Episode Transcript
[00:00:00] SAM welcome to AI Today. I'm your host, Dr. Alan Badot. And, you know, this week we're going to look at some of the, the headlines that we've seen over the past week. I had a completely different show planned, but, you know, I figured I needed to address this, and we're going to spend an entire show on it so that I can start to get the, you know, the message a little bit clearer so people can understand, really, some of the impacts that AI is having on the job market. So this week, you know, we saw Amazon announce that they were cutting 30,000 jobs, 30,000 jobs.
[00:01:09] And, you know, of course, that is, that's a headline that's going to get everybody's attention no matter what. But, you know, in today's market, it's only going to explode. It's going to cause things to really go crazy. And it was, you know, you saw media headlines all over the place that AI is coming for all of us and no job is safe and, oh, the robots are taking over. That was actually one of my favorite ones, you know, and, and I get it.
[00:01:38] The, you know, people are worried. They see headlines like that, they need, they hear numbers that are, you know, that big. And it's just, it just scares everybody. It's terrifying for a lot of folks because that is impacting, you know, real lives, real jobs, even all the way up through management.
[00:01:56] And on the tech side, we've already seen some major job cuts from folks over the past year. And it's scary, especially if you're in the early years of your career, just coming out of school, just getting excited about AI and then you start to see these sort of events that are taking place. We saw the same thing with, with Meta and how they were getting rid of, you know, one of their AI divisions and a whole bunch of other things that were taking place. But, you know, here's the thing.
[00:02:32] This is why, you know, we do these shows like we do and why I'm doing this show tonight. It's because you see things and it's all about fear, because fear grabs headlines. You know, we've, we've talked about this, right, and we've seen how, you know, it can be shaped and it can be molded so that, you know, maybe it's not quite telling the whole story, you know, and in fact, I would say it's barely telling half of the story.
[00:03:01] And, you know, that's, that's the thing that we, you know, we take issue with because, you know, we're, you know, if you're Going to, you know, talk about these kind of things, especially, you know, when it can impact, you know, the daily lives of people that are out there. You know, that is, that's, that's troublesome to me.
[00:03:24] It's, it's easier to say that, you know, Terminator is coming, stuff like that. You know, you, a lot of people can brush that off, but it's, it's a lot harder when you're talking about careers, employment, you know, somebody's job, somebody's future. They get, they get really nervous about that. And I think that's why tonight we're going to go way beyond the headlines. So we're going to look at what, you know, what's actually happening with AI and jobs. This is not a dystopian fantasy. This is not a Silicon Valley, you know, utopia. It's real data. We're going to talk about some real numbers and, you know, we are going to address some of the risks that are, that are out there, but it's not going to be the type of risks that you actually think, you know, are there. We're going to, like always, I'm going to present you the facts. I'm going to give you maybe my opinion a little bit in some of those, those areas. But I want folks to really just start to understand the basics of, you know, you know, how they are coming up with some of these numbers, the timing that you hear about these numbers. And, you know, we're gonna show that, you know, the truth is way more complicated, way more interesting and ultimately way more useful than, you know, panic and the types of things that we're seeing, you know, today.
[00:04:57] And, you know, the challenge is that, you know, all of these things that are taking place everywhere you go, it's always going to be about something associated with AI doing something that is generally going to be seen as, you know, having a negative impact on the economy.
[00:05:19] You know, you look at those, you say, okay, it's widespread.
[00:05:23] Everybody's saying that they're, they're laying off people.
[00:05:26] But, you know, I think in some cases it's a little irrational.
[00:05:31] You know, when 30% of US workers, that's a recent poll, believe that their jobs are going to be replaced by AI by 2025, you know, the end of 2025, that's now then, you know, that's really not nothing. That is, you know, almost 50 million people that are thinking every night that maybe, maybe, you know, the next paycheck is next week.
[00:06:01] And then it actually starts to even get worse when, you know, people Ask about the next decade. The number jumps to almost 50%.
[00:06:12] That's nearly half of Americans, you know, American workers that think their role could be safe, seriously threatened in the next 10 years.
[00:06:22] That is not insignificant. And it's something that is not trivial, and it's not something that you can ignore.
[00:06:28] Now, here's where it gets interesting, okay? And also really concerning young workers, people between 18 and 24 years old, you know, you know, 100, and I think it was 92% more likely than older workers believe that their job is, you know, either going to be replaced or it's not going to really exist.
[00:06:56] They think that, oh, the, all the things that they did for college, all of that work is really just not going to be there fairly soon. And so that's a, that's a big concern, and we've got to think about that. But let me say again, right, you know, if you are building a career now, you know, more than, more than twice as likely, you know, young people think that AI is coming for their job. That's, that's pretty scary. So I want you to think about that. That's an entire generation entering the workforce feeling like they're already obsolete.
[00:07:31] And if that doesn't scare you, then, you know, you really need to reassess how we're looking at, you know, things from an AI perspective. Because globally, you know, research estimates are coming in at about the same sort of percentages and the same sort of, you know, activities that are taking place. And that's just by the end of, you know, the decade. And, you know, that represents a significant amount of those jobs across the world. Now, here's the thing, and we talk about this all the time on the show.
[00:08:08] Fear is easy to sell.
[00:08:10] It grabs headlines. Everybody wants it, you know, because it gets them. You know, you go viral with something like that. And if you're the first one with these headlines, then, you know, you're going to be able to grab everybody's attention. And so that's what everybody does.
[00:08:25] It's better to lead with a fear, you know, title, get everybody's attention and try to walk it down. But in some cases, they're not even doing that.
[00:08:33] And so, you know, we, we've done some digging, and what I want you to do is I want you to think about where you are in your career. I want you to think about, you know, the activities that you're doing. I want you to think about the things that you believe no other human can do, because that's your. That's your job. You know it better than anybody else or think about just the general activities of, you know, what it takes for you to do your daily job and think about how tough it is just to have AI either check your email, write a spreadsheet, or even pull together a PowerPoint presentation.
[00:09:13] And so when we come back, we're going to deep dive into that.
[00:09:17] We're going to talk about some of the realities and we're going to set the record, say straight. So stay with us. We'll be right back. SA Foreign welcome back to AI Today. I'm your host, Dr. Alan Badot. And you know, this week we're talking about really some current events that are taking place in how AI is being blamed, there's no other way to put it, blamed for all of these mass layoffs that are taking place, particularly at Amazon and Meta. Now, I said in the last segment we were going to talk about some of those, you know, realities that, you know, are just, you know, show the facts that you just, you know, AI is, is just not in a mature place yet to be able to just completely replace, you know, all of these jobs and really be blamed for a lot of this. And so we got to dig a little bit deeper.
[00:10:47] And so, you know, in this segment, I want, I want you to think about it from the perspective of, you know, really a, you know, a software developer, right? Because that's the, that's the, the, the skill set that everybody's saying is going to completely, you know, turn software development, software engineering, those kind of skill sets on its head and folks are going to be really obsolete as soon as, as soon as AI is, is capable of handling all of that. Now, as you look at, and if any of you have used, you know, some of these new software development tools that are out there or, you know, if you have seen the show and you've seen how I have shown you some of the nuances associated with using these tools, then you would already recognize that it's not ready, it's not ready for prime time.
[00:11:44] Why is that? Well, I've shown you that if you let it go on its own, it's going to write code that is 10 times more inefficient than it needs to be the other time I've shown you how it will create things. It will generate code, it'll insert fake code and it'll tell you everything is production ready.
[00:12:09] Oh, that's a problem, right.
[00:12:13] And so as you're a software developer and you're thinking about that, that say, for instance, you've Been coding a few years. You're, you started right out of college and, you know, that was about the time that large language models were really starting to pick up. They were starting to go from, you know, some, some basic prototypes and some folks trying some pilots to just, you know, using it everywhere that you can and saying it's the greatest thing since sliced bread and it solves all problems and all AI now should, should bow down to large language models. But we know the realities of that. We know that, you know, from the time that ChatGPT was released to GitHub, Copilot and to some other, you know, tools that were out there very early on, you know, we thought it was cool. We thought it would be able to do a lot of things, but we knew at the time it just wasn't ready. It was awful.
[00:13:19] And now we think, oh, it can do all these things and what do we do now?
[00:13:26] So as you realized some of those impacts, as you looked at, you know, those skill sets that you have spent a long time developing now to come in and think, oh, AI is just going to replace me and it's going to do all of these other things, that's where 40, the numbers, 40% can come from, right? Because you think, okay, I can understand why 40% of developers, software developers think that their job is going to be replaced, especially by 20, 30. That jumps up to almost 60%.
[00:14:01] Now.
[00:14:02] I can't tell the future, but what I can tell you is that as you look at AI and its impacts with humans and how we are using those tools, that you still have to have a human in the loop. And oftentimes we forget, you know, sometimes it's going to go awry, it's going to hallucinate, it's going to make up things, and that's where the human has to come into play.
[00:14:32] And when you start looking at taking a broader, you know, look at these, these sort of things, you know, Amazon is a great use case for, for this because if you think about it, you know, Amazon's got a lot of different business lines. If they decide that they want to go into a certain market, then, you know, it can almost be, you know, the end in many cases for that market segment books. Look where, look how that happened, right? You know, and now, you know, food and clothing and everything else and, you know, it starts to build. But that's on the commercial side of their market.
[00:15:12] You know, that is a very thin margined, you know, business unit.
[00:15:19] You don't make a lot of money by, by selling those kind of things, because that's how they can. That's how they can start to dominate that market.
[00:15:29] But when you start to look at the broader picture and that 30,000 jobs that had taken place, and even Amazon said it in their own press release, a lot of that is due from the fact that coming out of COVID they had staffed up, they had huge management bureaucracy.
[00:15:46] And what they are trying to do is they're trying to get their hands around that.
[00:15:51] And you could have multiple, multiple managers in a chain of command that were, you know, sometimes when you want to be innovative, that oftentimes that stifles it.
[00:16:04] And here's what's worse.
[00:16:06] You know, it's not going to be the only one. It's sure not going to be the last one. You know, in the first half of 2025, almost 70,000 tech jobs were lost in the, in the U.S. and, you know, look, when you're one of those 70,000 people, the reason doesn't really matter.
[00:16:29] You know, whether it's AI or restructuring or economic conditions or you don't have enough, you know, OPEX to be able to afford your chips that you need from Nvidia. Whatever the reason is, your job is gone.
[00:16:43] So, you know, I understand that.
[00:16:45] But overall, the reason does matter, especially when you're trying to understand what's happening to the job market as a whole.
[00:16:55] And that's very important because here's what the headlines are not telling you, right? And you know, Amazon didn't say we're replacing 30,000 people with AI.
[00:17:06] That's just what everybody heard.
[00:17:09] That's not what they released. That's not what they said.
[00:17:12] What they actually announced was that, you know, a workforce reduction across multiple departments. Some of it's operational restructuring, some of it's economic, some of its market conditions. And yes, you know, some could be automation, you know, with AI, but we don't know the breakdown of that, you know, and that is what matters.
[00:17:35] You know, right now, though, we're in a moment where every job loss seems to get blamed on, on AI. You know, it's an easy story.
[00:17:44] It's a. It's a scary story. It gets clicks, it's going to get excitement by readers, it's going to get people that are up in arms, but that's not likely to be accurate, you know, and, you know, that's the unfortunate thing because I have shown you the power of using it for your business. I've shown you how you can really save a lot of time. I've shown you how it can Help you grow. And I've shown you that, yes, it could affect, you know, some of those jobs data. You know, the data shows it. There are certain job categories that are going to be impacted.
[00:18:25] Now, is it easier to just, you know, lie down and, and take it and say, okay, there it is, the end of the world. I'm, you know, there goes my job? Or is it better to embrace the challenge, understand that it's real and it's, it's happening, but then figure out a way that you can improve your skill sets and do an awful lot of other things? Because, you know, when you take a look at that broader labor market, you're gonna see it's gonna contradict all of the panic that folks are experiencing and that people are writing about and that they're seeing.
[00:19:05] And, you know, this is a huge piece that I want you to think about as we go into break, because when we come back, we're going to highlight that a little bit. I'm going to explain it a little bit deeper, and then we're going to, we're going to start to look at really the realities of all of these things, how they're impacting us, the different job categories, the different skill sets, and how you can prepare for it. So stay with us. We'll be right back.
[00:19:59] FOREIGN welcome back to AI Today, before the break, we talked about fear. We were talking about AI and how easy it is to get a response out of saying AI is taking everybody's job.
[00:20:21] And, you know, that fear, I, you know, I wish I, I didn't have to say this, but that fear is real.
[00:20:27] Millions of workers are genuinely worried about AI taking their jobs.
[00:20:33] And, you know, I can understand because that's all they've been fed. That's all they've seen.
[00:20:39] Many folks, you know, haven't been exposed to it, haven't seen it. They should watch the show. But, you know, you know, we're trying to really dispel some of those myths.
[00:20:51] You know, going back to the software developer. You know, again, I have shown you that these things can go off the rails. And you have it audited itself and it's said, yeah, everything's great until you run it, it's not going to work.
[00:21:02] Now, imagine taking that to an operational environment where you're manufacturing things or you're making medicines or whatever that is, you know, primetime.
[00:21:14] It's just not ready.
[00:21:16] Now that leads us into our ability to talk about the realities of the situation.
[00:21:22] You know, when you look at what jobs are actually declining, which ones are actually Being replaced and what the data shows, it's a different picture. It really is. You know, here are, just think about it. Some of the jobs that you're, you're, you know, we are seeing that are really starting to be automated and you know, what you need to do to create a plan how you can prepare for some of these things. And you know, let's just be honest with you what's happening and what we've seen because this is not the first time this has happened, right? The, you know, technology revolution that took place in the early 1900s and the, the manufacturing line and the assembly line, you know, all of those things were, you know, accelerants to job market displacement.
[00:22:16] So instead of having, you know, so many factory workers, we continue to automate some of those and build these robots and steel and we kept doing that for other types of industries. So this is not the first time this has happened. You know, if you think about today though, think about bank tellers, you know, by, I think the stat was 2032, 2035, something like that.
[00:22:44] Bank teller jobs is, it's really, the projection is about a 15% loss in the next, you know, almost 10 years.
[00:22:55] That's about 50,000, you know, 51,000, something like that. Different types of jobs that are going to be gone now. Why is that? Well, mobile, we're going mobile for everything. We got mobile apps, we got ATMs, we can move money around. You've got cryptocurrency coming up in some cases, you've got online transfers. And when is the last time that you went to a bank branch for something that you couldn't do on your phone? I can tell you, from my perspective, it was about two weeks ago when I had to wire some money out. But even some of those processes are starting to go away. Then some banks, you can, you can do some of those things.
[00:23:34] So you're starting to see this convergence where, you know, those, those are, are going away, but it's not because of AI, it's because of the mobile devices and our ability to do some of these things. And you know, in transit.
[00:23:49] Cashiers, cashiers are even worse. We've seen that decline for, for many years, but it's going to get even worse. They're saying that almost 30% of those jobs are going to be gone by, you know, the same time frame that I saw in the, in the bank teller, you know, stats.
[00:24:07] Again, that's about 300 though, and 50,000 jobs that are going to be lost.
[00:24:14] So that's real impact.
[00:24:17] And you know, those self checkout lanes, you know, a lot of us love them when the scan and go technology, but even the robots and even the, you know, the, the automations that are taking place are, are, are going away. Why? Because you can scan the bar device on your mobile and it puts your entire, you know, shopping list on there. And then when you're ready to check out, boom, you show them your, your receipt and you're done.
[00:24:43] Amazon did that.
[00:24:45] All that scan and go technology was Amazon. Why? Because that's what they do. They innovate, they're trying to, you know, take some reliance off, you know, some of the local stores and some of the people part of that process and they're trying to automate those kind of things now.
[00:25:03] You know, another one is medical transcriptions.
[00:25:10] That's almost going to be down. Oh, I think they said 47, 48, almost 50%.
[00:25:16] And why? Because that is something that AI can do.
[00:25:21] You know, my, my medical assets, it can translate in real time.
[00:25:26] So as I'm talking to somebody, they can be talking in another language there. I think there's 18 or so languages that you know that it understands and it can translate for you in real time. So allow you to communicate just as though you're having a normal conversation. But they can talk their language, I can speak English. And then, you know, you continue like everything's fine.
[00:25:49] That's, that's amazing.
[00:25:51] And from a technology perspective, I love it. But from a medical transcriptionist, that's a, that's an issue. And then we can go all the way down the line. We can do credit analysts, we can do anything associated with, you know, insurance assessments. You, you know, insurance, you know, you know, that entire industry is, is being automated and AI.
[00:26:15] Now here's the pattern though, because there is a pattern.
[00:26:19] All of those involve routine tasks.
[00:26:23] They're predictable.
[00:26:26] You've got tasks that follow rules. They're basic rules.
[00:26:29] In some cases you call them expert systems. Right? Because if this, then that type activities, it can be tasks that encode some kind of algorithm, doesn't matter, but it's still repeatable, it's easy to replace and it's very ripe for automation and AI to take that in.
[00:26:55] But you know, as you start to expand and you start to look at all the other factors that are going into that, you know, we have lost since, let's see, since the year 2000. I'm trying to remember exactly what it was.
[00:27:14] Almost 1.7 million manufacturing jobs.
[00:27:19] And that's been due in many cases to automation. Whether you're automating a part of the assembly line. Whether you're automating some of the back office stuff, the financials, the receivables, the pays, but not all of it is AI.
[00:27:34] A lot of it's robotics, of course, but the trend is pretty clear.
[00:27:40] You know, if your job is repetitive, if it's rule based, it can be reduced to a flowchart and if it can be reduced to a flowchart, it can be replaced.
[00:27:53] Doesn't matter what it is.
[00:27:55] And that's the, that's the area of folks that, that should really be concerned.
[00:28:01] Now that means entry levels, you know, type opportunities probably.
[00:28:08] However, if you're young and you're just starting your career, that doesn't mean that, you know, you have to just give up. And I've seen a lot of people that are saying that, you know, they can't, they're coming out of college, they're just giving up because, you know, they don't want to do whatever, whatever it is, they feel defeated even before they start.
[00:28:32] And you know, that is, that's not a, you know, that's not a individual feeling in, in this generation. It really is something that, you know, a lot of folks are just disenfranchised with the activities that are taking place.
[00:28:49] And that's unfortunate because, you know, I saw something that Stanford did that was actually pretty clever and how they were looking at, you know, the market as a whole. They said they got access to some payroll data and I, you know, it's not surveys, it wasn't predictions, it wasn't, you know, that kind of stuff, but it was real hiring and firing numbers. And what they did is they tracked what was happening after ChatGPT and other AI tools like Claude, you know, became widely available. And that was about 2022, right? 2022, late 2021, 22.
[00:29:26] Now what they found really should alarm people about thinking of, you know, future work, of course, because they saw that, you know, a high, you know, portion of, you know, management jobs were, you know, were vulnerable. A high portion of software developer jobs were potentially vulnerable.
[00:29:54] Customer service reps, you know, entry level data analysts, you know, these types of workers, you know, they, they, they realized that that could be, you know, pretty significant. And actually it wound up being they were estimating by about 13% over the next few years.
[00:30:11] Now meanwhile, you know, older workers in the same field, you know, this is something brand new to them. You know, they've been doing these things for many years and you know, now it's a, it's a risk that they didn't have in the past. So a lot of people are saying that, you know, it's a, it's a stress that, you know, they haven't had to see. It's a, it's a retraining opportunity that they're not quite sure about. And you know, it's a stability factor in their lives, in their family lives that are, you know, really the biggest concern for them, and rightfully so.
[00:30:46] But, you know, as you, as you take what we are doing today and you see those exposures and you see those unemployment rates and you see those other occupations and, you know, computer science and mathematics, those jobs, you know, are, you know, really becoming a little bit harder to see, a little bit harder to, you know, take advantage of and really, really put yourself out there for.
[00:31:15] And, you know, it's, it's, it's one of those things where the hard sciences are actually starting to, to have some impacts as well.
[00:31:25] Now, again, this, is, this, is this the study that they were coming up with. But, you know, as you are thinking about where and how companies are, are training folks to do it their way and how you're learning about specialized systems and specialized processes and you're doing foundational work potentially where, you know, other things are being built around what you do or on top of what you do, then your ability to handle complex problems is going to separate you from anything else that's out there. And specifically any AI that is out there.
[00:32:09] It's very difficult for AI to do complex things, especially in today's environment. It's hard enough to get it to do a darn PowerPoint presentation.
[00:32:19] Now there are tools that are coming along, but they're not meant to replace humans. Even the tool that I've developed is part of my company. It's not meant to replace people.
[00:32:31] Why?
[00:32:32] Because it's not making the foundational decisions. Okay.
[00:32:38] The whole point is so that you can take a person and you can elevate their skill sets so that they can do their jobs better, faster, cheaper, or you can run your small business better, faster, cheaper, or you can start a business and do something that you didn't think that you would be able to do a few years ago because you didn't have the knowledge to run it, started it to go get loans to do all those things.
[00:33:04] And so my counter argument to AI replacing everything is that this could be the point in time, your opportunity, when you can expand your skill set and take over.
[00:33:24] So think about that.
[00:33:26] Think about the opportunities that you now are afforded to get expertise, to pursue a job that you want to, that you want to do, start a business, take what you have and, you know, create something. There are ways that you can do that.
[00:33:44] And what I want you to think about as we are going into, you know, the break, as you are learning systems, as you are learning processes, as you're doing all of those things, I want you to say, you know what, I'm paying attention to this because I either may be able to use it to help kick off my AI learning path that I have to go down, or, you know, I may be able to use all of this to make myself better, to give me greater skill sets in using AI. And maybe I'm one of the only ones in the company that knows how to use AI and do my job doing a lot better.
[00:34:26] That's a much better story, and that's much more of a reality for people.
[00:34:32] So, as you know, I want you to stick around. We'll be back after a few messages, and we're gonna, we're gonna really, we're gonna end the show talking about some ways that we can help facilitate that. So stay with us. We'll be right back.
[00:34:51] Sam welcome back to AI Today. I'm your host, Dr. Alan Badot. And we have been talking about the realities of AI and its impacts on the job market. And with, with the headlines of the past week, you know, the, the large numbers that, that people were seeing as far as job cuts and, and other other, you know, technology segments that are following Amazon suit. It also is pretty worrisome for a lot of folks. And that's why I wanted to address it this week, because I did not want to wait another week to talk about it.
[00:35:54] We see these kind of things all the time.
[00:35:57] And if you also saw what happened when those numbers were released, it's the end of the quarter, it's time to report earnings, right?
[00:36:07] And going into earnings and shareholders and how they like to see some of those things.
[00:36:14] It's about cost. It's about bringing costs down. It's about showing some sort of AI impact, those kind of things. And it's about being able to, to have a story that you're trying to tell about restructuring and becoming more lean and mean, and it helps, only helps the profit margin and all those things. And so, of course, everything has got to be, you know, taken from a negative perspective, and AI is an easy target.
[00:36:40] Now, last study that I'm gonna, I'm gonna mention to you all, because, again, it goes to the heart of some of these Things I saw Goldman Sachs study and they were doing some analysis and they said that, you know, they had calculated that. I want to get this number right.
[00:36:55] It was, let's see, yeah, 6 to 7% of the US workforce would be displaced by AI if adoption becomes widespread.
[00:37:08] 6 to 7%, that's millions of people.
[00:37:13] You can't minimize that. Right. But again, here is what they left out of the headlines and what I want to bring to you. You know, they noted though, that the effect would be transitory, meaning temporary displaced workers, they thought and they found would be new employees at either another segment or even an AI segment within about two years.
[00:37:43] Now, that's a completely different discussion and completely different tone to AI is permanently destroying all the jobs.
[00:37:55] You know, we as a society have always seen and always strived to innovates. That's part of our nature. We try to push boundaries, but as we are pushing those boundaries, it creates opportunity. It always has and it always will.
[00:38:13] Because you will see with AI, you will be extraordinarily frustrated sometimes, or sometimes it'll work and you'll have a eureka moment.
[00:38:25] And that'll make the frustrating moments even that more frustrating because you'll see that, you know, AI is just not ready. It's not ready to take over all those things.
[00:38:36] It still needs a human out there to say, no, I don't think so. I think putting a chocolate chip cookie recipe, which I showed you guys in code, is a problem.
[00:38:48] It can happen.
[00:38:50] And, you know, the thought of a company just allowing all of their employees to be let go and replacing it by AI because they're so confident in that should trouble you. Remember I told you and I gave you examples of how companies leaned too fast into it.
[00:39:15] The next day, for example, when ChatGPT came out with their API, there were 900 companies that were saying they were deploying it into the production and, you know, they were gonna, some companies were gonna lay off all their service desk workers. Ask them how that went. I can tell you I got a phone call to try to help fix it, and I got many phone calls to try to help fix those because again, too fast, not ready.
[00:39:44] And granted, AI is better, but in some cases it's worse. Okay, You've got to have a nuanced understanding of these because it is not just black and white. It's not just AI is taking over. You know, everybody has this perception, AI is so powerful, you know, it's going to replace everybody. But the realities are. And let's, let's, let's get 100% real when it comes to these.
[00:40:16] We can't solve all these challenges by the end of the year.
[00:40:20] We can't.
[00:40:22] There are deep structural limitations with the mathematics that go into some of these.
[00:40:29] We have deep infrastructure challenges to get AI to the point where it can do a lot of these things. Look at the data center boom that's going on.
[00:40:41] That data center boom is also going to pull, you know, fund a power supply boom.
[00:40:48] It's going to fund Westinghouse and I think it's the $80 billion that they're getting to bring in a whole bunch of new people and construction workers and those kind of things to build more nuclear power plants. It's going to fund the transmission lines, it's going to fund all the hardware that goes into that. There's a five year wait on generators for data centers until they figure out how they can make more. It's a five year wait.
[00:41:13] So that means we're not even going to have enough power to run these.
[00:41:18] And so take a step back and you think, geez, you know, installation jobs, maintenance jobs, repair jobs, electricians, plumbers, extraordinarily important moving forward.
[00:41:34] And those are going to only get in higher demand.
[00:41:39] So in some ways we're going back to, you know, the, the early 80s, the 90s, you know, where these, these trade jobs are being more sought after.
[00:41:52] You need more of those. You don't need less.
[00:41:55] Listen, I'm, I'm pretty good at a lot of things.
[00:41:58] I stink at plumbing. It drives me crazy, it really does. And I'm awful at it.
[00:42:04] I can't replace a plumber. Heck, I wouldn't let AI anywhere near it.
[00:42:10] Solar panels, all of these kind of jobs, you know, that are craftsmanship experts, folks that can do those things, those skilled trade jobs are coming back. And a lot of that's because of AI. AI is driving that.
[00:42:24] But AI doesn't get credit for that.
[00:42:27] You know, it's kind of like a quarterback, if you think about it. When you win, you're great. When you lose, it's somebody else's fault.
[00:42:33] AI, it's like that jobs are going away. It's AI's fault. Jobs being created on the backside. Oh, that's something else.
[00:42:41] We're not going to talk about that because that kind of goes against what we've been saying the last 18 months.
[00:42:47] Personal services is the same sort of thing.
[00:42:50] You know, if you rely on a person to either interact with someone, a customer to help them do something, some sort of skill set, some sort of even food preparation, you know, serving.
[00:43:08] I don't know the last time you had a robot bring your food to you. I've had it done a couple of times. Once was in Japan. Pretty cool. It was four. A fun experience, but, man, it was slow when it dropped things.
[00:43:21] And if you're a business owner, that's the last thing you want to do is throw stuff away.
[00:43:26] And we've seen all these robot chef videos and, you know, its ability to do so many things. And we've seen. We saw the first McDonald's, it was going completely automated.
[00:43:38] Yeah, yeah. It's again, more headlines, less reality.
[00:43:44] You know, more, you know, more big bang in the reality. It's more of a thud.
[00:43:50] And those sort of things are not going to change. In some places, again, it's going to work well. In other places it's not.
[00:43:59] And the easiest place to look at that is health care.
[00:44:03] Nurses, therapists, doctors, aides, whatever that's projected to grow significantly. Nurse practitioners, you know, almost.
[00:44:13] I saw a stat, I think it was the American Academy of Nurses, I think.
[00:44:20] But they're thinking that 52% growth over the next three to five years.
[00:44:26] And that's. That's all. That's awesome. That's outstanding. And why is that?
[00:44:31] Because people, when they go into a hospital or they go to get something done, they don't want to be treated by a robot.
[00:44:39] Heck, some people think that their doctors are robots now, and they don't want it to get worse.
[00:44:48] If you're in the hospital and you're. You're sick and you don't feel well, the last thing you want is a robot coming around that's happy all the time.
[00:44:56] You know, I'd want to. I'd want to punch it.
[00:45:00] And those sort of jobs are.
[00:45:02] Are only, you know, becoming more in demand.
[00:45:06] And that is not, you know, that's not despite AI but that's because of AI you know, AI is augmenting these jobs with the volume that a radiologist has to see.
[00:45:25] And, you know, if you think about it, a radiologist, if you go in, you break something, you have pneumonia, whatever that is. They're not just looking for that. If you thought about that, when you have a chest scan done because you may have pneumonia, think about what happens if a radiologist is looking at that and they say, yeah, they've got pneumonia, but then they miss a tumor. Right.
[00:45:46] Radiologist is a perfect example of that. We can train AI to look at pictures and pick out certain features and those kind of things, but again, it's not ready. It can't do that. It can't do what a radiologist does and say, okay, I see that, but I also see this.
[00:46:03] AI's not capable of doing that in many cases. And the systems that I've seen just don't do it well. And you talk to the doctors and they'll agree.
[00:46:14] That's the bigger story.
[00:46:16] That's the thing for you all to think about.
[00:46:20] Healthcare requires social intelligence, emotional intelligence, you know, the ability to read a patient's concern, the ability to improvise, the ability to do something in a reaction to something that unexpected might take place.
[00:46:38] And that also includes providing comfort when there is a moment of fear.
[00:46:44] And AI can't do that, not yet. And we're not going to be able to do that in five years either.
[00:46:49] And just because we can't do it doesn't mean it's going to be accepted and it doesn't mean it's going to drive out millions of jobs. And, you know, those are the types of headlines that we have to get away from. We just have to. Because, you know, people are missing an opportunity. You're missing a chance to take advantage of a situation where jobs are naturally changing.
[00:47:15] They're not vanishing, they're changing.
[00:47:18] And that's your opportunity to grab onto it and say, you know what? I'm going to change with it, and I'm going to see if there's an opportunity that I can do something that really I've always wanted to do, but I didn't have the skills to do it.
[00:47:36] That is how we go through these shifts.
[00:47:41] That is how we adapt. That is how we better ourselves as a. So, you know, a society. And that's how we can get through these things. And at the end, we always come out better.
[00:47:54] Generation after generation. It improves.
[00:47:58] Maybe it'll stay stagnant going into the next one, but it should improve now.
[00:48:06] No more panic, okay?
[00:48:09] Think about it. Let's. Let's put some. Let's put some filters on those glasses. When you read some of those crazy headlines, like I always say, it's only about 25% truthful. The rest of it is to get your attention. So you'll buy something, you'll click something, you'll go somewhere, you'll. You'll get concerned, and you can, you know, scream at the top of your lungs that there's a problem and you're going to fix it when there's probably not a problem.
[00:48:34] It's disrupting the markets.
[00:48:36] Some jobs are declining, some jobs are coming back, and some jobs are going to really take off.
[00:48:44] And hopefully, hopefully you can get one of those jobs that takes off. If you prepare, if you start looking at it, I gave you some examples, then that is how you're going to succeed.
[00:48:56] You know, if the nature of the work is changing, that means you have to take the initiative to do something about it and figure out the skills that you need so that you'll thrive in that career.
[00:49:10] Right? That's. That's fundamentally what we try to do.
[00:49:13] That does not change. All right, so as we close, I want you to think about these things going forward. I love the emails. You all know I love the emails. I love when you guys send me and ask me questions. This week, I could not get through all of them because, you know, I got a lot of them and, you know. But I'll continue to try.
[00:49:35] But remember, you know, every email that I sent out this week was a positive because again, take advantage of the opportunity, grab onto it, embrace it. Use AI to better yourself. And you're going to be one of those that are going to get hired into these new jobs that are going to take place. Because I always say it's not AI that is going to replace you.
[00:49:57] There's somebody that knows how to use AI that is going to replace you.
[00:50:03] So keep that in mind. Thank you.
[00:50:05] I appreciate you always. And we will see you next week with another great show. Have a great week.
