Think Twice Before Taking That Fancy AI Job

Gusto Editors

Episode No. 23

Episode summary

Interest and investment in generative AI are booming, and many people are eager to find a job in this new darling of the tech sector. But not so fast, says Liz. She and Caleb discuss a new paper that should give anyone pursuing a career in an emerging technology pause about its long-term impact.

Shownotes

Innovation Booms, Easy Financing, and Human Capital Accumulation [NBER]

Transcript

Liz Wilke (00:00:31) – Hi, I’m Liz Wilke. 

Caleb Newquist (00:00:36) – And I’m Caleb Newquist. 

Liz Wilke (00:00:37) – And this is the Gustonomics Podcast. In each episode, we bring you a little bit of economics knowledge so you can be more informed, use the information in your business or work, or something to wow the gang on Galentine’s Day. 

Caleb Newquist (00:00:53) – Please remember to rate, review, and subscribe to the show or share it with an economics curious friend. Anything you can do to spread the word about the podcast is greatly appreciated. 

Caleb Newquist (00:01:06) – Great to see you, Liz. 

Liz Wilke (00:01:08) – Great to see you too, Caleb. 

Caleb Newquist (00:01:11) – So we’re going to get right into it. In this episode, you shared a very interesting paper with me that brings up a lot of interesting kind of economic things to think about. I’ll just read the title quickly. It’s called Innovation Booms, Easy Financing, and Human Capital Accumulation. And the authors are Johan Omber. That’s how I’m choosing to pronounce his name. Johan. Sorry if I butchered it. And his co-author is Adrian Matre. Again, sorry if I butchered it, but that’s, I’m saying it confidently. And so those are the names. And rather than read folks the abstract, I would just prefer, I think, if you summarize it for the folks and tell them why you thought it was interesting. 

Liz Wilke (00:02:00) – Sure. Well, I’m happy to do that. So I’ve been thinking a lot about the sort of generative AI enabled tech speculation boom, right? There’s lots of money going into these generative AI startups. And from an economic big picture point of view, we think that’s a really good thing. It’s going to generate a lot of dynamism. It’s going to generate a lot of new products. It’s going to increase our productivity and the value that the economy produces. That’s probably going to happen. 

Caleb Newquist (00:02:28) – Yeah. It’s like, it’s the new gold rush, right? 

Liz Wilke (00:02:32) – Yeah. Yeah. It’s the new gold rush. And some people are going to be the next Molly Brown. And some people are going to lose their shirts. And that’s really what this paper is about. But it’s not about the companies. It’s actually about the workers that work for the companies that don’t make it. 

Caleb Newquist (00:02:46) – OK. I like that. So are we going to talk a little bit about failure? Is that what you mean? 

Liz Wilke (00:02:52) – We are definitely going to talk about failure. And really, I think this is going to turn into a career conversation for people that are thinking now about joining the generative AI tech boom. 

Caleb Newquist (00:03:03) – OK. So my initial question is, aren’t economists usually OK with failure? Like the activity of failure, like a bunch of activity precedes failure. There’s all kinds of production and productivity associated with that. And the failure tends to reallocate talent and capital and all kinds of resources to better places. So isn’t failure OK? Yeah. 

Liz Wilke (00:03:30) – Economists are very comfortable, as an economic concept, with failure. We basically think that if you were paying somebody to do a job that’s not actually valuable in the market, then when your company fails, you freed up that person to go do something that is more valuable in the market with a higher performing or more productive company. 

Caleb Newquist (00:03:50) – Yeah. 

Liz Wilke (00:03:50) – That’s exactly how we think about it. 

Caleb Newquist (00:03:52) – Cool. And so what’s important about failure in the context of this paper? 

Liz Wilke (00:03:58) – So what this paper does is it looks at the late 90s, early 2000s tech boom. There was a ton of money coming into personal computers and a little bit of the internet. And it was really this dynamic time. Anybody who’s more elder, millennial, or above will remember this time as the go-go days of tech financing. And some companies really grew out of this. And some companies won. And some companies failed. And the question for these authors is, well, what happened to the workers? Because you can think that one of two things happened to them. You can think that the people who worked for these companies that failed learned a lot from the experience that made them way more valuable later on in life. That’s actually the story that tech entrepreneurs tend to tell about failure is, I failed. I learned so much. That has led to my success now. Or you could think maybe they’re learning practices or products or technologies that actually are not so good because they’re learning them in companies that ended up not to sort of win the contest about who was going to come out on top. So they learn technologies and practices that aren’t all that useful. And that, in fact, it’s not good for workers who actually end up working for companies that end up failing during these tech booms. 

Caleb Newquist (00:05:16) – OK. So Liz, let me just try to provide you with a crude example to illustrate this idea. The period of time that you’re talking about was the late 90s, early 2000s. come immediately to mind from that period are Amazon and Pets.com. Amazon, as most people know, went on to wild, wild success, has created lots of wealth, has created lots of jobs, created lots of economic activity. Pets.com, on the other hand, kind of flamed out in relatively short order. And so the argument is that if you went to Amazon and you met people there and you developed skills there, then you likely went on to achieve greater earnings and more economic productivity than someone who went to Pets.com, learned some skills, met some people, but ultimately moved on to something that didn’t result in as great of economic productivity. Is that roughly what this is about? 

Liz Wilke (00:06:21) – Yeah, so that’s what’s so interesting about this article. You could think that I learned, I was at Pets.com, the business failed, but my skills are better, right? I learned what doesn’t work. I can go and take that learning to somewhere else. That’s actually not what this article finds. It finds the other thing. I actually learned how to do some things badly and that seems to affect my long-term earnings, right, as opposed to if I had been at a successful company or not in the tech boom in the first place. 

Caleb Newquist (00:06:52) – So the paper is making the argument that if you worked at Amazon or eBay or PayPal, then it’s likely that the skills that you gained there, the difference in that person’s earning potential, let’s say, is pretty meaningful compared to the person who worked at Pets.com. The difference between those two experiences is significant and meaningful and that’s kind of what this paper is saying. Is that right? 

Liz Wilke (00:07:17) – Yeah, so this paper basically compares people who weren’t in the tech boom at all, but had similar levels of education or were sort of otherwise like similar earnings potential people, right? So they were in finance or they were in some other industry. 

Caleb Newquist (00:07:32) – HR or something, yeah. Are you talking about a function or an industry? 

Liz Wilke (00:07:37) – I’m talking about industries. 

Caleb Newquist (00:07:38) – Okay, so like a CFO that worked in tech versus a CFO that worked in manufacturing. 

Liz Wilke (00:07:45) – That’s right, but these are mostly entry-level, like early career positions, right? So like I, instead of being a software engineer for JP Morgan, right, I became a software engineer for Pets.com. 

Caleb Newquist (00:07:58) – Okay, yep. 

Liz Wilke (00:07:59) – Right. And so they sort of compare people who weren’t in the industry and then they also compare companies that had really high valuations, but then those valuations tanked, right? These companies folded and they were really overvalued versus really successful companies like Amazon. So what it sort of all says is if you were working in the late 90s, early 2000s for a business that had a huge valuation and then failed, you probably learned how to do things wrong in your craft. And by wrong, I mean you learned how to do things that didn’t work in the market, right? 

Caleb Newquist (00:08:37) – Right. 

Liz Wilke (00:08:37) – So other people, right, learned things that do work in the market and they either grew very fast because they were at a successful company that figured out how to figure it out, or they learned other things on sort of a normal skill development trajectory, right? Like you would if you had gone to work in finance or some other industry, right? 

Caleb Newquist (00:08:57) – Yep. 

Liz Wilke (00:08:57) – People accrue skills, people develop skills over the course of their career, right? And those skills are either productivity enhancing, they make you a better worker, or they are productivity decreasing, right? They sort of either they don’t matter or they make you a worse worker. And what this paper suggests is that the people that actually worked in failed companies learned productivity decreasing skills. They actually learned how to run a business badly, essentially. And then those skills don’t transfer and then the long-term earnings of these folks is actually lower than if they just hadn’t joined the tech boom at all. 

Caleb Newquist (00:09:35) – So let me ask you this then, what’s the big takeaway here? Is this like a cautionary tale for job seekers? 

Liz Wilke (00:09:42) – I think it is, right? So the real trick, I think what I might have done is just like upped the anxiety medication dosage of people that are currently working in generative AI startups. But I mean, I think the thing is, you know, a lot of the companies that are in the generative AI tech boom right now are going to fail. That’s the nature of having a dynamic economy. For people that are working in these companies, right, they need to, I think it will benefit them to be a little mindful of the fact that unless they’re very sure that their company is going to succeed, which it’s hard to tell in advance if your company is going to succeed or fail, especially on valuation. So many of these companies had really high valuations and then they just dropped. But if you are at a company that doesn’t make it, you might have learned technology, digital or otherwise, that’s actually not very good for you to carry forward. So think about how you’re going to tell the difference between you in a successful company versus you in an overvalued company. But then also if you turn out to be in a flop company, think about how much of your learning you should carry forward and how attentive you might need to be to new ways of doing what you were doing. 

Caleb Newquist (00:11:03) – So here’s another question for you. Is there a case to be made here for pursuing job opportunities with established, more legacy type of businesses where there’s conceivably less risk in this regard? So like you mentioned J.P. Morgan earlier, J.P. Morgan’s not going anywhere. Should you pursue an opportunity with an employer like that and it just doesn’t. It doesn’t have to be a bank, it could be manufacturing, it could be anything, but it seems like you would be. You’d have less risk of learning the wrong technology at a place like that, as opposed to working at your garden variety generative AI business. 

Liz Wilke (00:11:53) – I don’t know that I would give that advice specifically, lots of people enter unless you want to work for one of those businesses right like we have, like let’s remove, like people’s desires for a second right like what people want to do. 

Caleb Newquist (00:12:06) – I guess my question is: is it obviously less risky to work at a place like JP Morgan that’s firmly established and that you’re gonna- you’re gonna learn valuable stuff there because it’s a vastly successful business, versus taking a chance on a new technology that people are just sorting out and you might learn how to do stuff the wrong way for a while. I mean, is that like? How big of a risk is that? I guess is my question. 

Liz Wilke (00:12:33) – I don’t think that the risk is necessarily larger than the sort of base level riskiness of choosing between a big, established, legacy company like JP Morgan and A startup in the middle of a tech boom around a brand new, untested set of technologies. The risk between those two things is just very, very different. I think the only thing I would say is that you think it’s just a matter of the money, right, and the payout that you’ll get. You think, oh, I have all these stock options. I will either be made independently wealthy off of them or I will have worked for you know, monopoly money for a certain portion of my life and I’ll be out and I’ll have to work a little longer into retirement. What I’m, what this paper is suggesting, which I think is really important to think about, isn’t that you’ll, you won’t. You don’t run the risk of just losing out on the income that you would have earned in the time that you were working for this company that failed. You also risk losing out on future income because your skills aren’t fit for the market if you make the wrong choice. So it’s not that I think it’s so much riskier than choosing to go into a tech boom environment. Anyway, it’s that it is definitely. Really there’s an added layer of risk, right. So if you want to take on the risk, just know the risk you’re taking, and it’s not just a monetary one today, it’s a monetary one in the future, too. 

Caleb Newquist (00:14:02) – I think my big takeaway is that this is another kind of level of depth to think about career development that a lot of people probably don’t think about. I don’t know about you, but that’s kind of the takeaway that I had from this. 

Liz Wilke (00:14:20) – Yeah, I think that’s the takeaway that people should have. 

Caleb Newquist (00:14:22) – Or is there something else? Or is there something else that you think people should also think about? 

Liz Wilke (00:14:27) – I think the takeaway for everybody- whether or not you are thinking about a jump into generative AI tech boom- is that as you are working for money, you are also investing in your future capabilities, because you are learning skills, and the question that every worker should be asking themselves is: is this leveling me up for the future? 

Caleb Newquist (00:14:52) – So, in my case, I started my career as an accountant. I am no longer an accountant. However, I can read financial statements and like numbers don’t scare me in that regard. So in that way, things are still serving me okay, but now I work on a marketing team and that’s pretty weird. I didn’t go to school for marketing and maybe I’m just a bad example and people shouldn’t, you know, listen to me. I have told many people. It’s like: please do not try to replicate my career path. Do not try to do that. Okay, it will not. It there’s no, there’s no guarantees. It’s worked out for me, but I got lucky in a lot of different ways. So what I’m saying is, when I, even when I- joined gusto, it didn’t occur to me. It’s like, oh, I’m joining a marketing team, these skills will will serve me down the road someday. I am, I am slightly embarrassed to say now, having now read this paper, that I’m slightly embarrassed to say that I didn’t think about being on a marketing team and what I would learn and how that would serve me long term. But now, perhaps that’s all I’m going to be able to think about. 

Liz Wilke (00:15:55) – When people talk about career development and earnings over the over the course of their lives, we often talk about it as if we can see the future and we know what’s gonna happen right, and we can make sort of purely optimal decisions right with full information. 

Liz Wilke (00:16:15) – And the fact is that one of our greatest human weaknesses is that we cannot in fact see the future and also that we value things in our work at different times and we can’t always know who we will be in the future, let alone what will happen, and so career paths are, in fact, winding, and so, at the same time that you’re thinking about what are the skills today gonna get me tomorrow, we have to hold, at the same time, the idea that we won’t know who we will be tomorrow or what our options will be. 

Caleb Newquist (00:16:49) – Okay, that was great, Liz, and that’s it for this episode. We hope you learned something new and useful for yourself or your business. Please let us know what you think of the podcast by leaving a review, or share with a friend or colleague who might enjoy it. I’m Caleb Newquist. 

Liz Wilke (00:17:04) – I’m Liz Wilke. Thanks for listening.

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