Change Is Inevitable and So Is AI. Are You Ready?

Micheal Mendenhall: So a small business guru who knows almost everything about small businesses, and he does have some compelling thoughts on what is happening in the world of AI. He's the editor in chief of Entrepreneur Magazine, a podcast host, a book author, a startup advisor and an in-demand keynote speaker and he's a non-stop—he's very much like Burton—optimistic machine. So let's hear it for Jason Feifer.

Jason Feifer: Hey, how are you?

Michael: So here we are. And you've covered this a lot, AI. And you have some great stories that I want you to get into. That over breakfast he was telling me, I thought, "Wow Samantha, our general counsel would be interested in hearing a part of your conversation, what AI is going to possibly do to the legal field."

AI has a lot of people concerned. Some people think that your competitor could use AI to damage your brand and damage your company and put you on the defense very quickly. So, there's that concern. There's the concern that there's the fake piece to this that can sway people's opinions about a product or a brand.

Where are the controls around all of that? Yet, you see some of the optimistic stories that we're hearing about every day about what it's solving, how it's helping, whether it's in life sciences, health or within optimizing businesses. What is your perspective right now as we sit here with something that is probably not as edited as it should be?

Jason: No, it is not. So first of all, hello everyone. Thank you for being here with us. I had a realization through talking to a law firm, which is what you were teeing up there, and I'll tell you that in a second, but first I actually want to just back up and set the stage for how I view AI and transformative technologies and just the kind of rapid change that we all go through and navigate.

And that is this observation that the moments of greatest disruption are also the moments of greatest opportunity. It was something that I learned for myself in March of 2020. The world is disrupted. I live in Brooklyn. My wife and I and our two very little boys at the time lived in Park Slope in a two bedroom apartment not far from here and the day school shut down, we thought, "I don't know how we're going to manage this—being boxed up in this tiny space." So we moved out to my parents' house in Colorado because they had some more space. And so then we were 40-year-olds living with my parents, which felt really good. And I started to think, as I think we all did, "Is anything good going to come of this? Is anything good going to come of this terrifying moment?" And there was no way to know, March of 2020, what was going to happen. And so I thought, "Is there anything good that came out of the worst version of this that I could think of?" And again, the very beginning of the pandemic, we don't know what's going to happen.

What was the worst version of this that I could think of? The answer was the bubonic plague of the 1300s. Did anything good come out of that? And so I decided to call someone who would know; his name is Andrew Rabin and he's a medieval scholar at the University of Louisville. And I said, "Andrew, did anything good come out of the bubonic plague?"

And he said, "Actually, some tremendous things came out of the bubonic plague." He told me one of them. I'll share it with you right now. So as you might remember, the medieval European economy was a lord and serf system, right? We learned this in grade school. The lords owned the land. They also owned the serfs.

The serfs worked the land for free. It was slavery. What we're talking about is slavery. And then the bubonic plague, 1300s, kills upwards of 60% of Europe. 60% of Europe—gone. And as the dust settles, the lords think, "We gotta get back to work. Serfs! Serfs! Start to work on the land." And yet something has changed. What's changed is that there aren’t enough serfs for all the lords because so many of them died, which means that these serfs are experiencing something really new and interesting, which is multiple lords coming to them and saying, "Come work for me,” “No, no, no come work for me."

And the serfs realized that something has changed. Today, we would call this a labor shortage. But back then, what the serfs realized is that, for the first time, they could demand something, because their labor was in demand and they realized that maybe, they should be compensated for that labor. And so began in Europe, the very, very beginning of the employment contract, as we know it. The idea that labor has a value and that the people who do that work should be compensated for it. The thing that brings all of us together in this room right now—that comes from the bubonic plague. Now, why am I telling you this story?

Because here's the thing. Would anybody in this room say, Michael, would you say, "I want 60% of Europe to die for that?" No. But it happened. It happened. And the thing is, that we spend far too much time debating whether or not something should happen when it has already happened. And that is the moment that we're in with AI.

And what we need to do instead is we need to put our energy towards figuring out how to use it. The thing that I don't like about the debate over AI is that so much of it goes like this. "This is new. This is terrifying. How do we stop it?" It's not a useful use of our energy or our conversation. So, what can we do with this amazing new technology? Scary new technology, but amazing. And that is what I hope that everybody in business is really focused on.

Michael: Have you seen that? Because I know you go out and you're speaking to a lot of different companies, a lot of small businesses. Where have you seen it being deployed very quickly? Because, you know, there's this whole idea of first mover status, right? If we get in and we're first mover, we'll take advantage, we'll take market share, we'll figure it out quickly. How many of them are just jumping in? They're winding up taking risks. There could be some failures along the way, but they're like, "We're going to try to own this." And those that you're saying are just sitting back watching it all happen, hoping maybe it goes away.

Jason: If you're sitting back and hoping it's going away, you're going to be disappointed. So this is a good tee up to the legal story that I had told you over breakfast. So let me share that. I was hired about a year ago to speak to a regional law firm. And I flew out to San Francisco and they had their attorney retreat.

And so I get on stage and generally what I talk about is change, change management, how to find new opportunities in times of change. And so I give my talk to this assembled group of lawyers and then when it comes time to the Q&A session, almost every question is about AI and ChatGPT, which I didn't anticipate that all these lawyers are so focused on AI and ChatGPT. And so I answered them and then when I got off stage, I was talking to the CEO and I said to him, "It's really fascinating that all of your lawyers are really focused on AI."

And he said, "You know what they didn't say, what they wouldn't say aloud, but I'll tell you what's really on their mind. And that is that ChatGPT is going to make motion writing, writing motions, legal motions, more efficient. And that's bad for lawyers, because lawyers work on billable hours. So lawyers don't actually want their work to become more efficient."

And that's the concern, right? To which I said, "Fantastic! This is fantastic, isn't it?" And this is not in an anti-lawyer way, right? Lawyers can be very useful. I've paid plenty. Here's why it's fantastic. Because nobody likes billable hours. Does anybody in this room like billable hours as a means of paying a very expensive person to do very important work for you? Billable hours? It's ridiculous. Everybody hates it, but nobody has had an incentive.

Michael: Tell them what the CEO said.

Jason: Well, right. So that's what I said. I said to him, "This is fantastic because everybody hates billable hours. And now, something is going to have to change." And he said, "Exactly. That's why we just hired an AI expert." Because, what he's thinking is, there's a moment now. There's a moment in which this old system that this entire industry had been operating on that nobody liked, but we kept anyway, right? It's a crazy thing. If something breaks in our house, we get rid of it. But if something breaks in our lives or our businesses, we often keep it. Why do we do that?

And so billable hours is a thing that doesn't work, but everybody has kept because nobody was incentivized to move away from it. Everybody would have seemed crazy if one law firm was like, "actually, we do it different." What? But now, we are going to break something that is already broken and that is what I think is the true power of AI.

What's going to happen here is that you had a system, a system that was broken, a system that nobody liked, a system that we kept. AI is going to break it. And in its stead, for the first movers that you're describing, are going to be opportunities to build something based on what we actually need now.

That's what this law firm is thinking about. And you might think, "Well, but is this going to mean a lot of laid off lawyers?" No, because what the CEO said next is, what they're thinking is, alright, let's say that the work of their lawyers doing their very expensive legal work for very high paying clients becomes more efficient.

Well, what happens next? What about this? What about now there's a lot of freed up human capital at this law firm? And the ability to do work more efficiently and therefore at a lower cost, which means that this law firm can now actually expand who it serves. Because now it can reach people who might not be able to currently afford their services.

It's a totally different way of thinking about the business. That's what you get to do when you break something that's already broken. I told this to my friends in academia. They are worried that people, or that their students, are going to be using ChatGPT, are going to be. They're already doing it, are using ChatGPT to write papers, right?

And they say, "Well, this is terrible. How do I know, how do I know what my students have actually absorbed? Because I don't know if they're writing these papers." To which I say, "Fantastic. Because essays were always a terrible way to assess whether or not somebody has actually absorbed the information. It was terrible!" But we kept doing it! Why? And now, we're gonna break something that's broken. It's already broken. Now we can fix it.

Michael: Are there any other examples like that in other industries you've seen?

Jason: Sure! Well, so I'm seeing it all the time. And look, it's very early days. Right. It's very early days. So anybody who has told you that they have figured out their AI strategy is incorrect. And so what I'm hearing now are just experiments, but I think really good experiments. So, here's another one that I really like. In a couple weeks, I'm flying out to do a talk for a company called AppFolio. They make management software for property owners. And they have started to integrate AI tools into their software.

Things like, for example, if you manage a building and the elevator broke, you have to contact everybody who would be impacted by that. And maybe they speak a lot of different languages, which means that you have to now, like, figure out how to translate it and reach everybody. And it's just a lot of work. So what if AI can just do that really simply? It can immediately identify everybody who would be impacted by this elevator. It can write an email. It can translate it into every language that all these people speak and just instantly send it out. Sounds good, right? So, that's the thing that they've built in.

Now, what they're really excited about, as they told me, is this. They've done surveys of their users. And when they ask their users, these property managers, "What do you hate about your job?" The answer is often, "Data entry," right? "Rote tasks." The kind of boring stuff that nobody actually gets into any kind of business to do.

"What do you love most about your work?" They ask. And the answer is, "interacting with others—humans, helping residents, working with people." And now, because of this new AI tool, what could happen is that you free up this human labor that had been absorbed into doing thankless tasks in data entry and all this stuff. And now these people can do more of the thing that they love. And this isn't just idealistic, right? This is also good business. Because now, these property managers can start to think, "Well, what additional services can we start providing? How can we make our residents happier?" Happier residents stay longer.

That's better for your business. Maybe you can even charge them more in rent because they're going to be happier because they have more of a human connection with the people that manage their business. Once you start to take some things off the plate that people don't want to do anyway, it's not like there's just a net zero loss of work. Instead, what happens, just like the law firm, just like the property managers, is you start to figure out how best to utilize that time. You start to expand into it with new value.

Michael: That's awesome. Are you seeing that with any bigger enterprise? Certainly, these are all small businesses and we're looking at a poll right now from online. How many of your companies are experiencing AI? 41% are saying, "not really." They're not even sort of engaged in it. A lot is only 22% and we were talking about that first mover. Should people jump in and start to try to figure out how to use this, whether it's for productivity, developing new products, providing new services? Should they be doing that now or will they get caught behind sort of the wave and lose market share?

Jason: I think that if you have the interest and ability, you should be experimenting with it or you should task somebody on your team to do it. It's not a must, though. I think that right now we're in this, you're familiar with the Gartner hype cycle, right? So new technology, it begins and so we're kind of tracking hype, right? And you reach this crazy moment of hype where, "this is going to change everything.” This is the biggest thing you've ever seen. And then, of course, it doesn't do that because no technology just radically changes everything in the way that people predict.

So then there's a crash. And then people say, "this thing is stupid. I hate this thing." And then it starts to climb back up and finds its actual purpose. And that's what we see over and over again in how new technologies are adopted. And I think that right now, the moment that we're in with AI is a lot of expectation that it can do everything, and it can't. I like to think of AI kind of like a microwave in your kitchen, which is to say, it's amazing technology. It's amazing, right? I mean, we don't think about this often enough. You like, you know, you put a frozen thing in the microwave and you press a button and then it's unfrozen. What?

Like a hundred years ago people, their minds would explode. It's amazing technology. But you don't make a gourmet meal in the microwave. It's not for everything. It's for some things. And the question is, "with AI, well, what is it for?" And that's what we're exploring right now.

Marc Andreessen, of Andreessen Horowitz, lays out this really interesting thought about how technology gets adopted. And he said that really pre-internet, technology generally moved top to bottom because technology was so expensive to develop and to use. So things like the computer, for example, it starts with the government. The government is often the developer or very engaged in the development of new technologies.

It's incredibly expensive. It's slow. And then it eventually starts moving downward. So then very large companies with incredibly large budgets start to have access to this new technology, and then it becomes refined and a little more expensive, and then small businesses are able to start using this new technology, and then eventually it makes its way to the consumer.

But now that's been reversed, particularly with the internet, but now, especially with AI, you see it, where now a lot of new technologies are really introduced first to the consumer. Consumer has no barrier to entry, right? You post ChatGPT on the internet and everyone can just start playing with it.

And then somebody at a small company has to make a decision. There's a little bit of a barrier to entry, right? Somebody has to make a decision. Maybe we should start playing with this. Do I have the time? Do I have the resources? I should start playing with this. Then it starts moving to larger companies, because adoption at larger companies takes more time.

You have compliance, you have rules, you have committees. It takes some time. And then eventually, the government becomes the adopter. And so we're really at the early stages now, where the consumer is playing around with it, and I think in doing so is testing it, identifying its many flaws, right?

The hallucinations that everyone hears about with AI. That's real. That's problematic. That's a good thing that we've identified and then we can start having conversations about how to manage that. And it's going to start moving into small business, into large business. I think that if you have the ability to start thinking about, "how do I adopt this in a way that's going to create value and unlock new value?" You should, but I think that we're in such early days that if you don't have the bandwidth for that, I don't think that at this point you're literally left behind because we're still in experimental days and I think that's good.

Michael: Do you have an example of industries that you think are progressing faster? So whether financial services, professional services, you're talking about the legal capabilities. Certainly we're hearing a lot in the creative world under professional services. So you know, there's a lot of talk, there's a strike that has something to do with AI. Maybe premature, because nobody really knows how to define it. So how are we going to promise something that we don't know? So talk to us about the industries and is there one that's progressing further with this than another?

Jason: Yeah, so. I think that some of the industries where AI can be most transformative have to very reasonably also be the most conservative in their approach. Legal is a great example. A world in which legal services becomes considerably more affordable to the average person is a wonderful world. Right? The world of legal services right now is outrageous. It's so expensive. And there's such a barrier to entry. Which, by the way, fun fact, as you can tell from the opening, I'm a bit of a history geek.

Did you know about Law French? This is such an aside, but it's just such a fun fact. So, Law French, after, I believe it was the Norman Conquest of England, somebody can fact check me on that, but anyway, but for decades through the medieval era and I think into the Renaissance, all law was practiced in a language called Law French, which was a language that people didn't speak.

They learned it specifically to conduct law. It wasn't a common language, so English speaking people, if they needed access to legal services would have to access someone who knew Law French, and this was very specifically a way to keep the average person out of the legal system so that they couldn't understand or read the laws, they couldn't engage with discussions about law, and this is the legacy we still live with, right?

Because if anybody's ever tried to read a legal motion, it's basically impossible, right? It's now actually written in English, but it's not really accessible to the average person. AI could change that. It could make law far more accessible to the average person. The individual person might be able to file a motion without having to hire a lawyer. That's amazing.

But, we have to be real conservative about that, because people's lives and people's businesses are at stake. And so we don't want to be cavalier about it. We want to be excited about it, but not cavalier. And I think the same is through financial services, there's all sorts of really interesting conversations happening, but boy, the regulations around that industry are there, they're real and they're there for a reason, too. I don't want to let ChatGPT make financial decisions for me, not right now. That sounds crazy. So what I think that we see right now are industries that are engaging with it because they have really the lowest stakes. The creative field is a really...

Michael: I wanted to go there because there's so many stories now and sort of beta tests that have happened with AI where AI is actually producing better results. And yet it's crawling the internet and it's pulling the best of the best from the public sector, pulling it in and giving you something. And so there's a lot of authors now that are pulling their books back, putting them under firewalls so they're protected. You know, is that a good way of doing this? Is there a better way? Who owns the IP, right? Who owns the content at that point, or the trademarks, or the patents?

Jason: So I'm not a lawyer who is going to get replaced by AI, so I can't answer those questions specifically, but here's what I can tell you. When in the dawn of recorded music—another little history thing—dawn of recorded music, Thomas Edison releases a commercially viable telegraph in 1877. People are like, "what is this?" Eventually it becomes a thing that people actually start to bring in—a phonograph, their first earliest record players.

Originally, it's a cylinder, then it becomes a kind of record like we know. People see this, and they can't believe it. Can't believe it! It's amazing. Literally, for all of human history, for all of human history, until the phonograph, the early record player, the only way to listen to live music was to have a human being playing an instrument in front of you.

It was the only way. And then suddenly a machine could do it. It was incredible. People couldn't believe it. When they first saw it, they thought it was a trick and there must be a band playing behind the wall somewhere. And then eventually, they believed it. They loved it, they bought it, they brought it into their homes.

Very exciting for the consumer. You wanna take a guess who was not excited? The musician. Yes, the magicians, the musicians. I said the magicians. I don't know about the magicians, but the musicians. Musicians were very concerned. And there were a couple notable moments that I think track really well to the kinds of conversations that we're having right now about AI and the creative field. And I don't think that this is just contained to the creative field, but it's a really good test point because the creative field is going to be impacted by AI a lot earlier than some other businesses.

Michael: For the businesses, people do white papers.

Jason: Yes, right.

Michael: And they publish those. That becomes public at that point. That's being crawled. That's being pulled into the OpenAI universe. And so you sort of get concerned, right?

Jason: John Philip Sousa, whose name maybe you don't know, but whose music you do. All the military marches, da da da da da da da da da, John Philip Sousa. John Philip Sousa was concerned for many reasons about the rise of recorded music. One of his arguments—he has a lot of funny arguments, somebody can find me afterwards and I'll tell you them—but one of his arguments was that he thought that it would just lead people to create less. Why would you learn how to play an instrument when a machine could just play the music for you? He saw the destruction, not just of the music industry, but of the art itself.

Instead, the exact opposite happened. What happened was that the machine played music, which inspired more people to create their own music. And it is this kind of unpredictable response and engagement that I think actually should be as predictable as possible because we, as people, are creators. And we don't just sit around wanting to be fed things by a machine so that we, like, in Wall-E can just kind of, like, do you remember that movie where people just you know, like, that's not, we're not going to become that.

That's this fear but we're not going to become that because if we did, if we were to become that, it would have already happened. We had plenty of opportunity. A couple decades later, James Petrello, who in, I think, the 50s—again, somebody can fact check me—was the leader of the Musicians Union who was very concerned about the losses of jobs, very reasonable concern about losses of jobs that was happening because there wasn't as much opportunity to perform live, because people were listening to records, they were listening to radio, and so, he had his musicians go on strike. This would have been in the 40s, I guess. And so his musicians went on strike. And nobody performed and nobody recorded. And as a result, it created an opportunity for people who had not really been considered the kind of musician who would ever even be welcomed into the music union. What does that mean?

Well, back at the time, it was the big band era, so all the union members were jazz players who played in big bands. Vocalists weren't really a part of it, people who played odd instruments, guitarists, not really a part of it. So this entire industry went on freeze, and it created the opportunity to start experimental music, and thus became the rise of rock and roll.

And this, I think, is what I worry about the most when we talk about AI, is industries saying, "I don't like how this is going to impact the only way in which I know how to do business." What I don't want them to do is to stop, to stop creating, to withdraw from the way in which we're going to be engaging and creating going forward. Because all they're going to do is take themselves out of the conversation and let others rise up, which is also fine because every moment of disruption is really mostly a disruption for the incumbent and it creates new opportunity for the upstarts. We saw that during the pandemic, where major companies were rocked and smaller companies were given the opportunity to step up and say, "Ah, consumer, I know how to help you now," and we can see that too.

I don't think it's wise for writers to be saying, "I want to withdraw from this system." I do think that it's good to be having conversations about, "Okay, we have AI now. Let's talk about how this is engaging with our current understanding of intellectual property." That's a good conversation to have. And we can only get there by running into these kinds of conflicts and then talking about them. But if you withdraw, if you say, "I'm out because I don't like this," I think all that's going to happen is you get left behind.

Michael: Do you think, because we've had machine learning, I mean, that's been around for a decade, right? So we've had a form of AI. Do you think that the bigger part of this transformation is—we've now given access to the consumer, right? It's not just B2B, now it's B2C.

Jason: Yeah.

Michael: Is that the big change or the big sort of moment of realization? Because all these technologies, consumers then start to adopt it very quickly, and at times they get ahead of the businesses, and they already start to set the behavior and it's sort of, you can't pull back at that point. Is that what's happening now, that the consumers now have access to this technology?

Jason: Yeah, well, I think that's a really wonderful point and it's something that you've been seeing for a long time, in particularly, the technology field, where a lot of the features that you know and love are features that were functionally created by users.

A classic example is the retweet at Twitter, or, I'm just going to keep calling it Twitter. So, you know, when Twitter was first launched, it didn't have a retweet option and users started to realize that what they wanted to do was be able to comment on somebody else's tweet. And so, I don't know if you remember this: I do, because I was an early enough user. What you would have to do is, you know, somebody just came up with it and it started to be used. What you'd have to do is you would have to literally copy and paste somebody's tweet, and then into your own tweet, and then you write RT, and then before all that, you write your comment. This is stupid. But it was the only way to do it. And then the executives at Twitter saw this user behavior develop and they say, "Oh, this is really smart. Let us build it into a feature." This is what all businesses should be doing all the time, which is to be letting their users lead and creating the systems by which you can recognize what your users want, and identify new behaviors, and then build it in.

So we've been doing this for a long time. Does AI create new opportunities to do that? I think, yes, clearly. I think that's wonderful. I don't think that we lose anything from that. I actually think that what we do is we gain from it. Now, we're gonna see some shifts, some major shifts. But we've already been seeing them.

As users become creators, we discover that sometimes the things that we thought users wanted, they didn't. Or that what we thought quality was isn't to the user. I see this in publishing, right? The editor in chief of Entrepreneur Magazine. We publish a lot of stuff. A lot of it, especially on entrepreneur.com, not written by professional writers. Not professional writers; they're small business owners.

Michael: Well there you go, guys. You have a second career.

Jason: You do! I want to tell you, writing doesn't pay very well, sorry. So, take it from me. But what I've seen is fascinating in the data at Entrepreneur, and I know that every other business publisher sees it too, which is that very often, the pieces that are written by small business owners, non-professional writers, traffic just as well, if not better, than the stuff written by professional writers.

Now, you could say, "that is terrible." And it is terrible if you only think of this business in one way, but if you back up and you say, what are we in the business of? Are we just in the business of publishing the work of professional writers or are we in the business of serving readers? And if we're in the business of serving readers, then it's a different model. It's a different way of thinking about how are we producing the most useful things for those people. I think the more that we can back up and say, "What is our actual purpose here?" Not, "What have we done?" What is our purpose? The more in which every new tool becomes an opportunity to better refine and pay off on that purpose.

Michael: So we still have issues. There's a poll that was taken with all the people online. And there's still people, some concern that creative jobs are going to be eliminated by AI.

Jason: How concerned are you that AI will eliminate the people creative aspect of work? 48% say some, 37% say not at all. 15% say a lot. That was a reading test for the day. Yeah, yeah.

Michael: There's still concern.

Jason: Sure. Yeah, there should be. I mean, if I could sit up here for half an hour, however long we've been up here and eliminate everybody's concern about AI, well, somebody better be paying me millions of dollars. But that's, you know, like, I don't expect that. What I hope to accomplish with this kind of message is, bringing more people into the conversation. I think the scariest thing that we can do is just drop out of the conversation or try to halt the conversation. Because that's not just bad for our businesses, that's bad for our economy, right? I mean, the idea, for example, that we can run to Congress, as if Congress does anything, we can run to Congress and we can say, "Congress, stop this." Right? And there can be some law passed that just like halts AI development. Well, you know, I mean, Congress could pass a law that does that, but that's not going to stop AI development, that's just going to stop AI development in America.

Michael: Well, then it's a disadvantage.

Jason: It's a disadvantage, then you're out of the conversation. And you just let other nations develop AI. That's not what we want. That's not what we need. Are you familiar with the term 'lump of labor fallacy'?

Michael: No.

Jason: So lump of labor fallacy. It's my favorite economic term. I also don't know very many economic terms, but I love this one. So the lump of labor fallacy is this idea that the considerable fear that often shows up with the development of new technology, with the cultural shifts, is that there is a fixed lump of labor. There is a fixed amount of work to be done and a fixed amount of people to do that work. And that whenever something comes along and disrupts that balance, so for example, automation technology, new AI that might replace people's jobs, or also immigrants coming in and taking people's jobs—that when you create an imbalance, it is a permanent imbalance that there are now, for example, more people than there is work, because there's a fixed lump of work.

But it's called the lump of labor fallacy for a reason, and that's because it doesn't work that way, because we are flexible, because every time that there is new space, it gets filled with new innovation. The reason why, when you let immigrants into a country, they don't replace people, they don't take people's jobs, is because immigrants aren't just workers, they're also consumers. And so they come in, and they want work, but they also will buy things. They create jobs just as they work jobs. And the same is true with technology.

When, in the dawn of the industrial revolution, the machines were now able to knit socks in a way that people used to have to sit and, you know, knit themselves. I heard this from a knitting historian. There's a historian for everything. It's amazing. So I called the knitting historian and asked about this.

Her name is Liz Christen. You call her, she'll tell you all about knitting. So, people used to knit. That would be how any kind of knitwear was created in medieval times. So the industrial revolution comes along. These machines can now do it.

And what happens? Well, people are put out of work. It's true. These are real concerns that need any kind of disruption. It's not to be dismissed. I don't want to dismiss it. People should be concerned and we should figure out solutions to all disruption. People are put out of work. What happens?

Well, what happens is not that these people stop creating, they stop knitting, they disappear. And it's not that machines just take over. Instead, what happens is an incredible, at this moment, knitting machines replacing humans who used to knit socks and pants all day or whatever. Instead, what happens is an incredible blossoming of innovation in knitwear.

So all the regional styles that you're familiar with, which you may not even recognize the sort of Irish cords, the fair isle sweaters, all these things that all came out of a moment in which the industrial revolution created machines that replaced people doing utility work, creating the basic knitwear.

And then those people to compete against the machines got more creative because their human capital had been liberated because people who were innovative, who had ideas, who never got to express them because all day long they were just making the same thing over and over again, now couldn't, because the machine could do it for them.

And they didn't go away. What they did is they created. They innovated. They brought new things into the world. Did it create problems? Yes. Were there concerns? Yes. Did things have to be addressed? Yes. If there was online polls in the Industrial Revolution, a lot of people would have been concerned. That would be a good thing, right? But what did we end up with? What we ended up with was better.

Michael: Is this sort of the second technological transformation that we've seen in a major way? You had the World Wide Web, there was lots of concerns about that, "Www, what's that mean and what do I do and how do I?" Right? And now all of a sudden, we've got another one. Is this sort of the second wave of something that's gonna impact our lives in probably a major way?

Jason: I think that really remains to be seen. Yeah. I gotta be honest. Because, right now, AI is the subject. Right? But we haven't had ChatGPT for very long. The idea of language models and this kind of automation—it's been around since the 40s. It's only until very recently that we were technologically sophisticated enough to bring it to life and to release something that could be engaged with by the public. And the original things that we're doing with it are really amazing.

I mean, I have this newsletter that I put out every week called “One Thing Better” and I use DALL·E 2 to draw what I always call a one-line illustration at the top. It's great. I love it. It's not putting an illustrator out of work, because I would have not paid an illustrator. I don't have the money for that. I wouldn't have paid an illustrator every week, but now I get to have that, right?

And yet, what is it for? What are we going to do with it? The answer is, it's so early days that we don't know. I think it's entirely possible that if you flash forward 10, 15, 20 years, that the majority of the predictions about what AI is going to do today did not come true. Because it turns out that this technology was actually for something else.

It had more specific use cases and purposes in the way that, remember a year ago, nobody was talking about AI; everyone was talking about the metaverse, and we were all going to wear these big goggles, and that didn't turn out to be anything. But you know what, I think, that again, flash forward five, 10 years, we'll use that technology. We will, just not in the way that people said.

It'll be for something else, it'll turn out that these big goggles were mostly for training purposes or for very specific kind of remote work and that's how technology goes. Is this the most transformative thing? I think that it's just too early to know, but what I do know is that it's incredible technology and we should be spending our time figuring out how to put it to work.

Michael: That's awesome. What a great way to end.

Jason: Thank you.

Michael: Jason.

Jason: Thanks, everybody.

Michael: That was awesome.