 1:14:25
  Speaker 1: and now they're on the Internet. So do we want
• 1:14:27
  Speaker 1: those data centers to exist in the U.S. because they're
• 1:14:30
  Speaker 1: going to create jobs and create economic value, or do
• 1:14:33
  Speaker 1: we want them to be built offshore? Do we want
• 1:14:35
  Speaker 1: to have the AI models built in the U.S., or
• 1:14:37
  Speaker 1: do we want to have them built by China? Those are,
• 1:14:40
  Speaker 1: I think, the important policy decisions. The idea that you
• 1:14:42
  Speaker 1: can slow or stop AI development, I unfortunately think at
• 1:14:46
  Speaker 1: this moment, it's too far too late. Like the AI
• 1:14:49
  Speaker 1: is out there. The framing on is it bad or
• 1:14:53
  Speaker 1: is it good, I think requires observation on what's going
• 1:14:59
  Speaker 1: on on the ground. And I do think there's a
• 1:15:01
  Speaker 1: ton of stories. I mean, look at the number of
• 1:15:03
  Speaker 1: companies that are doing stuff that you could never do
• 1:15:05
  Speaker 1: before because of AI. I mean, just to get into
• 1:15:08
  Speaker 1: your point about delivery. I mean, there are delivery companies
• 1:15:11
  Speaker 1: delivering robots on the ground, robotic cars, drones, those companies
• 1:15:16
  Speaker 1: aren't employee lists. There's now 15,000 new jobs being created
• 1:15:20
  Speaker 1: at the factory that's making the robots or 15,000 jobs
• 1:15:23
  Speaker 1: to service the robots because they're breaking down all the time,
• 1:15:26
  Speaker 1: or 15,000 jobs to get the food made that goes
• 1:15:29
  Speaker 1: into the robots, or maybe that gets automated. But like,
• 1:15:31
  Speaker 1: as you kind of think about the impact, the economy
• 1:15:33
  Speaker 1: doesn't just shrink in terms of jobs. We're just not
• 1:15:36
  Speaker 1: seeing it in the data. It's not happening. And when
• 1:15:39
  Speaker 1: it does happen, I think that's a good time to
• 1:15:42
  Speaker 1: have a conversation about AI taxes and all this sort
• 1:15:44
  Speaker 1: of stuff.
• 1:15:44
  Speaker 2: Okay, so let's ask that question. And what would have
• 1:15:46
  Speaker 2: to happen? What sort of metrical piece of evidence?
• 1:15:49
  Speaker 1: Job loss.
• 1:15:50
  Speaker 2: Job loss.
• 1:15:50
  Speaker 1: Yeah, and wage growth, right? So if wages are declining
• 1:15:53
  Speaker 1: and unemployment is climbing, that's a red flag. I mean,
• 1:15:59
  Speaker 1: that's an alert moment. And that's when we have to
• 1:16:01
  Speaker 1: address this from policy. But it's very speculative right now.
• 1:16:05
  Speaker 1: And if you get in the way and you stop
• 1:16:06
  Speaker 1: it and you stop advancement or like the ability to
• 1:16:09
  Speaker 1: create higher paying jobs, the ability to create new jobs,
• 1:16:12
  Speaker 1: and you turn it, you turn all of that off,
• 1:16:14
  Speaker 1: it's going to happen in China, it's going to happen
• 1:16:16
  Speaker 1: in Europe, it's going to happen in South America, and
• 1:16:18
  Speaker 1: the US gets left behind. Maybe that's the decision that,
• 1:16:21
  Speaker 1: you know, we decide to make. But I would argue
• 1:16:24
  Speaker 1: that this kind of tracking of what's the consequence that
• 1:16:27
  Speaker 1: we're worried about is the most important thing to be
• 1:16:28
  Speaker 1: doing at the moment.
• 1:16:30
  Speaker 2: You might have heard about the study that, I think
• 1:16:31
  Speaker 2: it was Stanford that did it, and they showed that
• 1:16:32
  Speaker 2: there was a 13% relative decline in employment for workers
• 1:16:36
  Speaker 2: aged 22 to 25 in roles most exposed to generative AI.
• 1:16:40
  Speaker 2: Could it be that by the time we start seeing
• 1:16:44
  Speaker 2: significant job loss, it's a little bit too late to
• 1:16:46
  Speaker 2: be having the conversation because it could be quite a
• 1:16:48
  Speaker 2: rapid decline? If you think about the nature of this
• 1:16:50
  Speaker 2: technology and the adoption of it.
• 1:16:51
  Speaker 1: No, no, I think what you're describing is exactly the
• 1:16:53
  Speaker 1: right time.
• 1:16:54
  Speaker 2: When we see the first sign.
• 1:16:56
  Speaker 1: Yeah, so what are those changes that are happening? Now,
• 1:16:57
  Speaker 1: the question is, if you dig into that, And I
• 1:17:00
  Speaker 1: do understand this. Like in software engineering, what's happening right
• 1:17:03
  Speaker 1: now is young people are not getting hired. You can
• 1:17:06
  Speaker 1: use AI to write a lot of code. But in
• 1:17:09
  Speaker 1: order to be really good at using AI to write
• 1:17:11
  Speaker 1: a lot of code, you got to have experience writing code. Yeah.
• 1:17:15
  Speaker 1: And so there's a fight for senior experienced software engineers.
• 1:17:20
  Speaker 1: And there's disinterest in junior software engineers because you're not
• 1:17:23
  Speaker 1: just putting a junior software engineer in a seat to
• 1:17:25
  Speaker 1: have them write their first line of code, which is
• 1:17:27
  Speaker 1: what you used to do. With AI, you can turn
• 1:17:30
  Speaker 1: one engineer into 100, but the junior guy is not
• 1:17:32
  Speaker 1: going to do that. The senior person is. So you
• 1:17:35
  Speaker 1: want to hire more senior people, and that's what's happening
• 1:17:37
  Speaker 1: in software across the board right now.
• 1:17:39
  Speaker 2: But more of the operational functions that used to be
• 1:17:42
  Speaker 2: done by people are also just being done by software.
• 1:17:45
  Speaker 2: So if I think about, you might have had a
• 1:17:47
  Speaker 2: PA whose job was to respond to your emails and
• 1:17:49
  Speaker 2: check your emails and organize them and put them in
• 1:17:51
  Speaker 2: your Monday board. Now with agents, I have an agent
• 1:17:54
  Speaker 2: that goes across all of my inboxes every single day,
• 1:17:56
  Speaker 2: pulls everything into this central system. And I used to
• 1:17:59
  Speaker 2: have someone doing that kind of work. Now it's a
• 1:18:00
  Speaker 2: software job. Now it's Claude doing it.
• 1:18:01
  Speaker 1: So now the PA can use Claude to do it.
• 1:18:04
  Speaker 2: I don't need the PA. I can just do it myself. Okay.
• 1:18:06
  Speaker 1: What else could you use that PA for in your
• 1:18:07
  Speaker 1: life that you couldn't even contemplate using that PA for
• 1:18:09
  Speaker 1: in the past?
• 1:18:10
  Speaker 2: At the moment, it's real world stuff. I probably would
• 1:18:13
  Speaker 2: have continued to hire more in that team, but now
• 1:18:16
  Speaker 2: I don't need to because I've got this agent that
• 1:18:19
  Speaker 2: does my scheduling, can help me with my scheduling.
• 1:18:21
  Speaker 1: What are you going to do with the money you have,
• 1:18:22
  Speaker 1: the extra money you have that you're not spending?
• 1:18:23
  Speaker 2: This is a good point.
• 1:18:24
  Speaker 1: And then that money you're investing, you're not going to
• 1:18:26
  Speaker 1: just put that money in the bank and leave it
• 1:18:28
  Speaker 1: as cash you're going to invest it in something.
• 1:18:30
  Speaker 2: I can invest it in assets and.
• 1:18:32
  Speaker 1: What's an asset it's either productive or non-productive asset if
• 1:18:34
  Speaker 1: it's productive it's employing someone it's doing stuff.
• 1:18:36
  Speaker 2: I could but i could theoretically go buy the s
• 1:18:39
  Speaker 2: & p.
• 1:18:39
  Speaker 1: 500 and when you buy the s & p 500
• 1:18:40
  Speaker 1: that money goes to individuals that are now going to
• 1:18:43
  Speaker 1: be able to employ more people that capital finds a
• 1:18:46
  Speaker 1: way to get spent it goes into the economy and
• 1:18:49
  Speaker 1: that's my point This is why economies grow when technology
• 1:18:52
  Speaker 1: shows up. The leverage you got gave you more capital.
• 1:18:55
  Speaker 1: You could either build a new product and hire more
• 1:18:57
  Speaker 1: people to do it here, or you could choose to
• 1:18:58
  Speaker 1: go buy the S & P. But when you buy
• 1:19:00
  Speaker 1: the S & P, that money ends up in other
• 1:19:01
  Speaker 1: people's coffers, and they're using that money to hire people
• 1:19:04
  Speaker 1: and do new stuff. At some point, the whole point
• 1:19:06
  Speaker 1: of the economy is that money flows. And that money
• 1:19:09
  Speaker 1: is going to ultimately flow into individuals that are productive.
• 1:19:12
  Speaker 2: Do you not think a lot of it's going to
• 1:19:13
  Speaker 2: flow disproportionately into the billionaires and the most wealthy that
• 1:19:16
  Speaker 2: are building the robots?
• 1:19:18
  Speaker 1: I am a huge advocate for open source for this reason.
• 1:19:20
  Speaker 2: Open source. What does that mean for Janet and Dave
• 1:19:22
  Speaker 2: who might not know what that term means?
• 1:19:24
  Speaker 1: So open source just means the software is free for
• 1:19:28
  Speaker 1: anyone to use. If you go back to the early
• 1:19:30
  Speaker 1: days of the internet, Netscape made server software and Netscape
• 1:19:34
  Speaker 1: made a browser. So in order to produce a website,
• 1:19:37
  Speaker 1: you needed to pay for Netscape software. And you installed
• 1:19:40
  Speaker 1: it on a server, and you pay Netscape a fee
• 1:19:43
  Speaker 1: for that software. And then you could create a website. Okay.
• 1:19:46
  Speaker 1: And then if you want to browse the internet, you
• 1:19:47
  Speaker 1: got to pay for Netscape Navigator. And then you use
• 1:19:50
  Speaker 1: that navigator to browse the internet. So charge chart, gatekeeper, gatekeeper.
• 1:19:55
  Speaker 1: And guess what came along? The Mozilla Foundation made an
• 1:19:58
  Speaker 1: open source browser called Firefox. And the Apache Foundation came
• 1:20:02
  Speaker 1: along and made an open source web server. And now
• 1:20:05
  Speaker 1: anyone could download Apache and make their own website and
• 1:20:08
  Speaker 1: plug it into the internet and it would be available
• 1:20:10
  Speaker 1: to everyone in the world for free. And anyone could
• 1:20:13
  Speaker 1: download Firefox, go on their computer and browse the internet
• 1:20:17
  Speaker 1: for free. Open source then enabled all the entrepreneurs that
• 1:20:21
  Speaker 1: built websites that made money to proliferate. They weren't gatekept.
• 1:20:25
  Speaker 1: In the idea of AI, open weight models, open source
• 1:20:28
  Speaker 1: models are free. So now you don't have to go
• 1:20:31
  Speaker 1: pay Anthropic or Claude or Gemini or ChatGPT for AI.
• 1:20:36
  Speaker 1: You can actually use this AI model for free and
• 1:20:40
  Speaker 1: no one's making money off of you using it. There's
• 1:20:42
  Speaker 1: no one getting paid. The only cost is the cost
• 1:20:45
  Speaker 1: of finding a computer to run that model. So you
• 1:20:48
  Speaker 1: could have your own computer, you could rent one, but
• 1:20:49
  Speaker 1: that cost is coming down like crazy now too. So
• 1:20:52
  Speaker 1: this is the benefit of, this is why technology without
• 1:20:54
  Speaker 1: government intervention is so amazing. It always gets cheaper and
• 1:20:57
  Speaker 1: then everyone benefits.
• 1:20:59
  Speaker 2: That could be a risk. Is that one of the
• 1:21:00
  Speaker 2: key arguments of the open source idea, which is if
• 1:21:02
  Speaker 2: anybody can download these AIs onto their computer, they can
• 1:21:05
  Speaker 2: jailbreak them, they can use them as.
• 1:21:08
  Speaker 1: So there's two things that people are fighting about. Number one,
• 1:21:10
  Speaker 1: government people are saying, hey, that's coming from China. We
• 1:21:13
  Speaker 1: don't know if there's backdoors. That's not how open weight
• 1:21:15
  Speaker 1: models work, by the way. So people that are technically
• 1:21:18
  Speaker 1: deficient don't fully grok what the open weight model really is.
• 1:21:21
  Speaker 1: It's not like some backdoor program that you're running. It's
• 1:21:24
  Speaker 1: literally just a list of numbers in a document. It's just,
• 1:21:28
  Speaker 1: you know, Trillions of numbers. That's all it is. And
• 1:21:30
  Speaker 1: then some people are arguing like, okay, so now that
• 1:21:32
  Speaker 1: AI is everywhere, everyone has access to it. You can
• 1:21:35
  Speaker 1: use it to design a cyber weapon. You can use
• 1:21:39
  Speaker 1: it to design a bioweapon. You can use it to
• 1:21:40
  Speaker 1: design a physical weapon. There's all these things that you
• 1:21:43
  Speaker 1: can now do. You know, the same is true with
• 1:21:46
  Speaker 1: DNA printing and DNA sequencing. Everyone can buy a DNA
• 1:21:49
  Speaker 1: sequencer and a DNA printer and they could theoretically make
• 1:21:51
  Speaker 1: a virus. That exists today. We haven't stopped DNA sequencing.
• 1:21:55
  Speaker 1: We haven't stopped DNA printing. We don't have like constraints
• 1:21:58
  Speaker 1: around it. Similarly, we haven't stopped people from buying guns.
• 1:22:02
  Speaker 1: We haven't stopped people, you know, in the US. I mean,
• 1:22:04
  Speaker 1: I don't think we can roll our eyes at this one. Right. Yeah. But,
• 1:22:08
  Speaker 1: but I mean, look, there's a very good argument to
• 1:22:10
  Speaker 1: be made that you could say that any sort of
• 1:22:12
  Speaker 1: technology that theoretically could be used to cause harm should
• 1:22:16
  Speaker 1: be banned and, or the government should control it and
• 1:22:18
  Speaker 1: decide who gets access to it. And the flip side
• 1:22:21
  Speaker 1: is that if it's allowed to proliferate, there's far more
• 1:22:24
  Speaker 1: benefit than risk. And the risk side needs to be mitigated.
• 1:22:28
  Speaker 1: And that's where you build good defense systems and so on.
• 1:22:30
  Speaker 1: So we've got all these technologies for monitoring, for cyber defense,
• 1:22:33
  Speaker 1: for biodefense, and all these sorts of things that are
• 1:22:36
  Speaker 1: critical for, you know, especially in a post-AI era, like
• 1:22:40
  Speaker 1: what are the big attack factors? So I think that's
• 1:22:42
  Speaker 1: probably the way to think about this.
• 1:22:44
  Speaker 2: And that might help the sort of inevitable inequality, golden gooses,
• 1:22:47
  Speaker 2: all collecting into insight.
• 1:22:49
  Speaker 1: I will bet you anything that in the next 10 years,
• 1:22:51
  Speaker 1: there will be a billionaire that will emerge that has absolutely...
• 1:22:56
  Speaker 1: zero net worth today, downloaded open-sourced AI, and built a
• 1:22:59
  Speaker 1: company that made them a billionaire five years from now,
• 1:23:02
  Speaker 1: seven years from now. And they're going to be someone
• 1:23:05
  Speaker 1: that's going to come from nowhere. And everyone's going to
• 1:23:07
  Speaker 1: be like, wow, look at that. And there's going to
• 1:23:08
  Speaker 1: be a lot of these sorts of stories. And that's
• 1:23:10
  Speaker 1: what we saw with the internet.
• 1:23:12
  Speaker 2: This is something that I've made for you. I realized
• 1:23:14
  Speaker 2: that the Divers here audience are strivers, whether it's in
• 1:23:17
  Speaker 2: business or health, we all have big goals that we
• 1:23:20
  Speaker 2: want to accomplish. And one of the things I've learned
• 1:23:22
  Speaker 2: is that when you aim at the big, big, big goal,
• 1:23:25
  Speaker 2: it can feel incredibly psychologically uncomfortable because it's kind of
• 1:23:30
  Speaker 2: like being stood at the foot of Mount Everest and
• 1:23:32
  Speaker 2: looking upwards. The way to accomplish your goals is by
• 1:23:35
  Speaker 2: breaking them down into tiny, small steps. And we call
• 1:23:38
  Speaker 2: this in our team, the 1%. And actually this philosophy
• 1:23:41
  Speaker 2: is highly responsible for much of our success here. So
• 1:23:44
  Speaker 2: what we've done so that you at home can accomplish
• 1:23:47
  Speaker 2: any big goal that you have is we've made these
• 1:23:49
  Speaker 2: 1% diaries and we released these last year and they
• 1:23:53
  Speaker 2: all sold out. So I asked my team over and
• 1:23:55
  Speaker 2: over again to bring the diaries back, but also to
• 1:23:57
  Speaker 2: introduce some new colors and to make some minor tweaks
• 1:23:59
  Speaker 2: to the diary. So now we have a better range
• 1:24:04
  Speaker 2: for you. So if you have a big goal in
• 1:24:06
  Speaker 2: mind and you need a framework and a process and
• 1:24:08
  Speaker 2: some motivation then I highly recommend you get one of
• 1:24:11
  Speaker 2: these diaries before they all sell out once again and
• 1:24:14
  Speaker 2: you can get yours at thediary.com and if you want
• 1:24:18
  Speaker 2: the link the link is in the description below. there
• 1:24:20
  Speaker 2: should be a button just down below here. And if
• 1:24:22
  Speaker 2: it says subscribe, you're already subscribed. If it says subscriber,
• 1:24:27
  Speaker 2: that means you're not yet. And if you're not subscribed,
• 1:24:29
  Speaker 2: please could you do us a favor and hit that button?
• 1:24:30
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• 1:24:35
  Speaker 2: you haven't yet hit that button. Thank you so much.
• 1:24:37
  Speaker 2: So when Elon says that working will be a choice,
• 1:24:41
  Speaker 2: you think he's wrong?
• 1:24:42
  Speaker 1: He's selling robots, but like, I do think he's right
• 1:24:47
  Speaker 1: in a sense. And what I mean by that is like,
• 1:24:49
  Speaker 1: think about how many hours a week you work. Do
• 1:24:51
  Speaker 1: you have a sense?
• 1:24:53
  Speaker 2: Just, I work all the time when my fiance is
• 1:24:55
  Speaker 2: not around.
• 1:24:55
  Speaker 1: Yes.
• 1:24:55
  Speaker 2: So she's not around at the moment.
• 1:24:56
  Speaker 1: Well, you and I are similar in the sense. So
• 1:24:58
  Speaker 1: like every moment I can, I work, but like we're
• 1:25:01
  Speaker 1: more entrepreneurial. I would say that like, um, you know,
• 1:25:04
  Speaker 1: look at Denmark, for example, 37 hours a week. What
• 1:25:07
  Speaker 1: was the average number of hours worked 50 years ago,
• 1:25:09
  Speaker 1: 60 years ago, a hundred years ago in the U
• 1:25:12
  Speaker 1: S when you did farm labor and you were managing
• 1:25:14
  Speaker 1: your own farm and that was your whole business or
• 1:25:16
  Speaker 1: you worked in a factory. I mean, there was 12-hour shifts.
• 1:25:20
  Speaker 1: There was a lot more work per week being done.
• 1:25:23
  Speaker 1: Going from 100 hours a week to 80 to 60
• 1:25:26
  Speaker 1: to 40, I mean, that is part of the progress
• 1:25:28
  Speaker 1: of humanity, is that we're no longer encumbered by this
• 1:25:31
  Speaker 1: labor category being told what to do and how to
• 1:25:33
  Speaker 1: do it and when to do it in order to
• 1:25:34
  Speaker 1: get money to pay our bills. But we get to
• 1:25:37
  Speaker 1: this world where we have more capital. That capital is
• 1:25:39
  Speaker 1: also time. And I've now accumulated the ability to make
• 1:25:43
  Speaker 1: a choice on what do I do with 40 hours
• 1:25:44
  Speaker 1: of my week.
• 1:25:46
  Speaker 2: You know, we all have a hypothesis about how AI
• 1:25:48
  Speaker 2: is going to play out. And I've heard many different
• 1:25:49
  Speaker 2: hypotheses here. Which is the part of your hypothesis, like
• 1:25:53
  Speaker 2: the principle within it, that could quite easily be a miscalculation?
• 1:25:58
  Speaker 2: And how could you be wrong? Mass unemployment. But where
• 1:26:02
  Speaker 2: in your current hypothesis would you have been, do you
• 1:26:05
  Speaker 2: think is the weakest part of your sort of first
• 1:26:06
  Speaker 2: principles that could result in that?
• 1:26:09
  Speaker 1: The choice that people will make to go to higher
• 1:26:11
  Speaker 1: paying jobs, to different jobs, that they see an opportunity
• 1:26:13
  Speaker 1: and they make a choice to change. Because I think
• 1:26:16
  Speaker 1: that that's the key to this whole thing. Like if
• 1:26:19
  Speaker 1: you were a taxi driver in New York and you
• 1:26:21
  Speaker 1: were paying rent on a medallion.
• 1:26:23
  Speaker 2: What's a medallion?
• 1:26:24
  Speaker 1: So a medallion is a right to drive a cab
• 1:26:26
  Speaker 1: in New York.
• 1:26:26
  Speaker 2: Okay.
• 1:26:27
  Speaker 1: So there was a limited number of them. And so
• 1:26:29
  Speaker 1: the medallions were restricted. The New York City said, well,
• 1:26:32
  Speaker 1: only allow so many cabs on the streets. So the
• 1:26:34
  Speaker 1: price of medallions went up and up and up. So
• 1:26:36
  Speaker 1: then New York cab drivers would trade the medallions. And
• 1:26:38
  Speaker 1: the price of medallions got up to 500 grand. And
• 1:26:40
  Speaker 1: Citigroup was a big lender on medallions. So they would
• 1:26:43
  Speaker 1: loan you 500 grand to go buy a medallion. Then
• 1:26:45
  Speaker 1: Uber came along. And this was one of the big
• 1:26:47
  Speaker 1: battles around Uber at the time. You could get paid
• 1:26:49
  Speaker 1: more and there's more rides with Uber. Uber grew the
• 1:26:55
  Speaker 1: number of people taking car transportation around New York considerably.
• 1:26:59
  Speaker 1: And when Uber demand shot up, a lot of these
• 1:27:00
  Speaker 1: guys said, I'm not going to be a cab driver anymore.
• 1:27:02
  Speaker 1: I'm going to go be an Uber driver. I can
• 1:27:03
  Speaker 1: make more money as an Uber driver. And the number
• 1:27:05
  Speaker 1: of Uber drivers grew. And look, there's a lot of
• 1:27:07
  Speaker 1: regulation that's happened in New York since then with respect
• 1:27:10
  Speaker 1: to Uber and whatnot. But everyone made the choice. They moved.
• 1:27:13
  Speaker 1: They found, the market found its way. Individuals said, oh
• 1:27:17
  Speaker 1: my God, I can make more money doing that. I
• 1:27:18
  Speaker 1: could pick my own hours. I don't have to rent
• 1:27:20
  Speaker 1: the medallion.
• 1:27:21
  Speaker 2: It's a very similar sidestep.
• 1:27:24
  Speaker 1: Yes.
• 1:27:24
  Speaker 2: Going from being a taxi driver to a taxi driver
• 1:27:26
  Speaker 2: for a different firm using an app is quite a.
• 1:27:30
  Speaker 1: So I could sit here and pontificate all day with
• 1:27:32
  Speaker 1: you on this and we'd both be wrong, I'm sure.
• 1:27:34
  Speaker 1: I don't know what the leap is going to be
• 1:27:36
  Speaker 1: for an individual. I think we have to start to
• 1:27:38
  Speaker 1: pull these stories out of the economy, what's going on.
• 1:27:41
  Speaker 1: Palantir put out this promotional video, which I thought was
• 1:27:43
  Speaker 1: quite good, where they interviewed a hospital administrator. And she's like, well,
• 1:27:47
  Speaker 1: I've got the AI doing all my paperwork, so I
• 1:27:49
  Speaker 1: get to spend more time with patients now. Sorry, it
• 1:27:51
  Speaker 1: was a nurse, not an administrator. She was a nurse.
• 1:27:53
  Speaker 1: So she's like, I normally spend most of my time
• 1:27:55
  Speaker 1: filling out paperwork on the computer, but Palantir, the software
• 1:27:58
  Speaker 1: takes care of all that for me. So now I
• 1:28:00
  Speaker 1: can spend more time doing rounds face-to-face with patients. It's
• 1:28:03
  Speaker 1: a better job. And it's better for her. And so
• 1:28:06
  Speaker 1: she You know, I think it was a very poignant
• 1:28:09
  Speaker 1: story about kind of what AI actually does on the ground. So,
• 1:28:13
  Speaker 1: you know, look, I mean, I think there's a lot
• 1:28:14
  Speaker 1: of these sorts of examples. We could counter-argue back and
• 1:28:17
  Speaker 1: forth about them all day long and probably both be wrong.
• 1:28:20
  Speaker 1: But this is what I would kind of observe on
• 1:28:21
  Speaker 1: the ground on what's actually happening.
• 1:28:23
  Speaker 2: I think we agree on the fact that jobs are
• 1:28:24
  Speaker 2: going to get more human in every sense of the word.
• 1:28:26
  Speaker 2: That was your yoga teacher example. That was the nurse
• 1:28:28
  Speaker 2: that can spend more time with her patients.
• 1:28:30
  Speaker 1: Yep.
• 1:28:30
  Speaker 2: Actually, that'll become even more valuable. It'll become more scarce.
• 1:28:33
  Speaker 2: I think my concern still, or the gap that I
• 1:28:35
  Speaker 2: have in my head is like how that transition looks,
• 1:28:37
  Speaker 2: especially at speed, retraining. You know, you talked about the
• 1:28:41
  Speaker 2: human agency point and should we be preparing for such
• 1:28:44
  Speaker 2: a transition? Because I do also believe that we'll get
• 1:28:46
  Speaker 2: to a, providing there's no existential issues, I do think
• 1:28:50
  Speaker 2: we'll net out in a better place. Mm-hmm. But the
• 1:28:52
  Speaker 2: journey to that better place, I thought, is just this
• 1:28:54
  Speaker 2: big question mark.
• 1:28:54
  Speaker 1: I think that's right. And I'm not trying to defend
• 1:28:56
  Speaker 1: it and say it's going to be a clean, smooth line.
• 1:28:58
  Speaker 1: I'm just trying to say, like, we are going to
• 1:28:59
  Speaker 1: get to a better place. You know, we could argue
• 1:29:02
  Speaker 1: all day long about displacement or dysfunction along the way.
• 1:29:06
  Speaker 1: Or maybe a lot of people are smiling as they
• 1:29:08
  Speaker 1: jump to new jobs and try new stuff out. And
• 1:29:10
  Speaker 1: they're like, oh, my God, my life's better. I'm optimistic
• 1:29:13
  Speaker 1: in that sense. I think you're right. We have to
• 1:29:14
  Speaker 1: track it. And if people are out of work and
• 1:29:16
  Speaker 1: can't find work and they're challenged in paying their bills,
• 1:29:18
  Speaker 1: we have a frigging problem.
• 1:29:20
  Speaker 2: And what's the solution to that problem? Is it UBI?
• 1:29:21
  Speaker 1: Well, that's going to be socialism.
• 1:29:24
  Speaker 2: So in that, in that messy middle, you think we'll
• 1:29:25
  Speaker 2: adopt socialism if that messy middle does occur. Yeah. And
• 1:29:29
  Speaker 2: what does that look like in reality? Is it just
• 1:29:30
  Speaker 2: giving money and free food? And I saw them in
• 1:29:32
  Speaker 2: Ghani grocery stores.
• 1:29:34
  Speaker 1: Well, that's not going to work, but that'll take time
• 1:29:36
  Speaker 1: to not work. But in the meantime, it'll look great.
• 1:29:38
  Speaker 1: But yeah, it'll be more, more checks, more government employees.
• 1:29:41
  Speaker 1: It's like the government creates jobs to pay people. They're
• 1:29:44
  Speaker 1: not productive jobs. Meaning if you get paid a hundred dollars,
• 1:29:47
  Speaker 1: do you create $ 120 of value? No, you're getting paid
• 1:29:50
  Speaker 1: a hundred dollars. Maybe you're creating 60 or $ 80 of value,
• 1:29:54
  Speaker 1: but you know, that's just, there's going to be more
• 1:29:56
  Speaker 1: government payments, whether it takes the form of UBI government, um, uh,
• 1:30:00
  Speaker 1: jobs grow or some other sort of financial support.
• 1:30:04
  Speaker 2: I mean, that's the direction of travel at the moment. Yeah.
• 1:30:06
  Speaker 2: All directions point to more socialistic America. How'd you feel
• 1:30:10
  Speaker 2: about that?
• 1:30:11
  Speaker 1: I'm actually, I don't want to lose my agency. I
• 1:30:13
  Speaker 1: don't want to lose my capacity, my Liberty, my freedom.
• 1:30:16
  Speaker 1: And I feel sad for people that embrace it because
• 1:30:18
  Speaker 1: I think that they don't realize that they're losing their
• 1:30:19
  Speaker 1: freedom in that process too. I think they're losing their agency.
• 1:30:23
  Speaker 2: But it's offering them a solution where there's no other
• 1:30:27
  Speaker 2: solution being offered.
• 1:30:28
  Speaker 1: That they feel there's no other solution being offered. That's right.
• 1:30:31
  Speaker 2: But it's also logical to say, if we talk about incentives,
• 1:30:34
  Speaker 2: that billionaires want to stay billionaires. And billionaires aren't actually
• 1:30:38
  Speaker 2: that philanthropic as they claim to be. And actually what
• 1:30:42
  Speaker 2: billionaires are protecting are their interests. They want to remain.
• 1:30:45
  Speaker 1: free. I had a call with Ro Khanna about this.
• 1:30:47
  Speaker 2: Can you give context on who he is?
• 1:30:48
  Speaker 1: Ro Khanna is a congressman from California who's been, he
• 1:30:52
  Speaker 1: used to be a moderate Democrat and he's kind of
• 1:30:54
  Speaker 1: pivoted to becoming a hard left true socialist in Silicon
• 1:30:58
  Speaker 1: Valley is his district, California 17. He was asking me
• 1:31:01
  Speaker 1: why are people so outraged at my support for a
• 1:31:04
  Speaker 1: wealth tax?
• 1:31:05
  Speaker 2: He means billionaires being outraged.
• 1:31:06
  Speaker 1: No, it's not billionaires. It's anyone that has built something
• 1:31:10
  Speaker 1: and created value. Yeah. And It's just entrepreneurs, people that
• 1:31:14
  Speaker 1: have had success. And he's like, I don't get it.
• 1:31:17
  Speaker 1: It's just 5% or 2% a year or 1% a year. Like,
• 1:31:20
  Speaker 1: why do people care? And I'm like, Ro, it's the
• 1:31:23
  Speaker 1: first time in American history that you're talking about taking
• 1:31:28
  Speaker 1: something from someone after they've paid their taxes. And it's
• 1:31:32
  Speaker 1: now their private property. And the government gets to decide
• 1:31:35
  Speaker 1: how much of their private property they get to keep.
• 1:31:37
  Speaker 1: It doesn't matter that it's 1% or 5% or they'll
• 1:31:39
  Speaker 1: be fine. And Bernie Sanders, like the billionaires will be fine.
• 1:31:42
  Speaker 1: It's fundamental to private property rights. It makes me feel like,
• 1:31:47
  Speaker 1: and everyone can think about this. It's not just rich people.
• 1:31:50
  Speaker 1: Anyone can think about what does it mean to list
• 1:31:52
  Speaker 1: out everything you own and send it to the government
• 1:31:54
  Speaker 1: every year, and they decide what you get to keep.
• 1:31:57
  Speaker 1: That's what it feels like to everyone. Also, financially, it
• 1:32:00
  Speaker 1: doesn't solve a problem. And I'll just give you the statistics.
• 1:32:02
  Speaker 1: Total net worth of people in the U.S. is $ 183 trillion.
• 1:32:07
  Speaker 1: Billionaires' total net worth is $ 8 trillion. And even if
• 1:32:11
  Speaker 1: you take it from billionaire down to 50 millionaire, so
• 1:32:13
  Speaker 1: people that have 50 million or more, the total assets,
• 1:32:16
  Speaker 1: the total net worth is 23 trillion. 160 trillion is
• 1:32:20
  Speaker 1: everyone else. The problem is that the bottom 50% of
• 1:32:25
  Speaker 1: Americans only have 6 trillion. And the middle, that kind
• 1:32:30
  Speaker 1: of 50% up to the 50 millionaire, they've got 160 trillion.
• 1:32:35
  Speaker 1: That's where the net worth is in the United States.
• 1:32:38
  Speaker 1: It's in that kind of population... that people call boomers
• 1:32:41
  Speaker 1: or Gen X or whatever, the bottom 50% have nothing.
• 1:32:45
  Speaker 1: And so if you taxed 100% of the billionaire's net worth,
• 1:32:49
  Speaker 1: that's $ 8 trillion. That's one year of the government spending.
• 1:32:53
  Speaker 1: One year. It doesn't stop fundamentally a wealth tax. It
• 1:32:56
  Speaker 1: doesn't actually solve a fiscal problem. It creates a system
• 1:32:59
  Speaker 1: where you're like, everyone feels better about taking money from
• 1:33:01
  Speaker 1: the billionaires. Are the billionaires paying their fair share of taxes?
• 1:33:04
  Speaker 1: This is the politician's trick. The politician's trick is they say,
• 1:33:08
  Speaker 1: how much tax did you pay as a percent of
• 1:33:10
  Speaker 1: your assets versus how much tax did you pay as
• 1:33:12
  Speaker 1: a percent of your income? Your income is when you
• 1:33:15
  Speaker 1: sell stocks or when you make money for services you provide.
• 1:33:18
  Speaker 1: And every year, if you're wealthy in the United States,
• 1:33:20
  Speaker 1: in California, I pay a 53% tax. I pay 14%
• 1:33:24
  Speaker 1: in California plus 39% federal.
• 1:33:27
  Speaker 2: But you must try and avoid that. No, I just
• 1:33:29
  Speaker 2: pay it. But I mean, in terms of when I
• 1:33:31
  Speaker 2: say avoid that, I mean, you would rather take it
• 1:33:33
  Speaker 2: like a capital gains tax, which is lower.
• 1:33:35
  Speaker 1: California, there's no difference.
• 1:33:36
  Speaker 2: Oh, there's no difference.
• 1:33:37
  Speaker 1: Yeah, in California, capital gains or income is the same,
• 1:33:39
  Speaker 1: which by the way, should be the case at the
• 1:33:41
  Speaker 1: federal level if you want to solve this compounding problem.
• 1:33:44
  Speaker 1: So can we lower income tax in the United States
• 1:33:46
  Speaker 1: and raise capital gains tax? Absolutely. Can we make income
• 1:33:50
  Speaker 1: tax lower for people that are working for their money
• 1:33:52
  Speaker 1: versus people that are earning gains on their capital assets? Absolutely.
• 1:33:56
  Speaker 1: And we can solve the problem that way. But by
• 1:33:57
  Speaker 1: taking their assets, even if you took 100% of the
• 1:34:00
  Speaker 1: billionaire's assets. That's one year of spending. It doesn't actually
• 1:34:03
  Speaker 1: solve a fiscal problem. The tax rate is the fiscal problem.
• 1:34:07
  Speaker 2: So for these people, the 63% that are, you know,
• 1:34:09
  Speaker 2: potentially championing socialism because they need a solution, and it
• 1:34:13
  Speaker 2: sounds like a solution, make my bills cheaper. What they
• 1:34:17
  Speaker 2: don't hear from, you know, other politicians is a better solution.
• 1:34:21
  Speaker 2: And this one sounds great.
• 1:34:22
  Speaker 1: This is what's crazy to me. I don't get why
• 1:34:23
  Speaker 1: all the politicians are fighting against a wealth tax or
• 1:34:25
  Speaker 1: for a wealth tax when there's like literally 15 other
• 1:34:28
  Speaker 1: things you could do to make this better. Like, this
• 1:34:31
  Speaker 1: is crazy. Make the capital gains and income tax the same.
• 1:34:34
  Speaker 1: Cut stupid spending at the federal level. And all of
• 1:34:36
  Speaker 1: a sudden, things become more affordable. People have more take-home pay.
• 1:34:39
  Speaker 1: They can afford more stuff.
• 1:34:40
  Speaker 2: But let's be honest. You're not going to be able
• 1:34:41
  Speaker 2: to cut the spending at the federal level. They've tried that.
• 1:34:45
  Speaker 2: And because of this whole thing we just talked about,
• 1:34:47
  Speaker 2: the four-year election cycles, Elon went in, he tried to
• 1:34:49
  Speaker 2: cut it. He bounced straight back out. Yeah. Yeah.
• 1:34:51
  Speaker 1: And I think that that to me was the most
• 1:34:52
  Speaker 1: depressing piece because I was like, oh, my God, Elon's
• 1:34:54
  Speaker 1: going to go in. He's going to blow up spending.
• 1:34:56
  Speaker 1: We're finally going to cut all the nonsense out of
• 1:34:58
  Speaker 1: the spending. And if Elon can't, no human can. And
• 1:35:01
  Speaker 1: then I went and visited D.C. and I went to
• 1:35:03
  Speaker 1: all these Congress meetings and sat with senators. And I
• 1:35:05
  Speaker 1: was like, oh, my God, none of them want to
• 1:35:07
  Speaker 1: cut it. Like they're all on board with it. This
• 1:35:10
  Speaker 1: isn't even a party thing. This is like everyone's doing it.
• 1:35:14
  Speaker 1: And I'm like, this is the system. This is how
• 1:35:15
  Speaker 1: it's set up. Holy shit.
• 1:35:19
  Speaker 2: We've had Brian slightly change direction, but linked to AI.
• 1:35:21
  Speaker 2: I know you work in the life sciences. So I
• 1:35:24
  Speaker 2: wanted to ask you, do you think we're going to
• 1:35:26
  Speaker 2: be able to live forever soon or at least extend
• 1:35:28
  Speaker 2: life significantly within the next couple of decades? I do.
• 1:35:31
  Speaker 1: And I think the reason is we've discovered the mechanism
• 1:35:34
  Speaker 1: of aging, which is the most fundamental of human diseases.
• 1:35:37
  Speaker 1: We have 10 trillion cells in our body. Every one
• 1:35:40
  Speaker 1: of those cells has a copy of our DNA in
• 1:35:43
  Speaker 1: the nucleus of the cell. That DNA, segments of it
• 1:35:46
  Speaker 1: are called a gene. A, C, T, and G make
• 1:35:49
  Speaker 1: up the little nucleotides, and you put a bunch of
• 1:35:51
  Speaker 1: them together, and that's a gene. What is a gene? Well,
• 1:35:55
  Speaker 1: a copy of that comes over to a protein printer
• 1:35:58
  Speaker 1: in the cell called the ribosome, and the A, C, T,
• 1:36:01
  Speaker 1: and G is the programming for which of 20 amino acids,
• 1:36:05
  Speaker 1: three letters is one amino acid, that ribosome takes a
• 1:36:08
  Speaker 1: segment of the DNA copied as RNA, and it prints
• 1:36:11
  Speaker 1: out amino acids. And a sequence of amino acids from
• 1:36:15
  Speaker 1: that gene, which is defined by that gene, makes a protein.
• 1:36:18
  Speaker 1: So all a protein is is a chain of amino acids.
• 1:36:22
  Speaker 1: As soon as it's done printing, those amino acids collapse
• 1:36:25
  Speaker 1: into a three-dimensional machine called a protein. So proteins are
• 1:36:30
  Speaker 1: three-dimensional machines and they do crazy shit. Like there is
• 1:36:33
  Speaker 1: a protein in your mitochondria that spins 6,000 times a
• 1:36:36
  Speaker 1: second as hydrogen protons go through it and that's what
• 1:36:39
  Speaker 1: makes energy in your cells. That's what makes ATP. It's
• 1:36:42
  Speaker 1: literally like a propeller, like a turbine in your mitochondria
• 1:36:45
  Speaker 1: in your cell. It's an incredible machine. There's machines that
• 1:36:48
  Speaker 1: carry oxygen from your lungs into your cells in your
• 1:36:52
  Speaker 1: body to give them oxygen that they need to work.
• 1:36:54
  Speaker 1: I mean, there are proteins that do all sorts of
• 1:36:56
  Speaker 1: crazy stuff. So all the genes are, are the programming
• 1:37:00
  Speaker 1: for making proteins in your cell. Now, your DNA is
• 1:37:03
  Speaker 1: not a strand like this. It's actually kind of a
• 1:37:06
  Speaker 1: small clustered thing. And there are little molecules that sit
• 1:37:08
  Speaker 1: on top of the DNA that turn a gene on
• 1:37:12
  Speaker 1: or off. So if the molecule is sitting on top
• 1:37:14
  Speaker 1: of a certain gene, that gene is off.
• 1:37:16
  Speaker 2: Like a little switch?
• 1:37:17
  Speaker 1: Like a switch.
• 1:37:18
  Speaker 2: What's it called? Someone used the name before. Histones. Histones, okay.
• 1:37:21
  Speaker 1: Or acetyl markers.
• 1:37:22
  Speaker 2: I thought it was epigenetics, but maybe not.
• 1:37:23
  Speaker 1: So this is all epigenetics.
• 1:37:24
  Speaker 2: Okay.
• 1:37:25
  Speaker 1: So for a given cell, there are genes that are
• 1:37:28
  Speaker 1: on or off. The genes that are on, those proteins
• 1:37:30
  Speaker 1: are being made in that cell. And the genes that
• 1:37:32
  Speaker 1: are off, those proteins are not being made in that cell.
• 1:37:35
  Speaker 1: And that's what makes all of our cells in our
• 1:37:37
  Speaker 1: body different. Every one of our cells has the same DNA,
• 1:37:40
  Speaker 1: but our eye cell and our brain cell and our
• 1:37:43
  Speaker 1: heart cell and our skin cell Just have different genes
• 1:37:46
  Speaker 1: that are on or off. Okay, so those markers that
• 1:37:48
  Speaker 1: sit on the genes, those little switches. Every time you
• 1:37:52
  Speaker 1: drink a glass of alcohol or you go in the
• 1:37:53
  Speaker 1: sun and get hit by the sunlight or smoke a
• 1:37:56
  Speaker 1: cigarette or eat some bad food that's burnt, all of
• 1:37:59
  Speaker 1: these things can cut DNA. And when DNA gets cut,
• 1:38:03
  Speaker 1: your cell is really good at fixing it. Puts it
• 1:38:05
  Speaker 1: right back together. Happening millions of times a second in
• 1:38:09
  Speaker 1: your body. Literally all over your body. And your DNA
• 1:38:12
  Speaker 1: is breaking and your cell is fixing it. But every
• 1:38:14
  Speaker 1: time your cell fixes it, there's a chance that that
• 1:38:17
  Speaker 1: switch moves a little bit. And if the switch moves
• 1:38:20
  Speaker 1: to the wrong place, suddenly that cell starts making the
• 1:38:25
  Speaker 1: wrong protein or stops making the right protein. So statistically,
• 1:38:29
  Speaker 1: over time... when you're a baby, everything is tuned great,
• 1:38:32
  Speaker 1: working right. All the right proteins are being made in
• 1:38:34
  Speaker 1: every cell. You're young. Your skin is not wrinkly. You
• 1:38:37
  Speaker 1: can run. You can breathe. You can see perfectly. As
• 1:38:40
  Speaker 1: you're a young person, suddenly you turn 30 and you're like, wait,
• 1:38:42
  Speaker 1: my vision's kind of fading a little bit. I can't
• 1:38:45
  Speaker 1: run as fast. I can't breathe as deep. Oh my God,
• 1:38:47
  Speaker 1: I'm getting wrinkles around my eyes. 40, 50, What happens
• 1:38:50
  Speaker 1: as we get older is those switches kind of move
• 1:38:52
  Speaker 1: around to the wrong places. And as those switches move around,
• 1:38:56
  Speaker 1: that cell stops making the right protein and starts making
• 1:39:00
  Speaker 1: the wrong protein and it becomes dysfunctional. And if that
• 1:39:04
  Speaker 1: happens in enough cells, then that tissue starts to misbehave.
• 1:39:08
  Speaker 1: You get wrinkles. Your heart can't beat quite right. Your
• 1:39:11
  Speaker 1: retina doesn't pick up light as well and transmit the
• 1:39:14
  Speaker 1: signal of the light and things get blurry. Your hearing
• 1:39:16
  Speaker 1: starts to lose. You can't think as quickly. You can't
• 1:39:18
  Speaker 1: respond as quickly. That's what aging is. Aging is the
• 1:39:22
  Speaker 1: core human disease. And as epigenetics, which is where the
• 1:39:25
  Speaker 1: switches are on a cell, start to get moved around
• 1:39:28
  Speaker 1: to the wrong place and that tissue starts to misbehave,
• 1:39:32
  Speaker 1: we get all these diseases. That could be one of
• 1:39:34
  Speaker 1: the core drivers of cancer.
• 1:39:37
  Speaker 2: Why is aging so even across my body then?
• 1:39:39
  Speaker 1: Because all these cells are suffering the same statistical effect
• 1:39:43
  Speaker 1: of time as DNA breaks happen in every cell in
• 1:39:45
  Speaker 1: your body. And as those DNA breaks happen, those switches
• 1:39:48
  Speaker 1: are moving around the same rate in all parts of
• 1:39:51
  Speaker 1: your body. And that's why parts of your body start
• 1:39:53
  Speaker 1: to suffer kind of a, it's like, oh my God,
• 1:39:55
  Speaker 1: my hip hurts, my eye, my brain. Your young viewers
• 1:39:59
  Speaker 1: may not appreciate this, but being 46, I'm starting to
• 1:40:01
  Speaker 1: appreciate it. And it's becoming more of an issue. Now,
• 1:40:04
  Speaker 1: in 2006, a guy named Shinya Yamanaka discovered four proteins
• 1:40:11
  Speaker 1: that you could put into a cell or apply to
• 1:40:13
  Speaker 1: a cell and it would basically take all the switches
• 1:40:16
  Speaker 1: in that cell and move them to the place that
• 1:40:19
  Speaker 1: a stem cell has, which is basically an embryo in
• 1:40:21
  Speaker 1: a human. And now that cell operates like an embryonic cell.
• 1:40:27
  Speaker 1: And you can take that embryo cell and you can
• 1:40:29
  Speaker 1: put other proteins on to move the switches around even
• 1:40:32
  Speaker 1: more to turn that stem cell into an eye cell,
• 1:40:36
  Speaker 1: into a skin cell, into a heart cell, into a
• 1:40:38
  Speaker 1: lung cell, into a brain cell. So we suddenly developed
• 1:40:42
  Speaker 1: this technology in the mid-2000s, to take any cell and
• 1:40:47
  Speaker 1: turn it into a stem cell, re-differentiate it, it's called differentiation,
• 1:40:51
  Speaker 1: from one cell type to another. But then years later,
• 1:40:55
  Speaker 1: another guy said, well, what if instead of putting a
• 1:40:57
  Speaker 1: lot of that protein on the cell, we just put
• 1:40:58
  Speaker 1: a little bit? So they took the Yamanaka factors, which
• 1:41:01
  Speaker 1: are just four proteins, and they put a microdose of
• 1:41:04
  Speaker 1: them on a couple cells. And the switches started to
• 1:41:08
  Speaker 1: move around, but they didn't move back to being a
• 1:41:10
  Speaker 1: stem cell. what happened is they moved back to being
• 1:41:13
  Speaker 1: a young version of that cell type. So the eye
• 1:41:16
  Speaker 1: cell basically became a young eye cell. The skin cell
• 1:41:19
  Speaker 1: became a young skin cell. The heart cell became a
• 1:41:22
  Speaker 1: young heart cell by putting a small dose of these proteins.
• 1:41:25
  Speaker 1: So it turns out that these proteins kind of move
• 1:41:27
  Speaker 1: the switches around. And if you put just a small
• 1:41:29
  Speaker 1: amount of them on, you can move the switches just
• 1:41:31
  Speaker 1: back to the right position. That's now called epigenetic reprogramming.
• 1:41:35
  Speaker 1: That's this new area of science that seems to indicate,
• 1:41:37
  Speaker 1: and they've now done it in mice and where the
• 1:41:39
  Speaker 1: mice can live to the equivalent of 100 plus years old.
• 1:41:42
  Speaker 1: They've put it on the tissue of monkeys and gotten
• 1:41:44
  Speaker 1: rid of the wrinkles. We now have just David Sinclair,
• 1:41:48
  Speaker 1: just one of his companies did the dosing in the
• 1:41:50
  Speaker 1: retina to reverse blindness in people with a retinopathy. So
• 1:41:55
  Speaker 1: this epigenetic reprogramming is an entirely new lane of medicine
• 1:42:00
  Speaker 1: that says not just can we address all of the
• 1:42:03
  Speaker 1: downstream effects of aging, but can we go to the core?
• 1:42:06
  Speaker 1: Can we reset aging in all these cells in the body?
• 1:42:09
  Speaker 1: And the answer so far is yes. The risk is
• 1:42:12
  Speaker 1: if you reset it too much, it becomes an embryo
• 1:42:14
  Speaker 1: and it turns into cancer. So that's what everyone's been
• 1:42:17
  Speaker 1: working against in the last couple of years is how
• 1:42:19
  Speaker 1: do you put the right dose of the right proteins
• 1:42:21
  Speaker 1: in the right cells to get them to reverse their
• 1:42:24
  Speaker 1: age and become young again? And the path, it's really
• 1:42:27
  Speaker 1: just an engineering exercise at this point, as opposed to
• 1:42:29
  Speaker 1: a biological proof of concept. The science is there. The
• 1:42:32
  Speaker 1: foundation is there. We're just doing the engineering. So I
• 1:42:35
  Speaker 1: am extremely excited and optimistic about about this work it
• 1:42:39
  Speaker 1: seems very likely that in the next couple of years
• 1:42:41
  Speaker 1: we're going to have more human therapy trials that are
• 1:42:43
  Speaker 1: going to not just address the core of aging but
• 1:42:46
  Speaker 1: they'll start to put in like you know like they
• 1:42:47
  Speaker 1: did with the eye cell maybe reverse wrinkles maybe improve
• 1:42:51
  Speaker 1: cardiomyocytes improve the heart tissue so I think there'll be
• 1:42:55
  Speaker 1: a lot more of this sort of thing coming to
• 1:42:57
  Speaker 1: market over the next few years and AI.
• 1:42:59
  Speaker 2: Is going to play a role I assume in accelerating
• 1:43:01
  Speaker 2: this because you can perform I mean you can theoretically
• 1:43:04
  Speaker 2: make new discoveries but you can run the tests faster right.
• 1:43:06
  Speaker 1: You know just to help provide some context on what
• 1:43:12
  Speaker 1: goes on in a cell. You can kind of think
• 1:43:13
  Speaker 1: about a cell has about 10 billion proteins interacting with
• 1:43:18
  Speaker 1: each other, building things, breaking things, creating new molecules, creating
• 1:43:21
  Speaker 1: new proteins, interacting, interacting. So the proteins are these machines,
• 1:43:24
  Speaker 1: 10 billion of them in a cell. So if you
• 1:43:28
  Speaker 1: assume each protein is the size of a human, the
• 1:43:30
  Speaker 1: cell would be the size of Manhattan. So now imagine
• 1:43:33
  Speaker 1: a city the size of Manhattan, with 500-story tall skyscrapers
• 1:43:38
  Speaker 1: in the Manhattan skyline, and 10 billion people living in
• 1:43:41
  Speaker 1: these buildings, going back and forth, building stuff together, talking,
• 1:43:45
  Speaker 1: making babies, and assume they just do this for 80 years,
• 1:43:48
  Speaker 1: all these humans interacting, 10 billion humans in Manhattan for
• 1:43:51
  Speaker 1: 80 years, nonstop, they don't sleep, and they just keep working.
• 1:43:54
  Speaker 1: That entire set of interactions is one second in one cell.
• 1:43:58
  Speaker 1: That's how complicated biology is. And we have 10 trillion
• 1:44:02
  Speaker 1: cells in our body, and those cells are all shooting
• 1:44:04
  Speaker 1: out proteins and messages to each other all the time.
• 1:44:07
  Speaker 1: To answer the question, AI allows us to build models
• 1:44:12
  Speaker 1: to better understand what the heck is going on and
• 1:44:14
  Speaker 1: to make predictions about proteins we could put into the
• 1:44:16
  Speaker 1: cells that can affect the outcome of changing the epigenome
• 1:44:21
  Speaker 1: on that DNA without us having a deterministic understanding of
• 1:44:24
  Speaker 1: what's going on. So with AI, I can come up
• 1:44:26
  Speaker 1: with a million different ideas for a new protein. I
• 1:44:29
  Speaker 1: can test it in silicon how it would interact with
• 1:44:31
  Speaker 1: other stuff, meaning on computers. I could see what happens.
• 1:44:34
  Speaker 1: I could see if it actually has the same sort
• 1:44:35
  Speaker 1: of effect as the other protein. Would it be more efficacious?
• 1:44:38
  Speaker 1: And then I reduce my candidate list down and I
• 1:44:40
  Speaker 1: take that candidate list and I put it in a
• 1:44:41
  Speaker 1: lab and now the labs are being automated and I
• 1:44:44
  Speaker 1: can test it on cells and see if it's actually
• 1:44:45
  Speaker 1: reversing aging. I can test it in models and then
• 1:44:48
  Speaker 1: I take that candidate and now I've got a probability
• 1:44:51
  Speaker 1: of success in 10 years that instead of being 1%
• 1:44:54
  Speaker 1: is now like 75%. And so that's the way AI
• 1:44:57
  Speaker 1: plays a role in life sciences discovery. And it's transforming
• 1:45:00
  Speaker 1: not just epigenetic reprogramming, which is this whole big avenue
• 1:45:03
  Speaker 1: of medicine now, but it's transforming every aspect of biology
• 1:45:07
  Speaker 1: and our understanding of life sciences, where we can use
• 1:45:09
  Speaker 1: AI to make these simulations and have a better understanding
• 1:45:12
  Speaker 1: of what these complicated, incredibly immense interaction sets look like
• 1:45:16
  Speaker 1: or drive at the end state versus me needing to
• 1:45:19
  Speaker 1: kind of be a scientist being like, oh, I got
• 1:45:20
  Speaker 1: a good idea. Let's try that. Okay, five weeks later, okay,
• 1:45:22
  Speaker 1: I got another good idea. Let's try that. And that
• 1:45:25
  Speaker 1: all gets reduced to silica.
• 1:45:26
  Speaker 2: And are you using your own model? Are you training
• 1:45:28
  Speaker 2: your own AI? Are you using some of the publicly
• 1:45:29
  Speaker 2: available frontier models?
• 1:45:31
  Speaker 1: In my world, we use both. So we take our
• 1:45:33
  Speaker 1: own data and then we build our own predictive models
• 1:45:35
  Speaker 1: from it. And then separately, we use off the shelf
• 1:45:38
  Speaker 1: life sciences models. And then we also use some of
• 1:45:39
  Speaker 1: the general models. So it's a great combination. And to
• 1:45:42
  Speaker 1: your questions and talking about AI earlier, oh my God,
• 1:45:45
  Speaker 1: the stuff we can do is unbelievable and it's mind blowing.
• 1:45:48
  Speaker 1: And we're hiring more people because of it. And so like,
• 1:45:51
  Speaker 1: it's not like AI got me to get rid of jobs.
• 1:45:52
  Speaker 1: It's like, the frontier has gotten so much wider. That's
• 1:45:56
  Speaker 1: why I'm so optimistic about AI not destroying jobs, because
• 1:45:59
  Speaker 1: all I see is opportunity with new companies, new ideas,
• 1:46:02
  Speaker 1: new pathways, new things, new breakthroughs in sciences, in materials,
• 1:46:07
  Speaker 1: in engineering, things that we could have never, ever tackled,
• 1:46:10
  Speaker 1: we can now tackle with AI.
• 1:46:13
  Speaker 2: It is a persuasive argument. Okay, so what are the
• 1:46:15
  Speaker 2: great lies in America in your view?
• 1:46:18
  Speaker 1: If you go to any college with any degree, you're
• 1:46:20
  Speaker 1: going to have a great job waiting for you at
• 1:46:22
  Speaker 1: the end.
• 1:46:22
  Speaker 2: Okay, number one.
• 1:46:24
  Speaker 1: If you buy a home, you've achieved the American dream,
• 1:46:27
  Speaker 1: and all of your assets should be in that home.
• 1:46:31
  Speaker 2: Okay.
• 1:46:32
  Speaker 1: Social security will take care of you when you get old,
• 1:46:35
  Speaker 1: and it's a fair system. Everyone should have ownership in
• 1:46:39
  Speaker 1: stocks is the truth about that lie. Because all the
• 1:46:43
  Speaker 1: money that went into social security went out to the
• 1:46:45
  Speaker 1: government to pay bills, and it wasn't actually kept in
• 1:46:48
  Speaker 1: the trust.
• 1:46:49
  Speaker 2: No.
• 1:46:50
  Speaker 1: And so as a result, Social Security is going to
• 1:46:52
  Speaker 1: go bankrupt. So Social Security was one of the great
• 1:46:53
  Speaker 1: lies on, you know, you'll be safe and protected when
• 1:46:57
  Speaker 1: you retire.
• 1:46:59
  Speaker 2: Those are three great lies. Is there any more that
• 1:47:00
  Speaker 2: come to mind?
• 1:47:01
  Speaker 1: I don't know about public pensions. And it's the same
• 1:47:05
  Speaker 1: as the Social Security lie. When you put money into
• 1:47:07
  Speaker 1: a pension plan, and that's called a defined benefit plan.
• 1:47:12
  Speaker 1: When you retire, you're going to get $ 1, 000 a week
• 1:47:13
  Speaker 1: or whatever it is. And every paycheck, some money is
• 1:47:17
  Speaker 1: taken out. And the idea is that the accountants and
• 1:47:19
  Speaker 1: the investors will do a good job investing that money
• 1:47:21
  Speaker 1: for you and you'll get your benefit at the end.
• 1:47:24
  Speaker 1: If they don't do a good job, then the pension
• 1:47:25
  Speaker 1: plan is bankrupt and you don't get your retirement check.
• 1:47:28
  Speaker 1: And if they do too good a job or you
• 1:47:30
  Speaker 1: put too much money in, then the pension plan is
• 1:47:32
  Speaker 1: overfunded and you should be getting more money out than
• 1:47:35
  Speaker 1: you're actually getting. So what companies realized was that pension
• 1:47:39
  Speaker 1: plans are unfair. They either go bankrupt or they're overfunded.
• 1:47:43
  Speaker 1: So that's when everyone moved to 401Ks. And that middle
• 1:47:46
  Speaker 1: class that we talked about earlier, those people that have
• 1:47:48
  Speaker 1: $ 160 trillion of assets, the reason they have $ 160 trillion
• 1:47:52
  Speaker 1: of assets is because a lot of them had 401ks. Meanwhile,
• 1:47:56
  Speaker 1: the bottom 50% of people that are just relying on
• 1:47:58
  Speaker 1: social security, they were making less than 3.5% a year
• 1:48:01
  Speaker 1: on their money. So that's the great lie is that
• 1:48:04
  Speaker 1: these public retirement funds would take care of their people.
• 1:48:10
  Speaker 2: Is there a fifth great lie that comes to mind?
• 1:48:13
  Speaker 1: I actually don't have a great answer for you on healthcare.
• 1:48:15
  Speaker 1: I think that there's a moral obligation on healthcare. So
• 1:48:19
  Speaker 1: I do buy into this. In a civil society, I
• 1:48:22
  Speaker 1: could make the libertarian argument, but I won't. Because I
• 1:48:25
  Speaker 1: do think it's probably the right thing to say, in
• 1:48:27
  Speaker 1: a civil society, no one should be without healthcare. How
• 1:48:32
  Speaker 1: do you make that work where the government's paying bills
• 1:48:34
  Speaker 1: and the costs don't go through the roof? That's a long,
• 1:48:37
  Speaker 1: probably six-hour conversation.
• 1:48:39
  Speaker 2: Mm-hmm.
• 1:48:39
  Speaker 1: And it's very technical, I think, on what you have
• 1:48:41
  Speaker 1: to do to make healthcare accessible. And it's definitely got
• 1:48:45
  Speaker 1: to be a multi-tiered system.
• 1:48:47
  Speaker 2: I guess one of the things that I was curious
• 1:48:49
  Speaker 2: to get your take on, because I've not really heard
• 1:48:50
  Speaker 2: you talk about this a lot on the All In podcast,
• 1:48:53
  Speaker 2: is your view on everything that's going on with this
• 1:48:55
  Speaker 2: bloody war and the situation there. I'm not sure if
• 1:48:57
  Speaker 2: this is within your area of expertise, but it appears
• 1:48:59
  Speaker 2: that the US is now stuck.
• 1:49:00
  Speaker 1: It's a quandary. I read Ray Dalio's piece a few
• 1:49:03
  Speaker 1: weeks ago, which I thought was exactly right. The Chinese
• 1:49:06
  Speaker 1: make their influence known In the same way that you
• 1:49:10
  Speaker 1: would kind of read about it in Sun Tzu's Art
• 1:49:12
  Speaker 1: of War, if you have to go to war, you've
• 1:49:15
  Speaker 1: already lost. And that's a big difference between how the U.S.
• 1:49:20
  Speaker 1: behaves and how China behaves. If you look back on
• 1:49:23
  Speaker 1: the track record of presidents' decisions as it relates to
• 1:49:25
  Speaker 1: foreign policy in the United States over the last couple decades,
• 1:49:29
  Speaker 1: there have not been a lot of good actions that
• 1:49:32
  Speaker 1: have ended up in a good place. I think China
• 1:49:34
  Speaker 1: has this capacity for influence without action, which... It's a
• 1:49:39
  Speaker 1: really interesting model to observe. And the U.S. has this
• 1:49:43
  Speaker 1: kind of, I don't want to say incentive, but when
• 1:49:47
  Speaker 1: you go to a general and say, hey, should we
• 1:49:50
  Speaker 1: go attack these guys? The general spends the whole time
• 1:49:52
  Speaker 1: training to attack the guys. So, you know, and then
• 1:49:55
  Speaker 1: you have a National Security Council and you have advisors
• 1:49:57
  Speaker 1: and all this sort of stuff. But there's a priming
• 1:50:01
  Speaker 1: in the U.S. that I think maybe plays out in
• 1:50:02
  Speaker 1: a way that maybe we take action when we shouldn't
• 1:50:04
  Speaker 1: always be taking action.
• 1:50:06
  Speaker 2: China's position that only possible because there is a dominant
• 1:50:08
  Speaker 2: force that is running around trying to police everything. So
• 1:50:11
  Speaker 2: they can kind of chill and let the US go
• 1:50:13
  Speaker 2: police all the problems and wars.
• 1:50:15
  Speaker 1: Their military capacity is pretty impressive, but it's untested at scale,
• 1:50:18
  Speaker 1: I guess, is one argument you can make against that point.
• 1:50:21
  Speaker 1: I mean, China's got a lot of economic gamesmanship that
• 1:50:25
  Speaker 1: they do. You know, we'll give you cheap stuff if
• 1:50:27
  Speaker 1: we can get these things from you. You know, we'll
• 1:50:31
  Speaker 1: keep an eye on you if you need help. I mean,
• 1:50:34
  Speaker 1: there's like a lot of stuff that doesn't require direct
• 1:50:37
  Speaker 1: kinetic action that they can kind of get things done.
• 1:50:39
  Speaker 2: In terms of the US's position in Iran right now,
• 1:50:41
  Speaker 2: there is, it appears, a threat to oil in terms
• 1:50:45
  Speaker 2: of like the price at the pump. And I think
• 1:50:47
  Speaker 2: it's the US oil reserve is down to a couple
• 1:50:49
  Speaker 2: of weeks.
• 1:50:50
  Speaker 1: I want to say that's on the order of 24
• 1:50:52
  Speaker 1: million barrels in the SPR.
• 1:50:54
  Speaker 2: So at the G7 summit in France, President Donald Trump
• 1:50:57
  Speaker 2: addressed the precocious state of global oil inventories following the
• 1:51:00
  Speaker 2: supply disruption he said we run out of reserves at
• 1:51:04
  Speaker 2: about four weeks you know there are reserves all over
• 1:51:08
  Speaker 2: the world and we would really run out and there'll
• 1:51:11
  Speaker 2: be a time when you wouldn't be able to get
• 1:51:14
  Speaker 2: it it would be bedlam and this was just as
• 1:51:19
  Speaker 2: i think this was the explanation as to why he
• 1:51:21
  Speaker 2: signed that mou with iran so i mean if this
• 1:51:25
  Speaker 2: is true then something needs to happen but again It
• 1:51:29
  Speaker 2: doesn't appear that Iran have much of an incentive now
• 1:51:31
  Speaker 2: you've decapitated the leader to do really anything.
• 1:51:33
  Speaker 1: The game theory is Iran knows that the U.S. can't
• 1:51:36
  Speaker 1: do much more.
• 1:51:37
  Speaker 2: Yeah, we're going to drop more bombs. Right.
• 1:51:40
  Speaker 1: And well, I mean, Iran's now threatened Arab neighbors with
• 1:51:46
  Speaker 1: retaliation against their energy infrastructure, which would be devastating to Saudi, Qatar, UAE.
• 1:51:52
  Speaker 1: So at this point, it seems like a bit of
• 1:51:53
  Speaker 1: a stalemate that the U.S. can't act for fear of
• 1:51:56
  Speaker 1: the retaliation and the impact it would have on America's
• 1:51:59
  Speaker 1: actual allies in the region.
• 1:52:00
  Speaker 2: What do you think happens here? Trump, straight-up Hormuz, Iran
• 1:52:03
  Speaker 2: now have this sort of chokehold on the world, it seems.
• 1:52:06
  Speaker 1: I mean, the biggest driver also is the election cycle
• 1:52:08
  Speaker 1: we're in.
• 1:52:09
  Speaker 2: The midterms?
• 1:52:09
  Speaker 1: The midterms. So going into November, this war is deeply
• 1:52:14
  Speaker 1: unpopular on both sides. And so trying to get rid
• 1:52:17
  Speaker 1: of the war is the incentive at the moment. It's
• 1:52:22
  Speaker 1: a tough situation.
• 1:52:23
  Speaker 2: You seem hesitant here.
• 1:52:26
  Speaker 1: No, I just, I'm not a great guy to... a
• 1:52:28
  Speaker 1: pine on this i just i don't know what to do.
• 1:52:30
  Speaker 2: But just when you look at it from the outside
• 1:52:32
  Speaker 2: you see a president that says he's going to bomb
• 1:52:34
  Speaker 2: he's not going to bomb he's calling off he's bombing
• 1:52:36
  Speaker 2: he's not bombing he's calling it off we've got a
• 1:52:37
  Speaker 2: deal there's no deal and you're flopping around and i
• 1:52:40
  Speaker 2: think even that as a behavior to observe from the
• 1:52:42
  Speaker 2: outside you go oh okay um.
• 1:52:44
  Speaker 1: Well let me ask you one question it kind of
• 1:52:46
  Speaker 1: makes him unpredictable right and that unpredictability can can in
• 1:52:50
  Speaker 1: some cases be an advantage i do think people have
• 1:52:52
  Speaker 1: made this case that the president's unpredictability makes it hard
• 1:52:56
  Speaker 1: for people to have a clear path on how to attack.
• 1:52:58
  Speaker 1: Like my poker player buddies, their whole poker strategy, the
• 1:53:02
  Speaker 1: guys who are the best in the world, who I'm
• 1:53:03
  Speaker 1: friends with, their whole strategy is like create randomness in
• 1:53:05
  Speaker 1: your gamesmanship so that it's very hard for someone to
• 1:53:08
  Speaker 1: exploit your gameplay. And, um, you know, I just don't
• 1:53:12
  Speaker 1: know if you know what you're going to get with
• 1:53:13
  Speaker 1: president Trump. You can meet with him and hear him
• 1:53:16
  Speaker 1: say one thing, and then he'll do something different later.
• 1:53:18
  Speaker 2: I understand the merit of that argument. In this situation,
• 1:53:21
  Speaker 2: what I'm observing now is he's become predictable. Yeah.
• 1:53:25
  Speaker 1: In terms of.
• 1:53:26
  Speaker 2: In terms of not being able to do anything.
• 1:53:29
  Speaker 1: Not taking action.
• 1:53:30
  Speaker 2: Not taking action. Threat, post, biggest strike coming since World
• 1:53:35
  Speaker 2: War II, call it off.
• 1:53:35
  Speaker 1: What would you do if you were him?
• 1:53:37
  Speaker 2: Fucking hell. What would I do? There's only bad outcomes.
• 1:53:43
  Speaker 2: So it's which bad outcome... Honestly, I think which bad
• 1:53:45
  Speaker 2: outcome am I willing to accept the most? And I
• 1:53:47
  Speaker 2: guess for someone like Trump, I don't know him, but
• 1:53:50
  Speaker 2: I guess he's probably thinking which one would save the
• 1:53:52
  Speaker 2: most face.
• 1:53:53
  Speaker 1: That's probably... the right kind of, you know, objective function
• 1:53:57
  Speaker 1: for him.
• 1:53:58
  Speaker 2: I think the worst thing is all outcomes, in my view,
• 1:54:00
  Speaker 2: lead to the Strait of Hormuz being now basically a
• 1:54:03
  Speaker 2: tool of Iranian negotiation. And it wasn't before.
• 1:54:06
  Speaker 1: New point of leverage.
• 1:54:07
  Speaker 2: Yeah, new point of leverage in that region, which is
• 1:54:09
  Speaker 2: a powerful point of leverage. Yeah.
• 1:54:10
  Speaker 1: Yeah, but it may create alternatives. There's conversation about creating
• 1:54:15
  Speaker 1: other pipelines out to Israel. Oh, yeah. And so on.
• 1:54:18
  Speaker 1: So maybe at the end of the day, it creates
• 1:54:20
  Speaker 1: incentive for other channels to be opened. I do think
• 1:54:25
  Speaker 1: it's not just about the Iranian program, but it's like,
• 1:54:28
  Speaker 1: where's all the enriched uranium? That's probably, if you're kind
• 1:54:31
  Speaker 1: of asking a military advisor, I would say that's probably
• 1:54:34
  Speaker 1: what they're thinking about is the core. Because it takes
• 1:54:35
  Speaker 1: a long time to enrich uranium to use for nuclear
• 1:54:38
  Speaker 1: fuel like this. So getting the enriched uranium is probably
• 1:54:42
  Speaker 1: a key objective.
• 1:54:43
  Speaker 2: The next election, 2028, for the presidential office, do you
• 1:54:46
  Speaker 2: think a Republican is going to win in the course
• 1:54:48
  Speaker 2: of how things are going?
• 1:54:49
  Speaker 1: For 2028? Yeah. No, I think it's going to be AOC. Okay.
• 1:54:52
  Speaker 2: You think it's going to be AOC?
• 1:54:53
  Speaker 3: Yeah.
• 1:54:54
  Speaker 1: Really? At this point.
• 1:54:56
  Speaker 2: Why?
• 1:54:57
  Speaker 1: It's all the stuff we've talked about. I just think
• 1:54:58
  Speaker 1: that that's the state of the nation. I think that's
• 1:55:01
  Speaker 1: where people are at. They want help. People feel desperate
• 1:55:04
  Speaker 1: and they want a candidate that can promise to help
• 1:55:07
  Speaker 1: make their life better. I think they're less concerned about
• 1:55:11
  Speaker 1: freedom of movement, the kind of stuff we talked about.
• 1:55:14
  Speaker 1: I think they're much more concerned about paying their bills
• 1:55:16
  Speaker 1: and getting health care and getting child care. You think
• 1:55:19
  Speaker 1: she's going to run? I think she'll run. I think
• 1:55:21
  Speaker 1: she'll beat Buttigieg and– Kamala? Kamala.
• 1:55:25
  Speaker 2: Newsom?
• 1:55:26
  Speaker 1: Newsom. I don't think Newsom is going to have like
• 1:55:29
  Speaker 1: a great presence on a national stage. I think he
• 1:55:34
  Speaker 1: looks and acts the part, but it's going to be
• 1:55:37
  Speaker 1: hard for him to sell the rest of America. And
• 1:55:40
  Speaker 1: I think Kamala is just like– it's just no one
• 1:55:42
  Speaker 1: wants to take the risk. AOC is just like Mamdani
• 1:55:46
  Speaker 1: in the sense that she brings a very different voice.
• 1:55:49
  Speaker 1: And I think this DSA movement has real legs to it.
• 1:55:51
  Speaker 1: Because I don't see a lot of young people speaking
• 1:55:53
  Speaker 1: out against the DSA movement. I see a lot of
• 1:55:56
  Speaker 1: old Democrats speaking out against the DSA movement.
• 1:55:58
  Speaker 2: You see Kamala Harris being perceived as more of a
• 1:56:00
  Speaker 2: risk than AOC? Yeah.
• 1:56:02
  Speaker 1: Because she's lost before. Oh, okay. Because she's lost before.
• 1:56:05
  Speaker 2: Yeah.
• 1:56:06
  Speaker 1: But look, what do I know?
• 1:56:08
  Speaker 2: It's interesting to you. I think I've heard you guys
• 1:56:10
  Speaker 2: on the All In podcast say before that you think
• 1:56:12
  Speaker 2: in 2020, it will be a Democrat or a socialist
• 1:56:14
  Speaker 2: that wins.
• 1:56:17
  Speaker 1: I mean, there's a lot of runway between here and there.
• 1:56:20
  Speaker 1: And look, I mean, I want to talk about the
• 1:56:23
  Speaker 1: profound frontiers in front of us, because I think that
• 1:56:27
  Speaker 1: there really is this idea. And, you know, there's a
• 1:56:29
  Speaker 1: lot of my friends who have this idea of this
• 1:56:30
  Speaker 1: golden age hypothesis that we're entering this golden age and
• 1:56:35
  Speaker 1: people don't realize we're in it, that AI unleashes this
• 1:56:39
  Speaker 1: capacity for human advancement. So the age reversal stuff. Right now,
• 1:56:44
  Speaker 1: we have a billion people in the world that are starving.
• 1:56:47
  Speaker 1: We have hundreds of millions of people dying from curable disease.
• 1:56:51
  Speaker 1: I think these are the sorts of things that are
• 1:56:52
  Speaker 1: going to get resolved more quickly than we realize. I
• 1:56:55
  Speaker 1: think that the productivity gains that are going to arise
• 1:56:57
  Speaker 1: from AI are not just going to kind of, you know,
• 1:57:01
  Speaker 1: be a battle on does the painter have a robot
• 1:57:03
  Speaker 1: or not. But I think it's going to be about
• 1:57:05
  Speaker 1: all this new stuff that's starting to be realized. Material
• 1:57:08
  Speaker 1: science is going to have a profound revolution right now.
• 1:57:12
  Speaker 1: Traveling to the moon, which might seem like a billionaire's fantasy,
• 1:57:15
  Speaker 1: but ends up becoming kind of a real, true industrial
• 1:57:19
  Speaker 1: frontier that everyone's going to participate in. There's just extraordinary
• 1:57:23
  Speaker 1: abundance that arises from this stuff. Not in the sense that, oh,
• 1:57:27
  Speaker 1: we're just making everything that we've had in the past cheaper.
• 1:57:30
  Speaker 1: But the stuff that's in front of us, the frontier
• 1:57:32
  Speaker 1: is that all of the entrepreneurs want to pursue, that
• 1:57:35
  Speaker 1: all of the dreamers see as the opportunity and the
• 1:57:37
  Speaker 1: hope for tomorrow. that all of the pragmatists are kind
• 1:57:40
  Speaker 1: of acknowledging is like legit for the first time in
• 1:57:43
  Speaker 1: our history. That's where I think there's a light kind
• 1:57:47
  Speaker 1: of rising off this horizon. I feel very good about that.
• 1:57:51
  Speaker 1: Maybe AOC gets elected. That's just my view on timing
• 1:57:53
  Speaker 1: where we sit today, sociopolitically. But I do think that
• 1:57:56
  Speaker 1: the light is rising in a way that like everyone's
• 1:57:59
  Speaker 1: going to have a profound change to their lives in
• 1:58:01
  Speaker 1: the next couple of years. So I am profoundly optimistic.
• 1:58:05
  Speaker 1: We kind of talked a lot about socialism and government
• 1:58:07
  Speaker 1: spending and all this shit today. but my experience on
• 1:58:10
  Speaker 1: the ground is just like, holy shit. And there's no
• 1:58:14
  Speaker 1: stopping it. Like this, this amazing, these amazing breakthroughs are here.
• 1:58:18
  Speaker 2: One of the things you learn when you hire lots
• 1:58:19
  Speaker 2: of people is that in every change or every announcement
• 1:58:22
  Speaker 2: you make in your company or we've raised money or
• 1:58:24
  Speaker 2: whatever it might be, there's a second question, which is
• 1:58:28
  Speaker 2: what everyone, all of your team members are actually asking.
• 1:58:30
  Speaker 1: What does it mean for me?
• 1:58:30
  Speaker 2: What does it mean for me? And actually on the ground,
• 1:58:34
  Speaker 2: talking about being on the ground, it's the 63%. They
• 1:58:38
  Speaker 2: look up and they see trillionaire, world's first trillionaire. They
• 1:58:42
  Speaker 2: see AI.
• 1:58:43
  Speaker 1: Katy Perry with the flower out the window.
• 1:58:45
  Speaker 2: They see a job displacement coming and then they go, well, listen, can't,
• 1:58:49
  Speaker 2: can't pay the bills so what's the mechanism for doing
• 1:58:51
  Speaker 2: that right now for helping the people on the ground
• 1:58:54
  Speaker 2: to benefit from the advances in this technology what would
• 1:58:57
  Speaker 2: the mechanism be.
• 1:58:58
  Speaker 1: 401ks to own this stuff would would be what we
• 1:59:00
  Speaker 1: need to change from a public policy perspective so that
• 1:59:02
  Speaker 1: they all have direct ownership in these things.
• 1:59:04
  Speaker 2: And they can look on their phone and see how
• 1:59:05
  Speaker 2: they're benefiting from i'll tell.
• 1:59:07
  Speaker 1: You everyone thinks that ai is going to accumulate to
• 1:59:09
  Speaker 1: two or three companies i don't think that's how it's
• 1:59:11
  Speaker 1: going to play out everyone's using ai and everyone's using
• 1:59:14
  Speaker 1: open source ai now meaning every company is going to
• 1:59:16
  Speaker 1: benefit from AI, which means every company is going to
• 1:59:18
  Speaker 1: have more money to pay their employees, hire more people,
• 1:59:21
  Speaker 1: train them up, do other things with them. So I'm like,
• 1:59:25
  Speaker 1: I don't buy into the narrative that Dario, Elon, and
• 1:59:28
  Speaker 1: Sam end up having all the value in AI. I
• 1:59:30
  Speaker 1: think the Chinese blew that up. I think the open
• 1:59:33
  Speaker 1: source stuff is the best thing to happen.
• 1:59:34
  Speaker 2: Doesn't that mean there's going to be a bit of
• 1:59:35
  Speaker 2: an economic collapse here?
• 1:59:37
  Speaker 1: Those data centers still need to exist to run the models.
• 1:59:40
  Speaker 2: Are we in an AI bubble in that regard? No.
• 1:59:42
  Speaker 1: This CapEx and AI, if the cost... to run a
• 1:59:46
  Speaker 1: Chinese model comes down by some number of fold over
• 1:59:51
  Speaker 1: the cost to run a proprietary model, I'm going to
• 1:59:53
  Speaker 1: run more models. I'm going to do it more. And
• 1:59:56
  Speaker 1: as I do it more, I'm going to need more compute.
• 1:59:58
  Speaker 1: I need more data centers. I need more thing to
• 2:00:00
  Speaker 1: do that. So that's where I should go. By the way,
• 2:00:02
  Speaker 1: on the data center argument, I totally buy into people's
• 2:00:05
  Speaker 1: concerns about data centers driving up the cost of energy.
• 2:00:09
  Speaker 1: The water thing is, I think, BS. But the cost
• 2:00:13
  Speaker 1: of energy thing, every data center should be on its
• 2:00:14
  Speaker 1: own grid. And every data center should make enough power
• 2:00:17
  Speaker 1: not just to be on their own grid, but to
• 2:00:18
  Speaker 1: pump energy back into the grid. If you set that
• 2:00:21
  Speaker 1: as a standard for every data center project in the
• 2:00:22
  Speaker 1: US going forward, you've solved the data center problem because
• 2:00:25
  Speaker 1: now you're dropping the price of electricity for everyone in America.
• 2:00:28
  Speaker 1: And these data centers are all off the grid. And
• 2:00:30
  Speaker 1: then everyone can own those. They can all be in
• 2:00:31
  Speaker 1: REITs and people can buy stock. And many of those
• 2:00:33
  Speaker 1: are publicly traded. So they should be in your 401k
• 2:00:37
  Speaker 1: and everyone can own a piece.
• 2:00:38
  Speaker 2: David, we have a closing tradition on this podcast where
• 2:00:40
  Speaker 2: the last guest leaves a question for the next guest
• 2:00:41
  Speaker 2: not knowing who they're leaving it for. And the question
• 2:00:43
  Speaker 2: left for you is what is one idea you have
• 2:00:46
  Speaker 2: that is uncomfortable for people to hear that you don't
• 2:00:49
  Speaker 2: typically say out loud?
• 2:00:54
  Speaker 1: I think we should end the federal student loan program
• 2:00:56
  Speaker 1: in the United States. And I think education costs will
• 2:00:59
  Speaker 1: come way down, and the private market will still provide
• 2:01:02
  Speaker 1: all the student loans that people need. I think if
• 2:01:05
  Speaker 1: the federal student loan program, because it doesn't discern colleges, degrees,
• 2:01:11
  Speaker 1: individual performance... I think that by ending that federal student
• 2:01:14
  Speaker 1: loan program, the quality of education in the U.S. will
• 2:01:16
  Speaker 1: improve dramatically and the price will drop dramatically. And more
• 2:01:20
  Speaker 1: people will have access to higher quality education. I know
• 2:01:23
  Speaker 1: it's counterintuitive, but that's what will happen. It's sort of like,
• 2:01:26
  Speaker 1: you know, Malay removed rent control in Argentina and rents declined.
• 2:01:32
  Speaker 1: We've propped up the price of education in the U.S.
• 2:01:34
  Speaker 1: with the federal student loan program. And so the federal
• 2:01:37
  Speaker 1: student loan program was replaced by a program that is accountable,
• 2:01:40
  Speaker 1: meaning the person that's underwriting the loan knows that that
• 2:01:44
  Speaker 1: loan has to perform meaning that that school has to
• 2:01:45
  Speaker 1: be good or that individual has to be doing a
• 2:01:48
  Speaker 1: good degree the market will correct itself and people will
• 2:01:53
  Speaker 1: end up getting a loan if they go to one
• 2:01:55
  Speaker 1: get one degree versus another so if you get another
• 2:01:58
  Speaker 1: if you get a bad degree you know pick your
• 2:02:01
  Speaker 1: basket weaving you know major there's no loan available but
• 2:02:05
  Speaker 1: if you get a degree in something that might be
• 2:02:07
  Speaker 1: useful and you're likely to get a job there's a
• 2:02:09
  Speaker 1: loan available.
• 2:02:10
  Speaker 2: But for those people that can't get a loan because
• 2:02:12
  Speaker 2: they want to do basket weaving, they're going to have
• 2:02:14
  Speaker 2: to go find something else to do. So they might
• 2:02:17
  Speaker 2: have to go work somewhere else.
• 2:02:18
  Speaker 1: Because the alternative was we put them in $ 200, 000 of
• 2:02:20
  Speaker 1: debt and then they didn't have a job afterwards.
• 2:02:22
  Speaker 2: Is the counter argument also that the most privileged will
• 2:02:24
  Speaker 2: get the best education? And a privilege can be intellectual
• 2:02:28
  Speaker 2: privilege or it can be financial privilege. But there'll be
• 2:02:30
  Speaker 2: a divide between, okay, you guys are all going to Harvard.
• 2:02:32
  Speaker 1: You still have a scholarship system. Scholarship system doesn't change.
• 2:02:35
  Speaker 1: You still have scholarships and it's all for that.
• 2:02:37
  Speaker 2: And education is... with AI is changing as well.
• 2:02:41
  Speaker 1: You know, I'll just say like there's a lot of
• 2:02:42
  Speaker 1: these universities that get accredited and they provide terrible education.
• 2:02:47
  Speaker 2: Yeah, it's true. And just give you debt.
• 2:02:49
  Speaker 1: And then they give you debt. And so you graduate
• 2:02:51
  Speaker 1: with a degree from, you know, whatever crappy university or college,
• 2:02:57
  Speaker 1: but you assumed that because the government gave you the loan,
• 2:02:59
  Speaker 1: you were going to have a job at the end.
• 2:03:01
  Speaker 2: Yeah, it's a scam.
• 2:03:02
  Speaker 1: It's a scam. It's one of the great lies. Imagine
• 2:03:05
  Speaker 1: if it was all privately funded. There's plenty of lenders.
• 2:03:07
  Speaker 1: I mean, the amount of money that's going into... student
• 2:03:09
  Speaker 1: loans it's actually a small percentage of what's going into
• 2:03:11
  Speaker 1: home loans so there's plenty of bank capital out there
• 2:03:14
  Speaker 1: to fund student loans so the student loan debt would
• 2:03:17
  Speaker 1: suddenly become hey if you go to this crappy university
• 2:03:19
  Speaker 1: we're not giving you two hundred thousand dollars of debt.
• 2:03:21
  Speaker 2: True i see what you're saying it would also force
• 2:03:23
  Speaker 2: people to pick things that were linked to the employment
• 2:03:26
  Speaker 2: market versus say like basket weaving use as an example
• 2:03:30
  Speaker 2: But maybe if, you know, maybe I'd be forced more
• 2:03:31
  Speaker 2: into things that had a higher guarantee of return because.
• 2:03:34
  Speaker 1: Of the private markets. And it doesn't mean.
• 2:03:36
  Speaker 2: It's a retraining mechanism in that regard.
• 2:03:37
  Speaker 1: It is. And I think this is a great reset
• 2:03:40
  Speaker 1: that's needed. If we got rid of the federal student,
• 2:03:41
  Speaker 1: because I don't think you can reform federal student loans.
• 2:03:43
  Speaker 1: It's just too complicated. But if you shut it down,
• 2:03:46
  Speaker 1: or you transition it over time and let the private
• 2:03:48
  Speaker 1: market underwrite it, you'd have a better path. David, thank you.
• 2:03:53
  Speaker 2: Thank you. Thank you to you and all your co-hosts
• 2:03:55
  Speaker 2: on the All In podcast. It's one of my favorite podcasts.
• 2:03:57
  Speaker 2: So I highly recommend everybody goes and listens to that.
• 2:03:58
  Speaker 2: I listen to it all the time and It really
• 2:04:00
  Speaker 2: helps me develop my own perspective on the world. So
• 2:04:03
  Speaker 2: I really appreciate the fact that you guys take the
• 2:04:04
  Speaker 2: time to do that amongst your very busy schedules.
• 2:04:06
  Speaker 1: Thank you for having me.
• 2:04:08
  Speaker 2: And yeah, appreciate you coming here today. And hopefully we
• 2:04:10
  Speaker 2: can continue this conversation once we get more of these
• 2:04:13
  Speaker 2: answers and the fog clears a little bit.
• 2:04:14
  Speaker 1: Absolutely.
• 2:04:15
  Speaker 2: Thank you so much. And I'll link all of your
• 2:04:16
  Speaker 2: links below for people to go read your stuff. Is
• 2:04:18
  Speaker 2: there anywhere else in particular people can get more of
• 2:04:19
  Speaker 2: your content?
• 2:04:20
  Speaker 1: All ends really where I'm at.
• 2:04:22
  Speaker 2: Okay.
• 2:04:23
  Speaker 1: Yeah.
• 2:04:23
  Speaker 2: Anywhere else follow you on social media?
• 2:04:25
  Speaker 1: Follow me on Twitter at Friedberg. I don't post very much,
• 2:04:27
  Speaker 1: but that's it. I mean, That's where I'm at.
• 2:04:31
  Speaker 2: Great. We'll see you then.
• 2:04:31
  Speaker 1: Thank you.
• 2:04:32
  Speaker 2: Thank you, David. YouTube have this new crazy algorithm where
• 2:04:34
  Speaker 2: they know exactly what video you would like to watch
• 2:04:37
  Speaker 2: next based on AI and all of your viewing behavior.
• 2:04:40
  Speaker 2: And the algorithm says that this video is the perfect
• 2:04:44
  Speaker 2: video for you. It's different for everybody looking right now.
• 2:04:47
  Speaker 2: Check this video out. I bet you, you might love it.