Latest / Motivation study / AI Experts_ What Life Will Look Like After AI Takes Over

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AI Experts_ What Life Will Look Like After AI Takes Over · Motivation study

0:00
Speaker 1: Are you optimistic about the future or pessimistic? Are we
0:03
Speaker 1: heading to a bad place if things don't change?
0:06
Speaker 2: I think we are headed to a bad place if
0:07
Speaker 2: things don't change. I'm not confident in that. I would
0:11
Speaker 2: say something like 70%. It's very, very hard to predict,
0:13
Speaker 2: of course. But yeah, it seems like the current default
0:16
Speaker 2: path is heading towards a very, very scary place.
0:19
Speaker 3: The few of Silicon Valley's top leaders have warned that
0:22
Speaker 3: AI is coming for people's jobs and fast.
0:25
Speaker 4: I'm a little bit more worried about the labor impact
0:27
Speaker 4: simply because it's happening so fast.
0:29
Speaker 5: They may not adapt fast enough.
0:31
Speaker 3: It's especially difficult for Gen Z, trying to break into
0:35
Speaker 3: a tight and rapidly changing job market. The challenge is
0:38
Speaker 3: if everyone takes that mindset of, I can't guarantee these
0:42
Speaker 3: folks are going to stick around and be my mid-level talent.
0:45
Speaker 3: I'm just going to save a buck today. If everyone
0:48
Speaker 3: does that, the entire pipeline of talent starts to collapse.
0:53
Speaker 1: You know, you're hearing about all these layoffs, and it
0:55
Speaker 1: seems that the CEOs of these companies are announcing these
0:58
Speaker 1: layoffs with a certain amount of, I wouldn't say the
0:59
Speaker 1: word is joy, but they are very keen to explain
1:03
Speaker 1: that they're laying off lots of people because of AI.
1:06
Speaker 4: The narrative that connects AI to job loss, for many
1:10
Speaker 4: of the CEOs that are doing.
1:11
Speaker 1: It, it is just too lazy. It's just too lazy.
1:14
Speaker 6: AI has just arrived.
1:15
Speaker 7: How is it possible they're already losing jobs?
1:18
Speaker 8: Amazon slashed 16,000 positions in January.
1:22
Speaker 9: Uber is cutting 23% of its people division.
1:25
Speaker 10: AI was the leading reason why employers announced layoffs in May.
1:30
Speaker 11: Public company CEO reached out to me and said, I'm
1:33
Speaker 11: going to fire 30% of my workforce and my revenue
1:35
Speaker 11: is going to go up 200%.
1:35
Speaker 1: I'm going to get a raise. What do we do?
1:40
Speaker 12: I suspect that the big tech companies are thinking, if
1:43
Speaker 12: we could be the first to get really good AI,
1:45
Speaker 12: human-level AI, then we can make a lot of money
1:49
Speaker 12: sending AI to companies so that they can replace workers.
1:52
Speaker 12: As far as I can see, that's the only place
1:54
Speaker 12: they can get their huge investments back.
1:56
Speaker 11: And a lot of folks I know who are in
1:58
Speaker 11: the industry say, I can tell they're training the AI
2:01
Speaker 11: to replace me. I'm training my own replacements.
2:04
Speaker 13: Everything's getting more expensive. Our skills are being devalued, right?
2:07
Speaker 13: So the stage is set for people to.
2:10
Speaker 4: Be really pissed off. But I think people are right
2:15
Speaker 4: to be anxious. I understand it, you know. This is
2:18
Speaker 4: not even a technological shift that happens every generation. This
2:21
Speaker 4: is one of the big ones.
2:22
Speaker 14: We are talking here about a potential social and political revolution.
2:27
Speaker 14: I mean, you can't have that number of people finding
2:29
Speaker 14: they've got no career and no job without there being
2:32
Speaker 14: absolutely massive social and political consequences.
2:35
Speaker 1: I completely agree. I've been speaking to a few people
2:38
Speaker 1: about artificial intelligence to try and understand it. And I
2:43
Speaker 1: think where I am right now is I feel quite
2:45
Speaker 1: scared But when I get scared, I don't get, it's
2:50
Speaker 1: not the type of scared that makes me anxious. It's
2:52
Speaker 1: not like an emotional scared. It's a very logical scared.
2:55
Speaker 1: It's my very logical brain hasn't been able to figure
2:57
Speaker 1: out how the inevitable outcome that I've arrived at, which
3:01
Speaker 1: is that humans become the less dominant species on this planet,
3:06
Speaker 1: how that is to be avoided in any way.
3:10
Speaker 15: So all of us be included, feel what you just described,
3:15
Speaker 15: when you first get to grips with the idea of
3:18
Speaker 15: this new coming wave. It's scary, it's petrifying, it's threatening.
3:22
Speaker 15: Is it going to take my job? Is my daughter
3:25
Speaker 15: or son going to fall in love with it? You know,
3:28
Speaker 15: what does this mean? What does it mean to be
3:30
Speaker 15: human in a world where there's these other human-like things
3:34
Speaker 15: that aren't human? How do I make sense of that?
3:36
Speaker 15: It's super scary. And a lot of people over the
3:41
Speaker 15: last few years, the default reaction has been to Avoid
3:46
Speaker 15: the pessimism and the fear, right? To just kind of
3:50
Speaker 15: recoil from it and pretend that it's like either not
3:54
Speaker 15: happening or that it's all going to work out to
3:56
Speaker 15: be rosy.
3:56
Speaker 1: It's going to be fine.
3:57
Speaker 15: We don't have to worry about it. People often say, well,
4:00
Speaker 15: we've always created new jobs. We've never permanently displaced jobs.
4:05
Speaker 15: We've only ever seen new jobs be created. Unemployment is
4:08
Speaker 15: at an all-time low, right? So there's this default optimism
4:12
Speaker 15: bias that we have. And I think it's less about
4:15
Speaker 15: a need for optimism and more about a fear of pessimism.
4:19
Speaker 15: And so that trap, particularly in elite circles, means that
4:24
Speaker 15: often we aren't having the tough conversations that we need
4:27
Speaker 15: to have in order to respond to the coming wave.
4:32
Speaker 16: I think.
4:34
Speaker 17: Maybe Microsoft just released a huge 40-page white paper looking
4:38
Speaker 17: at the jobs that are most likely to be displaced
4:40
Speaker 17: and the ones that are least likely to be displaced.
4:43
Speaker 17: When you look at it, a lot of very working,
4:45
Speaker 17: like lumbering, lumberjacks, logging, boat captains, none of those, they
4:53
Speaker 17: were the lowest down on the list. Middle management... sports broadcasters, historians, analysts,
5:00
Speaker 17: middle-level legal sort of bods, all that sort of stuff, logistics, drivers.
5:07
Speaker 17: So it really does sort of cross the spectrum. It
5:09
Speaker 17: doesn't seem like anybody's particularly safe. It doesn't look like
5:12
Speaker 17: anyone at any area is going to be protected from this.
5:15
Speaker 1: Aren't there going to be lots of new jobs created, though?
5:18
Speaker 1: Because when we think about the other.
5:20
Speaker 1: Over time, whether it was the industrial revolution or other
5:24
Speaker 1: sort of big technological revolutions. In the moment, we forecasted
5:28
Speaker 1: that everyone was going to lose their jobs, but we
5:31
Speaker 1: couldn't see all the new jobs that were being created.
5:33
Speaker 18: Because the machines replaced the human strength at a point
5:38
Speaker 18: in time, and very few places in the West today
5:42
Speaker 18: will have a worker who carry things on their back
5:46
Speaker 18: and carry it upstairs.
5:48
Speaker 19: The machine does that work, correct?
5:49
Speaker 1: Yeah.
5:51
Speaker 18: Similarly, AI is going to replace the brain of a human.
5:56
Speaker 18: There's absolutely nothing wrong with AI. There's a lot wrong
5:58
Speaker 18: with the value set of humanity at the age of
6:00
Speaker 18: the rise of the machines, right? And the biggest value
6:03
Speaker 18: set of humanity is capitalism today. And capitalism is all
6:06
Speaker 18: about what? Labor arbitrage.
6:09
Speaker 1: What's that mean?
6:10
Speaker 18: I hire you to do something, I pay you a dollar,
6:14
Speaker 18: I sell.
6:14
Speaker 1: It for two.
6:17
Speaker 18: And most people confuse that because they say, oh, but
6:19
Speaker 18: the cost of a product also includes raw materials and
6:21
Speaker 18: factories and so on and so forth.
6:23
Speaker 1: All of that is built by labor.
6:26
Speaker 18: So basically labor goes and mines for the material and
6:29
Speaker 18: then the material is sold for a little bit of margin,
6:31
Speaker 18: then that material is turned into a machine, it's sold
6:34
Speaker 18: for a little bit of margin, then that machine and
6:35
Speaker 18: so on.
6:37
Speaker 19: It's always labor arbitrage.
6:38
Speaker 18: In a world where humanity's minds are being replaced by AIs,
6:44
Speaker 18: virtual AIs, and humanity's power, strength, within three to five
6:50
Speaker 18: years' time can be replaced by a robot, you really
6:58
Speaker 18: have to question how this world looks like. It could
7:01
Speaker 18: be the best world ever. And that's what I believe
7:03
Speaker 18: the utopia will look like. Because we were never made
7:06
Speaker 18: to wake up every morning and just, you know, occupy
7:09
Speaker 18: 20 hours of our day with work, right?
7:12
Speaker 1: We're not made for that.
7:14
Speaker 18: But we've fit into that, you know, system so well
7:18
Speaker 18: so far that we started to believe it's our life's purpose.
7:27
Speaker 13: You can never really predict what jobs are coming. I mean,
7:29
Speaker 13: I think of this crazy situation where I tell my
7:33
Speaker 13: grandfather what is a personal fitness trainer. And his mind
7:38
Speaker 13: would be blown by this idea that, well, okay, I
7:42
Speaker 13: don't really want to go to the gym, so I
7:44
Speaker 13: have to make an appointment and pay someone to go
7:46
Speaker 13: to the gym and meet with me there. And then
7:48
Speaker 13: he stands there and tells me to lift heavy things
7:50
Speaker 13: that I don't really want to lift. And then he
7:52
Speaker 13: counts them and tells me that I've done a good job.
7:55
Speaker 13: And then I put the heavy things down. And then
7:58
Speaker 13: at the end of that, I feel really good and
7:59
Speaker 13: I pay him a bunch of money. My grandfather would
8:01
Speaker 13: be like, what on earth have you been scammed? So
8:05
Speaker 13: we can never predict what this future of jobs would
8:08
Speaker 13: look like. Even just 20, 30, 40 years apart, the
8:12
Speaker 13: jobs rapidly and convincingly just morph into something else. I
8:17
Speaker 13: think it's very dangerous, the idea that we need to
8:20
Speaker 13: focus on skills. I think the future is not in skills.
8:23
Speaker 13: Skills are being replaced now. It's this idea that the
8:25
Speaker 13: education system has to stop being compartmentalized and has to
8:28
Speaker 13: be a lifelong learning approach. The Department of Education needs
8:33
Speaker 13: to be seeing people as lifelong learners who are constantly
8:36
Speaker 13: disrupted and need re-education.
8:38
Speaker 1: Interesting.
8:39
Speaker 5: That's going to be a thing.
8:41
Speaker 13: The Department of Education needs to start as a kid
8:44
Speaker 13: and go right through to maybe 70.
8:46
Speaker 1: Does the Department of Education have a role anymore at all?
8:49
Speaker 5: Depends on your definition of education.
8:50
Speaker 13: I think if you're trying to teach kids or if
8:53
Speaker 13: you're trying to teach kids to, you know, remember facts
8:56
Speaker 13: and figures from a history book, then no. But if
9:01
Speaker 13: it's about coaching, mentoring, being displaced, finding the next thing,
9:05
Speaker 13: and maybe if it's AI driven and all of those
9:07
Speaker 13: kinds of things, then it's a different paradigm shift around
9:10
Speaker 13: what education is and what its purpose is.
9:14
Speaker 20: It's worth backing up and thinking about like, what is
9:16
Speaker 20: it that makes humans valuable workers? I don't think it's
9:20
Speaker 20: mainly their raw intellect. I think it's their ability... When
9:24
Speaker 20: you work with people, why are they basically useless the
9:27
Speaker 20: first month or the first week? And you couldn't live
9:30
Speaker 20: without them six months later. It's their ability to build
9:33
Speaker 20: up context. It's their ability to interrogate their own failures
9:37
Speaker 20: and learn from them in this really organic way.
9:39
Speaker 9: And....
9:41
Speaker 20: This ability just doesn't exist in these models. They exist
9:44
Speaker 20: session to session and everything that they have learned about
9:48
Speaker 20: you evaporates after every hour. And so it's a frustrating
9:52
Speaker 20: experience where you can try to get them to do
9:54
Speaker 20: a task. uh they'll do a five out of ten
9:56
Speaker 20: job at many language in language out tasks but there's
9:59
Speaker 20: no way for them to get better and given that
10:01
Speaker 20: that's a fact you just kind of have to like
10:02
Speaker 20: rely on humans.
10:04
Speaker 17: Uh it's like 50 first dates over and over every
10:07
Speaker 17: time that you do it you've got you've got to
10:08
Speaker 17: reintroduce yourself and explain what's going on.
10:10
Speaker 20: Yeah groundhog day yeah yeah that's right So I think
10:15
Speaker 20: people have this idea that even if all AI progressed
10:17
Speaker 20: up right now, these systems would still be economically transformative.
10:20
Speaker 20: And they say, look, JP Morgan and McDonald's and whatever
10:22
Speaker 20: just haven't integrated these systems into their workflows. But if
10:24
Speaker 20: they had, they would be seeing all these benefits. And
10:27
Speaker 20: I don't really think that's the case. I think it's
10:29
Speaker 20: just genuinely hard to get human-like labor out of these models.
10:34
Speaker 1: And hopefully in your closing remarks, you can capture something
10:37
Speaker 1: actionable for the individual that's listening to this now on
10:41
Speaker 1: their commute to work or the single mother, the average
10:43
Speaker 1: person who maybe isn't as technologically advanced as many of
10:46
Speaker 1: us at this table, but is trying to navigate through
10:49
Speaker 1: this to figure out how to live a good life
10:51
Speaker 1: over the next 10, 20, 30 years.
10:53
Speaker 7: I think we live in the most interesting time in
10:57
Speaker 7: human history. So for the single mother that's listening, for
11:00
Speaker 7: someone who wouldn't be the stereotype of a tech bro,
11:04
Speaker 7: Don't assume that you can't do this stuff. It's never
11:08
Speaker 7: been more accessible today within your work. You can be
11:11
Speaker 7: an entrepreneur. You don't have to take massive risk to
11:14
Speaker 7: go create a business, quit your job and go create
11:18
Speaker 7: a business. So I really want people to break away
11:25
Speaker 7: from this concept of entrepreneurship being, this is your podcast,
11:30
Speaker 7: Diary of a CEO. You started this podcast. by talking
11:33
Speaker 7: to CEOs, I assume, right? And over time, it changed
11:38
Speaker 7: to everyone can be a CEO. Everyone is some kind
11:41
Speaker 7: of CEO in their life. I think that we have
11:46
Speaker 7: unprecedented access to tools for that vision to actually come
11:51
Speaker 7: to reality.
11:51
Speaker 21: I think the potential here does allow us to refactor
11:58
Speaker 21: just about everything. Maybe we have finally arrived at the
12:01
Speaker 21: place where mundane work doesn't need to exist anymore and
12:06
Speaker 21: the pursuit of meaning can replace it. But that's not
12:09
Speaker 21: going to happen automatically if we don't figure out how
12:11
Speaker 21: to make it happen. And I hope that we can
12:15
Speaker 21: recognize that the peril of this moment is best utilized
12:20
Speaker 21: if it motivates us to confront that question directly.
12:25
Speaker 1: The International Monetary Fund has expressed profound concerns that generative
12:28
Speaker 1: AI could cause massive labor disruptions and rising inequality and
12:33
Speaker 1: has called for policies that prevent this from happening. I
12:36
Speaker 1: read that in the Business Insider. Have they given any
12:39
Speaker 1: idea what the policies should look like?
12:41
Speaker 9: No.
12:42
Speaker 1: Yeah, that's the problem.
12:43
Speaker 22: I mean, if AI can make everything much more efficient
12:45
Speaker 22: and get rid of people for most jobs, or have
12:48
Speaker 22: a person assisted by AI doing many, many people's work, it's.
12:54
Speaker 1: Not obvious what to do about it. Universal basic income?
12:58
Speaker 1: Give everybody money?
12:59
Speaker 22: Yeah, I think that's a good start. And It stops
13:04
Speaker 22: people starving. But for a lot of people, their dignity
13:07
Speaker 22: is tied up with their job. I mean, who you
13:09
Speaker 22: think you are is tied up with you doing this job, right?
13:12
Speaker 23: Yeah.
13:13
Speaker 22: And if we said, we'll give you the same money
13:16
Speaker 22: just to sit around, that would impact your dignity.
13:22
Speaker 15: Everywhere you look in the next 50 years, we have
13:27
Speaker 15: to do more with less. And there are very, very
13:30
Speaker 15: few proposals let alone practical solutions for how we get there.
13:37
Speaker 15: Training machines to help us as aides, scientific research partners, inventors,
13:44
Speaker 15: creators is absolutely essential. And so the upside is phenomenal.
13:50
Speaker 15: It's enormous. But AI isn't just a thing. It's not
13:55
Speaker 15: an inevitable whole. Its form isn't inevitable, right? Its form
14:02
Speaker 15: is the exact way that it manifests and appears in
14:05
Speaker 15: our everyday lives and the way that it's governed and
14:07
Speaker 15: who it's owned by and how it's trained, that is
14:11
Speaker 15: a question that is up to us collectively as a
14:14
Speaker 15: species to figure out over the next decade. Because if
14:18
Speaker 15: we don't embrace that challenge, then it happens to us.
14:23
Speaker 15: And that's really what I'm I have been wrestling with
14:26
Speaker 15: for 15 years of my career is how to intervene
14:31
Speaker 15: in a way that this really does benefit everybody. And
14:34
Speaker 15: those benefits far, far outweigh the potential risks.
14:40
Speaker 1: Do you think the people building these AI companies believe
14:44
Speaker 1: that the outcome is going to be all good? It's
14:47
Speaker 1: going to be, it's going to serve everyone. It's going
14:49
Speaker 1: to be the age of abundance. Everything's going to go well.
14:52
Speaker 1: Do you think they believe?
14:54
Speaker 9: These companies tell us that AI is going to benefit
14:57
Speaker 9: everyone and that's their mission. But you really start to
15:00
Speaker 9: see that rhetoric break down when you go to the
15:03
Speaker 9: places that look nothing like Silicon Valley.
15:07
Speaker 3: The jobs most exposed to AI, like coding and accounting,
15:11
Speaker 3: have seen a 13% drop in employment for workers under 25.
15:16
Speaker 18: We think 50% of entry-level jobs are going to be
15:18
Speaker 18: eliminated in the next five years.
15:20
Speaker 1: How many was that?
15:21
Speaker 6: How many was that right?
15:22
Speaker 1: 50%. Driving, I think, is one of the biggest employees
15:26
Speaker 1: in the world.
15:27
Speaker 19: I mean, we've got nine and a half million drivers
15:29
Speaker 19: and couriers on our platform.
15:31
Speaker 7: Amazon announcing its largest job cuts in years.
15:34
Speaker 5: Job listings in both the US and UK are plummeting.
15:39
Speaker 16: You know, if the CEO of one of those companies
15:40
Speaker 16: was to say, we're not going to do this anymore,
15:42
Speaker 16: they would just be replaced. Because the investors are putting
15:46
Speaker 16: their money up because they want to create AGI and
15:49
Speaker 16: reap the benefits of it.
15:54
Speaker 19: You can imagine the majority of our trips being fulfilled
15:58
Speaker 19: by robots probably not 10 years from now, but you
16:01
Speaker 19: go 15, 20 years from now, you're going to start
16:04
Speaker 19: getting there.
16:04
Speaker 1: What do the 9 million people do?
16:05
Speaker 19: I don't know.
16:10
Speaker 1: What are the occupations that you genuinely believe won't exist
16:15
Speaker 1: five years from now as we know them? People say
16:18
Speaker 1: lawyers are going to be disrupted.
16:20
Speaker 13: Well, I recently had a legal case that I had
16:23
Speaker 13: to resolve And it was going to cost us £ 50, 000,
16:27
Speaker 13: so $ 60, 000, as a start the process with a law firm.
16:31
Speaker 13: We took matters into our own hands and we used
16:33
Speaker 13: Claude and we actually fixed the process and resolved the
16:36
Speaker 13: process by spending $ 20 a month. And Claude gave us
16:40
Speaker 13: a coaching session on how to handle it, gave us
16:43
Speaker 13: multiple decision tree pathways, gave us the documents that we
16:47
Speaker 13: would need. gave us an Excel spreadsheet of do say this,
16:50
Speaker 13: don't say this in the negotiation.
16:52
Speaker 5: And it made me realize, my goodness, what are lawyers
16:54
Speaker 5: going to do?
16:55
Speaker 13: Because if all they do is charge for time for
16:58
Speaker 13: money to regurgitate contracts, I don't need that anymore, right?
17:03
Speaker 1: Multiple reports say legacy legal tech and data firms have
17:06
Speaker 1: lost roughly 20% of their value so far in 2026.
17:10
Speaker 13: $ 280 billion was wiped off the value of publicly traded
17:12
Speaker 13: companies like that in the last week.
17:15
Speaker 5: Like, it's wild. because we're not going to need that.
17:19
Speaker 13: I don't believe we're going to need these business models
17:22
Speaker 13: as they currently stand.
17:23
Speaker 5: I think they're going to have to change and adapt.
17:25
Speaker 13: I think a lawyer needs to take a completely different shape,
17:28
Speaker 13: part business coach, part lawyer, part prompt engineer. They're going
17:31
Speaker 13: to be the key person of AI in the room
17:34
Speaker 13: who the lawyer's job will be to work with you
17:36
Speaker 13: on your AI prompting and help you get the resolution.
17:40
Speaker 13: You're probably going to need a lot less of a
17:41
Speaker 13: lawyer's time. Blue-collar work has been devalued. And we've seen
17:45
Speaker 13: people who work with their hands and people who turn
17:48
Speaker 13: up to your house and fix your house in a
17:51
Speaker 13: devalued role.
17:52
Speaker 5: And it could be in the next.
17:55
Speaker 13: Couple of years, these are the roles that are elevated
17:58
Speaker 13: the most and that plumbers regularly earn more than lawyers.
18:02
Speaker 5: But it is really this human thing.
18:04
Speaker 24: And I don't know if machines will have these things
18:11
Speaker 24: in the future, but for certain, we do. And there
18:15
Speaker 24: will be jobs where we want to have people. If
18:20
Speaker 24: I'm in a hospital, I want a human being to
18:24
Speaker 24: hold my hand while I'm anxious or in pain. The
18:31
Speaker 24: human touch is going to, I think, take more and
18:35
Speaker 24: more value as the other skills.
18:40
Speaker 5: Become more and more automated.
18:44
Speaker 1: At some point, I think what remains is actually the
18:48
Speaker 1: IRL irreplaceably human stuff. Human to human. Our Maslowian needs
18:52
Speaker 1: of being in person like we are now aren't going
18:54
Speaker 1: to change. We need connection. Humans get very sick when
18:57
Speaker 1: they don't have other human beings in their life and strong,
19:00
Speaker 1: deep relationships.
19:01
Speaker 9: I 100% agree.
19:02
Speaker 1: So that stuff is going to matter a whole lot.
19:04
Speaker 1: I have this contrarian weird take that actually maybe this
19:06
Speaker 1: is the first technology that's going to deliver on the
19:09
Speaker 1: promise of making us human and connected. Because we're going
19:11
Speaker 1: to be rendered useless at everything else other than what
19:13
Speaker 1: humans are good at. Because all the other technologies said, oh,
19:16
Speaker 1: we're going to make you more connected. Connecting the world.
19:18
Speaker 1: And they disconnected the world and isolated the world. But
19:20
Speaker 1: maybe this is the one that's so intelligent now that
19:22
Speaker 1: it doesn't need us to fuck around in spreadsheets anymore.
19:24
Speaker 5: Do you see.
19:27
Speaker 9: That actually happening in real time right now? That it's
19:30
Speaker 9: making us more able to be in person, connected with
19:34
Speaker 9: one another, having deeper social community engagements?
19:39
Speaker 19: Yes. Yes.
19:40
Speaker 1: And I'll give you some data points. Okay. Data point
19:42
Speaker 1: number one. The Financial Times released a report on social
19:46
Speaker 1: media usage and what they saw is 2022 was the
19:50
Speaker 1: peak and it's plateaued ever since. The generation that's plateaued
19:53
Speaker 1: the fastest and heading down. is the younger generations. The
19:56
Speaker 1: boomers are still off to the races, right? On Facebook
19:59
Speaker 1: and stuff. And then you look at the way Gen
20:01
Speaker 1: Alpha are using social media. They're not posting as much.
20:04
Speaker 1: They call it posting zero. They're scrolling sometimes, but they're
20:07
Speaker 1: in dark social environments like WhatsApp and Snapchat and iMessage.
20:10
Speaker 1: They're not like performing to the world. They also value
20:13
Speaker 1: IRL experiences much more than any other generation. They're like
20:15
Speaker 1: not getting smashed. We're seeing every brand has a run club.
20:18
Speaker 1: And we're seeing this real sort of, sort of almost
20:21
Speaker 1: like innate, that like technology let us down at some
20:26
Speaker 1: fundamental level. Like dating apps let us down, social networking
20:29
Speaker 1: kind of has let us down. And we're seeing, I think,
20:32
Speaker 1: maybe a bifurcation of society where a lot of people
20:34
Speaker 1: are going back this, like I want to go back
20:35
Speaker 1: to what it is to be a human. Yeah. I
20:38
Speaker 1: was looking at the top 10 jobs according to AI
20:42
Speaker 1: that are most likely to be disrupted. And it said
20:44
Speaker 1: things like drivers with McKinsey estimating 30% of them will
20:46
Speaker 1: be automated by 2030. Customer service, representative and call center reps,
20:50
Speaker 1: which I used to be. Mm-hmm. 50% headcount reductions after
20:54
Speaker 1: AI rollout, according to some estimates, some go up to
20:56
Speaker 1: about 80%. I actually saw a tool on my timeline
20:59
Speaker 1: yesterday that is real human voice, indistinguishable from humans, that's
21:04
Speaker 1: just launched and is causing a huge stir. So they're
21:06
Speaker 1: thinking that will replace even more of the customer service roles.
21:10
Speaker 1: I did speak to the CEO of Klarna. TLDR, as
21:13
Speaker 1: he said, we currently have 7,000 employees. We're going to
21:16
Speaker 1: be able to get down to 3,000, he said, after
21:19
Speaker 1: summer because of AI rollout. And we'll be using our
21:25
Speaker 1: existing team members that are in customer service roles to
21:28
Speaker 1: do more sort of bespoke white glove VIP stuff.
21:30
Speaker 13: VIP stuff will go up. In fact, Jevlin's paradox would
21:34
Speaker 13: suggest that a lot of the dehumanizing repetitive work will
21:40
Speaker 13: go away. But actually, if there are AI bots that
21:45
Speaker 13: are really good at setting appointments for a VIP human
21:49
Speaker 13: person to have a conversation, then that work will go
21:51
Speaker 13: through the roof. Because one of the reasons that people,
21:54
Speaker 13: like right now, most companies wish they could have more
21:57
Speaker 13: VIP conversations, but the appointment setting, they don't have a
22:00
Speaker 13: lot of the low-level appointment setting stuff happening. And if
22:03
Speaker 13: the appointment setting stuff, if the cost of that goes
22:05
Speaker 13: to zero, then the affordability of the VIP-level treatment becomes
22:13
Speaker 13: much more feasible.
22:14
Speaker 1: Retail cashers, admin assistants, bookkeepers, and payroll clerks, sales, development reps,
22:18
Speaker 1: warehouse workers with... Amazon and others reporting that robots now
22:23
Speaker 1: assist or replace labor in roughly 40% of fulfillment tasks.
22:26
Speaker 1: And that Boston Dynamics video, which I'll put up on
22:27
Speaker 1: the screen, shows a humanoid robot working in a factory.
22:30
Speaker 13: What's nice about some of this is that many of
22:33
Speaker 13: the jobs here are jobs that a lot of people
22:35
Speaker 13: don't actually like doing. They are repetitive and dehumanizing.
22:39
Speaker 5: They're late night. They're early mornings.
22:41
Speaker 13: So potentially, provided there is a Jevlin's paradox that something
22:46
Speaker 13: happens that's more fun.
22:47
Speaker 5: More humanizing, more interesting, more VIP.
22:50
Speaker 13: more chaotic and, you know, all of that sort of stuff,
22:53
Speaker 13: it could be a very positive thing.
22:56
Speaker 9: But people also want human experiences. So it's not actually
23:00
Speaker 9: just about the capabilities of the models. It's also about
23:03
Speaker 9: what people want. Some things they would turn to AI
23:07
Speaker 9: for and some things they wouldn't, irrespective of whether or
23:10
Speaker 9: not AI is.
23:11
Speaker 8: Capable of doing it.
23:13
Speaker 9: But because of a preference that they want human-to-human interaction.
23:18
Speaker 9: And so what we're seeing right now is, yeah, the
23:23
Speaker 9: thing that happens with every wave of automation, which is
23:26
Speaker 9: that there is a bunch of entry-level work that gets
23:29
Speaker 9: automated away. And there are also new jobs created, but
23:33
Speaker 9: the jobs that are created are in one of two categories.
23:37
Speaker 9: There are people that get even higher skilled jobs. And
23:41
Speaker 9: what he was saying, we pay people more for the
23:43
Speaker 9: handcrafted code now. And there's also the people who get
23:47
Speaker 9: way worse jobs. And so there was this amazing article
23:51
Speaker 9: in New York Magazine that was talking about how a
23:55
Speaker 9: lot of people are getting laid off. And then... They
23:59
Speaker 9: end up working in data annotation, which is the labor
24:03
Speaker 9: that I've been referring to throughout this conversation that companies
24:05
Speaker 9: need in order to teach their models the next thing
24:09
Speaker 9: that the companies are trying to automate. And so like
24:12
Speaker 9: a marketer gets laid off and then they go and
24:15
Speaker 9: work for a data annotation firm to train the models
24:19
Speaker 9: on the very job that they were just laid off in,
24:23
Speaker 9: which will then perpetuate more layoffs if that model then
24:27
Speaker 9: develops that skill. And the article was talking about how
24:31
Speaker 9: this has become a huge catch-all for a lot of
24:38
Speaker 9: people that are struggling with finding job opportunities right now,
24:41
Speaker 9: including award-winning directors in Hollywood that are actually secretly doing
24:46
Speaker 9: this data annotation work to put food on the table.
24:49
Speaker 9: And so when they talk about There's going to be
24:53
Speaker 9: mass unemployment, and then there's going to be some new
24:56
Speaker 9: jobs created that we can't even imagine. I think a
24:58
Speaker 9: lot of these narratives rarely talk about the jobs. A
25:02
Speaker 9: lot of the jobs that are created are way worse
25:05
Speaker 9: than the jobs that were there. And it breaks the
25:08
Speaker 9: career ladder. So it's the entry-level and the mid-tier jobs
25:12
Speaker 9: that get gouged out. It's higher-order jobs and then way
25:16
Speaker 9: more lower-order jobs that get created.
25:20
Speaker 5: And so how do.
25:22
Speaker 9: People continue to progress in their careers. There's no more
25:25
Speaker 9: rungs on the ladder.
25:26
Speaker 1: Now, driving, I think, is one of the biggest employees
25:28
Speaker 1: in the world, like as a profession.
25:30
Speaker 19: I mean, we've got nine and a half million drivers
25:33
Speaker 19: and couriers on our platform. We are the largest organizer
25:37
Speaker 19: of flexible work around the world. And I think the
25:40
Speaker 19: second largest workforce is the Chinese army.
25:43
Speaker 9: Wow.
25:44
Speaker 19: Yeah. It's a big group of folks that we've organized.
25:47
Speaker 1: And statistically, there's less accidents in an autonomous Tesla than
25:51
Speaker 1: there is if a human drives it. So it's safer
25:54
Speaker 1: for my car to drive itself statistically than for me
25:56
Speaker 1: to drive it. That's true, right? That the autonomous driving
25:58
Speaker 1: is currently safer. Those 9 million drivers' careers that you
26:02
Speaker 1: have will be out of work, conceivably. Talking about being
26:06
Speaker 1: honest about the situation.
26:08
Speaker 19: Yeah, I think, again, it goes to physical AI as well, right?
26:11
Speaker 19: So I think 20 years from now, you can imagine
26:14
Speaker 19: that those 9 million will be 20 million AVs maybe,
26:20
Speaker 19: but we have time between now and then, partially because
26:24
Speaker 19: we don't operate in the virtual world, right? We operate
26:26
Speaker 19: in the physical world. You have to get the regulations up.
26:28
Speaker 19: You have to build the cars. You have to build
26:30
Speaker 19: the sensor stacks. The models have to get there. So
26:33
Speaker 19: there is time between now and then, but you can
26:36
Speaker 19: imagine the majority of our trips being fulfilled by robots
26:42
Speaker 19: of some kind, probably not 10 years from now, but
26:46
Speaker 19: you go 15, 20 years from now, you're going to
26:48
Speaker 19: start getting there.
26:50
Speaker 1: What do the 9 million people do?
26:53
Speaker 19: I don't know. Now we are expanding the kind of
26:57
Speaker 19: work that's available on, on, on the platform partially as
27:00
Speaker 19: a result of it, right? We used to be the
27:02
Speaker 19: only work is driving. Now there's delivering, you can have
27:06
Speaker 19: shoppers as well. I think it'll be a little while
27:08
Speaker 19: at least before you get AI shoppers. And now actually
27:12
Speaker 19: we have a team called Uber AI solutions, that allows
27:16
Speaker 19: people to train these same agents and train AI agents
27:21
Speaker 19: and AI models and do all kinds of knowledge-based work
27:26
Speaker 19: on their phone as well to kind of extend the
27:30
Speaker 19: kind of work that we offer humans on our platform
27:33
Speaker 19: and different opportunities for them to make money. So we
27:37
Speaker 19: are extending the platform. And then the question is how
27:39
Speaker 19: much of the platform gets automated and what's the velocity
27:43
Speaker 19: at which we can extend our platform into other kinds
27:45
Speaker 19: of work versus the velocity of automation. I can't tell
27:48
Speaker 19: you which is going to go faster.
27:49
Speaker 1: Hand on heart, though, it does appear that unemployment is
27:53
Speaker 1: going to be significantly increased in a world of AI,
27:55
Speaker 1: especially we just imagine this sort of continual rate of improvement.
27:59
Speaker 1: I just can't. You would have to.
28:01
Speaker 19: Unless, again, historically in societies, new kinds of jobs have
28:06
Speaker 19: come up.
28:07
Speaker 1: Knowledge jobs, physical jobs.
28:08
Speaker 6: Yeah.
28:09
Speaker 1: Now we've disrupted both.
28:11
Speaker 19: That's why. There's a question here. And I do think
28:14
Speaker 19: there's a real question as to the ability of societies
28:16
Speaker 19: to retrain, the abilities of human beings to retrain themselves.
28:21
Speaker 19: AI is going to be a part of that. But
28:23
Speaker 19: the timing there, how fast is it going to go?
28:26
Speaker 19: It's a real question mark. I think you're absolutely right.
28:28
Speaker 19: I don't think it's going to be a big issue
28:33
Speaker 19: in the next five years. But when you go five
28:35
Speaker 19: plus years, it's going to become more of an issue
28:38
Speaker 19: for society at large.
28:40
Speaker 16: The question of, well, if everything goes right, if we
28:43
Speaker 16: create AGI, we figure out how to make it safe,
28:46
Speaker 16: we achieve all these economic miracles, then you face a problem.
28:50
Speaker 1: And this is not a new problem.
28:53
Speaker 16: So John Maynard Keynes, who was a famous economist in
28:56
Speaker 16: the early part of the 20th century, wrote a.
28:58
Speaker 5: Paper in 1930.
28:59
Speaker 16: So this is in the depths of the Depression. It's
29:03
Speaker 16: called On the Economic Problems of Our Grandchildren. He predicts
29:06
Speaker 16: that at some point science will evolve will deliver sufficient
29:11
Speaker 16: wealth that no one will have to work ever again.
29:14
Speaker 16: And then man will be faced with his true eternal problem.
29:20
Speaker 16: How to live, I don't remember the exact word, but
29:22
Speaker 16: how to live wisely and well when the economic incentives,
29:27
Speaker 16: the economic constraints are lifted. We don't have an answer
29:31
Speaker 16: to that question, right? So AI systems are doing pretty
29:35
Speaker 16: much everything we currently call work. Anything you might aspire to,
29:40
Speaker 16: like you want to become a surgeon, it takes the
29:44
Speaker 16: robot seven seconds to learn how to be a surgeon
29:46
Speaker 16: that's better than any human being.
29:48
Speaker 1: Elon said last week that the humanoid robots will be
29:51
Speaker 1: 10 times better than any surgeon that's ever lived. Quite possibly, yeah.
29:56
Speaker 5: Well, and they'll also have, you know, hands.
29:59
Speaker 16: They'll have hands that are, you know, a millimeter in
30:01
Speaker 16: size so they can go inside and do all kinds
30:04
Speaker 16: of things that humans can't do. And I think we
30:06
Speaker 16: need to put serious effort into this question. What is
30:10
Speaker 16: a world where AI can do all forms of human
30:15
Speaker 16: work that you would want your children to live in?
30:19
Speaker 5: What does that world look like?
30:21
Speaker 16: Tell me the destination so that we can develop a
30:25
Speaker 16: transition plan to get there. And I've asked AI researchers, economists,
30:30
Speaker 16: science fiction writers, futurists, no one has been able to
30:35
Speaker 16: describe that world. The kind of AI systems we're building now,
30:42
Speaker 16: we don't understand how they work.
30:44
Speaker 1: We don't understand how they work.
30:46
Speaker 16: With most machines, we designed it to have a certain behavior.
30:50
Speaker 16: So we don't need to pull it apart and see
30:52
Speaker 16: what the cogs are because we put the cogs in
30:54
Speaker 16: there in the first place. One by one, we figured
30:56
Speaker 16: out what... what the pieces needed to be, how they
31:00
Speaker 16: work together to produce the effect that we want.
31:03
Speaker 6: It's like a.
31:03
Speaker 1: Chain link fence.
31:04
Speaker 16: Lots of these connections, and each of those connections can be,
31:08
Speaker 16: its connection strength can be adjusted. And you just keep
31:12
Speaker 16: adjusting all the connection strengths in this network until the
31:14
Speaker 16: outputs of the network are the ones you want.
31:17
Speaker 25: There are points where humans should assert control. And I've
31:21
Speaker 25: been trying to think about where are they? I'll give
31:23
Speaker 25: you an example. There's something called recursive self-improvement. where the
31:26
Speaker 25: system just keeps getting smarter and smarter and learning more
31:29
Speaker 25: and more things. At some point, if you don't know
31:33
Speaker 25: what it's learning, you should unplug it.
31:35
Speaker 1: But we can't unplug them, can we?
31:36
Speaker 19: Sure you can.
31:37
Speaker 5: There's a power plug and there's a circuit breaker.
31:39
Speaker 1: Go and turn the circuit breaker off.
31:43
Speaker 15: These technologies are omni-use. So the same core technology can
31:47
Speaker 15: be used to identify, you know, cancerous tumors in chest x-rays.
31:54
Speaker 15: as it can to identify a target on the battlefield
31:57
Speaker 15: for an aerial strike. So that mixed use or omni
32:01
Speaker 15: use is going to drive the proliferation because there's huge
32:05
Speaker 15: commercial incentives because it's going to deliver a huge benefit
32:08
Speaker 15: and do a lot of good. And that's the challenge
32:11
Speaker 15: that we have to figure out is how to stop
32:13
Speaker 15: something which on the face of it is so good,
32:17
Speaker 15: but at the same time can be used in really
32:19
Speaker 15: bad ways too.
32:20
Speaker 1: What is your biggest fear about AI?
32:23
Speaker 25: My actual fear is different from what you might imagine.
32:25
Speaker 25: My actual fear is that we're not going to adopt
32:27
Speaker 25: it fast enough to solve the problems that affect everybody.
32:31
Speaker 25: And the reason is that if you look at everyone's
32:35
Speaker 25: everyday lives, what do they want? They want safety. They
32:39
Speaker 25: want health care. They want great schools for their kids.
32:42
Speaker 25: Let me just work on that for a while. Why
32:44
Speaker 25: don't we make people's lives just better because of AI?
32:47
Speaker 25: You will not notice how much of your world has
32:52
Speaker 25: been co-opted buy these technologies because they will produce greater delight.
32:57
Speaker 25: If you think about it, a lot of life is inconvenient.
33:02
Speaker 25: It's fix this, call this, make this happen. AI systems
33:05
Speaker 25: should make all that seamless. You should be able to
33:07
Speaker 25: wake up in the morning and have coffee and not
33:09
Speaker 25: have a care in the world and have the computer
33:11
Speaker 25: help you have a great day.
33:14
Speaker 23: So I'll ask my Uber driver, are you worried about
33:16
Speaker 23: self-driving cars? And they go, nope. No one can do
33:19
Speaker 23: what I do. I know the streets of New York.
33:22
Speaker 23: I can navigate like no AI. I'm safe. And it's
33:26
Speaker 23: true for any job. Professors are saying this to me. Oh,
33:29
Speaker 23: nobody can lecture like I do. Like this is so special.
33:32
Speaker 23: But you understand it's ridiculous. We already have self-driving cars
33:35
Speaker 23: replacing drivers. That is not even a question if it's possible.
33:41
Speaker 1: It's like how.
33:41
Speaker 23: Soon before you're fired. Here we're inventing. a replacement for
33:47
Speaker 23: human mind, a new inventor capable of doing new inventions.
33:51
Speaker 23: It's the last invention we ever have to make. At
33:54
Speaker 23: that point, it takes over. And the process of doing science, research,
33:58
Speaker 23: even ethics research, morals, all that is automated at that point.
34:03
Speaker 16: And I think we need to put serious effort into
34:06
Speaker 16: this question. What is a world where AI can do
34:11
Speaker 16: all forms of human work that you would want your
34:14
Speaker 16: children to live in?
34:17
Speaker 5: What does that world look like?
34:19
Speaker 16: Tell me the destination so that we can develop a
34:23
Speaker 16: transition plan to get there.
34:26
Speaker 13: I think the industrial age created a bunch of jobs
34:28
Speaker 13: that are very dehumanizing and we've just kind of gotten
34:31
Speaker 13: used to them and put up with them. The idea
34:33
Speaker 13: that work should be repetitive and, you know, you just
34:36
Speaker 13: repeat the same loop over and over and over again.
34:39
Speaker 13: And over a 10 year period of time, you might get,
34:42
Speaker 13: you know, graduated up one gear and all that kind
34:44
Speaker 13: of stuff.
34:44
Speaker 5: I don't think that's very human.
34:46
Speaker 13: Um, The idea that you could be simultaneously writing a book,
34:50
Speaker 13: launching a business, running a team, launching a festival, having
34:54
Speaker 13: an event, that you could actually be doing this kind
34:59
Speaker 13: of like mini kingdom work where you've got this little
35:04
Speaker 13: ecosystem around you of fun things that you're involved in.
35:07
Speaker 13: That is actually made possible for a vast majority of
35:10
Speaker 13: people if they embrace these kind of tools. You can
35:13
Speaker 13: live an incredibly... fulfilling and amazing and impactful existence. I
35:19
Speaker 13: know that I do as a result of having these
35:21
Speaker 13: tools in my life. I'm doing things that I could
35:24
Speaker 13: have only dreamed about as a kid.
35:26
Speaker 25: My own view is that there will be a lot
35:29
Speaker 25: of job dislocation, but there will be a lot more jobs,
35:33
Speaker 25: not fewer jobs.
35:34
Speaker 1: And here's why.
35:36
Speaker 25: We have a demographic problem in the world, especially in
35:39
Speaker 25: the developed world, where we're not having enough children.
35:42
Speaker 1: That's well understood.
35:44
Speaker 25: Furthermore, we have a lot of older people, and the
35:47
Speaker 25: younger people have to take care of the older people,
35:48
Speaker 25: and they have to be more productive. If you have
35:50
Speaker 25: young people who need to be more productive, the best
35:52
Speaker 25: way to make them more productive is to give them
35:54
Speaker 25: more tools to make them more productive, whether it's a
35:59
Speaker 25: machinist that goes from a manual machine into a CNC machine,
36:02
Speaker 25: or in the more modern case of a knowledge worker
36:05
Speaker 25: who can achieve more objectives.
36:07
Speaker 5: We need that productivity group.
36:10
Speaker 8: I have real fear when it comes to, like, productivity
36:13
Speaker 8: and the reshaping of business. You know, technologists and people
36:16
Speaker 8: who were part of the internet revolution, they love to say,
36:19
Speaker 8: you know, 20 years ago, 80% of the jobs we
36:21
Speaker 8: have now didn't exist. They love to say that, right?
36:24
Speaker 8: But when you ask them now, they seem to think,
36:29
Speaker 8: I think it's the same, which is all those people
36:30
Speaker 8: who are going to lose those jobs in white collar,
36:32
Speaker 8: you know, white collar jobs and knowledge workers, they're not
36:34
Speaker 8: going to not work. There's going to be new jobs.
36:37
Speaker 8: The IRS digitized a whole bunch of years ago. They
36:40
Speaker 8: got rid of all the accountants and they put in
36:42
Speaker 8: all the computers. Do you know how much money the
36:45
Speaker 8: IRS saved when it completely changed the way it looked?
36:50
Speaker 6: The answer is zero.
36:51
Speaker 8: Yes, they got rid of all the accountants and they
36:53
Speaker 8: need to hire all the IT people. The workforce looked different,
36:59
Speaker 8: but it didn't get smaller. I think it's the same thing.
37:03
Speaker 8: We already know the massive, incredible amounts of energy that
37:09
Speaker 8: it takes for AI to work. Data centers that use
37:13
Speaker 8: up massive amounts of electricity like we've never seen in
37:15
Speaker 8: our lives. Like, nuclear has to be a thing. There
37:18
Speaker 8: isn't enough coal or oil or solar or wind to
37:22
Speaker 8: power these things. It just doesn't exist. So, nuclear has
37:26
Speaker 8: to be a thing. So, go be a nuclear engineer.
37:28
Speaker 19: Go.
37:29
Speaker 8: You want to get an advanced degree? I don't need
37:31
Speaker 8: you to be a coder. You know, coding was a
37:33
Speaker 8: thing for a... Go be a nuke. Because, by the way,
37:35
Speaker 8: you've got to be just as smart to be a
37:37
Speaker 8: nuke as you have to be a.
37:40
Speaker 8: So you're going to start to see that. You're going
37:42
Speaker 8: to see energy work. I just think the jobs will change.
37:46
Speaker 8: I don't think they're going to... One thing I do
37:49
Speaker 8: disagree with, it's not like you're going to be a
37:51
Speaker 8: bunch of people walking around bored.
37:53
Speaker 5: I just think the jobs will change.
37:56
Speaker 16: Even if we get halfway, in the sense that, okay,
37:59
Speaker 16: perhaps not surgeons, perhaps not great violinists, there'll be pockets
38:06
Speaker 16: where perhaps humans will remain.
38:09
Speaker 8: Good at it.
38:09
Speaker 1: Where?
38:11
Speaker 16: The kinds of jobs where you hire people by the
38:13
Speaker 16: hundred will go away where people are in some sense,
38:17
Speaker 16: exchangeable that you, you, you just need lots of them. And, uh,
38:21
Speaker 16: you know, when, when half of them quit, you just
38:23
Speaker 16: fill up those, those slots with more people in some sense,
38:27
Speaker 16: those are jobs where we're using people as robots.
38:30
Speaker 23: There are jobs where you want a human, maybe rich
38:33
Speaker 23: and you want a human accountant for whatever historic reasons.
38:38
Speaker 23: Old people like traditional ways of doing things. Warren Buffett
38:43
Speaker 23: would not switch to AI. He would use his human accountant.
38:47
Speaker 23: But it's a tiny subset of the market. Today, we
38:50
Speaker 23: have products which are man-made in US as opposed to
38:55
Speaker 23: mass-produced in China. And some people pay more to have those.
38:59
Speaker 23: But it's a small subset. It's almost a fetish. There
39:03
Speaker 23: is no practical reason for it. And I think anything
39:06
Speaker 23: you can do on a computer... could be automated using
39:09
Speaker 23: that technology. Look at computer science. Two years ago, we
39:14
Speaker 23: told people, learn to code. You are an artist, you
39:18
Speaker 23: cannot make money, learn to code. Then we realized, oh,
39:21
Speaker 23: AI kind of knows how to code and getting better.
39:25
Speaker 23: Become a prompt engineer. You can engineer prompts for AIs.
39:30
Speaker 23: It's going to be a great job. Get a four-year
39:31
Speaker 23: degree in it. But then we're like, AI is way
39:34
Speaker 23: better at designing prompts for other AIs than any human.
39:37
Speaker 23: So that's gone. So I can't really tell you right
39:40
Speaker 23: now the hardest thing is design AI agents for practical applications.
39:45
Speaker 23: I guarantee you in a year or two, it's going
39:46
Speaker 23: to be gone just as well.
39:48
Speaker 15: The default reaction has been to avoid the pessimism and
39:54
Speaker 15: the fear, right? To just kind of recoil from it
39:57
Speaker 15: and pretend that it's like either not happening or that
40:00
Speaker 15: it's all going to work out to be rosy. It's
40:02
Speaker 15: going to be fine. We don't have to worry about it.
40:04
Speaker 15: People often say, well, we've always created new jobs. We've
40:07
Speaker 15: never permanently displaced jobs. We've only ever seen new jobs
40:11
Speaker 15: be created. Unemployment is at an all-time low, right? So
40:14
Speaker 15: there's this default optimism bias that we have. And I
40:18
Speaker 15: think it's less about a need for optimism and more
40:21
Speaker 15: about a fear of pessimism. And so that trap, particularly
40:26
Speaker 15: in elite circles, means that often we aren't having the
40:30
Speaker 15: tough conversations that we need to have in order to
40:33
Speaker 15: respond to the coming wave.
40:37
Speaker 13: Every single one of us has probably got ancestors that
40:39
Speaker 13: were enslaved, probably got ancestors that died too young. probably
40:46
Speaker 13: got ancestors that worked horrific conditions.
40:50
Speaker 5: We all have that.
40:51
Speaker 13: And they would all just look at this moment and say, wow,
40:54
Speaker 13: so are you telling me that you have the ability
40:56
Speaker 13: to solve meaningful problems, to come up with adventures, to
41:00
Speaker 13: travel the world, to pick the brains of anyone on
41:04
Speaker 13: the planet that you want to pick the brains of?
41:05
Speaker 13: You can just listen to a podcast. You can just
41:08
Speaker 13: watch a video. You can talk to an AI. Like,
41:11
Speaker 13: are you telling me that you're alive at this particular
41:13
Speaker 13: moment please make the most of that. Like do something
41:17
Speaker 13: with that. You know, you can sit around pontificating about
41:21
Speaker 13: society and how society might work, but ultimately it all
41:24
Speaker 13: boils down to what you do with this moment.
41:27
Speaker 15: Because I'm fundamentally a humanist. And I think that we
41:31
Speaker 15: have to make a choice to put our species first.
41:36
Speaker 12: And I.
41:39
Speaker 15: Think that that's what we have to be defending for
41:41
Speaker 15: the next 50 years.
41:44
Speaker 13: AI has two superpowers. One superpower is to distract people,
41:48
Speaker 13: such as TikTok algorithm.
41:49
Speaker 19: That's right.
41:50
Speaker 13: And the other superpower is to make you hyper-creative, so
41:53
Speaker 13: you become a hyper-consumer or a hyper-creator. And in this
41:56
Speaker 13: marathon race, the vast majority of people have got their
41:59
Speaker 13: shoes tied together because AI is distracting them. Some people
42:03
Speaker 13: are running traditional race. Some people have got a bicycle,
42:06
Speaker 13: and some people have got a Formula One vehicle. And
42:10
Speaker 13: it's going to be very confronting to when the results
42:14
Speaker 13: go on the scoreboard and you say oh wait a
42:16
Speaker 13: second there's a few people who finished this marathon in
42:18
Speaker 13: about 30 minutes and there's a lot of us who
42:21
Speaker 13: finished in like 18 hours because we had our shoes
42:24
Speaker 13: tied together and i can't understand if we've got equal
42:28
Speaker 13: opportunity why there's so much disparity between how fast you
42:32
Speaker 13: know and you know i'm using an analogy but this
42:34
Speaker 13: idea that you know someone like a lot of people
42:37
Speaker 13: are going to start earning a million dollars a month
42:39
Speaker 13: And a lot of people are going to say, hey,
42:41
Speaker 13: I can't even get a job for $ 15 an hour.
42:43
Speaker 10: The exponential growth phase is going to be over. And
42:45
Speaker 10: like so many before you, you're going to be buying
42:47
Speaker 10: at the top, fighting for small gains, while early adopters
42:51
Speaker 10: reap the benefits of moving fast. Steve Jobs and Steve
42:54
Speaker 10: Wozniak is one of the three co-founders of Apple. Just
42:58
Speaker 10: 12 days in, worried the company would fail, he sold
43:01
Speaker 10: his 10% stake back to the boys for $ 800 today. Today,
43:07
Speaker 10: that stake would be worth over $ 200 billion, a sum
43:13
Speaker 10: that would make him one of the richest people in
43:14
Speaker 10: the world. In 1962, Decca Records passed on signing a
43:18
Speaker 10: scrappy little band from Liverpool because it was obvious that,
43:22
Speaker 10: and I quote, guitar music was on the way out.
43:26
Speaker 10: That band was none other than The Beatles, one of
43:28
Speaker 10: the highest selling bands of all time. They went on
43:30
Speaker 10: to sell over 600 million records. In 1998, Yahoo had
43:35
Speaker 10: the chance to buy Google for $ 1 million, but they
43:38
Speaker 10: passed because.
43:39
Speaker 6: They didn't think the company was worth it. They were wrong.
43:42
Speaker 6: Google's market cap today is over.
43:43
Speaker 10: $ 2 trillion. In 2005, Blockbuster was offered the chance to
43:49
Speaker 10: buy Netflix for $ 50 million.
43:51
Speaker 6: They actually laughed at the price.
43:53
Speaker 2: Whoops!
43:54
Speaker 6: Netflix is now worth over.
43:55
Speaker 10: $ 250 billion, while Blockbuster has but one remaining store left
44:00
Speaker 10: in Bend, Oregon that sells merch. There are so many
44:05
Speaker 10: more of these stories. I could literally go on for days,
44:08
Speaker 10: but the point is simple. It's not enough to live
44:10
Speaker 10: during a revolution. You have to recognize it and take
44:13
Speaker 10: action before it becomes obvious to everyone. And with AI,
44:17
Speaker 10: that window is getting more narrow by the day. It
44:20
Speaker 10: is already terraforming the technological and professional landscape. By 2030,
44:25
Speaker 10: AI is projected to eliminate or transform up to 800
44:29
Speaker 10: million jobs worldwide.
44:31
Speaker 6: That's nearly one in five workers on planet Earth.
44:34
Speaker 10: In 2023 alone, the number of corporate earnings calls mentioning
44:38
Speaker 10: AI surged over 360% compared to the prior year. AI-related
44:43
Speaker 10: IPOs in 2023 raised over $ 11 billion, the highest total
44:48
Speaker 10: for any sector that year. And the average AI-related ETF
44:51
Speaker 10: gained over 50% in 2023, more than quadruple the S
44:56
Speaker 10: & P 500's 10-year average annual returns. Over the last
45:00
Speaker 10: couple of years, if you weren't invested in AI, odds
45:03
Speaker 10: are you missed the boat. Goldman Sachs estimates AI could
45:07
Speaker 10: drive $ 7 trillion in global GDP growth over the next decade.
45:11
Speaker 10: And yet, most households own zero AI-linked assets.
45:17
Speaker 6: That is insanity.
45:19
Speaker 10: As inflation robs their purchasing power, they are sitting on
45:22
Speaker 10: the sidelines.
45:23
Speaker 6: Here is the harsh truth no one wants to face.
45:25
Speaker 10: Opportunities like this have an expiration date. Once adoption hits
45:29
Speaker 10: a certain point, the upside collapses and whoever owns the
45:32
Speaker 10: right basket of stocks wins and everybody else loses.
45:36
Speaker 1: You work with thousands of entrepreneurs. What are you telling
45:39
Speaker 1: them in terms of their current businesses or business opportunities
45:43
Speaker 1: that you're foreseeing?
45:44
Speaker 13: So I think that small teams have infinite leverage now
45:47
Speaker 13: and that when you have a team of say five
45:51
Speaker 13: to 10 people who share an incredible passion for a
45:54
Speaker 13: meaningful problem in the world and they want to see
45:56
Speaker 13: that meaningful problem solved and they come together in the
45:59
Speaker 13: spirit of entrepreneurship to solve that problem that little five
46:03
Speaker 13: to ten person team armed with the technology that we
46:06
Speaker 13: now have available you can have a big impact you
46:11
Speaker 13: can make a lot of money you can have a
46:12
Speaker 13: lot of fun you can solve meaningful problems in the
46:14
Speaker 13: world you can scale solutions you can probably do more
46:18
Speaker 13: in a three-year window than most people did in a
46:20
Speaker 13: 30-year career and then that little band of five to
46:23
Speaker 13: ten people could either go together onto a new meaningful problem,
46:28
Speaker 13: or they could disband and, you know, work on other
46:31
Speaker 13: meaningful problems with different teams.
46:33
Speaker 10: Here is the harsh truth no one wants to face.
46:35
Speaker 10: Opportunities like this have an expiration date. Once adoption hits
46:39
Speaker 10: a certain point, the upside collapses and whoever owns the
46:42
Speaker 10: right basket of stocks wins and everybody else loses. History
46:50
Speaker 10: shows this time and time again. When the personal computer
46:53
Speaker 10: revolution took off in the 1980s, early investors in Microsoft
46:58
Speaker 10: saw 50,000% returns over two decades. But if you bought
47:02
Speaker 10: after 2000, you were looking at single digit annual growth.
47:06
Speaker 6: The rocket fuel was spent.
47:09
Speaker 10: During the internet boom, Amazon went from 7 cents adjusted
47:14
Speaker 10: IPO price to over $ 3 within two years, a 4,000%
47:19
Speaker 10: gain and much, much more if you held longer. But
47:22
Speaker 10: by the time the average investor felt safe to buy in,
47:25
Speaker 10: those gains were history. Latecomers both miss the upside and
47:30
Speaker 10: take the inflationary hit of holding their money in cash
47:33
Speaker 10: or best case, underperforming assets. Now layer AI on top
47:38
Speaker 10: of that same pattern and you get moving at warp speed.
47:42
Speaker 10: AI's adoption curve is so steep that the window for
47:45
Speaker 10: massive early stage gains is being measured in months, not decades.
47:49
Speaker 10: Companies are hitting valuations in one year that took internet
47:52
Speaker 10: giants a decade to reach. The AI chip market is
47:56
Speaker 10: projected to more than 5X from 2022 to 2032. More
48:01
Speaker 10: than half of Fortune 500 companies are already integrating generative
48:06
Speaker 10: AI into their core operations. In 2024, Google, Meta, Amazon,
48:12
Speaker 10: and Microsoft collectively invested over $ 400 billion in AI infrastructure,
48:18
Speaker 10: surpassing the U.S. government's spending on social services. And for 2025?
48:24
Speaker 10: Big tech is planning to spend over 300 billion more
48:28
Speaker 10: on AI infrastructure. Things are moving so fast, you need
48:32
Speaker 10: to do your research now. People tell you that AI
48:38
Speaker 10: is overhyped, that it's going to hit a wall, that
48:41
Speaker 10: it's not going to be as disruptive as people are saying.
48:44
Speaker 10: And that runs the risk of lulling you into a
48:47
Speaker 10: sense that there's going to be plenty of time to
48:49
Speaker 10: react or that there's not going to be anything to
48:52
Speaker 10: react to. And that's exactly how you end up missing
48:54
Speaker 10: this opportunity. Now, no one can see the future clearly,
48:57
Speaker 10: certainly not myself. But the reality is that AI is
49:01
Speaker 10: already changing every aspect of our lives, and the depth
49:04
Speaker 10: and rate of change is accelerating. The only promise I
49:08
Speaker 10: can make is that AI is going to surprise us.
49:11
Speaker 10: It's going to do things that we can't even yet imagine.
49:13
Speaker 10: So if the stuff it's already doing is phenomenal, imagine
49:16
Speaker 10: what the future holds.
49:17
Speaker 15: I would say knowledge is power. embrace understand grapple with
49:23
Speaker 15: the consequences don't look the other way when it feels
49:27
Speaker 15: scary and do everything you can to understand and participate
49:33
Speaker 15: and shape because it is coming And.
49:37
Speaker 10: While I'll talk about this more later, the goal is
49:39
Speaker 10: not to try and be the smartest or most informed
49:41
Speaker 10: investor on the planet. Most people simply do not have
49:44
Speaker 10: time for that. Find a broad way into the sector
49:47
Speaker 10: and avoid getting seduced by headlines. Time in the market
49:51
Speaker 10: is better than trying to time the market. This is
49:54
Speaker 10: the world we live in. If we kill the Fed,
49:56
Speaker 10: we harden money, balance the budget, and only use debt
49:59
Speaker 10: to spur outside growth, then you can go back to.
50:02
Speaker 6: Just saving your money. AI is moving 10 times faster.
50:05
Speaker 10: In an inflationary environment like the one we're all living in,
50:07
Speaker 10: owning assets is not an option. Find what's right for
50:11
Speaker 10: you and make your move. Doing nothing is the same
50:14
Speaker 10: as guaranteeing that you are going to get eaten alive
50:16
Speaker 10: by inflation. And on top of that, no matter how
50:19
Speaker 10: well any of us think we understand what's coming, the
50:22
Speaker 10: only thing I can guarantee you is that we are
50:24
Speaker 10: going to be surprised.