In this YouTube mentoring session, Michael Strong guides 14‑year‑old Ilana through three chapters from Henry Hazlitt’s classic economics text. They first unpack “Taxation Discourages Production,” clarifying how taxes can reduce incentives to work and produce. Next they explore “Government Credit Diverts Production,” contrasting private‑sector capital—where investors demand accountability—with government‑funded projects that often lack the same discipline, illustrated with examples like private shoe manufacturing and public stadium financing. The third chapter, “The Curse of Machinery,” examines the historical fallacy that machines cause permanent unemployment; Michael links this to modern AI, noting past transitions from farms to factories. Ilana then shares her personal anxieties about AI replacing jobs, recounting an Instagram‑reel experiment where AI‑generated birthday cards outperformed her own designs, leaving her feeling devalued. The conversation shifts to broader concerns about AI’s impact on creative work and even mathematicians, and Ilana emphasizes that human connection may remain the core value in an AI‑driven economy. Michael proposes a follow‑up reading on humans and work in an AI world, ending the session with plans to continue the dialogue.
Chapters
TranscriptAuto-generated · 13 min
So at your request, 3 chapters this time. Where do you want to start?
I guess just overall, the 3 chapters talking a lot about the difference between like private sector business and then public and then government spending, and why, if you consider the lessons that we learned earlier on, Opportunity costs and the fact that there could be other things going on. Government spending is really just more taxation and taking away from things in the private sectors.
So I just out of curiosity, have you been talking about this with your dad at all or not at all?
I've asked him about it a little bit, but he's actually away in Vegas right now with my brother at a competition. So I haven't been able to recently.
Got it. I know. Thank you. That's a good start. Um, just to go chapter by chapter. So, um, so the first chapter we read was Taxation Discourages Production. Um, you kind of addressed that, but you want to address what does Hazlitt mean by taxation discourages production?
Yeah, like, if you know that you're going to get taxed, why would you spend that extra hour working? And why would you, or why would you want to make more money just for it to get taxed anyways? I think that was his point.
And by the way, had you thought about or heard about these issues at all before reading this, or this is all pretty new to you?
I've heard about it before just because I've heard my parents talking about taxes and I don't know, just other people around me, but I haven't really learned too much of it on my own, which is why I was interested in reading this.
Okay, cool. And just by the way, the And maybe this is obvious, or maybe you said it, but often economists divide things into consumption versus production. And so, for instance, right, when your dad is— he's still doing Friendly Shoes, correct?
I'm not sure how or where it is in the stage right now, but he's still involved in it. Yeah.
Yeah. So, you know, when Friendly Shoes is producing shoes, then that's production. When You know, you guys are buying breakfast or clothes for a tournament or for school or whatever, that's consumption. So just useful to have, you know, some things when we invest money to make things in businesses, that's production, or that's going to production. Whereas when some income is just we eat the thing or we wear the thing, and then that's not production, that's consumption. Makes sense?
Yeah, that does. Thank you.
Yeah, you're welcome. Just, you know, that's sort of in the background of all of this. And then the next chapter was credit diverts production, and specifically government credit diverts production. What does Hazlitt mean by that?
I think in that chapter, chapter 6, there was an example between 2 different— I don't know if this is the right word, but 2 different companies. So one was getting investment through Or privately, so private investment through other people. And one wasn't very accountable, and it was doing very good, so it asked for government investment, I believe. But if I think the lesson was, if you think about it, the government is just using tax dollars or borrowing money to invest in that company, which is taking away from other people and putting money into that. organization that isn't trustworthy or efficient are going to do a lot with that. Am I thinking of the right thing?
Yeah, yeah, no, I would say that's again a decent summary. And just to fill in some details, um, you know, typically in the private, you know, going back just because your dad is associated with a company, it's always nice to have concrete companies. So with Friendly Shoes, I don't know if they've raised capital from investors, but if they get loans from a bank or whatever, but in order for Friendly Shoes to get capital, they have to persuade either private investors or banks to invest or give them loans or something. And private people expect their money back, so they have to be accountable. Whereas, right, government tends to be less accountable. And so going back to the stadium example, stadiums often lose lots of money for governments and people get a stadium, which may or may not be a good thing, but the government often doesn't get its money back when it loans money. And so, yeah, private basically, and you were kind of going there, but basically in the world of private credit, there's a lot more accountability. And you're more likely to— private loan investors or people who loan money are more likely to make sure it's a credible You know, accountable investment, whereas government, who knows? Does that make sense?
Yes, that makes sense.
Okay. So that, yeah, that's, those are pretty good summaries of those 2 chapters. Then the next one on machinery. What does Hazlitt mean by the curse of machinery?
I think he was describing the fallacy that people think that machinery and production, like maybe machines and factories, are Just machines that help people create things cheaper and more efficiently are a cause of unemployment. And, and actually, it made me think of AI, but I'll come back to that later. But he was saying that it really doesn't, because those employees who were put out of work will go and take jobs elsewhere in different, in different areas.
Yeah. And just empirically, a couple of interesting things that I'm actually very glad you brought up AI, because of course it's relevant. Yeah. But, you know, 100 years ago, most Americans lived on farms. Cars were beginning to take over at this point. But, you know, 120 years ago, most parents— most people had horses rather than cars. And, you know, there were all the horse and buggy, you know, horse riders, buggy drivers. Yeah. And yeah, now the population of the US is much higher than it was. And people have work and have a lot more money. And so does it make sense that people might be afraid that machines would put people out of business? Because—
Yeah, for sure. It makes sense.
So yeah, it's kind of, I would say, we can go into the mechanics and Hazlitt's arguments and what you think. In some ways, it's kind of a miracle that, yeah, we kicked all the people off farms. We didn't kick them off, but, you know, all these farm workers left the farms and now people are richer than ever, have more leisure and more, jobs than ever. So, and, you know, you can see there are a lot of things that exist now that did not exist 100 years ago. So the people who make the cars, the people who make the computers, the people that, you know, make Las Vegas, the people that make tatami, you know, fightwear, none of this existed 100 years ago. So yeah, we've just got this incredible world. So going to AI, give me your thoughts on how This applies to AI.
Well, I thought of this just briefly, but I was trying to apply the same logic to AI. Like, the people that are unemployed will go and find jobs elsewhere, and the AI is just a way to make things cheaper and efficient. But I was kind of stuck because I feel like AI could be applied to lots more than just building things. And you could say, oh, I mean, the more jobs it takes, the more jobs there are for other people, I guess. But I've been listening to everyone think about or talk about how AI is going to, like, take over all the jobs and take over the world and stuff. Doesn't that mean there will be no jobs for me to get?
I don't know.
I just feel like it's a lot more complicated.
Lots of interesting stuff here. First, where are you, out of curiosity, where are you hearing these conversations? Is this online and friends, family? Where do you hear the conversations?
Podcasts and online and friends speculating. I don't know if— yeah, that's just pulled from a bunch of different conversations.
Yeah, no, certainly people are talking about it for sure. And so, right, then the question is, do Hazlitt's arguments continue to apply or do they not apply or do they apply in some ways or not? So you're certainly right to wonder if the arguments still apply. In some ways, that's why I was actually emphasizing it sort of seems like a miracle that we kicked all the farm workers off the farms and they still got jobs. And so maybe you have to hope for a miracle. And I'm kind of playing around with miracle. I don't know. Let's pause. Suppose you were a farm girl in 1900 and there were these tractors coming and these combines and all this mechanical equipment. And people were saying, oh, there are no more jobs on the farms. What are you going to do? I don't know. Would you have thought that there were going to be no more jobs or would you have thought, A miracle has to occur, or it's hard to put your mind in that space, but you know what I mean?
I can try. I mean, I probably would have been thinking, or if I wanted to move completely out of the farm business or whatever, I would have been thinking about my skill set and what other things I could go into. But also maybe if I could find a way to work with the machinery, like someone has to drive those trucks or whatever. I'm not really sure what we're referring to. But trying to apply that to AI, I mean, I've, I've tried working with AI in different things and it does work, but it can do so much of it on its own that sometimes it's kind of, it's not the right word, but demeaning for me to like do anything with it. So it's different all around, but I guess the same things could apply.
Just again, super interesting. And people are talking, a lot of people are talking about this in lots of different ways. So it is a relevant conversation. Tell me about the demeaning part, what feels demeaning. meaning about it?
I'm just gonna pull from one example that I experienced recently. So I was— my mom sent me an Instagram reel about like, oh, you don't need to go get a job in 2026, go open Canva and make birthday cards and sell it. So I was like, okay, I guess I'll try that. And I did that. And I had AI help me like find a target demographic and niche, like what I should create. And so I started, and then I was looking at the thing I was creating, and I was like, this is kind of bad. I don't know if anyone would buy it. I wonder if AI can make it. So AI made it. The AI made it for me, and it was like 100 times better than what I made. And I was like, well, if I just have AI to create it, why don't I just like sell what the AI makes? And it's just like a couple more loopholes I have to go through, but it'll be easier. But then I felt like this sense that I was doing something wrong. and I wasn't really sure how to deal with it. That's what I was thinking of.
Super interesting. Interesting example, interesting phenomenon. Um, so let's shift a little bit. How might human— given that there are certainly tasks and more tasks that AI will be better at than humans, no doubt about it. Um, there are mathematicians who are depressed because they think AI is going to take over a lot of mathematics. So given that, um, You know, people are concerned. Could you imagine a world where human beings are still valuable in a world of AI, or do you think that human beings will not be valuable?
I can't really— or I think they will still be valuable, if anything, just for like that human connection and interaction. But I'm not sure if they'll be valuable for the physical things. Um, because, okay, not the physical things I meant, um, just like the complicated framework behind everything. I feel like there's something like that and everything, and then eventually the AI will be able to handle it, you know what I mean? But in a world where, let's just say, it is already dependent on AI, I think the main thing for me is human connection.
So this is a super interesting topic, and we're going to run out of time. What I suggest is that I, I've— let me pick an article for read next time, take a little break for Hazlitt, but let's go specifically into the issue of humans, human work in the world of AI. And then, you know, we can look at some arguments and then go back and see if Hazlitt's argument still applies or not, or how it might apply or not. But yeah, I think human connection is certainly part of the answer. And then, as you're pointing out, what does that actually do to jobs and things? But— I don't
know.
Does it seem like a fair digression to bounce out of Hadlet and Haslett and address the AI and future of work conversation a little bit?
Yes, that sounds super interesting.
Okay, great. In which case, wonderful to see you, Ilana, and I'll send you an article for next week.
