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Job Titles Don’t Mean What They Used To (And That Affects Your Pay) — with Dr. Ben Zweig (Part 2 of 2)
01:09:50
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- [00:01]
Paula Pant
There are 90 million job titles that are floating around online. 90 million. But are there actually 90 million different jobs? Because the thing is, sometimes two people with completely different titles can essentially be doing the same type of work, and other times, two people with the same title could be doing totally different work. Across companies and across industries, job titles and job descriptions don't map to each other in any standardized way. Here's the problem. If there are 90 million job titles floating around online, how are you supposed to know what you're qualified for? How are you supposed to know whether or not you're underpaid, you're misleveled, or maybe you're applying for the wrong roles entirely? If job titles don't mean what you think they mean, that affects how you search for jobs, how you negotiate for your salary and benefits, how you position yourself. It affects, when you walk into a new role, what you think you do. Like if you don't have a clear sense of how your role is structured, what tasks define it, what kinds of skills cluster together around it, you can't even adapt when those pieces start to shift as they are quite rapidly right now. Because if AI is changing the tasks inside of jobs, how do you adapt? And how do you stay competitive if you don't know which parts of your role are scarce and which parts are becoming commoditized? And frankly, if your title doesn't accurately reflect what you do, how do you negotiate? How do you apply for the right roles? How do you assess the field and make comparisons to what people with similar roles to you are making in other industries or at other companies? How do you bring structure to something that's this chaotic? Dr. Ben Zweig joins us again today for part two of our conversation, which started in the last episode. So if you haven't listened to that yet, listen to that one first and then come Back to this. Dr. Ben Zweig is the CEO of Revelio Labs, a workplace data company that uses AI to analyze millions of job postings and map how work is actually structured. He also teaches a class on the future of work at NYU Stern School of Business. He holds a Ph.D. in economics from the CUNY Graduate Center. Welcome to the Afford Anything podcast, the show that knows you can afford anything. Not everything. This show covers five pillars financial psychology, increasing your income, investing, real estate, and entrepreneurship. It's double I Fire. I'm your host, Paula Pant. Today's episode is about that first letter, I. Increasing your income, or at a minimum, maintaining your income in a world in which jobs, especially among knowledge Workers are at risk and rapidly changing again. This is part two of our two part interview with Dr. Ben Zweig. Please start off by listening to part one, which is our previous, most recent episode. By the end of this episode, you will have a more clear way to think about how your role fits into the broader labor market and how to navigate your career in a world in which job titles just don't mean what they used to enjoy. I want to talk through the taxonomy of jobs. When people are looking for jobs or try trying to figure out what their next move is, a lot of times people will go on job boards, go to Glassdoor or Indeed or ZipRecruiter and search for a thing.
- [03:42]
Dr. Ben Zweig
Right.
- [03:43]
Paula Pant
But there is no standardization of how a job is described. And so the same role might be referred to as, for example, an executive assistant, a senior executive assistant, a chief of staff, a virtual assistant, an operations manager, a project manager. Yeah, take eight different companies and they might have significantly similar job descriptions for each of those titles.
- [04:10]
Dr. Ben Zweig
Yeah, it's really a mess. We collect so many different job postings and online profiles. I think we see 90 million unique job titles, which is obscene. There's no way a human can understand what all those are. And so many different companies have different conventions for how they use titles. And they all need to communicate to the external market, to a job candidate who is searching for something. It's a problem that exists on the employer side and also a problem that manifests itself for employees who actually just want to be able to search for something and find something that's a good fit, that's a good match. There are ways to solve this problem through LLMs where it wouldn't have been possible to solve this 10 years ago. Just to give some context, in economics, we sometimes think that there's two main factors of production in the economy. There's labor and capital. You can do some decomposition. And you know that the economy is roughly two thirds labor, one third capital. There is a science of allocating capital. It is finance. Finance is all about making capital markets rigorous and scientific. And there is no such science for labor. Part of the reason why that is, there's many reasons why, but one primary reason is the existence of accountants. Accountants are people that categorize. There are millions and millions of people in the world whose primary job is to categorize things for the purpose of financial analysis. So to categorize is this sales and marketing, is this cost of goods sold, like they're doing this categorization manually. And there are generally accepted accounting principles. There's a financial accounting standards boards. There are standards that have been worked on for 100 years, roughly. And we don't have millions of people categorizing job titles, and we never will. Maybe that would be nice. But we live in a time where LLMs are so good at categorizing things. It's really about finding out what's similar. And I love the way you explain that you have these different job titles where the job descriptions are the same. Because we actually do have a lot of text telling us what people do. If we think about what a job is carefully, we can think of it as this bundle of activities that needs to be coordinated. And those activities are right there. They're written down. We have responsibilities sections in job postings. We have bullet points on resumes, what people do. So we have billions and billions of sentences of what people do in their job in the economy. So we can create this way to find similarities between sentences. And we know that scheduling meetings, booking appointments, these are fundamentally the same thing. We know those are semantically similar, conceptually similar, and LLMs are great at telling us that. Then we can see for a given job title, what is the collection of work activities that they do. If they have the same work activities, we know they're the same. So personal assistant, virtual secretary, whatever it is, if we say they have the same set of activities, then they're the same job, full stop. One person says lawyer, another person says attorney, it doesn't matter, they're the same thing. There's also the harder problem that it can solve where one person might say, oh, I'm a product manager at Indeed, and another person says, I'm a product manager at Amazon. And these may be completely different things. The product manager at Indeed may be kind of an engineering lead. The product manager at Amazon might be doing client success work or something like that. If their collection of activities are different, even if their job title's the same, we should be able to say these are actually fundamentally different occupations. So then a job seeker who says, I'm looking for engineering lead jobs should actually see the job title for a product manager at Indeed. This is something that, if done right, gives candidates a lot more clarity on what they're seeing and also allows employers to organize their own workforce and figure out, what do we need more of, what do we need less of. It can also help the platforms like indeed in ZipRecruiter, because they are really in the business of facilitating discovery, so they need a common language for that.
- [08:26]
Paula Pant
Well, and the other complicating factor is that depending not just on the industry, but also the size of the company. And we've dealt with this when we've put up job postings, especially in a very small company, the role necessarily will involve wearing a lot of hats. And so there has to be some language within the job description that says, all right, maybe 70% of the time your role is going to fit this written job description. And the other 30% of the time it's respond to things as they come up.
- [08:54]
Dr. Ben Zweig
Yeah.
- [08:55]
Paula Pant
It is incredibly difficult to convey what it is that we need because we don't even know what it is that we need because all of these things come up all of the time. And when you are a company of four or five or six people, it's just deal with it totally.
- [09:11]
Dr. Ben Zweig
This is in some way one of the most important things to think about when we think about the future of work. Like how do your work tasks actually get determined? Maybe they just evolve organically. Maybe someone says, this is what I need you to do. Maybe you discover it yourself. But it's very fluid.
- [09:27]
Paula Pant
Right.
- [09:27]
Dr. Ben Zweig
So many people go into a job and then a year later they're doing something totally different.
- [09:31]
Paula Pant
Yeah.
- [09:32]
Dr. Ben Zweig
And this is such a common experience for so many people. And I. It's not like I think the firms are tricking them. It's that the needs change.
- [09:42]
Paula Pant
Right.
- [09:43]
Dr. Ben Zweig
Sometimes we think about, oh, AI as this thing which will reconfigure work, where we'll have these work tasks being taken away and others being introduced. And we think of technology as this secular trend which creates the need for job reconfiguration. But I think about small companies like yours and mine where job reconfiguration is just. It's an everyday thing. It has nothing to do with technology. Like, there's different demands on the business. Maybe a client says, oh, we need this. If a client says that to me, I think, okay, how do we do this? How much are they willing to pay? Who's got the bandwidth? Is it worth deprioritizing this other thing? And I'm trying to think, how should we reconfigure who's doing what? Or maybe someone quits. Or maybe we find out someone's actually not really good at something that we thought they'd be good at or not interested in something that they thought they'd be interested in. Or we automate something. There's so many different things that happen every day that causes us to think, okay, how do we shift the borders of teams? How do we make sure that the People we have can meet this changing, evolving set of needs of the business.
- [10:52]
Paula Pant
Right.
- [10:53]
Dr. Ben Zweig
If we had to think about what managers fundamentally need to do, I think it's about job reconfiguration. I think they need to understand the evolving needs of the business, understand the people and what they're doing, and reorient, try to continuously reorient what people do in their jobs to the needs of the business. And that's very fluid. The optimistic part of me thinks that if that's happening every day, then the emergence of a new technology may be big, but still relatively unimpactful in the general reconfiguration of work. Because the reconfiguration of work is so much a part of everyday business for so many people. Not to say there aren't organizations that are super rigid and bureaucratic and they have workers who are essentially like a cog on an assembly line. Those do exist, but I'd be much more nervous about them than I would about these adaptive, nimble organizations.
- [11:51]
Paula Pant
Would it then be the case that managers, especially as we move into a more AI driven world, managers become even more important because of the fluidity of job roles?
- [12:01]
Dr. Ben Zweig
I think that's right. The role of middle management will see an emergence. Yeah, that's my prediction. I still think. I mean, people love to hate on meetings, rightfully so. A lot of terrible meetings out there. But if I had to make a prediction, I think meetings will be more important as work needs to be reconfigured more often.
- [12:20]
Paula Pant
So then managerial skills become the skill of the future. For people who are listening, who are saying, what skill can I bring into the next couple of decades of my career? Managerial skills would be the skill to double down on.
- [12:33]
Dr. Ben Zweig
I think that's right. I mean, I don't know if they're easy to attain. I don't know if like management classes are any good or if there's like any good way to learn managerial skills, but it's definitely something that can be learned on the job. When I first started managing people, I was terrible at it and I hated it and then kind of grew to like it as I got better at it. I think it can clearly be learned over time.
- [12:58]
Paula Pant
Yeah, it can certainly be learned over time. In my own experience, I marvel at how slow of a learner I have been, at how long it has taken me to learn things that in hindsight seem obvious. To give a couple of examples, one is that given the fluidity of roles, I for a long time I resisted giving the people on my team formal Titles, because it seemed like. It seemed irrelevant anyway, given how fluid these roles are. So instead of giving them formal titles, I would give fun titles or funny titles.
- [13:33]
Dr. Ben Zweig
What was the funnest one?
- [13:34]
Paula Pant
So I had one who was a chief sanity officer. Okay, I have. This wasn't in my company, but I have a friend who has somebody on her team that she calls the Excellence Fairy. Okay, Excellence Fairy is in charge of qa, like quality assurance kind of thing. But yeah, fun or funny titles. The goal was it would evoke company culture that was sort of fun and light hearted, and that felt more like the camaraderie of friends who are all getting together to work on a project that was like what we wanted to evoke. In retrospect, I think it just caused a lot of role confusion. And it took me a lot of money, a lot of lost money before I finally, I brought in a fractional COO who did an audit of our company. And she was like, you need formal titles, you need formal job descriptions. You need KPIs for every role. You need a scorecard where you have outcomes and people are evaluated relative to those outcomes. And I was really resistant. I was like, no, no, that sounds like a government job. And that is not what we do here because our needs are so fluid. She explained to me that, like, no, if your needs are fluid, that means that you set procedurally, every six months, the job descriptions get reevaluated, rewritten, the scorecards get updated, and that just becomes part of your clockwork procedures. But you need that clarity and expectation in place. Otherwise, roles are too ill defined. Nobody knows what they're supposed to be doing. Nobody knows their scope of work, nobody knows their outcomes, and everything kind of descends into Lord of the Flies.
- [15:11]
Dr. Ben Zweig
Yeah, I struggle with this too. I mean, I also am, like, allergic to process in a way. Yeah, there's pros and cons to that. Sometimes there's confusion, and that's what you get. But also, I get that we don't want things to feel like you're working in a government job. And I wonder, this excellence fairy, like when she went to the proverbial cocktail party and someone said, hey, what do you do? Yeah, what do you think she said? Do you think she said, oh, I'm an excellence fairy? Or do you think she, like, outlined the stuff she did, or do you think she just chose a different title?
- [15:44]
Paula Pant
Yeah, that's a great question. I don't know.
- [15:46]
Dr. Ben Zweig
Yeah. When people ask what I do, I don't really know what to say because it's very Varied. Sometimes I say I'm an entrepreneur, but sometimes I say I'm an economist, which is more of an identity than an occupation for me. Like I did a PhD in economics. I feel like in my soul I'm an economist. But it doesn't really describe my day to day spend my time running a company and doing all the things that entrepreneurs do. And the fact that I have a background in economics is like not so relevant to that. I wonder if we kind of have these identities and the occupations where occupation is. And our job title. Our occupation is really shorthand for the collection of things we do. Like if someone says, oh, I'm a QA analyst, then we kind of know what they do. And you're like, okay, you like testing frameworks, you can do this and that. So we maybe have some sense of the stuff they do. And if someone says I'm an entrepreneur, then someone hears it and they say, okay, I kind of know the collection of things you do. If someone says you're a teacher, like you know what they do. I think we can also kind of maintain this other identity that is like, oh, well, I have my professional brand and professional, I don't know, I guess just professional identity that is a little bit distinct to the day to day. And maybe when people ask, what do you do? Maybe there's a part of them that's asking like, how do you spend your day? Because that's a valuable question to get to know someone. But maybe a part of that question is like, how do you think about yourself professionally? I don't know. It's like a tough question to answer. Yeah, yeah.
- [17:18]
Paula Pant
I mean. And so back to what does the Excellence Fairy say at the proverbial cocktail party? I would imagine most people would not lead with that title because the title is not informative. So I think you would have to. Going back to a job as a bundle of tasks. You would have to at that point just describe the bundle of tasks that you do. Technically, officially my title is Excellence Fairy. But what I read. Yeah, what that means is that I do A, B, C, D, E. Right?
- [17:46]
Dr. Ben Zweig
Yeah, but that, that like takes a while. Yeah, you do need some sort of like shorthand, right? I mean, I think that's in some ways like why we have taxonomies. Generally we have taxonomies of products and taxonomies of the animal kingdom. Like all over. We have the shorthand, which is like a mental. It's just a mental shortcut. I mentioned I have two girls in preschool and so much of raising a kid, I Think is about introducing categories. I've been working on taxonomies for longer than I've had kids, so sometimes I'm just like, oh, wow. We are instilling this idea of taxonomies at such a young age.
- [18:26]
Paula Pant
Right.
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Dr. Ben Zweig
We are just like, here's farm animals, here's shapes, here's colors, here's noise. Like we were trying to get them to a point where they think in terms of categories. And that way when we say, oh, there's a clock, we can glance at it in a millisecond. It could be a clock we've never seen before, but we know how it behaves, we know the direction things go, we know the properties that sometimes things are fast, things are slow. And that is something that we are also much better at than machines. It's very expensive, it's very computationally expensive for an AI system to recognize a clock. Our brains are wired in a way that's very cheap for us. It's like very computationally inexpensive. I think, really, because we have these categories sometimes I think that we are just taxonomical animals.
- [19:17]
Paula Pant
Right.
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Dr. Ben Zweig
We really need these heuristics to do kind of mental classification and association cheaply.
- [19:26]
Paula Pant
And yes, we are classification animals. Absolutely. Even the notion of an animal.
- [19:31]
Dr. Ben Zweig
Yeah, yeah, exactly. Right. I mean, we're not birds. Yeah, good.
- [19:35]
Paula Pant
I think a lot about the platypus because that is the animal that defies Linnaean classification. Right. It's an egg laying mammal, which, based on the rigidity of classification systems like that, should not exist. Mammals, by definition do not lay eggs, unless you're a platypus, in which case you do.
- [19:54]
Dr. Ben Zweig
Yeah.
- [19:54]
Paula Pant
And so you have occasionally, when you have these rigid taxonomical structures, you have the occasional outlier like the platypus, that defies those boundaries. And I don't know if there's ever been a good understanding about what to do. I feel like society has collectively just said, we're not going to talk about the platypus. Next question, please.
- [20:17]
Dr. Ben Zweig
Yeah, yeah. The way we categorize things should really be based on what's useful rather than what's like, technically correct. I'm sure we all have that annoying friend who tells us that a tomato is really a fruit. Yep. Yeah, yeah.
- [20:31]
Paula Pant
I like to say my favorite fruit salad is guacamole, because Avocado and tomato.
- [20:36]
Dr. Ben Zweig
Yeah, exactly. But like, practically we treat it like a vegetable and we categorize it like a vegetable and that is the more convenient categorization for us. There's this really fun book. It's called why Fish Don't Exist. And it's about the first president of Stanford University who has this crazy story. He probably murdered the wife of the founder of Stanford.
- [20:57]
Paula Pant
Wow.
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Dr. Ben Zweig
It was nuts. And he was a taxonomist, so he would categorize fish and try to find a new kind of fish and, like, label it and name it and all that. There's been these advances in computational evolution that can sequence the genome of all these different animals, and they found that fish aren't actually a category in that they don't descend from a common ancestor. There are fish that we consider fish that are descended from reptiles or amphibians or mammals or birds or mollusks or whatever. And we consider them fish now because that just is what happens when you live in an Ocean for 200 million years. You kind of become a fish. It's not actually, like the evolutionarily correct way to think about how to categorize animals. We shouldn't stop using the category of fish because it means something and you can explain it to a kid and you can understand it pretty easily. And we know they behave. We know they have fins of skin. We have all these properties that we associate with fish in this way of categorizing things. We always have things that are at the borders. And a platypus may actually be practically at the border of a lot of different things. That's kind of always the case. So even in occupations, we have marketing and sales, and it's useful to think of those. But then we have people that are kind of like, between marketing and sales.
- [22:17]
Paula Pant
Yeah.
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Dr. Ben Zweig
And they're this, like, platypus type role. There's some cost to discretization. By creating categories, we are discretizing, which means we are throwing away the, like, within category variants. We can say dogs, and we know there's like, big dogs, little dogs, and that is like a broad category. And we know that we're losing a lot of nuance when we just say dogs. And same thing when we say mammals. Like, there's weird ma. Like there's platypuses and there's humans and there's whales, and they're all really different. That's why we have hierarchy in our taxonomies. So then we have these, like, categories where maybe platypus is less weird but still quite different from, like, primates.
- [23:04]
Paula Pant
Yeah, I mean. Cause you think about the classification of dog. You have everything from a Chihuahua to a German shepherd or a Great Dane falls under this very broad category known as dog. You don't have that Same level of variance in cats, in the domestic house cat.
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Dr. Ben Zweig
Yeah.
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Paula Pant
A cat is a small carnivorous mammal that generally adheres to certain dimensions, a certain body weight, certain dimensions. It doesn't really stray outside of this very narrow band.
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Dr. Ben Zweig
Yeah.
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Paula Pant
And that is not the case with dogs.
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Dr. Ben Zweig
Yeah, it is weird that there's a lot of variance in size, but you could make the case that there's less variance in other things. So I don't have a dog. But people that have dogs, I think, see a lot of similarities in themselves and other dog owners, and they can relate to each other even if their dogs are totally different types of dogs, because there's some commonalities. They're friendly and they have this positive energy and they want to please you. And what. There's all these things that identify them, and there's other dimensions that don't identify them well, like size. Whereas cats, they are identified by some
- [24:17]
Paula Pant
dimensions, but they have a great deal of personality variance.
- [24:21]
Dr. Ben Zweig
Yeah, I mean, I'll take your word for it. I don't really know anything.
- [24:23]
Paula Pant
I like a huge degree of personality variance. Even two cats raised in the same household at the same time, massive personality variance.
- [24:31]
Dr. Ben Zweig
Same with humans. I mean, humans don't have a lot of size variance. We are relatively all the same size, especially compared to dogs, but. Yeah, lots of personality variants.
- [24:41]
Paula Pant
Yeah.
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Dr. Ben Zweig
And we categorize ourselves in all sorts of ways. There's all sorts of, like, demographic categories. We categorize ourselves based on ethnicity and things like that that are also kind of arbitrary.
- [24:56]
Paula Pant
Exactly. Yeah. I'm Nepalese. That's a definition based around a set of national borders that didn't even form until the late 1700s.
- [25:03]
Dr. Ben Zweig
Right.
- [25:05]
Paula Pant
So what would that make me pre 1700s? I don't know.
- [25:09]
Dr. Ben Zweig
I don't know. Yeah, yeah. I mean, maybe back then, you know, revert to big five personality traits or something. I think in some ways it's a good examp example of, like, how deep we want to go based on, like, how familiar we are with things. So with humans, like, we have such a nuanced understanding of different types of humans, you know, by saying someone's Nepalese, that's informative because it tells us about their background, how they might think about things. Like their upbringing probably carries information about socioeconomic status. There's information that we can convey, but that is relevant to us, but probably not relevant to. To a dog who's, like, looking at humans like they probably don't care. And in some way it's a little bit similar with jobs where if you're in the finance part of an organization, you probably only care about like what's sales and marketing, what's R and D, what's this and that, broad categories of occupations. But if you're in like talent acquisition, you really want to know like oh, what's the difference between like DevOps Manager and an infrastructure developer? Like things that are like really precise, right? So having this level of hierarchy, how much detail do we want to get? Like how deeply do we really care to understand something?
- [26:27]
Paula Pant
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- [31:05]
Dr. Ben Zweig
Sometimes when we build these taxonomies, we think, how many unique occupations are there in the world? How many unique activities? If we take the collection of things people do in their jobs, how many are there in the world? Like, how many distinct things do people do? It is finite. So for job titles, let's say at about 15,000, you start getting like, real synonyms. There's probably roughly 15,000 occupations. If you go deeper, you're really splitting true synonyms. And in work activities, probably like 60,000, which sounds like a big number. But sometimes I think about that and I'm like, oh, wow, that's actually like, not that big. It's a number that we can kind of wrap our head around and like just the collection of all the things in the world, in every industry, in every geography, the whole set of things that people do in their job. 60,000 things like that, that's the whole economy, that's the whole labor market. It just seems not that big. Sometimes I think about that and like, okay, we can understand this. That's not more than we can process. We can certainly store that amount of data. We can have a catalog that has 60,000 elements. It's way smaller than a library. And yeah, maybe this isn't so hard after all. Maybe understanding jobs, activities, skills, maybe these things are actually quite doable. Maybe. That does sound like a lot. Yeah.
- [32:28]
Paula Pant
And that 60,000 is always changing again, going back to how, what, 60% of the jobs that currently exist didn't exist back in the early 1900s. I don't know what the rate at which they're changing. And if that rate, I would imagine, although I don't know this, that rate has sped up quite a bit just in the last decade or two.
- [32:47]
Dr. Ben Zweig
I would imagine that too. It's very hard to. To get data on what work activities people did going back a long time. So we have good data on occupation, on the occupational breakdown, which is why we do these things at the occupation level and find there are lots of occupations that didn't exist. We have social media managers and AI engineers and all that. We don't have elevator operators and switchboard operators and things like that. The better question that we really can't answer is, what are people doing today that they weren't doing 100 years ago? I love to think of this example of bank tellers. There was this big article I think in the Wall Street Journal when ATM came out, that bank tellers were just going to be completely devastated, demolished, completely obsolete. Now we have something like 10 times more bank tellers than we did when that article was published. So we didn't see a reduction in the quantity of bank tellers. There's a very common narrative that we hear in economics, which I think is wrong, that says that this is an example of something called Jevons paradox. So Jevons Paradox is that when the price of an input falls, we can sometimes actually spend more on that input.
- [33:55]
Paula Pant
There are more use cases for it, more demand for it.
- [33:57]
Dr. Ben Zweig
Yeah, exactly. So if the price of gas to drive our car falls by half, maybe we'll drive more than twice the amount and actually spend more money on gas, something like that. It's, like, possible that's the case. The story goes that the price of depositing and withdrawing money became so much lower, that led to a scenario where instead of having a bank in the center of town, now you have a chase on every corner. So we just expanded the just banking as a phenomenon. The reason why I don't find that to be a satisfactory answer is that it assumes that bank telling is bank telling, and I think that's just not the case. So right now, people that are bank tellers are not primarily depositing and withdrawing cash. They're primarily doing customer support and relationship management and helping people navigate products and, like, different types of credit cards and things like that. And it's really much more of a customer service, customer success type role. And it's really just a different job. What could have happened where some executive at Chase Manhattan at the time had made a call that, we're gonna stop calling them bank tellers. We're gonna start calling them relationship managers. And we'd be telling a very different story right now. The fact that we call it the same thing is just kind of unimportant.
- [35:15]
Paula Pant
Six of one, half a dozen of the other.
- [35:17]
Dr. Ben Zweig
Yeah, yeah, it's a different job. Whether we use the same title or not is. You know, I almost wish we didn't, but sometimes we do. You know, sometimes jobs evolve gradually. I give this example where the role of statistician is totally different than it was 50 years ago? We still have the title statistician. Maybe we shouldn't. It's kind of irrelevant what it's called
- [35:37]
Paula Pant
in a way, when the role fundamentally changes so much that it is no longer recognizable to a person who had been practicing that same role, let's say 40 years in the past. This is, it's like a tree falling in an empty forest. Is it still the same job?
- [35:52]
Dr. Ben Zweig
Yeah, exactly.
- [35:53]
Paula Pant
It's an amoeba splitting into two. Like, is it still the same amoeba? I don't know.
- [35:56]
Dr. Ben Zweig
Yeah, I mean, maybe there is some convenience to keeping the same set of job titles, which is fine. I think that's like a good reason to keep job titles.
- [36:05]
Paula Pant
But it raises a very interesting point which is that then cast this question mark on the conversation of quote, unquote, will jobs survive? What does it mean for a job to survive if a job title iterates the scope of work and like iterates and iterates and iterates gradually enough that it evolves to something that it didn't used to be. And that new something requires a totally different set of qualifications, experience, skills. What does it mean for that job to have survived?
- [36:37]
Dr. Ben Zweig
Yeah, I think that's right. I mean, so much of this conversation I think ignores that within job transformation, which is I think the most important part of all of this, I mean, there was this famous essay by John Maynard Keynes in 1930 which is called Economic Possibilities for Our Grandchildren. He makes a prediction that a hundred years from now, and we're right around the corner to 100 years from 1930, we said that we'll be working 15 hour weeks so that productivity will grow so much that we will run out of things to do and we'll just live a life of leisure. That's basically the prediction every generation, with every technology. Sometimes I think about that essay and I think, oh, he was dead wrong. We're not working 15 hour weeks. Like he was actually right on our productivity growth. Like productivity has grown actually faster than he predicted. But we have this insatiable appetite and now we want to consume things that we didn't consume before. And we have this growing need for what we think should be done. And I think, okay, we're not going to run out of things to do. There's lots of things that we want in the world that don't exist in the world. So that kind of makes me feel like, oh, he was wrong because he didn't account for our growing appetites then. Sometimes I go back and forth on this. Sometimes I think actually maybe he was right, maybe we actually do live a life of leisure, but that's happening within our job. Like right now you and I are working and like I'm having fun, you know, so you know, this isn't like back breaking labor, you know, we're not in a sweatshop and that is the reality of a lot of people's jobs now. Like jobs have gotten more social and there's more, a little more fun, there's a little more leisure. And that is the transformation of work that does give us a little bit. I mean, people are pursuing jobs based on what they want to be doing more than what just pays the most. More and more, that's something we have lots of evidence for, that newer generations put a higher priority on things other than compensation, work, life balance and management and culture and all that. And that is consistent with this idea that we actually maybe are pursuing more leisure. But so much of these phenomena of job displacement, of automation, like it's happening within jobs, it's not happening between jobs. It's so important to think about what's happening within each job. How is each job transforming the advancement
- [39:03]
Paula Pant
and the proliferation of knowledge work? I mean that, that is a good point, that there's a degree of leisure within the domain of knowledge work in particular, because to be able to sit in a climate controlled environment with adequate air conditioning and adequate heat and push buttons with your fingers all day. Yeah, that is certainly quite leisurely in comparison to a lot of the very dangerous jobs that millions and millions of people have had and millions still do have in other industries. Which then, bringing it back to AI makes it so jarring. The notion that this is the first thing that has really disrupted knowledge work.
- [39:42]
Dr. Ben Zweig
Yeah, for sure. I mean, it does feel weird. I forgot who said it, but someone had some famous line that I want AI to do my laundry and dishes so I can write and make art. I don't want AI to write and make art so I can do laundry and do dishes. Yeah. And it is kind of threatening. The things we like about our jobs. The thoughtfulness, the deep thinking, the analytical component. I get that that's scary. The question is, what is the remainder? Is what's left over even more fulfilling or is it less fulfilling? Like if we really were being forced into more jobs that require dexterity and things like that. I don't think we all want to be busing tables and doing laundry, but maybe we do want to be overseeing more ambitious, exciting projects and coordinating more abstract activities that create more value. Maybe that is actually exciting in a way that AI can unlock our workflows to be more exciting and more. More human in a way, because there
- [40:52]
Paula Pant
are frontiers that we haven't even approached. We're not building cities underwater yet.
- [40:56]
Dr. Ben Zweig
Yeah.
- [40:57]
Paula Pant
It strikes me we still take trains just like we did in the 1800s. There are so Many facets of life that can be innovated and iterated and new frontiers that we haven't even approached that could be developed totally.
- [41:12]
Dr. Ben Zweig
There's so many pockets of our economy that have had really low productivity growth. Housing, you can argue, has had even negative productivity growth. That's creating all sorts of problems for affordability and walkability, you know, things that
- [41:26]
Paula Pant
are desirable and density of cities and having balanced density with people. I mean, people inherently do enjoy having space, but also enjoy living in the community that comes with living in density. And how do you balance those two?
- [41:39]
Dr. Ben Zweig
We need more productivity. And it's worth kind of remembering that, like, the future's already here. It's just not normally distributed. We sometimes talk about, like, our own jobs as being we can do more interesting, more enlightened work. But there's so many parts of the world where that's not the case, where they are still kind of working in sweatshops. And that kind of productivity, like, taking these innovations to other places can be really useful also bringing them here. We don't have bullet trains that they have in Korea or Japan. I took the Metro north today. It's fine. Super annoying.
- [42:12]
Paula Pant
Yeah.
- [42:13]
Dr. Ben Zweig
But it's not a bullet train.
- [42:14]
Paula Pant
Yeah.
- [42:15]
Dr. Ben Zweig
And it does feel like we as a society, I mean, me personally, probably all of us do feel a little bit impatient with how quickly we're, like, making progress or not making progress in certain pockets of the economy. It's like we are hungry for more. Yeah.
- [42:30]
Paula Pant
Whenever I take the trains around New York, like when I take the Metro north train or the New Jersey Transit line or I go to Penn Station, I do feel a little bit like I'm living in the Gilded Age.
- [42:39]
Dr. Ben Zweig
Yeah.
- [42:40]
Paula Pant
I feel like it's the late 1800s, early 1900s. I don't feel like I'm living in 2026.
- [42:47]
Dr. Ben Zweig
Yeah, we want more, and we'll get there. I mean, one is that we'll get there through technology, but also through combining labor with technology in my company. I'm sure you feel the same way. I would love to have 30 more people. I know exactly what I would do with that. If someone can free up more of their time. I've got a long list of things I want people to work on that grows faster than our ability to work on them. Even within a company, there's just so much more that we'd like to deploy labor to do.
- [43:19]
Paula Pant
Yeah. Yeah, that is true. And I think almost every small business owner feels that looking at the jobs report, looking at the labor, you know, labor stats from the Past year, what we've seen is job growth has been slow and most of that growth has accrued to the largest companies. Looking at the labor reports, the hardest hit companies have been the smallest ones. And yet, as you and I have just talked about, both of us lead small companies and both of us are like brimming with ideas for what. I know exactly what I would do with. I don't know what I would do with 30 people. I definitely know what I would do with like 10 more people. Yeah, I could definitely put 10 more people full time to work tomorrow and I would be thrilled if I had the hiring budget for that.
- [44:05]
Dr. Ben Zweig
Yeah.
- [44:05]
Paula Pant
And the minute those 10 more people were deployed, give me six months and I would know what to do with the next 10.
- [44:11]
Dr. Ben Zweig
You're right that employment has been slow, like way too slow for the economy at large. Especially slow for small firms. It's hard to pin down exactly what's driving that. I suspect it has more to do with capital markets than with labor markets. It is harder to get financing for a small business, for a startup today than it was back in 2021. Venture capital as an industry has transformed very rapidly. First of all, it's been very unsuccessful as a business model in the last decade or two. But also the nature of venture capital has been much more concentrated in specific debts that attract a lot of risk capital. And then they've been becoming more private equity esque with the rest of their capital. So the big Silicon Valley VC firms in the last decade have basically invested. The first five to 10 years ago were basically just investing in crypto and now they're just investing in AI. I mean, I'm exaggerating a little bit, but I think it's true enough that they're really frothy valuations, tons of money going toward AI startups. Still crypto startups now, but SaaS companies, hardware companies, science, you know, they are not getting funded. They're being funded on multiples of like earnings rather than like multiples of revenue, which is like weird. You know, we think of that as like private equity behavior.
- [45:44]
Paula Pant
Right.
- [45:45]
Dr. Ben Zweig
Which is very risk off and trying to, you know, pressure companies to focus more on profitability a little less on growth on the margin. So the excitement around AI is probably funneling some capital away from growth of small medium sized businesses.
- [46:01]
Paula Pant
So it makes sense to the extent that the VC model prioritized growth rather than profitability because the priority was forward looking earnings. Right? The priority was we're going to place a valuation on you based on what we think you might make five years
- [46:17]
Dr. Ben Zweig
into the future or 20 years into the future. Yeah.
- [46:20]
Paula Pant
And now that we're entering this AI world, forward earnings, forward revenue is so unpredictable, the value of a company is so unpredictable that the VC model can no longer place a valuation today on what a company might be worth two years in the future even. Because who knows what the world's gonna look like two years from now.
- [46:43]
Dr. Ben Zweig
Yeah.
- [46:44]
Paula Pant
So the. Because the future is so unpredictable, you can't discount that back to today. And therefore you can't really place a good valuation on companies today. And so then you just have to value a company based on a revenue multiplier.
- [46:59]
Dr. Ben Zweig
Yeah.
- [46:59]
Paula Pant
Which is the old fashioned way.
- [47:01]
Dr. Ben Zweig
I think that's exactly right. Investors, companies, I mean, we are in a high discount rate environment. We are discounting the future a lot relative to the present. We are prioritizing for the present. Some of that has to do with interest rates and the macroeconomy. I think a lot of it has to do with technology, like you said. I think a lot of it has to do with policy as well. There's uncertainty around like, what is the world going to look like. We have a lot more uncertainty around the geopolitical situation, around what the technological frontier is, around migration patterns. I mean, so many things that like really affect the composition of our economy, they're so uncertain right now. So I think it's creating an environment where it's very hard to invest in the future. So I think it's very rational. I don't want to blame VCs. I mean, maybe a little bit.
- [47:51]
Paula Pant
Yeah, no, it is, yeah. It's completely rational that the valuation. And I think that it's actually probably a good thing when you're making a lot of speculative bets, placing these speculative bets on companies not based on their current revenue, but based on expectations for future revenue, which is by definition speculative. You get a lot of busts. Whereas if you're, if you are placing valuations on companies based on current earnings or current earnings growth, when you're placing a valuation on a company based on actual numbers that they have achieved, the valuations come down, but the valuations are also rooted in something that is much more fundamental and real in your situation.
- [48:34]
Dr. Ben Zweig
If you wanted to hire 10 people, you could accept a bad valuation on your business and raise some money and hire 10 people, but that would be very expensive. But if we were in a different environment, you would borrow money cheaply and hire 10 people if you knew that they would be deployed to productive ends.
- [48:52]
Paula Pant
Is it then the case that because of the changing nature of the VC model and the changing nature of how we are placing valuations on small businesses. That's why we've seen so much of the labor growth accrue to large companies.
- [49:04]
Dr. Ben Zweig
I think so I'm sure there's other parts to the story, but that's one that I think is certainly happening. There's other frameworks to use to think through that maybe there are more efficiencies in large organizations. When I teach the future of work, I sometimes think, why don't firms grow to infinity? Why don't we have infinite specialization or the opposite? Why don't we just have a bunch of independent freelancers running the economy? What dictates the optimal size of firms? And I think ultimately it comes down to coordination costs. There's some cost to coordinating a small team. That's lower than coordinating a big team. And there's some returns to specialization. So a big company can have specialists and they can really benefit from that specialization in a way a small company can. I think it's this balance of coordination costs and specialization and the relative costs and benefits of those change due to technology and regulation and things like that. So I wonder if the technology we see now is reducing the coordination costs in large organizations relative to the coordination costs within small organizations. So a small company, a company of five people, they talk to each other, their coordination costs are the same as they've always been. But in a large company they coordinate using technology. And as technology gets better, we get slack and summarization and this and that and zoom and whatever. Maybe coordinating across lots of people is becoming cheaper.
- [50:46]
Paula Pant
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- [55:44]
Dr. Ben Zweig
Yeah.
- [55:45]
Paula Pant
But the orchestration of that in a team of five, a company of five is not going to change totally.
- [55:51]
Dr. Ben Zweig
The execution benefits accrue to small and large companies alike. That really shouldn't dramatically affect the different distribution of company sizes. I don't know if we have a lot of evidence driving the change in the returns to large companies versus small companies. It's worth thinking through.
- [56:07]
Paula Pant
Do you think this pattern will remain, this pattern of large companies being so far the winners in the AI landscape? Will that pattern continue to persist or will eventually small companies, which can have more niche specializations, will they be able to kind of innovate their way out of this?
- [56:26]
Dr. Ben Zweig
Yeah.
- [56:27]
Paula Pant
Or specialize their way out of this?
- [56:28]
Dr. Ben Zweig
Yeah. I would put my bets on small firms relative to large firms because here's one way to think about who's well positioned to take advantage of new technology. Like we spoke about job reconfiguration and how managers really need to like reconfigure jobs. I think a lot of big companies have been successful because they have very clearly streamlined processes and a Lot of efficiency from, like, fine tuning processes with a lot of structure. You know, if you think about a big bureaucracy, like with an assembly line, like, everyone's got a very specific job. I think it's harder for them to reconfigure the tasks in people's jobs. So I think that they will be not so well equipped to be able to restructure what people do as easily. Whereas small firms are adaptive in nature, we are constantly reconfiguring what people do. And when a new technology comes out, it's easy to use it. There's no bureaucracy to run through. I mean, I still hear big companies that are still struggling to figure out their privacy policy around using ChatGPT for their work. And they just have to use some, like, gated version that's super clunky and you can't export data. You know, they like, can't get it together. And I think that's gonna hurt them a lot. I'm also very concerned about artificial rigidities in what people do. So, like occupational licensing and professional trade organizations, like, if you are a phlebotomist, you're allowed to, like, draw blood. And if someone asks you a question that you know the answer to, you're like, legally not allowed to answer that question. You have, like, very hard constraints on what activities you're allowed to do, what activities you're not allowed to do. There are these regulated industries that I think will also not be able to adapt to technological change, and I think that'll hurt them. I'm concerned for the future of those organizations that are typically larger, whereas the smaller upstarts that are trying something a different way can adapt very flexibly.
- [58:39]
Paula Pant
That makes a lot of sense because the more you have that occupational rigidity, the less that you are able to. We just talked about the fluidity of roles. The less you are able to adapt to the fluidity of roles, which is necessary in a rapidly changing environment. And if you can't, it's adapt or die. If you can't adapt, you die.
- [58:57]
Dr. Ben Zweig
Yeah. And our company, someone, one of our economists, just wrote a newsletter about consulting firms and how consulting firms are shifting their workforce dramatically. They're taking on lots of AI roles. They're like, trying to embed AI in everything they do, like, very aggressively. And right now, these like, AI roles, like roles that didn't exist before. AI people whose job it is to use AI technologies and implement it, they now exceed the number of entry level consultants in consulting firms. I don't know when I saw that result. I was like, wow, this is crazy, because we think of consulting firms as like the launching pad for ambitious young people and.
- [59:36]
Paula Pant
Yeah, yeah, it's like the Harvard to McKinsey pipeline.
- [59:39]
Dr. Ben Zweig
Yeah, yeah, exactly. People talk about Palantir as this example of the Stanford computer science undergrad is the new Harvard mba. I think we are seeing some of that. And consulting firms have been allowed to adapt. And I think of law firms as kind of a good parallel to consulting firms because it's a similar model. It's a similar, like, up or out type of model where you have the partners who are the experts really selling business. I think there's just a lot of similarities in their operating model. But law firms are bound by professional associations. There is the bar association and consulting firms are not. We don't see this happening at law firms, but we do see it happening with consulting firms. I think that probably is due to the bar association having imposed rigidities on what lawyers are allowed to do, how they can do it. And I think that's worrisome.
- [60:34]
Paula Pant
How should an individual in either of those professions deal with that impending risk? Like, how should an individual who is currently a practicing attorney be thinking about that?
- [60:45]
Dr. Ben Zweig
For practicing attorneys, I think what the professional association is doing is sort of protecting the incumbents. So I'd be much more nervous if you were about to look for a
- [60:57]
Paula Pant
job in law if you're in law school, if you're like a. What is it? L3.3L.
- [61:01]
Dr. Ben Zweig
Yeah, yeah, something like that.
- [61:02]
Paula Pant
Yeah, yeah. The third year law student.
- [61:04]
Dr. Ben Zweig
Yeah. So I think they've been having a hard time even the last, like, couple decades. I think the majority of law school graduates do not end up practicing law, which is crazy. But, yeah, so it's been a tough market for lawyers generally. I think it'll get even tougher because there are, number one, like, constraints on new entrants and constraints on how productive they could be, how quickly they can implement new technology or just like, use new technologies. But also they're challenged by free and cheap substitutes for legal work. You know, if someone wants to, like, write up a contract, they can just do that using AI Right now, maybe there's a case to be made for whether that's a good idea or not. I personally use AI for a lot of contracts, but even just with this book, I wrote this book with Wiley and they sent a contract over. I just asked ChatGPT, like, what's standard? What's not standard? Like, is this a good term? What should I push back on? And I did this negotiation with essentially An AI lawyer. And I think it was fine. It was good. And who knows, maybe it'll come back to bite me. But you know, it's better than paying a couple thousand bucks for a lawyer to look it over. I think there is competition just from practitioners having less demand for lawyers, especially
- [62:22]
Paula Pant
for the kind of lower level tasks.
- [62:24]
Dr. Ben Zweig
Yeah, exactly.
- [62:25]
Paula Pant
You know, procedural lower level tasks. Drafting a lease for the rental of a single family home, that type of a thing.
- [62:33]
Dr. Ben Zweig
I mean most lawyers are just going to copy and paste that anyway.
- [62:36]
Paula Pant
Yeah, exactly. Or use the template.
- [62:38]
Dr. Ben Zweig
Yeah, exactly.
- [62:39]
Paula Pant
From the state. It reminds me of a joke. A couple of friends and I, we got these invitations. The invitation said, oh, dress code is business casual. My friend looked at me and she was like, what's business casual? And my other friend was like, eh, it's when you don't read the contract too closely.
- [62:56]
Dr. Ben Zweig
Yeah, nice.
- [62:58]
Paula Pant
So yeah, I think the new one is like eh, funny. Use AI to read the contract.
- [63:02]
Dr. Ben Zweig
Yeah, yeah. This is time and a place.
- [63:03]
Paula Pant
That's business casual.
- [63:04]
Dr. Ben Zweig
Yeah.
- [63:05]
Paula Pant
We talked earlier about somebody who's between the ages of 25 to 30 and they're starting their career. I want to close this out with someone who's old enough that they are established, they have a network, let's say between the ages of 35 to 55. Right. I guess that's a wide range. But like you're old enough that you're established, you're an incumbent, you're old enough that you don't necessarily want to retrain in a different occupation.
- [63:34]
Dr. Ben Zweig
Yeah.
- [63:35]
Paula Pant
At your age and your current stage of life, you don't want to go back to school to obtain some high barrier to entry credential, but you're also not ready to retire. So that 35 to 55 age range, what should anyone in that bucket know? As we think through the future of
- [63:55]
Dr. Ben Zweig
work, I would almost segment it into two types of people there. Some people in that age group are working at big companies, like you said, more and more. If you're playing a role in a big company, you're probably something like a knowledge worker. You're probably connecting things, answering emails, involved in a variety of different business functions. And your job probably does transform actively all the time. My advice to that person would be to try to pay attention to how your job is transforming. Even just like every once in a while just look back to what you were doing three months ago and just think, oh, how did my job transform? What led to that? Was that because my manager wanted me to do different things? Is that because I just Took on new responsibilities. I mean, there's this phenomenon of job crafting. It's this idea that people can sort of shape their own job based on what they like, what they think is more productive, what they find more meaningful. And that probably happens a lot, even when we don't explicitly think about it. So I would encourage people to just be purposeful about thinking through what you do in your job. Are there parts that you like and don't like? How would you like to transform that? And how should you interact with your manager to align that to the objectives of the business? If you can find a way to have a more fulfilling job and also be delivering productive output, great, go for it. Reconfigure your job such that it does that. There's other people in this age range who are in more narrow jobs that are not knowledge work. So let's say, you know, someone's an electrician or something that is. I mean, maybe that's not a good example because that's probably not so likely to get automated, but something where your occupation might be vulnerable to automation. Most jobs don't get automated wholesale, but there have been times when that did happen. Switchboard operator, typists, things like that. That is concerning. So will we see AI displacement, like labor displacement? How responsive can suppliers of labor be? I think probably quite responsive. So in this example of switchboard operators, there was really very little unemployment that resulted from switchboard operators. Most people who were operating switchboards went into secretarial work. They were able to reorient what they did very quickly. And I think because the skills and tendencies overlapped, even though the work activities were different. If you do feel like your job is sort of at the cusp of what might be automated, I think I would just encourage them to take an inventory of their skills, their interests, what they're good at, what they would do if they didn't have to worry about money. Which can be a good starting point to thinking about, like, where is my energy? But sometimes it does require some adaptation. Going back to the Luddites. Don't smash the machines. Don't be like John Henry. It's much more productive to think of how you can sort of reorient your capabilities towards some other productive ends.
- [67:09]
Paula Pant
Actually, we should close on the story of switchboard operators and typists, because I think there's some hope there. Both of those job categories became obsolete.
- [67:21]
Dr. Ben Zweig
Yeah.
- [67:22]
Paula Pant
But it actually then led to a proliferation of more advanced, more sophisticated jobs. Your mom was a typist?
- [67:30]
Dr. Ben Zweig
Yeah, my mom started her career as A typist. She was, like, trained on a specific typewriter, the IBM, whatever, and you had to get trained. And she was very proud of being able to do however many words per minute. That was her job. Now, what's interesting about being a typist is that you're not just typing. Like, you're also figuring out how to message things, how to translate information and make things concise. It's not really just hearing words and, like, typing them out. As computers became more widespread and typing got easier and easier, she kind of gradually made her way into more secretarial work and then started doing more secretarial things and was in that occupation for a while and then eventually was doing secretarial work at large companies, at law firms. She also worked at IBM for a little while, did more and more secretarial work, and eventually was involved in managing a lot of information and files and categorizing things, which is kind of what people do in. In as a secretary. And eventually just became the expert on filing documents related to. I think it was like, subsidiaries of a company and like, the documents for incorporating the subsidiaries of something, and became this, like, manager of a subsidiary database for a company. I don't think she ever thought of herself this way. When she told me about this, I was like, oh, so you're like a database administrator? And she was like, I guess, you know, like, she never thought of herself as a database administrator, but, like, that kind of is what she did. And that is a role that you can hire for today. But she always thought of herself as like, some hybrid of, like, secretary and paralegal and this hodgepodge job of, like, understanding and categorizing information. These things do happen gradually. The activities didn't change as much as the job titles changed, which is kind of a counterexample to the bank tellers, where the activities changed a lot and the title stayed the same. So, yeah, I mean, you kind of have both sides of the same coin.
- [69:42]
Paula Pant
And I think that there's quite a bit of optimism there for people who are worried about job displacement, because both the bank teller example and the typist to database administrator counter example both illustrate the changing nature of jobs, regardless of what the title is, the changing nature and then the very fluid nature of work.
- [70:04]
Dr. Ben Zweig
Yeah, I mean, we spoke about, like, how responsive is labor supply to automation? Can workers find new things to do? Another issue is how responsive is labor demand to automation, to technology? So do firms actually adopt technology? And when they adopt technology, is it fast or is it slow? And I Think for better or for worse, it's a bad thing. But firms don't adopt technology all at once. They're slow. Especially big companies are really slow in implementing change. On the one hand, that's not good for those companies, but on the other hand, it does give us time to adapt. Workers can find new things to do. They have time. Because firms are not going to implement new technology just like that. Yet we have a chance to kind of reconfigure work by ourselves through talking to our managers, by understanding the changing needs of the business. All of these things happen organically. And yeah, I think that is kind of a hopeful story.
- [71:03]
Paula Pant
Beautiful. Well, thank you for spending this time with us. Where can people find you?
- [71:06]
Dr. Ben Zweig
Yeah. Thank you. To learn more LinkedIn, I post a lot about labor market insights and data on LinkedIn. That's probably the easiest.
- [71:14]
Paula Pant
Wonderful. Well, thank you. Thank you so much.
- [71:16]
Dr. Ben Zweig
Thank you. Yeah, thanks for having me.
- [71:20]
Paula Pant
Thank you to Dr. Ben Zweig. What are three key takeaways that we got from this conversation? Key takeaway number one. Job titles are chaos. And that affects how much you make, because there are 90 million unique job titles floating around. That's messy and chaotic, but also it creates information asymmetry because if titles are inconsistent, then you can't easily compare roles. You can't easily figure out whether or not you're underpaid. So understanding your actual tasks and like how those tasks map to the market, that gives you leverage when you go in to negotiate for your pay.
- [71:59]
Dr. Ben Zweig
I think we see 90 million unique job titles, which is obscene. There's no way a human can understand what all those are. And so many different companies have different conventions for how they use titles. And they all need to communicate to the external market, to a job candidate who is searching for something. It's a problem that exists on the employer side and also a problem that manifests itself for employees who actually just want to be able to search for something and find something that's a good fit, that's a good match.
- [72:33]
Paula Pant
That is the first key takeaway. Key takeaway number two, managers become more valuable in an AI world. And because if AI automates execution, then the skill that is scarce and valuable is orchestration management. And so the ability to reconfigure roles, to realign teams, to rethink workflows, those orchestration types of tasks increase in value. And that means if you want job security, promotions, raises, be a great orchestrator.
- [73:09]
Dr. Ben Zweig
If we had to think about what managers fundamentally need to do, I think it's about job reconfiguration. I think they need to understand the evolving needs of the business, understand the people and what they're doing, and reorient. Try to continuously reorient what people do in their jobs to the needs of the business. And that's very fluid. The optimistic part of me thinks that if that's happening every day, then the emergence of a new technology may be big, but still relatively unimpactful in the general reconfiguration of work, because the reconfiguration of work is so much a part of everyday business for so many people.
- [73:55]
Paula Pant
Finally, key takeaway number three Jobs don't disappear, but they transform. Automation very rarely just wipes out a role overnight. Instead, it reshapes what happens inside of that role. It reshapes the tasks that are demanded of that role. And if you're adaptable, then that's good news because it means that your upside comes from evolving with the work rather than jumping ship.
- [74:22]
Dr. Ben Zweig
So much of these phenomena of job displacement of automation, like it's happening within jobs, it's not happening between jobs. It's so important to think about what's happening within each job. How is each job transforming? Firms don't adopt technology all at once. They're slow. Especially big companies are really slow in implementing change. On the one hand, that's not good for those companies, but on the other hand, it does give us time to Adapt.
- [74:48]
Paula Pant
Those are three key takeaways from this conversation with Dr. Ben Zweig. He is the CEO of Revelio Labs and the author of a book called Job Architecture, as well as an adjunct professor at NYU Stern School of Business Teaching the Future of Work. Thank you for being an afforder part of the Afford Anything community. If you enjoyed today's episode, please do three things. First, share this with your friends, family, neighbors, colleagues, cousins, babysitters, teachers, dog walkers, postal workers. Share it with your barista, with the guy at FedEx, with the person in your kid's carpool. Share it with your former professors. Share it with your favorite economist and your least favorite economist. Share it with all the people you know, because that is the single most important way that you spread these ideas and you spread the message of great financial health. Number two Please subscribe to our newsletter. It's completely free and worth every penny. Affordanything.com Newsletter number three please open your favorite podcast playing app and leave us up to a five star review. Please write a few words while you're doing so. Let us know what you enjoy about the show. I read every single one of these, and these are incredibly important at helping us book. Fantastic, insightful guests. Thank you again for being an afforder. My name is Paula Pant. This is the Afford Anything podcast and I'll meet you in the next episode.