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The idea that computer-driven artificial intelligence is going to take away all the human jobs and destroy all the jobs and give us somehow infinite output with nobody working is just a total myth.
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Who's going to pay for all these data centers, all this electricity, all this incredible investment that's going on?
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Who's actually paying the bill?
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We have a growing surplus of college graduates looking to be interns, to be middle management, to be tech workers.
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And we have a growing shortage of plumbers and roofers and construction workers.
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And I just think we have too many people going to college.
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So on last week's show, I had the great privilege of speaking with Professor Bob Gordon of Northwestern University.
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Bob Gordon is one of the foremost living economists in the world.
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His book, The Rise and Fall of U.S.
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Growth, is a bestseller.
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In the same year that his book was published, he was voted by Bloomberg as one of his most influential living economists.
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Last week's part one, we talked about the four headwinds debt, demographics, inequality, and education.
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Professor Gordon also spoke about the three industrial revolutions.
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A lot of us remember just one, but there are in fact three.
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This part two now we focus in on artificial intelligence.
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And Bob Gordon has some good news for graduates, professionals, but also some sobering news at the end of this interview.
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So I hope you enjoy the fantastic Professor Robert Gordon of Northwestern University.
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When your book came out, um Professor Gordon in 2016, it was deemed to be a bit controversial at the time, you know, uh perhaps arguing against the steamroller that is US the US economy.
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But this notion of perpetual growth, even that notion that we're always going to continue to grow in the context of 300,000 years where nothing happened until there was the Industrial Revolution, is that deeply flawed, this notion of perpetual growth in and itself?
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Oh, it goes beyond that.
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I mean, the the current Economist magazine talks about infinitely exploding growth, growth going up not to from 1 to 2% to 20 and 30% a year.
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That's a total fantasy.
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And that brings up uh artificial intelligence, which we might as well talk about now.
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Uh the idea that computer-driven artificial intelligence is going to take away all the human jobs and mean that human-like uh computers are gonna do everything and destroy all the jobs and give us somehow infinite output with nobody working is just a total myth.
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Artificial intelligence is nothing unless you're not sitting in front of a computer using it.
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But only about 30 percent of the employees, and I'll talk again about the United States, are have their jobs involved with staring at a computer.
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So the other 70% are not affected by artificial intelligence at all.
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They're engaged either with human-to-human jobs or human-to-material jobs, like construction, like mining, like manufacturing.
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The the future uh like nurses in a hospital.
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I've spent some time in hospitals, and I can tell you there's almost nothing that the people in that hospital are doing that can be replaced by a robot except for transporting patients back and forth for tests.
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I mean, a robot could push me down the hall on a gurney.
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I I accept that.
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But almost everything that they do when they come in to your hospital room requires a human person with enough touching and feeling uh to help you with all the different aspects of your uh your personal life.
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So you take all those different kinds of jobs and evolving person to person or person to materials.
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Uh and the the future doesn't depend on artificial intelligence at all for those jobs.
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It depends on the speed with which technology invents robots that are really human-like in their capabilities.
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And you know that we're way far away from that kind of robot.
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And just walk through your daily life and look at everybody who has a job and say, how likely is it that in the next 10 or 20 years that job is going to be replaced by a robot?
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So I think that brings down the temperature on the infinite growth aspect of artificial intelligence.
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The real issue is what percent of tasks are going to be eliminated by uh replaced by artificial intelligence?
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How much is that gonna hollow out white-collar work?
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How much of that's gonna aggravate what I described earlier as the education crisis of college graduates coming out and not being able to uh to find jobs?
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As the number of people working and being replaced by artificial intelligence uh grows, there will be a boost to productivity growth in that part of the economy that is centered around white-collar middle management uh kind of work.
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I imagine that to take a recent example, uh artificial intelligence could well take over pricing algorithms for airlines or airline scheduling and eliminate jobs of people who are now involved in doing that.
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That's an industry I know a lot about.
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It's not gonna take away two pilots in the cockpit.
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It's not gonna take away flight attendants going up and down the aisles.
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Can you imagine a robot going up and down the aisles of an airplane trying to serve you?
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It just is isn't uh conceivable with today's technology of robots.
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So uh you asked about whether growth is gonna be continual or fade away.
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I think it's a contest.
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I think it's a contest between the obvious now apparent effect of AI on white-collar work, competing against all these headwinds, the growing burden of old people who are not working at all and not really affected by AI, except to the extent that if AI can create um better diagnosis of Alzheimer's or uh invent new drugs for dementia, then that can have a big effect on the elderly population.
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But basically, we're we're talking about a growing share of elderly people who are not working, not affected by AI.
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And so that's the headwind aspect of growth, pushing against this growing ability of AI models to take over tasks that have traditionally been done by humans, like computer programming, software coding, uh, graphic design, designing book covers, making movies.
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I mean, every every night we watch a comedy show uh in the United States that starts out with a 45-second comedy video that's obviously been constructed by AI, with uh people talking in voices of other people and wearing uh clothing and being having bodies that are different from their heads and all sorts of stuff that is clearly being created by AI.
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So a lot of this is not even uh job displacing.
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Uh it's uh just adding to the quality of the entertainment that's available.
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Yeah, no, it's it's it's interesting.
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And uh from what from what I'm taking from what you're saying is, and it makes sense that you know the manual work, uh farming, mining, you know, uh other other other work like that is pretty safe nursing.
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But you would be kind of concerned if you if you have a grandson or granddaughter and you were uh they were going into accountancy or law school or looking to become a maybe a wealth manager like myself.
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Um we hear the line uh AI won't replace humans, but humans with AI will replace humans without.
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I don't know.
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Is that like you you obviously have some concerns about white-collar uh jobs, but how quickly is this gonna happen, do you think?
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I don't think that can be predicted.
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Ten years ago, we did not predict that the ability of these large language models would explode so quickly as it has in the last two or three years.
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Uh so um my gut feeling is that we've had this explosion in the last two or three years and it's gonna level off because these large language models have been built on scraping the internet of all this information.
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We're running out of information to scrape.
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You know, so we're gonna hit diminishing returns in the ability of these models to incrementally, they're gonna go from massive improvements in the ability to mimic humans.
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They now can write little essays on any question you ask them.
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But they can already write a book.
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Uh so what's the next step of their ability to uh to do this kind of conversion of existing knowledge into answers to questions?
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It's a great convenience, all of a sudden, to be able to type into Google search some question instead of being sent to three or four different websites which might or might not have the answer, immediately within two seconds you get a paragraph answer through AI.
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That's a great service, but it brings up the question I have: what's the underlying economics of AI?
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Who's gonna pay for all these data centers, all this electricity, all this incredible investment that's going on, that's allowing these millions of fancy computer chips to answer all these questions?
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Who's actually paying the bill?
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You know, we're getting this stuff for free from Google.
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Uh, who's gonna create the revenue to repay Microsoft and Meta and all these people for uh investing$500 billion in data centers?
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Uh the story waits to be told.
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I was looking at the Northwestern University website and your own.
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You you you still teach, you still teach uh economics and and and a couple of other modules.
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And I was looking at some of the notes, and it was interesting to see uh where you you don't allow laptops, computers uh in the um in the tutorial hall in the in the classroom.
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And I think that's wonderful.
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And so I I I have the same rule in my in my class because students are distracted, and um, but I mean, from your own perspective of having taught for decades and decades, I mean, how do you assess students in this environment?
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How do we are we are we eliminating independent thought uh in this new generation?
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How do we how do we approach that?
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It depends on the it depends on the class.
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I taught uh two classes, very different answers to your question.
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One class is a lecture course in intermediate macroeconomics.
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Uh that's where we we go beyond just the stories of elementary economics and teach models and graphs and definite specific answers to questions like to take the topic of the day, what's the effect of tariffs on the trade balance?
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We have a model we show that uh the trade balance depends on the balance of saving and investment in the economy, and that is or is not affected by tariffs.
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So we have models to do that.
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Now, in a course like that, which I've taught for many years, um there's no problem about AI, there's no problem about cheating, uh, there's no problem about students learning, because in my class, 84% of the grade is based on closed book tests.
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They are sitting in a classroom with a paper exam, a combination of multiple choice questions and short-answer questions where they have to come up with uh exact answers for uh numerical questions.
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And they're sitting there in a room with no notes, no laptops, no phones, no nothing.
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And they have to know in order to answer the questions.
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Um the role of AI actually has been present in my class for a while because 10% of the grade depends on doing electronic homework.
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And for each chapter, they're trained to do multiple choice questions.
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So they're trained to do what they later do in closed book form.
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But the tutorial that they go through, if they don't get the right answer, they don't get any points, and they're forced to stick with the same question until they get the right answer.
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And the software jumps them into the textbook explaining what they just missed, if they missed the question.
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And they've got to slog through this until they get 100%.
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So they are actually being tutored in a sort of computer interface, but that's only 10%.
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And that allows them to do well on the closed book stuff where they have to actually remember it out of their heads.
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And I must say that the most recent class I taught in the winter of 2025, I've never had higher grades on these closed book uh things.
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I'd like to think it's because I'm a brilliant lecturer, uh, but uh somehow the whole thing, the whole package uh came together.
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Now, what what you ask about AI being a threat to traditional education comes up in my other class, which is a freshman seminar called, Did Economics Win the Two World Wars?
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And it's about the politics and economics, and a little bit about the military aspects of the two world wars, and they write papers.
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And so the question is, how do I prevent them from just getting AI to write a paper?
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Now, this has only really become a threat in the last two or three years, as you know, because of the large language models.
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At least so far I'm okay in that I truly believe that they are writing their own papers.
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Now, how do I know?
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It's because there are enough typical freshmen writing mistakes and poor writing style that I know this was not written by AI.
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I know what AI is like.
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And by the way, we now have AI detectors where you can put a student's paper into an AI filter and have it figure out if AI wrote it.
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Uh so uh we're protected.
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So far in that class, uh, I believe they are actually writing the papers.
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Uh, and there are various ways I can tell.
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I'd like to just finish up um on a question and then maybe just a couple of uh personal questions in relation to advice for students, which which is always very beneficial for somebody with your ex experience and expertise.
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In relation to your original thesis, well, let's say back 2016, uh, and I would strongly encourage anybody listening or viewing to watch uh the TED Talk and the rebuttal to the TED Talk from Professor Gordon, I'll put the link and additional uh information in the notes.
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But in relation to where we stand today and those four headwinds, if you were to, and this is a difficult question I know, but if you were to pick and focus on one of them that is going to be the most uh crucial to study in terms of uh deflationary forces or our plateauing of growth, which which one would it be?
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Demographics, the aging population.
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Um I just saw a graph that showed that um if fertility stays at its same level in the U.S., which is 1.6.
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Remember the 2.1 is fertility where each woman has two children, therefore the population is replaced.
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And with the 2.1 fertility, you have a steady population forever.
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Uh with 1.6, the population is going to peak and then decline forever until the human race is wiped out three or four hundred years from now.
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Uh so demographics is clearly the big deal.
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And demographics means ever-rising burden of old people on uh the shrinking share of young people, leaving aside whether the young people are going to have jobs and the ability to uh to earn income.
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Uh one of the predictions about AI is that more and more money will go to the rich and to the owners of the AI companies, and less and less to the middle class that are being uh pushed out of jobs.
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Uh so the only real solution to the demographic crisis is to raise retirement ages.
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And that's sort of easy to say for white-collar work.
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I mean, look, I'm 85 and I'm just uh retiring now, not at age 65.
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The French The French are fighting to keep their retirement age at 62, which is ridiculous.
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People are really healthy in their 60s.
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People are pretty healthy these days in their 70s.
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Um and the problem with that is that life expectancy is not uniform across types of people.
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Uh people in the top 10% of the income distribution live about 10 or 15 years longer than people in the bottom 10%.
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People with manual jobs, really tough physical jobs.
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Uh, I think of the guy who takes care of our yard here, he's looks like he's getting on to age 70, and it's getting harder and harder for him to just do the bending and and physical work.
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So that retirement age issue is really a hot one because you've got a sort of obvious case for forcing people to retire at yet older ages before they get their retirement benefits.
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But on the other hand, you have about a third of the population maybe that's doing physically taxing jobs that they have to retire to keep their uh physical health.
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So that's a really tough one.
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And I don't think any country has wrestled with the possibility of having different retirement ages for different types of people.
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You've just raised something very, very interesting, and and it has been a common tread throughout all of my discussions, and that is the weak the failure of the political system to really address what's an obvious problem in terms of the entitlements, you might call it in the US, the unsustainable entitlements.
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Um because as politicians are voted, are their their number one aim is to get re-elected, and the system is not inducive to uh sustainable policies that are good for everyone, let's say.
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Let's not forget, wait a minute, let's not forget the big policy failure besides the retirement age, and that is immigration.
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To have enough legal immigration to fulfill the needs of meatpacking plants and agriculture and construction, all these places where the currently illegal immigrants work, if we had just had a much more generous and open immigration policy that had channels not only for high-skilled tech workers, but also for agriculture workers, the things that business firms find very hard to fill the jobs.
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We could have done that for the last 30 years, and we'd have this immigrant population now that wouldn't be deported because they'd all be legal.
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Uh now we have, if we have a threat to American economic growth now that the uh trade war seems to be subsiding, it's this merciless deportation of people, uh, stripping whole companies of all their workers.
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Uh and that's going to start to show up in job growth and economic growth over the next year if it continues, and I expect it will continue because uh Trump has not backed down on it.
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So just to complete your idea of political failure, political failure to deal with aging and immigration are the twin failures.
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And I would uh add for the in the U.S.
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context also failure to offset rising inequality by putting up taxes on rich people.
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We could have a supertax on people with over$100 billion,$100 million a year.
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It wouldn't stop innovation, it wouldn't stop economic growth, despite all the uh you know what political group is is uh going to talk about that.
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Listen, this is this has been absolutely uh wonderful, a real pleasure for me.
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Can I can I just finish up, please, uh Professor Gordon, by it's a couple of questions we ask every guest, and it's basically to give something.
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Back, there would be young people, uh, maybe career professionals listening to this.
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In terms of uh books uh that should influence you starting out even today, uh books that that that you would recommend for for students, for practitioners that uh would give them real insight.
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Any any tips?
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Um well my uh my focus is on on the US and and um the one I would point to that I would I I would read next if I was lining up the books that uh that I would want to read would be um Brad DeLong's book called Slouching Toward Utopia.
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That's also a history of the United States over the last hundred years, but it's a very different emphasis than mine.
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It's not really about economic growth, it's about you know it's got brilliant chapters on the two world wars, on the depression, on uh just very aerodite but easy to read.
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And so if I can just suggest one one book, he'd probably be surprised to hear me recommending his book, uh, but that's the one I would say.
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And and finally, that a little bit of advice for young students, uh, for graduates that are looking to that are living in this AI world now, okay?
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What kind of advice would you give them in terms of looking at a 30-40 year career?
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Is it to get in is it to just if you can't beat them, join them, or is it is there something else that you would advise uh young graduates, young students?
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Uh I think we're we're entering a world in which we have a growing surplus of college graduates looking to be interns, to be middle management, to be tech workers, and we have a growing shortage of plumbers and roofers and construction workers.
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And I just think we have too many people going to college.
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That's not very helpful advice for the people who are in college and worried about getting uh jobs out of college.
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Uh, but I think we have an imbalance in society.
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It's I think it's inevitable as we go forward with the effects of AI that we're gonna have a a growing share of these person-to-person and person-to-object jobs that are gonna be hard for robots to replace, and we're gonna have a shrinking share of the population doing white-collar work.
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And that's not what college graduates want to hear.
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So, my message is really for people coming out of high school: do you really think it's gonna be helpful to go to college, especially if you can't get into one of the top colleges?
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Yeah, that's very honest advice and useful.
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And um listen, I just want to thank you very much, uh Professor Gordon.
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That was really, really interesting.
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Um, and I'm sure.
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Send the questions, you really you really got it going.
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But that's high praise and I really appreciate it.
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Well, that was truly fascinating and and fairly profound.
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Uh so what's the difference between growth and productivity?
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That was one of the first questions I I asked um Professor Gordon.
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So growth really is what it says in the tin.
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You know, we've typically got averaged over in the US has around 2% growth.
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And that's kind of the natural rate of growth, you might say, because things generally have to grow in order for, you know, uh true innovation and entrepreneurship, that type of thing.
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Productivity is different.
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Productivity is the output.
00:25:28.880 --> 00:25:32.799
So if you've got growth, productivity brings in number of workers, okay?
00:25:32.880 --> 00:25:34.160
So output per hour.
00:25:34.319 --> 00:25:44.400
So then we're getting into demographics, Ivan, which he talks about, because you can have all this growth, but if it's concentrated in, say, an aging demographic, you're you've got to look at uh output.
00:25:44.480 --> 00:25:46.400
What's your output going to look like into the future?
00:25:46.720 --> 00:25:52.000
So then he talks about peak growth in the context of the United States economy.
00:25:52.160 --> 00:26:12.480
Because, you know, we've seen in other uh interviews that you've done as part of this series, people saying that maybe there was 80 years where America dominated the world economically and politically, even militarily, and that now we're entering into a phase of Asia leading the world and China.
00:26:12.640 --> 00:26:14.720
Uh, what does peak growth mean?
00:26:15.039 --> 00:26:20.400
Peak growth has to be framed from the likes of Professor Gordon in terms of history, right?
00:26:20.640 --> 00:26:24.720
So it's interesting, he looked, he looked, he is a bit of a financial historian as well.
00:26:24.799 --> 00:26:26.880
He looked back at hundreds of years.
00:26:27.119 --> 00:26:29.759
And for millennia, we had no growth at all.
00:26:29.920 --> 00:26:30.160
Okay?
00:26:30.720 --> 00:26:40.079
Around the end of the 18th century, beginning of the 19th century, there was a a number of uh really consequential inventions.
00:26:40.160 --> 00:26:45.920
Okay, we had electricity, uh, we had light, we had uh what did electricity do?
00:26:46.000 --> 00:26:48.480
It allowed for power tools, okay?
00:26:48.640 --> 00:26:52.720
So we became much more efficient, similar to AI today, you could argue, right?
00:26:53.119 --> 00:27:02.160
But what he calls, he talks about three industrial revolutions, not just the one we know about the late 19th century, but there was other industrial revolutions as well.
00:27:02.480 --> 00:27:16.240
And what his view is that we have peaked in terms of the US has definitely peaked in terms of peak growth for a number for because of those four reasons debt, demographics, uh, inequality, uh, and education.
00:27:16.480 --> 00:27:25.599
And yet, maybe he's just an oxygenarian who's out of time, because a lot of people talk to me about the industrial revolution 4.0.
00:27:26.079 --> 00:27:36.960
And it started with the internet and it's developing not only through software, through artificial intelligence and so on, that that is actually a 4.0 industrial revolution.
00:27:37.119 --> 00:27:37.680
You know what I mean?
00:27:37.839 --> 00:27:42.319
Maybe because he's coming near the end of his era, he he is not aware of what comes next.
00:27:42.559 --> 00:27:44.880
I mentioned Professor Gordon's TED Talk, right?
00:27:44.960 --> 00:27:51.119
But there was a rebuttal to his from a from a techno-optimist, and you can get the say you can get that TED talk as well, right?
00:27:51.200 --> 00:27:52.480
So they're back and forth.
00:27:52.720 --> 00:27:54.559
But you know, that's what this is debate.
00:27:54.640 --> 00:27:56.319
You're looking at different views, okay?
00:27:56.480 --> 00:28:00.720
So he talks uh your argument about 4.0, that's all fine.
00:28:00.799 --> 00:28:06.079
But what Gordon says is that you cannot look at just growth in isolation.
00:28:06.240 --> 00:28:07.599
You have to look at debt.
00:28:07.839 --> 00:28:21.599
Okay, so we have all okay, so is the AI revolution going to save us when we have when we the debt levels we have are completely different to where the growth period started 50, 60, 70 years ago?
00:28:21.680 --> 00:28:27.039
You cannot separate the two because debt is going to diminish the level of growth you could have.
00:28:27.200 --> 00:28:28.799
There's going to be winners and losers with this.
00:28:29.039 --> 00:28:32.559
We alluded at the outset to demographics and so on.
00:28:32.720 --> 00:28:35.200
Um, and is this an irreversible trend?
00:28:35.279 --> 00:28:44.960
Or is there like I remember when China had a one-baby policy, um, is there anything can be done to stimulate a reversal of this trend to encourage people to have more kids?
00:28:45.359 --> 00:28:46.240
Very, very difficult.
00:28:46.400 --> 00:28:51.839
I know there's the Chinese, for example, uh it's it's it's particularly acute in Asia, okay?
00:28:52.160 --> 00:29:07.119
Japan, uh, China, other Asian countries, uh, Europe is is under pressure, Germany, for example, and we saw Merkel's policy with the migrants to should you know a lot of people thought that was very altruistic, but there was there was rationale from a demographics point of view there.
00:29:07.279 --> 00:29:09.519
You ask the question, what can Pit Buck can do?
00:29:09.680 --> 00:29:15.519
I mean, the size of China, how much would it cost to incentivize families to have more children?
00:29:15.680 --> 00:29:17.359
It just doesn't make sense economically.
00:29:17.519 --> 00:29:20.079
Why are you gonna give$10,000,$20,000?
00:29:20.319 --> 00:29:21.519
Do the maths on that.
00:29:21.680 --> 00:29:23.039
So it's very difficult.
00:29:23.359 --> 00:29:28.400
Unfortunately, you're gonna see regions of the world like India become very attractive.
00:29:28.559 --> 00:29:31.359
The average age in India is something like 32 or 3.
00:29:31.759 --> 00:29:36.319
Compare that to late 50s and some in Asian countries.
00:29:36.480 --> 00:29:37.920
And what is productivity?
00:29:38.079 --> 00:29:41.519
It's number of workers per hour's worked.
00:29:41.759 --> 00:29:42.720
Simple maths.
00:29:42.960 --> 00:29:43.920
Thank you, Alan.
00:29:44.079 --> 00:29:52.240
Well, that concludes this week's episode of The Most Important Thing with an interview uh with Professor uh Bob Gordon.
00:29:52.319 --> 00:29:53.440
I hope you enjoyed it.
00:29:53.599 --> 00:30:09.119
Now, if you'd like to learn more about this whole uh investing, financing, economics, education, uh please do access the Truth Series, which is in conjunction with this particular series, the most important thing.
00:30:09.279 --> 00:30:12.000
Thank you for joining us until the next time.
00:30:12.160 --> 00:30:15.119
Looking forward to joining you again from Alan and me.
00:30:18.079 --> 00:30:20.799
Thank you for listening to the most important thing.
00:30:20.960 --> 00:30:24.880
This podcast is for general information and educational purposes only.
00:30:25.039 --> 00:30:36.400
Nothing in this episode is financial, investment, tax, legal, or pension advice, and nothing said should be taken as a recommendation to buy, sell, or hold any investment, asset, or security.
00:30:36.640 --> 00:30:41.680
Any assets, stocks, or markets we discuss are for discussion and illustration only.
00:30:41.920 --> 00:30:47.680
The views expressed by our hosts and guests are their own, and they may hold positions in investments mentioned.
00:30:47.920 --> 00:30:54.400
Investing involves risk, the value of investments can fall as well as rise, and you may get back less than you invest.
00:30:54.799 --> 00:30:58.160
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00:30:58.319 --> 00:31:06.559
Before making any financial decision, please seek independent advice from a regulated financial advisor who understands your personal circumstances.
00:31:06.799 --> 00:31:08.880
Thanks again for listening, until next time.
00:00:00.479 --> 00:00:13.119
The idea that computer-driven artificial intelligence is going to take away all the human jobs and destroy all the jobs and give us somehow infinite output with nobody working is just a total myth.
00:00:13.279 --> 00:00:19.039
Who's going to pay for all these data centers, all this electricity, all this incredible investment that's going on?
00:00:19.199 --> 00:00:20.640
Who's actually paying the bill?
00:00:20.879 --> 00:00:29.120
We have a growing surplus of college graduates looking to be interns, to be middle management, to be tech workers.
00:00:29.280 --> 00:00:35.200
And we have a growing shortage of plumbers and roofers and construction workers.
00:00:35.359 --> 00:00:37.759
And I just think we have too many people going to college.
00:00:38.079 --> 00:00:44.079
So on last week's show, I had the great privilege of speaking with Professor Bob Gordon of Northwestern University.
00:00:44.240 --> 00:00:48.640
Bob Gordon is one of the foremost living economists in the world.
00:00:48.799 --> 00:00:51.520
His book, The Rise and Fall of U.S.
00:00:51.679 --> 00:00:53.039
Growth, is a bestseller.
00:00:53.280 --> 00:01:01.039
In the same year that his book was published, he was voted by Bloomberg as one of his most influential living economists.
00:01:01.200 --> 00:01:09.200
Last week's part one, we talked about the four headwinds debt, demographics, inequality, and education.
00:01:09.439 --> 00:01:13.200
Professor Gordon also spoke about the three industrial revolutions.
00:01:13.359 --> 00:01:16.480
A lot of us remember just one, but there are in fact three.
00:01:16.799 --> 00:01:20.239
This part two now we focus in on artificial intelligence.
00:01:20.400 --> 00:01:30.159
And Bob Gordon has some good news for graduates, professionals, but also some sobering news at the end of this interview.
00:01:30.400 --> 00:01:37.760
So I hope you enjoy the fantastic Professor Robert Gordon of Northwestern University.
00:01:39.040 --> 00:01:56.239
When your book came out, um Professor Gordon in 2016, it was deemed to be a bit controversial at the time, you know, uh perhaps arguing against the steamroller that is US the US economy.
00:01:56.719 --> 00:02:15.360
But this notion of perpetual growth, even that notion that we're always going to continue to grow in the context of 300,000 years where nothing happened until there was the Industrial Revolution, is that deeply flawed, this notion of perpetual growth in and itself?
00:02:16.400 --> 00:02:17.759
Oh, it goes beyond that.
00:02:17.840 --> 00:02:27.680
I mean, the the current Economist magazine talks about infinitely exploding growth, growth going up not to from 1 to 2% to 20 and 30% a year.
00:02:28.080 --> 00:02:29.759
That's a total fantasy.
00:02:30.240 --> 00:02:35.680
And that brings up uh artificial intelligence, which we might as well talk about now.
00:02:36.000 --> 00:03:00.400
Uh the idea that computer-driven artificial intelligence is going to take away all the human jobs and mean that human-like uh computers are gonna do everything and destroy all the jobs and give us somehow infinite output with nobody working is just a total myth.
00:03:01.199 --> 00:03:06.800
Artificial intelligence is nothing unless you're not sitting in front of a computer using it.
00:03:07.120 --> 00:03:16.400
But only about 30 percent of the employees, and I'll talk again about the United States, are have their jobs involved with staring at a computer.
00:03:16.800 --> 00:03:22.639
So the other 70% are not affected by artificial intelligence at all.
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They're engaged either with human-to-human jobs or human-to-material jobs, like construction, like mining, like manufacturing.
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The the future uh like nurses in a hospital.
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I've spent some time in hospitals, and I can tell you there's almost nothing that the people in that hospital are doing that can be replaced by a robot except for transporting patients back and forth for tests.
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I mean, a robot could push me down the hall on a gurney.
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I I accept that.
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But almost everything that they do when they come in to your hospital room requires a human person with enough touching and feeling uh to help you with all the different aspects of your uh your personal life.
00:04:08.400 --> 00:04:16.160
So you take all those different kinds of jobs and evolving person to person or person to materials.
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Uh and the the future doesn't depend on artificial intelligence at all for those jobs.
00:04:22.399 --> 00:04:31.040
It depends on the speed with which technology invents robots that are really human-like in their capabilities.
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And you know that we're way far away from that kind of robot.
00:04:35.920 --> 00:04:45.439
And just walk through your daily life and look at everybody who has a job and say, how likely is it that in the next 10 or 20 years that job is going to be replaced by a robot?
00:04:45.680 --> 00:04:54.000
So I think that brings down the temperature on the infinite growth aspect of artificial intelligence.
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The real issue is what percent of tasks are going to be eliminated by uh replaced by artificial intelligence?
00:05:02.720 --> 00:05:05.759
How much is that gonna hollow out white-collar work?
00:05:05.920 --> 00:05:16.079
How much of that's gonna aggravate what I described earlier as the education crisis of college graduates coming out and not being able to uh to find jobs?
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As the number of people working and being replaced by artificial intelligence uh grows, there will be a boost to productivity growth in that part of the economy that is centered around white-collar middle management uh kind of work.
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I imagine that to take a recent example, uh artificial intelligence could well take over pricing algorithms for airlines or airline scheduling and eliminate jobs of people who are now involved in doing that.
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That's an industry I know a lot about.
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It's not gonna take away two pilots in the cockpit.
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It's not gonna take away flight attendants going up and down the aisles.
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Can you imagine a robot going up and down the aisles of an airplane trying to serve you?
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It just is isn't uh conceivable with today's technology of robots.
00:06:08.639 --> 00:06:16.160
So uh you asked about whether growth is gonna be continual or fade away.
00:06:16.720 --> 00:06:18.079
I think it's a contest.
00:06:18.319 --> 00:06:52.399
I think it's a contest between the obvious now apparent effect of AI on white-collar work, competing against all these headwinds, the growing burden of old people who are not working at all and not really affected by AI, except to the extent that if AI can create um better diagnosis of Alzheimer's or uh invent new drugs for dementia, then that can have a big effect on the elderly population.
00:06:52.639 --> 00:06:59.360
But basically, we're we're talking about a growing share of elderly people who are not working, not affected by AI.
00:06:59.839 --> 00:07:20.319
And so that's the headwind aspect of growth, pushing against this growing ability of AI models to take over tasks that have traditionally been done by humans, like computer programming, software coding, uh, graphic design, designing book covers, making movies.
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I mean, every every night we watch a comedy show uh in the United States that starts out with a 45-second comedy video that's obviously been constructed by AI, with uh people talking in voices of other people and wearing uh clothing and being having bodies that are different from their heads and all sorts of stuff that is clearly being created by AI.
00:07:47.519 --> 00:07:50.879
So a lot of this is not even uh job displacing.
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Uh it's uh just adding to the quality of the entertainment that's available.
00:07:55.839 --> 00:07:57.519
Yeah, no, it's it's it's interesting.
00:07:57.759 --> 00:08:11.360
And uh from what from what I'm taking from what you're saying is, and it makes sense that you know the manual work, uh farming, mining, you know, uh other other other work like that is pretty safe nursing.
00:08:11.680 --> 00:08:23.839
But you would be kind of concerned if you if you have a grandson or granddaughter and you were uh they were going into accountancy or law school or looking to become a maybe a wealth manager like myself.
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Um we hear the line uh AI won't replace humans, but humans with AI will replace humans without.
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I don't know.
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Is that like you you obviously have some concerns about white-collar uh jobs, but how quickly is this gonna happen, do you think?
00:08:45.120 --> 00:08:46.799
I don't think that can be predicted.
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Ten years ago, we did not predict that the ability of these large language models would explode so quickly as it has in the last two or three years.
00:08:55.600 --> 00:09:10.639
Uh so um my gut feeling is that we've had this explosion in the last two or three years and it's gonna level off because these large language models have been built on scraping the internet of all this information.
00:09:10.879 --> 00:09:13.440
We're running out of information to scrape.
00:09:13.679 --> 00:09:24.799
You know, so we're gonna hit diminishing returns in the ability of these models to incrementally, they're gonna go from massive improvements in the ability to mimic humans.
00:09:24.879 --> 00:09:28.559
They now can write little essays on any question you ask them.
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But they can already write a book.
00:09:32.240 --> 00:09:44.480
Uh so what's the next step of their ability to uh to do this kind of conversion of existing knowledge into answers to questions?
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It's a great convenience, all of a sudden, to be able to type into Google search some question instead of being sent to three or four different websites which might or might not have the answer, immediately within two seconds you get a paragraph answer through AI.
00:10:02.799 --> 00:10:10.639
That's a great service, but it brings up the question I have: what's the underlying economics of AI?
00:10:10.799 --> 00:10:23.840
Who's gonna pay for all these data centers, all this electricity, all this incredible investment that's going on, that's allowing these millions of fancy computer chips to answer all these questions?
00:10:24.080 --> 00:10:25.759
Who's actually paying the bill?
00:10:25.919 --> 00:10:28.720
You know, we're getting this stuff for free from Google.
00:10:29.919 --> 00:10:42.480
Uh, who's gonna create the revenue to repay Microsoft and Meta and all these people for uh investing$500 billion in data centers?
00:10:42.720 --> 00:10:46.080
Uh the story waits to be told.
00:10:46.480 --> 00:10:50.879
I was looking at the Northwestern University website and your own.
00:10:50.960 --> 00:10:56.000
You you you still teach, you still teach uh economics and and and a couple of other modules.
00:10:56.240 --> 00:11:09.120
And I was looking at some of the notes, and it was interesting to see uh where you you don't allow laptops, computers uh in the um in the tutorial hall in the in the classroom.
00:11:09.279 --> 00:11:10.799
And I think that's wonderful.
00:11:10.960 --> 00:11:26.559
And so I I I have the same rule in my in my class because students are distracted, and um, but I mean, from your own perspective of having taught for decades and decades, I mean, how do you assess students in this environment?
00:11:26.720 --> 00:11:33.039
How do we are we are we eliminating independent thought uh in this new generation?
00:11:33.279 --> 00:11:35.519
How do we how do we approach that?
00:11:36.000 --> 00:11:38.639
It depends on the it depends on the class.
00:11:38.799 --> 00:11:45.360
I taught uh two classes, very different answers to your question.
00:11:46.080 --> 00:11:51.200
One class is a lecture course in intermediate macroeconomics.
00:11:51.360 --> 00:12:09.679
Uh that's where we we go beyond just the stories of elementary economics and teach models and graphs and definite specific answers to questions like to take the topic of the day, what's the effect of tariffs on the trade balance?
00:12:09.919 --> 00:12:18.879
We have a model we show that uh the trade balance depends on the balance of saving and investment in the economy, and that is or is not affected by tariffs.
00:12:19.039 --> 00:12:20.720
So we have models to do that.
00:12:20.879 --> 00:12:38.879
Now, in a course like that, which I've taught for many years, um there's no problem about AI, there's no problem about cheating, uh, there's no problem about students learning, because in my class, 84% of the grade is based on closed book tests.
00:12:39.120 --> 00:12:56.879
They are sitting in a classroom with a paper exam, a combination of multiple choice questions and short-answer questions where they have to come up with uh exact answers for uh numerical questions.
00:12:57.039 --> 00:13:02.240
And they're sitting there in a room with no notes, no laptops, no phones, no nothing.
00:13:02.399 --> 00:13:05.440
And they have to know in order to answer the questions.
00:13:05.759 --> 00:13:16.639
Um the role of AI actually has been present in my class for a while because 10% of the grade depends on doing electronic homework.
00:13:16.879 --> 00:13:21.120
And for each chapter, they're trained to do multiple choice questions.
00:13:21.200 --> 00:13:25.120
So they're trained to do what they later do in closed book form.
00:13:25.919 --> 00:13:36.159
But the tutorial that they go through, if they don't get the right answer, they don't get any points, and they're forced to stick with the same question until they get the right answer.
00:13:36.399 --> 00:13:44.320
And the software jumps them into the textbook explaining what they just missed, if they missed the question.
00:13:44.399 --> 00:13:46.879
And they've got to slog through this until they get 100%.
00:13:47.279 --> 00:13:52.639
So they are actually being tutored in a sort of computer interface, but that's only 10%.
00:13:53.279 --> 00:14:00.080
And that allows them to do well on the closed book stuff where they have to actually remember it out of their heads.
00:14:00.320 --> 00:14:10.480
And I must say that the most recent class I taught in the winter of 2025, I've never had higher grades on these closed book uh things.
00:14:10.639 --> 00:14:17.840
I'd like to think it's because I'm a brilliant lecturer, uh, but uh somehow the whole thing, the whole package uh came together.
00:14:18.080 --> 00:14:30.960
Now, what what you ask about AI being a threat to traditional education comes up in my other class, which is a freshman seminar called, Did Economics Win the Two World Wars?
00:14:31.120 --> 00:14:39.600
And it's about the politics and economics, and a little bit about the military aspects of the two world wars, and they write papers.
00:14:39.840 --> 00:14:45.440
And so the question is, how do I prevent them from just getting AI to write a paper?
00:14:45.679 --> 00:14:52.399
Now, this has only really become a threat in the last two or three years, as you know, because of the large language models.
00:14:52.559 --> 00:14:57.759
At least so far I'm okay in that I truly believe that they are writing their own papers.
00:14:57.919 --> 00:14:58.960
Now, how do I know?
00:14:59.200 --> 00:15:10.639
It's because there are enough typical freshmen writing mistakes and poor writing style that I know this was not written by AI.
00:15:10.720 --> 00:15:11.840
I know what AI is like.
00:15:11.919 --> 00:15:23.039
And by the way, we now have AI detectors where you can put a student's paper into an AI filter and have it figure out if AI wrote it.
00:15:23.279 --> 00:15:25.600
Uh so uh we're protected.
00:15:25.759 --> 00:15:30.879
So far in that class, uh, I believe they are actually writing the papers.
00:15:31.039 --> 00:15:33.039
Uh, and there are various ways I can tell.
00:15:33.360 --> 00:15:49.440
I'd like to just finish up um on a question and then maybe just a couple of uh personal questions in relation to advice for students, which which is always very beneficial for somebody with your ex experience and expertise.
00:15:49.759 --> 00:16:09.440
In relation to your original thesis, well, let's say back 2016, uh, and I would strongly encourage anybody listening or viewing to watch uh the TED Talk and the rebuttal to the TED Talk from Professor Gordon, I'll put the link and additional uh information in the notes.
00:16:09.679 --> 00:16:31.120
But in relation to where we stand today and those four headwinds, if you were to, and this is a difficult question I know, but if you were to pick and focus on one of them that is going to be the most uh crucial to study in terms of uh deflationary forces or our plateauing of growth, which which one would it be?
00:16:31.519 --> 00:16:34.799
Demographics, the aging population.
00:16:35.279 --> 00:16:44.559
Um I just saw a graph that showed that um if fertility stays at its same level in the U.S., which is 1.6.
00:16:44.960 --> 00:16:52.799
Remember the 2.1 is fertility where each woman has two children, therefore the population is replaced.
00:16:52.960 --> 00:16:57.919
And with the 2.1 fertility, you have a steady population forever.
00:16:58.159 --> 00:17:07.599
Uh with 1.6, the population is going to peak and then decline forever until the human race is wiped out three or four hundred years from now.
00:17:07.759 --> 00:17:10.880
Uh so demographics is clearly the big deal.
00:17:11.119 --> 00:17:27.359
And demographics means ever-rising burden of old people on uh the shrinking share of young people, leaving aside whether the young people are going to have jobs and the ability to uh to earn income.
00:17:27.599 --> 00:17:42.000
Uh one of the predictions about AI is that more and more money will go to the rich and to the owners of the AI companies, and less and less to the middle class that are being uh pushed out of jobs.
00:17:42.240 --> 00:17:51.119
Uh so the only real solution to the demographic crisis is to raise retirement ages.
00:17:51.279 --> 00:17:54.480
And that's sort of easy to say for white-collar work.
00:17:54.640 --> 00:18:00.079
I mean, look, I'm 85 and I'm just uh retiring now, not at age 65.
00:18:00.640 --> 00:18:06.559
The French The French are fighting to keep their retirement age at 62, which is ridiculous.
00:18:06.799 --> 00:18:09.519
People are really healthy in their 60s.
00:18:09.680 --> 00:18:12.400
People are pretty healthy these days in their 70s.
00:18:12.640 --> 00:18:21.759
Um and the problem with that is that life expectancy is not uniform across types of people.
00:18:22.079 --> 00:18:28.720
Uh people in the top 10% of the income distribution live about 10 or 15 years longer than people in the bottom 10%.
00:18:29.359 --> 00:18:32.799
People with manual jobs, really tough physical jobs.
00:18:32.960 --> 00:18:43.359
Uh, I think of the guy who takes care of our yard here, he's looks like he's getting on to age 70, and it's getting harder and harder for him to just do the bending and and physical work.
00:18:43.599 --> 00:18:56.559
So that retirement age issue is really a hot one because you've got a sort of obvious case for forcing people to retire at yet older ages before they get their retirement benefits.
00:18:56.720 --> 00:19:09.759
But on the other hand, you have about a third of the population maybe that's doing physically taxing jobs that they have to retire to keep their uh physical health.
00:19:09.920 --> 00:19:11.440
So that's a really tough one.
00:19:11.599 --> 00:19:20.799
And I don't think any country has wrestled with the possibility of having different retirement ages for different types of people.
00:19:21.839 --> 00:19:42.000
You've just raised something very, very interesting, and and it has been a common tread throughout all of my discussions, and that is the weak the failure of the political system to really address what's an obvious problem in terms of the entitlements, you might call it in the US, the unsustainable entitlements.
00:19:42.160 --> 00:19:56.640
Um because as politicians are voted, are their their number one aim is to get re-elected, and the system is not inducive to uh sustainable policies that are good for everyone, let's say.
00:19:57.279 --> 00:20:04.400
Let's not forget, wait a minute, let's not forget the big policy failure besides the retirement age, and that is immigration.
00:20:04.640 --> 00:20:33.920
To have enough legal immigration to fulfill the needs of meatpacking plants and agriculture and construction, all these places where the currently illegal immigrants work, if we had just had a much more generous and open immigration policy that had channels not only for high-skilled tech workers, but also for agriculture workers, the things that business firms find very hard to fill the jobs.
00:20:34.160 --> 00:20:41.200
We could have done that for the last 30 years, and we'd have this immigrant population now that wouldn't be deported because they'd all be legal.
00:20:41.359 --> 00:20:55.599
Uh now we have, if we have a threat to American economic growth now that the uh trade war seems to be subsiding, it's this merciless deportation of people, uh, stripping whole companies of all their workers.
00:20:55.680 --> 00:21:05.839
Uh and that's going to start to show up in job growth and economic growth over the next year if it continues, and I expect it will continue because uh Trump has not backed down on it.
00:21:06.000 --> 00:21:15.359
So just to complete your idea of political failure, political failure to deal with aging and immigration are the twin failures.
00:21:15.599 --> 00:21:18.400
And I would uh add for the in the U.S.
00:21:18.720 --> 00:21:28.960
context also failure to offset rising inequality by putting up taxes on rich people.
00:21:29.279 --> 00:21:35.359
We could have a supertax on people with over$100 billion,$100 million a year.
00:21:35.680 --> 00:21:47.200
It wouldn't stop innovation, it wouldn't stop economic growth, despite all the uh you know what political group is is uh going to talk about that.
00:21:47.680 --> 00:21:51.359
Listen, this is this has been absolutely uh wonderful, a real pleasure for me.
00:21:51.519 --> 00:21:59.759
Can I can I just finish up, please, uh Professor Gordon, by it's a couple of questions we ask every guest, and it's basically to give something.
00:22:00.160 --> 00:22:04.640
Back, there would be young people, uh, maybe career professionals listening to this.
00:22:04.960 --> 00:22:19.119
In terms of uh books uh that should influence you starting out even today, uh books that that that you would recommend for for students, for practitioners that uh would give them real insight.
00:22:19.279 --> 00:22:20.400
Any any tips?
00:22:21.759 --> 00:22:45.599
Um well my uh my focus is on on the US and and um the one I would point to that I would I I would read next if I was lining up the books that uh that I would want to read would be um Brad DeLong's book called Slouching Toward Utopia.
00:22:45.759 --> 00:22:52.160
That's also a history of the United States over the last hundred years, but it's a very different emphasis than mine.
00:22:52.400 --> 00:23:02.480
It's not really about economic growth, it's about you know it's got brilliant chapters on the two world wars, on the depression, on uh just very aerodite but easy to read.
00:23:02.720 --> 00:23:10.799
And so if I can just suggest one one book, he'd probably be surprised to hear me recommending his book, uh, but that's the one I would say.
00:23:11.200 --> 00:23:19.839
And and finally, that a little bit of advice for young students, uh, for graduates that are looking to that are living in this AI world now, okay?
00:23:20.079 --> 00:23:25.039
What kind of advice would you give them in terms of looking at a 30-40 year career?
00:23:25.519 --> 00:23:34.400
Is it to get in is it to just if you can't beat them, join them, or is it is there something else that you would advise uh young graduates, young students?
00:23:34.799 --> 00:23:58.240
Uh I think we're we're entering a world in which we have a growing surplus of college graduates looking to be interns, to be middle management, to be tech workers, and we have a growing shortage of plumbers and roofers and construction workers.
00:23:58.640 --> 00:24:01.039
And I just think we have too many people going to college.
00:24:01.200 --> 00:24:08.000
That's not very helpful advice for the people who are in college and worried about getting uh jobs out of college.
00:24:08.079 --> 00:24:10.640
Uh, but I think we have an imbalance in society.
00:24:10.880 --> 00:24:31.039
It's I think it's inevitable as we go forward with the effects of AI that we're gonna have a a growing share of these person-to-person and person-to-object jobs that are gonna be hard for robots to replace, and we're gonna have a shrinking share of the population doing white-collar work.
00:24:31.279 --> 00:24:33.839
And that's not what college graduates want to hear.
00:24:34.079 --> 00:24:42.880
So, my message is really for people coming out of high school: do you really think it's gonna be helpful to go to college, especially if you can't get into one of the top colleges?
00:24:43.279 --> 00:24:45.839
Yeah, that's very honest advice and useful.
00:24:46.000 --> 00:24:50.160
And um listen, I just want to thank you very much, uh Professor Gordon.
00:24:50.240 --> 00:24:52.079
That was really, really interesting.
00:24:52.319 --> 00:24:53.200
Um, and I'm sure.
00:24:53.839 --> 00:24:56.319
Send the questions, you really you really got it going.
00:24:57.200 --> 00:24:59.599
But that's high praise and I really appreciate it.
00:24:59.839 --> 00:25:03.599
Well, that was truly fascinating and and fairly profound.
00:25:03.759 --> 00:25:06.240
Uh so what's the difference between growth and productivity?
00:25:06.400 --> 00:25:09.759
That was one of the first questions I I asked um Professor Gordon.
00:25:09.839 --> 00:25:12.000
So growth really is what it says in the tin.
00:25:12.319 --> 00:25:17.359
You know, we've typically got averaged over in the US has around 2% growth.
00:25:17.440 --> 00:25:26.240
And that's kind of the natural rate of growth, you might say, because things generally have to grow in order for, you know, uh true innovation and entrepreneurship, that type of thing.
00:25:26.400 --> 00:25:27.200
Productivity is different.
00:25:27.359 --> 00:25:28.720
Productivity is the output.
00:25:28.880 --> 00:25:32.799
So if you've got growth, productivity brings in number of workers, okay?
00:25:32.880 --> 00:25:34.160
So output per hour.
00:25:34.319 --> 00:25:44.400
So then we're getting into demographics, Ivan, which he talks about, because you can have all this growth, but if it's concentrated in, say, an aging demographic, you're you've got to look at uh output.
00:25:44.480 --> 00:25:46.400
What's your output going to look like into the future?
00:25:46.720 --> 00:25:52.000
So then he talks about peak growth in the context of the United States economy.
00:25:52.160 --> 00:26:12.480
Because, you know, we've seen in other uh interviews that you've done as part of this series, people saying that maybe there was 80 years where America dominated the world economically and politically, even militarily, and that now we're entering into a phase of Asia leading the world and China.
00:26:12.640 --> 00:26:14.720
Uh, what does peak growth mean?
00:26:15.039 --> 00:26:20.400
Peak growth has to be framed from the likes of Professor Gordon in terms of history, right?
00:26:20.640 --> 00:26:24.720
So it's interesting, he looked, he looked, he is a bit of a financial historian as well.
00:26:24.799 --> 00:26:26.880
He looked back at hundreds of years.
00:26:27.119 --> 00:26:29.759
And for millennia, we had no growth at all.
00:26:29.920 --> 00:26:30.160
Okay?
00:26:30.720 --> 00:26:40.079
Around the end of the 18th century, beginning of the 19th century, there was a a number of uh really consequential inventions.
00:26:40.160 --> 00:26:45.920
Okay, we had electricity, uh, we had light, we had uh what did electricity do?
00:26:46.000 --> 00:26:48.480
It allowed for power tools, okay?
00:26:48.640 --> 00:26:52.720
So we became much more efficient, similar to AI today, you could argue, right?
00:26:53.119 --> 00:27:02.160
But what he calls, he talks about three industrial revolutions, not just the one we know about the late 19th century, but there was other industrial revolutions as well.
00:27:02.480 --> 00:27:16.240
And what his view is that we have peaked in terms of the US has definitely peaked in terms of peak growth for a number for because of those four reasons debt, demographics, uh, inequality, uh, and education.
00:27:16.480 --> 00:27:25.599
And yet, maybe he's just an oxygenarian who's out of time, because a lot of people talk to me about the industrial revolution 4.0.
00:27:26.079 --> 00:27:36.960
And it started with the internet and it's developing not only through software, through artificial intelligence and so on, that that is actually a 4.0 industrial revolution.
00:27:37.119 --> 00:27:37.680
You know what I mean?
00:27:37.839 --> 00:27:42.319
Maybe because he's coming near the end of his era, he he is not aware of what comes next.
00:27:42.559 --> 00:27:44.880
I mentioned Professor Gordon's TED Talk, right?
00:27:44.960 --> 00:27:51.119
But there was a rebuttal to his from a from a techno-optimist, and you can get the say you can get that TED talk as well, right?
00:27:51.200 --> 00:27:52.480
So they're back and forth.
00:27:52.720 --> 00:27:54.559
But you know, that's what this is debate.
00:27:54.640 --> 00:27:56.319
You're looking at different views, okay?
00:27:56.480 --> 00:28:00.720
So he talks uh your argument about 4.0, that's all fine.
00:28:00.799 --> 00:28:06.079
But what Gordon says is that you cannot look at just growth in isolation.
00:28:06.240 --> 00:28:07.599
You have to look at debt.
00:28:07.839 --> 00:28:21.599
Okay, so we have all okay, so is the AI revolution going to save us when we have when we the debt levels we have are completely different to where the growth period started 50, 60, 70 years ago?
00:28:21.680 --> 00:28:27.039
You cannot separate the two because debt is going to diminish the level of growth you could have.
00:28:27.200 --> 00:28:28.799
There's going to be winners and losers with this.
00:28:29.039 --> 00:28:32.559
We alluded at the outset to demographics and so on.
00:28:32.720 --> 00:28:35.200
Um, and is this an irreversible trend?
00:28:35.279 --> 00:28:44.960
Or is there like I remember when China had a one-baby policy, um, is there anything can be done to stimulate a reversal of this trend to encourage people to have more kids?
00:28:45.359 --> 00:28:46.240
Very, very difficult.
00:28:46.400 --> 00:28:51.839
I know there's the Chinese, for example, uh it's it's it's particularly acute in Asia, okay?
00:28:52.160 --> 00:29:07.119
Japan, uh, China, other Asian countries, uh, Europe is is under pressure, Germany, for example, and we saw Merkel's policy with the migrants to should you know a lot of people thought that was very altruistic, but there was there was rationale from a demographics point of view there.
00:29:07.279 --> 00:29:09.519
You ask the question, what can Pit Buck can do?
00:29:09.680 --> 00:29:15.519
I mean, the size of China, how much would it cost to incentivize families to have more children?
00:29:15.680 --> 00:29:17.359
It just doesn't make sense economically.
00:29:17.519 --> 00:29:20.079
Why are you gonna give$10,000,$20,000?
00:29:20.319 --> 00:29:21.519
Do the maths on that.
00:29:21.680 --> 00:29:23.039
So it's very difficult.
00:29:23.359 --> 00:29:28.400
Unfortunately, you're gonna see regions of the world like India become very attractive.
00:29:28.559 --> 00:29:31.359
The average age in India is something like 32 or 3.
00:29:31.759 --> 00:29:36.319
Compare that to late 50s and some in Asian countries.
00:29:36.480 --> 00:29:37.920
And what is productivity?
00:29:38.079 --> 00:29:41.519
It's number of workers per hour's worked.
00:29:41.759 --> 00:29:42.720
Simple maths.
00:29:42.960 --> 00:29:43.920
Thank you, Alan.
00:29:44.079 --> 00:29:52.240
Well, that concludes this week's episode of The Most Important Thing with an interview uh with Professor uh Bob Gordon.
00:29:52.319 --> 00:29:53.440
I hope you enjoyed it.
00:29:53.599 --> 00:30:09.119
Now, if you'd like to learn more about this whole uh investing, financing, economics, education, uh please do access the Truth Series, which is in conjunction with this particular series, the most important thing.
00:30:09.279 --> 00:30:12.000
Thank you for joining us until the next time.
00:30:12.160 --> 00:30:15.119
Looking forward to joining you again from Alan and me.
00:30:18.079 --> 00:30:20.799
Thank you for listening to the most important thing.
00:30:20.960 --> 00:30:24.880
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00:30:25.039 --> 00:30:36.400
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00:30:36.640 --> 00:30:41.680
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00:30:41.920 --> 00:30:47.680
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00:30:47.920 --> 00:30:54.400
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00:30:54.799 --> 00:30:58.160
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00:30:58.319 --> 00:31:06.559
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00:31:06.799 --> 00:31:08.880
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