0:00:00 - 0:00:23 Value in an A I enabled society. So um it's not a credential that I flex very often, but I do have a phd in computer science and my specialty happens to be machine learning and artificial intelligence. And so I wanted to share some thoughts uh on the topic of A I. This is something I've spoken about 0:00:22 - 0:00:51 before, but I wanted to direct or focus the lens of what I discuss here on preparations for career and also just um general interactions with society to a lesser extent in hopes to mine out some relevant points uh from my experience and thoughts on this topic to help younger people who are still deciding 0:00:51 - 0:01:17 what they want to do or who are looking to do something else um as their jobs are eaten up by artificial intelligence. So this is sort of the limit of my cleverness for these illustrations. Um We'll move on so well, actually, no, there's something to this and this is I tend to, well, I think, I think 0:01:17 - 0:01:39 stories and images, they, they're uh they're rich communication tools and they're like parables where the more you look at it from different angles, the more you can extract from it. They're, they're very compressed and uh dynamic. So in where the wild things are, uh this kid Max, he's sort of a turd 0:01:38 - 0:02:00 and he gets sent off to his room and he ends up in this magical world and it's populated by monsters and the monsters are bigger than him and meaner than him. But he decides very quickly that if he's going to make it, he needs to be meaner than they are. And so that's what he does and whatever the validity 0:01:59 - 0:02:20 of the morals of the story, the application here is that A I is big and scary. Um, although most of what you hear about it is smoke and mirrors, there is something to it and it does absolutely have the potential to put many people out of work in surprisingly effective ways, however, in there or, or there 0:02:20 - 0:02:38 are, of course cascading consequences from this throughout society that we will see. However, there is a path where you can be scarier and meaner than A I. And that's what I want to try to help you to see in this presentation because the formula is not that difficult. Although I've never seen anyone 0:02:38 - 0:02:57 lay out the ideas that I'm about to share with you. Um, there may be people out there who've had them, but I have not seen that. And so, um, I've, I've walked across a lot of the notes that I've taken or presentations I've put together, uh, for the classroom across a diverse range of topics and added 0:02:57 - 0:03:19 some things to it. And, uh, we'll, we'll go through that here. Ok. So here's, here's just the basic breakdown of what makes money in the United States today. Uh, for a while now, the US economy, it's been service based, which means it's not so much about the product, it's about, um, how the product is 0:03:19 - 0:03:45 created and delivered, uh, high demand, high paying jobs, you're always going to find people with these, um, doing things better faster and less expensively than they were done before. That's, that's one quick way to slice, to value creation in the US economy today. So, um, when it comes to doing things 0:03:44 - 0:04:07 better, faster and less expensively, there are a set of things that computers do better than humans. And there are a set of things that humans do better than computers. There's also a set of things that it's roughly equivalent. So if you want to make money in an A I enabled economy, you have to be really 0:04:06 - 0:04:32 good at things that computers can't do better than humans. So that sounds easy enough, right? But it's not actually all that simple because those things are not widely found in people and they're certainly not developed in the structures we have to educate and train people today. In fact, most of what 0:04:32 - 0:04:56 you'll find in schooling is, is over here. It's just in rote memorization of facts and that sort of thing. So, uh, when you look at this, you'll find that a good question. D to differentiate jobs that will be replaced from those that will not, is, is, can it be copied? So, what are computers good at 0:04:56 - 0:05:16 ? Computers are good at doing the same specified set of instructions over and over and over and over again. That's what a program is. It's basically a recipe. It's a list of instructions and once someone writes that list, the computer can do it again and again and again. So this is why software as a 0:05:16 - 0:00:00 service is, is profitable. If you can find something that people need and you write a program that does it, you can sell it any number of times until you reach the entire market size. So what are some jobs that are formulaic? Well, secretary, whatever you wanna call that today? Um, a nurse teachers. 0:00:00 - 0:06:02 And I wanna, I wanna specify here, teachers, a great example of a job that is easily replaceable as most people do it. But there is a slot here for folks who will. So there's a bifurcation with technology that that occurs where with new technology, what it does is, uh it'll take a job class and split 0:06:01 - 0:06:24 it in two and in the much larger uh side of the side of the split, you have people who were doing it the rote way, the average way and those people are all replaced by the technology. But in the other split, you have folks who are really, really, really, really, really, really good at their job. And 0:06:24 - 0:06:45 these are the people who, for example, create curriculum who teach in novel ways and those people actually end up making more money in this sort of system. Uh But that's not as rosy as it sounds because as I think we'll get into in this presentation, one of the effects of A I is that it's reductive in 0:06:45 - 0:07:09 nature, meaning you build programs to replace people, but then things change and there aren't people anymore to go back to and adapt, write the adaptations to the new circumstances. So it's reductive. It simplifies things down to what fits the current circumstance. But it also obliterates the very people 0:07:09 - 0:07:31 that would be necessary to adapt to changing circumstances. So it's you, you get some efficiencies but they come in at cost and hr and there are a whole lot of other jobs that are very formulaic and those ones are toast. So um there's a whole list of jobs that are not toast and we'll get to those. But 0:07:31 - 0:07:52 first, we need to understand a little bit about creativity. Now, I just wanna be totally upfront that this is one of many topics that will trigger a nerd war if you uh argue about what, what the meaning of creativity is a bunch uh among a bunch of artificial intelligence, computer scientists, uh AAA 0:07:52 - 0:08:20 fight is certain to break out So, um, I, I happen to study, uh, under the advisement of, uh, a professional who's this is his research area, or at least it was back then and, uh, took a class from him on the topic. So, um, this, this is definitely, uh, a topic of much discussion but I will present my 0:08:20 - 0:08:42 perspective on this, which I happen to think is very defensible. I haven't heard arguments that persuade me to believe otherwise, even though I've looked, and like I said, from people who would know the good arguments if they existed, um with high likelihood anyway. Ok. So, um if you don't understand 0:08:41 - 0:09:01 what creativity really is, you're going to be susceptible to what I call the smokescreen of A I, which is people throw this term around a lot and they, they think that it means a lot more than it does. And it's, it's more of a marketing tactic than any sort of factual description. Um And the, the problem 0:09:01 - 0:09:19 with that is you need to get the smoke to clear in order to see what the real opportunities are. And also the, the dangers in inherent in A I, if you're looking at it in the smokescreen, you're going to be distracted thinking about dangers that don't actually exist while completely ignoring the ones 0:09:19 - 0:09:39 that do. And so you'll get, uh you'll get sideswiped by what you did not expect. Furthermore, it's really important to understand creativity in order to actually identify individuals who are creative now, that might not seem like an important thing, but it's actually vital because one of the problems 0:09:39 - 0:10:07 in um in entering into, uh I should say so, in finding opportunities of adding value in an A I enabled society. And also one of the problems of the society sustaining itself under those circumstances is that it's really hard to identify creative people. And I'll explain exactly why it's really important 0:10:07 - 0:10:30 to understand these things. So I think there are two ways you could measure creativity. One is in the degree of the creative work and also another is in the rate of occurrence. So how often, well, how creative is what you're doing and how often do you do it so that I guess sounds easy enough. But when 0:10:30 - 0:10:51 you think of something like artwork, if you were evaluating the creativity of an artist, a painter, let's say, um how exactly would you measure the creativity of their work? How could you measure the degree of creativity across their pieces? And also uh a little easier to measure is the rate of occurrence 0:10:50 - 0:11:12 , but that is obviously dependent on the degree. So if they have one whiz bang novel creation that has value, OK, great. We're sort of skipping over the, the problem of evaluating the degree of creativity there. But let's say that somehow we can measure that. What if the rest of what they produce is 0:11:12 - 0:11:37 absolute garbage. Well, it doesn't matter if they're CRE cranking out a painting a day if it's trash, right? So, there, there are many subtleties in this. Um, but I think that if we had to create some sort of, um, dichotomy, maybe this is one. And again, I just spun this up. I haven't read or, or heard 0:11:37 - 0:11:57 about this before. This is just my own thoughts. So, how about, um, the these degrees of something being truly novel, something being an imitation, a lateral extension or a combination? Let me explain what these mean with an example. So I hope you appreciate this. It took a minute to put together. OK 0:11:57 - 0:12:17 . So this is a familiar serial that everyone knows, right? So if you look into the second column here, these are, I have labels, these are imitations, right? Uh These are imitations. There's nothing novel here. It's just a total knockoff and then a different company is making it, but it's the same exact 0:12:16 - 0:12:44 cereal, right? So then you have what I call um lateral extensions. So this is slight modifications to the serial, but it's still recognizable, right? There's still a strong connection. It's not that far a field and then the the last layer is uh what I call combination. So that's just when you combine 0:12:44 - 0:13:06 more than one well known thing. So here we're, we're, we're applying the flavor and sometimes the shape and sometimes it looks like always the color. Well, almost always. This last one is a perfume I thought that was interesting. This is pretty far afi but um some recognizable aspect of the original 0:13:06 - 0:13:27 creation to things that aren't necessarily closely related and it's, it's just combining them with other things. Um So this is sort of step wise, so this is basically a clone. This is taking it a little further a field by connecting it to something that's not um completely related. And then this last 0:13:27 - 0:13:56 level is a combination of things that aren't necessarily related at all. So um how this helps us is as we peel back the layers and introduce more ideas into this previously amorphous uh smoke. What we, what we gain is the ability to make distinctions in terms of what people can do and what computers 0:13:55 - 0:14:23 can do. And so um what which of these is the domain of computers? Well, a computer can certainly imitate a computer, can certainly do lateral extensions and a computer can certainly combine things and uh all that's required is to give it a program that presents the framework of how to do it and then 0:14:23 - 0:14:43 it can apply this formulaic approach over and over and over again. So there's nothing creative about imitating, there's very little creativity and lateral extension and there's very little creativity in making combinations, you just sort of smash things together and see what happens. Now. What's more 0:14:42 - 0:15:04 difficult for the computer to do is to evaluate how good these things are. Computers can evaluate imitations. Well, if you give them the metrics to measure. Um, but a goodness measure for a lateral extension or a combination that's a lot harder to program. So, for example, if we're talking about this 0:15:04 - 0:15:26 specific situation, um, how would you know that fruit loops marshmallows is a good idea and that's going to sell and fruit loops, dog food is not right or, um, I don't know. Fruit loops sent to trash bags over here. How would you know, ahead of time? How is a computer going to know that? That's not a 0:15:26 - 0:15:51 good idea. But humans can know right away on a lot of these things that this this uh this idea is bad, not all of them, but, but you could evaluate a lot of them. Ok. So computers very bad at this one. Very good at this one and OK at these, so as a human, you want to focus on this. Ok. So I call this 0:15:50 - 0:16:14 high creativity, true novelty, right? Or approaching true novelty. So how can you identify whether we're dealing with that? Well, is it predictable if the answer is yes, it's not high, highly creative. Is it common if it's common? It's not highly creative? Is it recognizable if it's recognizable? It's 0:16:13 - 0:16:33 not highly creative. You think about the art of Andy Warhol? For example, it's instantly recognizable. If you know one of his pieces, you can recognize them all. So the first one was creative, but which of the following were subsequent creations? Well, they were, they were imitations, maybe extensions 0:16:33 - 0:16:55 of himself, right, of his prior work. So that, that happens. Um So producers, creators, they might be super creative in the first thing they do, but then they just replicate that over and over and over and over and over again. This happens a lot with scientists where they'll, they'll take a stab into 0:16:55 - 0:17:15 a novel direction and then maybe get a phd out of it and then they just keep beating that horse long after it's dead for the rest of their career, even though it's diminishing returns, and they're just sort of duplicating what they've already done. It's really, really hard to be truly novel again and 0:17:14 - 0:17:34 again and again, and this is where we come back to where we started with this, the, the rate of occurrence, you could be highly creative once. But does that make you a creative person? Now remember the whole context of this discussion is employment. So if you're the kind of person who is highly creative 0:17:33 - 0:17:57 , you're very different because most people are not that way, but maybe uh even amongst creative people, most creative people are only really creative once. And so how do you select someone accurately predicting that they're going to produce their one creative thing? Because everything in our hiring 0:17:56 - 0:18:17 process is based on what you've done in the past. And so if you've already created something, creative odds are you're not gonna do it again. Do you see the problem. That's just one of many problems with employment in this uh situation. OK. So how do degrees of creativity map to career opportunities 0:18:16 - 0:18:42 ? Uh We talked about how computers can't really do novel. But the other ones, they can probably do this better, faster and less expensively than you can. And remember that's the name of the game. So uh another subtle facet of this is that computers generate value by replicating in less time than it takes 0:18:42 - 0:19:06 a human to do so. Or maybe in higher quality. So like a robot arm with a laser on it can etch something more accurately again and again, than a human could. But uh novel creations, what is the value of it? You don't really know because no one's done it before and this is a real opportunity, but it's 0:19:06 - 0:19:23 also a danger. It's a, it's an opportunity because maybe the thing that you create is massively valuable. Maybe it has more value than most people make in a lifetime in a normal job where they're punching, you know, they're stamping out metal or something just doing the same thing over and over again 0:19:22 - 0:19:45 . Maybe it's got more value than an entire career in today's normal jobs. But um that actually produces its own challenges. And I mentioned some with hiring and, and predicting how people can do this. But there are, there are many other problems with that. Nothing in our society is designed around or 0:19:45 - 0:20:14 works well. With the idea of making all your money on one thing and it, it especially is ill fitting when it comes to, um, I, I lost my train of thought on that. Sorry. Ok. So when it comes to what jobs will be eaten up by A I, it's, it's these sorts of jobs, imitation, lateral extension combination 0:20:13 - 0:20:37 . So, think about what you do at work and even if it's not, hey, I do the same thing all the time. That's imitation. If it's all I do is slightly modify a very well described solution. Well, your toast and even if you think your job's creative because you're combining things that haven't been combined 0:20:36 - 0:21:05 before your job is toast. Computers can do this. All right. So, um another thing that makes it difficult to accurately predict what jobs are gonna be eaten by CRE uh by artificial intelligence is the fact that these things do not always break down along job titles along the lines of job titles. So, for 0:21:04 - 0:21:25 example, it just running down the, the alphabet. This list is not exhaustive. We could talk about accountants, actuaries, architects, authors, and so on. And not all people in these job titles are the same. Remember, we, we already sort of touched on this. Um If you're an accountant who's doing novel 0:21:25 - 0:21:44 things, you're not the same as most accountants who do imitative things, rep repetitive things. Uh If you're an actuary and you're creating brand new models for risk classes, you're not the same as an actuary who just has a spreadsheet and they punch the numbers through it. If you're an architect and 0:21:44 - 0:22:03 you're making truly novel designs every single time you do something or even just once and then copying it again and again, as most architects do, uh who are, who most famous architects do, um, you're very different than these architects who never ever do anything novel. They're just copying things that 0:22:03 - 0:22:23 other people have done. In fact, a lot of them are hired specifically for that and someone will say, I want it to look like this building and we're gonna get deep into authors, so I won't go there. Um Actually, sorry, we're gonna, we're gonna dive into that right now. So let's, let's deep dive into authors 0:22:22 - 0:22:40 . So let me ask you the question, what's the difference in creativity between Stephen King and Catherine Applegate? And I know you're saying Catherine, who and I say to that. Exactly. Right now, we could break down the number of books that these people have written, but they've both been prolific, but 0:22:40 - 0:23:00 you probably never heard of Catherine Applegate unless you have little kids because she's written about a bajillion kids' books. Now, this is a little dated. Um We, we happen to have lots of kids books in our house and most of them are at least second hand. So I think we have a lot of these books floating 0:23:00 - 0:23:27 around. That's the only reason I know about this lady, but she's the author of the Animorphs series. Now, look at the dates next to these titles and you can see just how many books she wrote and how little time. And in, in 1999 how many are there? 2468, 10. So more than one per month in 1999. Um, and 0:23:27 - 0:23:46 , and it looks like slightly less in the surrounding years, but a whole lot of books. So how on earth can you crank out this many books and have them all be novel, novel, novels? Right. You can't, is the answer as a human. You can't, it's just too much. Right. Or it would really be a feat if you could 0:23:46 - 0:24:11 . Well, it turns out they're not novel at all. Even their covers look the same. Right. But this is just a formulaic approach to writing books and for some reason kids just ate it up. Ok. Now this was in the nineties. Could this be done today? No, it couldn't. Why? Because this is repetitive and computers 0:24:11 - 0:24:29 could do it. And if a computer could do it, a computer is going to do it and then it will be done and no one else can do it. So, would you go out and see a movie that's already been made? Well, apparently a lot of people do with the remakes, but it's getting a lot less popular and these are starting 0:24:28 - 0:24:45 to turn into bombs. If someone said, oh, I, I'm just gonna make another movie and it's gonna be exactly like all the other marvel movies. No one's gonna go see it and no one does. Right. Which is why those movies are bombing among other reasons. So, if it's been done it's not gonna be able to be done 0:24:45 - 0:00:00 again. And if a computer can do it, a computer will do it. So that the, this lady could have never had her career today, even though she made tons of money on these books. If it hadn't happened, then it wouldn't be able to happen today. So that in the computers, they can even make these covers. Now, 0:00:00 - 0:25:28 if you, if you gave an A I drawing program, if you fed it some of these covers or you just sort of described what you want, it could crank this out. Ok. But a human had to make those originally, ee even though it was very formulaic, a human made those. So one of the takeaways with this is that what worked 0:25:27 - 0:25:46 yesterday will not work today. You can't just so in the seventies, you could roll out of bed, get a job at a local place and work your whole career there and make enough to, to be middle class. And that has not worked for the last 30 years. Well, in the same vein for the last 30 years, you could roll 0:25:46 - 0:26:05 out of bed, get a college degree in any stupid field and then make some good money and be middle class. And that's not true anymore. And the examples abound with this, what worked yesterday will not work today and there are many reasons for this, but one of them has to do with, uh, what we're talking 0:26:05 - 0:26:25 about here with the creativity and with a, I, if someone, what, how did computers change the game in this sense? Well, if someone's done it before, they've provided enough material for a computer to do it again and when the computer does it again, it will do it better, faster and less expensively. That's 0:26:24 - 0:26:45 the dynamic here. So it used to be one model for business is to solve a problem and then you can continue that. That's how you build the business, you continue executing that business and you continue making money but not so much anymore, right? There are other dynamics in play. All right. Now, I touched 0:26:44 - 0:27:03 on the idea that it's much harder to sustain high creativity than to do it once. So I have a specific example to make the case even better. There's this author, I should have looked up how to pronounce his name. He's Brazilian Paulo Coelho, maybe. Um You've probably heard of him. He wrote The Alchemist 0:27:02 - 0:27:26 , which is an amazing book. I I highly recommend it. Um But overall, he has, he has sold more than 320 million copies of his book so that you could definitely call him a success. He's made scads of money on his writing. But if you peel apart the, the specific performance of each book he's written, you'll 0:27:26 - 0:27:49 , you'll see some interesting things. You'll see a pattern emerge. The Alchemist by far was his most successful book and it accounts for about half of the copies he has sold. The thing is he wrote 32 other books and he started in 1974 which was long before he wrote The Alchemist. On average, his books 0:27:49 - 0:28:13 sell 60 times fewer copies than The Alchemist. That's crazy. Now, that being said that average is 2.5 million copies. So that's not too shabby, right? But what we're going to to what you're going to see as you look around for examples in the world and in your life is that um this is the Patto distribution 0:28:12 - 0:28:35 , it's all over the place and it scales. So you'll see the same pattern even with uh an author, an artist, any, any person that produces things that are creative, you're going to see that, that the vast majority of their success has been across very few examples, probably just one. And that's an amazing 0:28:35 - 0:29:00 thing to see as some people break this mold, but it's so rare. It's not even worth talking about since 1974. Uh This guy, he's written 30 books that you've never even heard of. Right? 31. I don't know how my math adds up here. So let me ask you a question. Why is it so hard for corporations to effectively 0:29:00 - 0:29:18 find or keep creative people? Because they're the ones that are driving the A I enabled economy, they're the ones that can do what computers can't do. They're the ones that can add more value than computers can. They're the only ones. So, why is it so hard for large companies to find and keep these people 0:29:18 - 0:29:41 well, um, in, in fact, I have here, they're more valuable than most of the others combined. That's a property of the preto distribution. So one of the reasons they're so hard to find is that it, how do you, how do you evaluate an employee when you're trying to measure a 60 fold variation? So um not across 0:29:41 - 0:29:59 employees but in on the same employee. So I mentioned before, if you're trying to hire a highly creative person in current structures, what you're going to do is look at their past performance, what if they haven't written the Alchemist yet? I can't remember off the top of my head. How many books he 0:29:59 - 0:30:19 wrote before that? But let's say it was six. If you were hiring him or you were his publisher trying to evaluate whether you wanted to fund the next book or book or not, which happened to be the alchemist, it would have been the best deal you've ever made in your life as a publisher. And yet you'd have 0:30:18 - 0:30:44 to make that bet based on him looking like any other Schmo author on paper because of his past performance, it turns out that, that uh we just aren't very good at measuring creative people in part because they're not always super creative. They create many things that are no good and, and maybe the thing 0:30:44 - 0:31:03 that they create that is good. It's just one thing and maybe it's 60 times better than anything else they've ever done. Now, the difficulty here, it's not just in evaluating potential employees. It also includes current employees. So again, let's pretend that Paulo is working for the same publisher this 0:31:03 - 0:31:24 whole time. And let's say that there were six books before the alchemist. So he'd get fired in most places or he'd get paid very poorly and, and the reason is because he's not hitting these home runs. And so if you wanted and, and you might push back that and say, look 2.5 million copies, that's, that's 0:31:24 - 0:31:47 not a small amount true. But like I said, this scales. So let's talk about someone else where the baseline is 20 copies or 2000 copies and the high water mark is 2 million copies, right? 2 million copies that might work, but 20,000 that's not gonna work. And so what does the company do? Well, it just 0:31:47 - 0:32:08 pretends like there's no way to solve this problem and hires people based on their baseline performance. And the problem with that is creative. People know or they believe anyway that they are going to produce a home run, that's why they're doing it and they're not daunted by the failures. And so they're 0:32:08 - 0:32:31 gonna be unhappy in that situation or they're not even gonna try because they know that no matter what they do, they're only gonna get paid for the baseline. So now we, if you're an employer, one way around this is to, to pay based on performance based incentives, but hardly any companies do that in 0:32:31 - 0:32:51 part because it's really hard to measure performance in most jobs. But also in part because they're just not thinking this way. It's really a shame because human performance is Pareto and therefore compensation packages ought to be Pareto. Not only should very few people make most of the money in a just 0:32:51 - 0:33:12 system because that is what reflects reality in terms of their performance and the actual value of it. But also each compensation plan should have performance based bonuses built in and, and they should be audacious and say, look, we only expect you to sell 2 million copies here. But if you sold 320 0:33:11 - 0:33:35 million, here's how we give you a piece of the pie in practice, hardly any jobs work this way. Um There are exceptions, such as sales jobs, sales jobs are probably the only ones that are, that are closely aligned with reality. Maybe that's an overstatement, but maybe it's true, maybe it's more true than 0:33:34 - 0:34:00 it is false. One of the reasons people don't get paid this way is that employers know they have to average out human performance across their employees and within employees, they can't bet on that 320 million copy book. So they have to plan everything based on averages. This is why, for example, in the 0:34:00 - 0:34:23 tech industry, um entry level people get paid way more than what they bring to the table. They're ridiculously overpaid that wears off as someone gets more and more productive, uh more and more capable at their job faster at solving problems, able to solve much harder problems and moves up the novelty 0:34:22 - 0:34:43 scale in terms of creativity and the problems that they're solving. But the problem is, and this is, this is widely known among senior developers. It's diminishing returns in this field. You do not get paid what you deserve. The further up the ladder you go, you get uh reduced raises, the better you 0:34:42 - 0:35:02 get. So you might be able to do the work of 10 or even 100 junior developers, but you will not get paid 10 or even five times what they make at best. You might get 2 to 3 times. And that's ridiculous, right? So, but the issue is that all that money goes to the junior developers who are overcompensated 0:35:01 - 0:35:22 and there are reasons for that. So, um but this, this boils down to human nature. The fact is very few people will take a job. If the boss sits down and says, look, I'm gonna pay you Jack Diddley squat. However, here's the schedule of all the things you could do and exactly what I will pay you in terms 0:35:22 - 0:35:43 of bonuses. If you do them, we call these people sales people that would take that kind of job. Um, so almost every other job people want the, the presumed comfort of a stable wage. And in fact, our whole society is built on that. You know, we have things like mortgages and car payments. Our debt is 0:35:43 - 0:36:01 structured in regular intervals. It's not structured in pay whenever you want or pay when you get the boon and we'll just keep stringing you along until then nothing really works that way. Even investment in companies, there's an expected rate of return and when the founder doesn't make it or the company 0:36:01 - 0:36:18 doesn't make it, the investors pull out and it will be very hard to get more money and it doesn't matter if you say no. But, but look, there's this, this huge return that's possible here. People aren't gonna give you money and if they do, they're gonna expect you to pay out the nose for it in terms of 0:36:18 - 0:36:40 whatever uh guaranteed returns come with it or share of the company that is purchased with it. So why don't people, why don't normal people? Um Why aren't they creative? Well, first off, there's a, there's a real question of whether or not it can be taught. Um, if it can be taught, it's certainly not 0:36:39 - 0:37:09 as easy as one could say, write a program. There's no formulaic way to teach creativity. But let's say that you have this, this, um creativity somehow, somehow or another. It's something you've got, there are substantial barriers to exercising it. So, um in most cases, those people will take jobs where 0:37:08 - 0:37:28 they're not practicing creativity. Why? Well, I already mentioned they want the stability of a check. Um Most people do not have the discipline to plan for the future and spread. So say, somehow your first book is the one you sold 320 million copies of most people will blow the money and they'll spend 0:37:28 - 0:37:48 it as if they're going to make that much on every single book they write. And that's a problem. And now I keep using examples of authors and artists, but this applies to all forms of work. That's just an easy to understand example. Uh What about emotional barriers? So how many people do you know that 0:37:48 - 0:00:00 can face repeated failure, just unending failure on things that cost their whole heart and soul and will get up, dust themselves off and do it again and again and again and again and again, with no indication that the next one's gonna be any more successful than the last one. So um the those people, 0:00:00 - 0:38:31 they're borderline delusional, I mean, that's madness, right? And yet they exist and they're the ones who become the most creative, who, who produce the, the highly creative things that society needs to thrive. Finally, another barrier is just a, a situational one. So if you're the sort of person, exactly 0:38:30 - 0:38:52 , what are you going to do for a living? So, yeah, you could write books, you could direct movies, you could uh paint paintings, whatever, but there just isn't that much for these sorts of people to do in the normal economy. And the reason is it's not built around creative works or I should say just 0:38:52 - 0:39:13 creativity in general, it's built around factory mindset of just stamping out a million copies of the same thing. And so when you're the kind of person who's innovative, you're like a, a square peg in the hole is round and it's really problematic if you look in history, this is an interesting exercise 0:39:13 - 0:39:34 and it's beyond the scope of the video. But I recommend you do it, look in history at the few 1000 people who created everything that matters in this world and it's really that small of a number. Now, instead we're just focusing on what they did or even how they did it, which is very interesting and 0:39:34 - 0:39:54 useful. Look at the situation they were in when they did it and what you'll find is that the novelty of their production is not so far separated from the novelty of their situation. So if you look at Thomas Edison, for example, before he did all that light bulb stuff. He was already a weirdo because 0:39:53 - 0:40:15 as a very young child I think he was 11. I don't recall exactly. His mom gave him permission for him to leave home because he had the idea that since trains traveled around all the time, he could, uh, create a newspaper, have a printing press on a train and sell more copies than the existing newspapers 0:40:15 - 0:40:37 because he'd have the news faster and he made a fortune doing this as a, as an 11 or something year old kid. So that's not exactly a normal situation, is it? So you need a system, if you're gonna be highly innovative and creative, you need a system that recognizes and promotes potential and that itself 0:40:36 - 0:40:56 is creative and novel, right? So you, if Thomas Edison was in public schools, you wouldn't know his name and we'd have candles, right? I, I'm sure someone else would have invented the light bulb. But, but the point is that you'd never know about him and it would have happened a lot later than it did 0:40:56 - 0:41:28 . So, um potentially you, you can't foster creativity in a stifled imitative prescribed system. It doesn't work that way and guess what, nearly every normal company is exactly. So, um I already spoke about how difficult it is to recognize these people uh in the specific example of the alchemist that 0:41:28 - 0:41:47 author was told when he was pitching the book, he was told by his publisher, the person who had published the previous books that that book would never sell more than 900 copies. And so that goes to show you this is a person who knew Paulo very well. He knew his work, well knew uh what, how many copies 0:41:47 - 0:42:05 he sold in the past, which was more than 900 copies by the way. And he said this is a stink bomb. It's never gonna go anywhere. This was the person most equipped in the entire world to see the value of this book. And they said it was garbage and they were completely and utterly wrong. They were as wrong 0:42:04 - 0:42:25 as a person can be. So, um anyway, that, that's the pattern here, you're gonna crank out a few things that are extremely valuable and everything else is going to stink and it's not gonna be on a 9 to 5 punch the clock kind of job. It's, it's going to be responding to random ideas that you get while you're 0:42:25 - 0:42:45 doing some random thing. You can't just sit there and force it right for the most part. And it's going to take weird experiences that you've had in the past and unique things that you've learned and done. Um It's not formulaic, it's not something that, that everyone can do in the same exact way and our 0:42:44 - 0:43:07 system does not accord with that. It's starkly contradictory to that pattern. Um We've, we've talked about how persistent you have to be sometimes I guess we'll dive into this a little further. It, it's not the case that when you create a highly valuable creative work, everyone instantly recognizes it 0:43:07 - 0:43:24 as such. That's not true at all. People will think you're crazy. At first, the more innovative you are, the further you are from people's ability to correctly evaluate the value of what you're doing. But in time it's revealed and through persistence and this exposes another weakness in human nature and 0:43:24 - 0:43:47 why it defies pure creativity. Um Looking at the alchemist, for example, that book, uh this guy Paulo, he had to push, push, push this book. It didn't just sell 320 million copies overnight. It was incrementally success successful. Um And it had to be fitted to the situation. He had to translate it into 0:43:47 - 0:44:09 many different languages and it really didn't take off until it hit the English speaking market. And even then there was tons of success after that as he pushed it into different languages. And so it wasn't just, oh I made it. I did one thing I hit send and now it's there. No, it and, and, and that's 0:44:08 - 0:44:33 the thing. It's not just about pushing on after you failed. So many times, it's also pushing on and something that people think is a failure and you just keep pushing and then one day it, it clicks and then you keep pushing, right? And these are not traits that normal people have So in fact, all the 0:44:33 - 0:44:55 things that make you good at pure creativity make you a terrible normal employee, an absolutely terrible normal employee. So that's interesting. So you have this optimization choice there. So where do you go if you are like this or if you want to be like this? Well, there's an argument that can be made 0:44:55 - 0:45:17 that you're headed for self-employment. Um You can make a lot of, you could say a lot of things about how organized corporations, large companies, uh contradict novelty. And I've mentioned many of them specifically here, but there are a lot more, um, self employment is probably the way to go. Now. That's 0:45:17 - 0:45:37 really difficult because who's gonna finance you? Right. So you're, you're probably going to be starving for a long time before you make it and you may never make it. And, and odds wise, it's much more likely that you'll keep failing than you will succeed. But some people do it anyway. And those are 0:45:37 - 0:45:58 the folks who are going to, to encounter the greatest success as our society morphs into something that's more A I enabled. Now, we've been talking about sort of the, I guess the more ideal sense of creativity here. But I want to say that this all occurs on a scale and you may find much more success 0:45:58 - 0:46:16 closer to normal life um by scaling down the level of creativity. So maybe you're the person on your team that solves all the problems. Right. And everyone else is just there for the ride. But like I said, what you're gonna find is that you're carrying those people and that they don't really contribute 0:46:16 - 0:46:34 very much compared to you and, and yet you're not going to get paid very much more than them, if you get paid more than them at all. There are all kinds of stories about managers who don't do Jack Diddley Squat, but they ride on the contributions of some highly creative member of, of uh subordinate that 0:46:34 - 0:46:56 they have anyway. Um It's kind of, I, I didn't want this to be depressing, but you are kind of between a rock and a hard place because you're gonna find obstacle after obstacle in um regular employment. But then at the same time, there are tons of obstacles for self-employment. I mentioned financing 0:46:55 - 0:47:17 , that's definitely an issue, start up capital. But if you go down that path, you are going to be incensed by the number of re uh regulations that impede what you're trying to do. And I'm not saying that because your idea is illegal. I'm saying you're going to be shocked by just how many absolutely stupid 0:47:16 - 0:47:41 rules, policies, fees, taxes and everything else under the sun exist that are obstacles to what you're trying to do. It's amazing. Um You're also going to find time after time that this is, this is a really depressing point. You're going to find that a whole lot of problems that are a big deal are completely 0:47:41 - 0:00:00 solvable. And the real reason that they haven't been solved is because of some pre-existing monopoly. Usually, uh, government enforced that, uh, whether directly or like I said, through all these regulations that small businesses can't afford to keep you're going to find obstacle after obstacle, um, 0:00:00 - 0:48:19 to these problems that really ought to be solved and could easily be solved and could make someone a lot of money in solving and make the world a much better place. So, so we're gonna start wrapping this up. Um And before we get to the last slide, the one question we want to ask is what does all of this 0:48:19 - 0:48:42 mean for society as a whole? Well, if you have to be highly creative to add value in the new economy, then the fact is that most people are not gonna be adding value because most people are not highly creative and a lot of highly creative people are not willing to exercise that creativity. So there will 0:48:41 - 0:49:06 be far less opportunity and far less wealth and there are many, many carry on effects out of that, that uh conclusion. All right. So um in summary, A I is going to increase employment and standard of living challenges that maybe that would have been worded better the other way around. Uh It will increase 0:49:06 - 0:49:28 challenges in employment and standard of living. It won't decrease them, it will increase them if this isn't some uh rainbow where there's a pot of gold at the end. This is not a good thing for society. It will be worse because of it. So my advice for all people is to start getting used to the idea of 0:49:28 - 0:49:50 doing more to come to the same outcomes than people had to do before. That's not a fun thing to hear, but those who wrap their heads around it and start living that way earliest will be in the best situation. Uh I encourage you to, to develop your creative abilities to the greatest extent. What do I 0:49:50 - 0:50:13 mean by that? Your critical thinking, your problem solving your decision, making, your ability to perceive things that other people don't see and the courage to act according to them, uh the courage that other people lack. How effectively can you use disciplined, rational, open minded, evidenced, informed 0:50:12 - 0:50:36 thinking to reach an answer or conclusion or a solution? That's what's going to make the distinction. Now, if you are a creative person already, then I encourage you to learn to intentionally plan and execute your life to put yourself in the best places. So places where you can best apply and be rewarded 0:50:36 - 0:50:58 for the value that you bring, that's not going to be in traditional employment. But maybe you'll find success in things that are slightly more autonomous. And again, one of the reasons that autonomy is necessary is because recognizing creativity in others is itself a creative task. It's not something 0:50:58 - 0:51:17 , there's a checklist for and it's not something that, that just a run of the mill manager is going to be able to do. Well, if they did, they wouldn't be a run of the mill manager. So you need to put yourself in places where you're free from the fetters of folks who don't see the things that you see 0:51:17 - 0:51:39 or who aren't willing or able to do the things that you're willing and able to do. So, uh if you're not a creative person, you should begin thinking about how you can adjust to a future that is very different than the past and that's not super optimistic. You need to wrap your head around the fact that 0:51:39 - 0:52:00 life is going to be much harder for you than it has been to, to date and much, much harder than it was for your parents and grandparents because, uh you've got a really rough row ahead of you. You're gonna be stuck in this, in this uh gulf between what computers can do better than you and what people 0:52:00 - 0:52:21 who can do more and better than you can do that. You cannot. And that is an enormous golf and it's not a fun place to be. So anyway, I hope that this was useful even if it wasn't super inspiring many times, if you want to help people, you have to tell them the hard truths that they're not gonna hear 0:52:20 - 0:52:21 elsewhere.