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IIIMPACT is a Product UX Design and Development Strategy Consulting Agency.
We emphasize strategic planning, intuitive UX design, and better collaboration between business, design to development. By integrating best practices with our clients, we not only speed up market entry but also enhance the overall quality of software products. We help our clients launch better products, faster.
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You have to be just adaptable to whatever the changing environment is, just like any animal that's out there. You know, it survives by being adaptable and you just gotta be hungry to learn. And most people stop learning after they're done with college or university. So you've got to change that mindset.
Brynley Evans:The older you get, you need to have more of a push to actually upskill yourself and use things like, you know, better better prompts.
Joe Kraft:You know, you can build out something that would have taken, you know, a year of development with 20 people. Now you can do it yourself in, like, a month or a week. But it's still just, you know, is that product happening already? Because there's other 50 other people can do the same now.
Makoto Kern:Everybody, welcome back to another episode of Make an Impact podcast. I'm your host, Makoto Kern. I'm here with Joe and Brinley.
Brynley Evans:Howdy. Hey.
Makoto Kern:Hey, guys. And, for today's topic, I think this is a really big one, an important one, especially for you parents out there or university or almost university students that are studying and trying to figure out what should I do, and how do I future proof my career for the next five to ten years, to what degrees are gonna be obsolete because of AI, and what kind of careers will thrive along with AI. And so in the recent news, we have the NVIDIA CEO who brought up something really important, and same with the CEO of Fiverr as well. They both brought up some really interesting points. I'll start off with the more negative one, which I think is from the Fiverr who basically says that, you know, you you may get replaced.
Makoto Kern:You're probably gonna get replaced unless you keep up with the the technology, and that was something that was leaked in an email by them or by him. That was an interesting leak. I'm sure it it scared a lot of people in their industry. But also with the NVIDIA CEO, what I read about that was really interesting is basically, he said it's the ability to prompt very well and and using it really, really well alongside with what you're doing. I think an interesting point that I I saw was it's not the people that people get replaced by AI, but it's the people who don't use AI will get replaced by people who use AI.
Makoto Kern:I think that's a really important point. And being able to prompt and do those things are, I think, really
Joe Kraft:Yeah, that's a good quote.
Brynley Evans:And it's also kind of pushing yourself out of, I think we're probably going to, you know, people that have been in the job market for longer. I was listening to an event with Sam Alban and he was talking about how they were looking at the demographics that use ChatGPT. They're saying that it's so fundamentally different, someone in their 50s versus sort of thirties and forties versus twenties in how they actually utilize ChatGPT. The older you get, the more you're sort of looking at it like a search engine, unless you're not plugged in. He's saying, and we've touched on this before in other podcasts, but the younger users sort of in their twenties are literally hooking it up to all their files, they're using the memory, and they're almost basing every single decision off of what ChatGPT guides them on.
Brynley Evans:So I need to make a career choice. What does it say? I need to respond to someone in a certain way. What does it say? How is it looking at all the files and the memory it's built up around them?
Brynley Evans:So such a massive shift from, you know, where you look at someone, you know, that's just saying, okay, well, how do I reset the cache on my browser? Yeah. It's interesting, and I think that's where there needs to be the older you get, you need to have more of a push to actually upskill yourself and use things like better prompts
Joe Kraft:You're saying engage that younger people are doing, are like using it better than older people? Do you think it's a good idea that they ask, you know, we've gone through this before too, but you know, basically ask it how to reply to someone, what do I do? Should I take this job? You know, on it a lot.
Brynley Evans:I don't know whether it's better, but I think it highlights how they're a lot more in tune with how AI tools are used. And if we're looking at the job market specifically and that becoming a requirement for jobs, you've got a lot more It used to be your computer literacy, now it's, well, how computer literate and AI literate are you? And I'm just saying that sort of generation is a lot further ahead than older generations who are maybe slower to adopt.
Joe Kraft:Is is this something new, though, or is it just you know, this has always been the case if you think about it. Right? Like, you know, when computers first came out and suddenly now it's like, you know, there's Windows and, you know, young people are jumping into Windows and we're, like, understanding it really well, but, like, all the generations, like, couldn't really figure out how to click around and open files and save things, and they'd lose their files all the time. And I'm just trying to think, like, taking a step back, is AI any different from any new kind of technology coming in? It's obviously a big game changer in that.
Joe Kraft:It's a huge, you know, power creep, power curve to, suddenly start using it as opposed to someone who's not, but I do wonder if it's is anything fundamentally different from it.
Brynley Evans:So if you look at the AI tools and just being sort of a factor of AI literacy, I think that's where it comes in in terms of what is the competitive advantage for younger generations who are more plugged in. I think this is something that Sam Altman brought up. He's saying, Well, look at older people with smartphones. It took ages to figure out how you can click and swipe, and they caught up, but there was a much faster adoption by younger generations.
Joe Kraft:But I guess the question is, as I was saying earlier, technology always moves forward. Older generations do fall behind no matter what the technology is, moving to computers with interfaces, to smartphones, to the Internet, and things like that. I wonder, though, if what what, you know, he's trying to bring up here is that AI is a larger game changer than those technologies. Like, being a bit slow with using your smartphone is one thing, but it won't really affect your job that much or your career. And so who's using it effectively versus someone who's not, there's a way bigger gap there, way more simply I
Brynley Evans:think I'm making the link to jobs. It wasn't necessarily he was just discussing how different it was in each generation. And I'm just bringing it back, really saying, if we're looking at employment and what Ricardo was saying about, you know, almost these AI skills being a defining factor in, you know, whether you're hired or not, you know, it's definitely a bigger push if you're in the job market at the moment, upskill yourself.
Joe Kraft:That question.
Brynley Evans:And understand how you can improve your efficiency because we're there now. The tools are right there ready for you to make your job a whole lot more efficient.
Makoto Kern:Yeah, definitely. Some interesting stats, just to bring up, is they're saying by 02/1930, 70% of the skills used in most jobs will change with AI emerging as a significant driver. And the role of artificial intelligence engineers among the fastest growing jobs in 15 countries. That's a pretty interesting stat. I think another one is over 10% of professionals hired today have different job titles that didn't exist in February.
Makoto Kern:In The US, this figure is 20%.
Joe Kraft:Wow, that's huge. That's crazy. Yeah.
Makoto Kern:Just the rapid ness of how things are changing. It's hard to know exactly what the pinpoint, like, you know this job is not going to be obsolete in ten years or five years. It's just almost impossible to determine that now. But I think some strategies around the education is really helpful to know, and I think that's something that, you know, where you're combining multiple fields. I think it's like the master of all versus jack of all trades.
Makoto Kern:You almost have to be a master of all trades where you're combining technology, computer science or engineering, psychology and design. This is something that is much harder to automate all three, or you're able to be the kind of dock connector between all three is really important.
Brynley Evans:I think something that we've spoken about before as well is critical thinking and skills like that are going to be so important. But I guess if we steer the conversation, say, if you're in high school now or you're university and you're thinking, Do I study something? Don't I study something? If we look at both of those aspects, it'd be interesting to unpack, well, what would be the reasons to actually study something now? You're often taking on a lot of debt.
Brynley Evans:Is there something that's worthwhile doing now? And I think from some of the research I did, you've obviously still got foundational knowledge, which is really beneficial. So if you're looking at things like computer science, AI ethics, design thinking, sustainability, cognitive science, psychology, they're all probably really helpful modules of knowledge almost that you could take forward and apply them, you know, to sort of changing AI. But then on the flip side, you look and you say, well, chances are the job that you're going to be going into, if you're interested in sort of computer science, probably hasn't even been created yet. By the time you finish your study, enter a workplace, it could be starting.
Brynley Evans:So do you say, Well, you're not going to incur that expense now of a university education? And I think, Makoto, you had some interesting stats on the sort of ROI and how that's changing, which could be good to bring up in terms of, I think some of your research had had sort of touched on how traditionally you would study a defined set of skills and that would be good for your career. You're set. It's not going to change that much. And it's been sort of coming down to, you know, your skills are relevant for five to ten years.
Brynley Evans:Think it was now, one of the stats you had, it was even three to five years, you know, how relevant your skills are before you actually need to adapt. Wow. And that's big. If you've got a massive student loan and you're actually having to study something, you know, completely new, is it better to maybe go into the industry and just, you know, be an intern or something for a year to figure out what the industry is like, where it's going, maybe study after that, or maybe build up skills that are actually gonna take you, you know, on that sort of trajectory to potentially career that hasn't been defined yet. Yeah.
Brynley Evans:It's
Makoto Kern:I mean, I just see, you know, from my kind of career arc, it's been interesting where I started off as a robotics engineer and did that for about a decade. And then basically everything was outsourced to China from The United States. No, education for me wasn't as expensive as it is now. I think the average cost in The United States for university, you're looking between 30 to $70,000 a year just on the university. I mean that will break most people's banks trying to do that or you graduate with loans in the $2.03, $400,000 which is just, I mean you're paying that debt off forever unless you have a very high paying job.
Makoto Kern:That kind of hole, you know, the hole that you're digging, you have to be just adaptable to whatever the changing environment is, just like any animal that's out there. You know, it survives by being adaptable and you just gotta be hungry to learn and most people stop learning after they're done with college or university. That's a good point. Because you gotta change that mindset.
Joe Kraft:Yeah. I think it also comes down to I know the way you view you view university, what you want to get out of it. If you're someone who's going in and your goal is just to get that piece of paper right, you're just in and out, then what we're trying to say here is that piece of paper may not be too applicable going forward because there's so much disruption in the industry. You know, it may not be relevant anymore. So I think there's two ways to sort of look at that.
Joe Kraft:First, I think university shouldn't be viewed as just that piece of paper. I think it does you know, technically, you know, all universities are different. Some are good. Some are bad. But at least the good ones are kind of meant to teach you more than just what you're getting out of it from that course alone.
Joe Kraft:It's kind of meant to be teaching you to work with other people, right, like student groups, work on projects, process information, research information, and you're going to get graded on your research. So it means you get given a topic, you go out, you study it, you research it, you put together a paper, you present that paper, it's meant to be graded. And it's all just about how we it's sort of training you how to process information, I think, is a large part of it. A bad university would be like, Here's a textbook, memorize it. That's not going to really do anything for anyone.
Joe Kraft:But the good universities, I do think, do teach critical thinking, teaches cooperation team work, understanding, and also tackling a big project. Because up to those points in your high school career, whenever you've got your homework, your little bits and pieces, you've got your big exams, but you never really, like, tackled a big project. Like, this is a big thing. It's like your thesis or, like, some big sort of thing that you've got to work towards. It could take months, and you never really encountered that in your life to that point.
Joe Kraft:So I do think you sort of gained skills out of working on those sort of bigger projects too, especially with people. So if if we were if we're trying to, like you know, if this whole conversation is around, like, know, would we recommend at this point in time someone goes to study, I do think you have to look at it from that side. The other side is that I would recommend is don't try and study something very niche and very specific. Like, don't put all your eggs in one basket of, okay, I'm going to study, you know, x and, I'm trying to think of a good example, but, like, some very niche specialized field that could get replaced. Right?
Joe Kraft:Because you just basically doubled down on some Yeah. Yeah. Something like I don't know. Something that could easily get replaced by AI, I guess, we're trying to say. Like, maybe some, you know, I don't know.
Joe Kraft:I I have to think of a good one. Maybe you guys can. But, you know, something that technically could very easily get replaced by AI wouldn't be a good one to go for. I would study something a bit more generalistic. Even a computer science degree, it does teach you, like, a whole bunch of fundamentals across computer science.
Joe Kraft:It's not just like, oh, well, this is how you program. Maybe that would be a bad thing to do. Right? If you're just going into university and you're just studying programming and you just that's all you do. You don't look at anything else around the industry or try and, you know, get into the technical side of it or, you know, the the engineering side of it.
Joe Kraft:You know, that would be, you know, a risky move. I would rather go for a more generalistic computer science degree that teaches, you know, across the board a whole different set of fields and and sort of allows you when you leave university, you have that piece of paper, you kind of have a good overview. Like you're kind of like, again, as you were saying earlier, it is kind of a jack of all trades, but at least you can pivot then really easily around to where you need to be, not kind of like narrowly focused to something that could not exist anymore by the time you finish.
Makoto Kern:Yeah, I think something from the physical side of things where it's not all software driven, anything that you have to work with your hands definitely has a more lifespan. Obviously everybody's working towards Tesla with the Optimus robot, Boston Dynamics, they have all these really crazy dexterity robots. I think that's something where, that's probably farther out, but at least I think from the physical side of things, if you can kind of combine whether it's like blue collar work and combine AI with that or construction or things like that, I think there's still an advantage there where that can work in conjunction with AI because that's traditionally very physical and more old school in the way they approach technology.
Brynley Evans:And it maybe depends on what you're looking for as well, because if you think there probably aren't courses on some of the emerging technology now, whereas you could actually, you know, be teaching yourself some of those and be a trailblazer in those fields, especially as AI kind of connects you more and more into sort of working with different technologies. And, you know, even if you get micro sort of qualifications from a lot of the universities, I think there's so many things to factor in there. And I agree with you, Joe. I think communication skills and then also the networks that you make. You know, do you meet the people that you're going into business with?
Joe Kraft:Do you
Brynley Evans:have the mentors that could steer you, you know, exactly, you know, where you need to go in life?
Joe Kraft:So I think there are a
Brynley Evans:lot of benefits there, but it's really up to, you know, up to the person to see, you know, what they're interested in and, you know, maybe it's even a hybrid approach of working and learning at the same time to sort of steer your, you know, the direction of your career as you learn more about certain things.
Makoto Kern:I think an important point is to tell you which jobs are most vulnerable just within the next few years. And what's interesting in our research is that what's happening right now, we could break it down into kind of what they call the first wave, what's already happening. And that's everything from data entry, content moderation, basic copywriting, and social media management are all seeing like 20 to 40% declines in job postings and opportunities.
Joe Kraft:I'm surprised about the social media management. You would think they would need a human touch more than the others.
Makoto Kern:I think that's where people are calling AI slop, where you're able to automate a lot more, but it's
Joe Kraft:just gonna be a lot more noise. Generates post a bunch of junk, yeah.
Makoto Kern:Yeah, so I think being able to be more unique, something that is more real is going to outpace all the AI slap that's gonna probably be coming out. Thank God we've got Brinley who's completely AI generated, who's talking right now.
Brynley Evans:Precisely. That's what we hear from.
Makoto Kern:Second way that's Turn in 10
Joe Kraft:times, that would be good.
Makoto Kern:So the second way within the next year or two, said is, entry level accounting, basic legal research. That's interesting because I've got friends that have their own law firms. So having their own paralegals, they can do a lot more with less because that's very time consuming. Reviewing documents and law the cases, just being able to quickly speed through that, you're cutting down on the amount of paralegals you need. And they said medical coding, first level customer service, We know that, I mean, that's the chatbots and help that you're trying to at least get them through that first point of safety before they start to hit somebody who's real.
Makoto Kern:And then as you guys know, the routine software development tasks, if you can leverage that and it's spitting out something that's actually good, not hackable, that's something that can help. It's a force multiplier basically is what that helps with. Third wave is the next three to five years. So they're saying that the advanced language models combined with specialized tools can significantly impact roles like again, paralegals, market research analysis. That's interesting because I've definitely used AI for just market research on competitors, things like that.
Makoto Kern:And trying to find things that would take me hours to do my own research on by just doing Google searching. Financial advisors, that's an interesting thing to just maybe not investments yet, but definitely for sure, like where should I put my money? How should I invest? I I think a lot of the messages are pretty much the same.
Joe Kraft:That is an interesting one and I do yeah. I'm really interested to see where that goes because if you're using AI to sort of guide you in a certain direction, you think that same AI is gonna guide everyone in the same direction. Yeah. In which case it just dilutes the value of things in a way when you're looking at shares and things like that.
Makoto Kern:That's true.
Joe Kraft:Instinct to see where that goes, yeah.
Makoto Kern:Yeah, we won't get into the whole, like, there's definitely emotional things of trading that maybe it's good to get you out of it because that's where people make the most errors when they start to get emotional with their stock trading. But yeah, I think the next one is really important is graphic designers. Think it sounds like it's more for routine work versus like creating a full blown app, which some of them are doing now with Vibe coding, but I've played around with those as well and they're just okay. You have to be very good at what you do as a UX designer to leverage that as kind of a thought starter versus this is all I need and it's gonna create an app for me. I think that in conjunction with kind of that is the ability to copy good ideas.
Makoto Kern:Like if there's a website and it's like, it does a certain thing, like, oh, I want that, I wanna do that same thing. You're able to replicate that very quickly, somebody else's idea, especially if it's like an e commerce idea, oh, this flow that they've done, you can really easily copy that because it's a very smart idea. And so being able to fend off competitors, you have to stay ahead of the game much So your acquisition and being able to like really create things that are frictionless, I think that's where the skill set's going to be. Because as you lower that barrier of entry, the competition grows exponentially. So you have to do other things to stay ahead of it.
Makoto Kern:And they said general medical diagnosticians. Is that a real word?
Joe Kraft:I haven't heard that one.
Makoto Kern:But I'm assuming it's like when you're looking at x rays and things like that, those things, I know I've heard that even AI from what, two years ago, ChadGBT was out performing doctors. I can only imagine now or in the next three years. We talked about the next wave, five to seven years as the humanoid robots, what can be done there, repetitive motions, cleaning, things like that's gonna be interesting.
Brynley Evans:So I do wish you start seeing them go inside. Yeah.
Joe Kraft:Was just gonna say, I do wonder though if it'll ever get to that price point. I mean, a robot surely is always gonna be more expensive than a human.
Brynley Evans:No. But what does its lifespan? Well, look at its cost to company. You buy something at, if it's mass produced, I don't know what the price point is, but let's say it's $100,000 and that robot can work twenty four hours a day and it needs maybe two hours of the day to recharge. So construction, anything like that, it can go, or warehouse, management, like building things, it can just go.
Brynley Evans:And it doesn't have sick leave. It's a scary thought that it is going to pay off and it is going to be cheaper once that robot is Maybe it takes two years break even with a normal employee, but you've got less risk and then it's got a lifespan of five years, and you're good for the next five years. You're running at, yeah, much
Makoto Kern:less I think some of that, what's interesting is that now the robotaxi is gonna be released soon in Austin and California. There's gonna be a dynamic shift in where if that works out, Tesla's gonna basically become an Amazon and replace a lot of industries. One thing parking lots and you've got all these vast parking lots. If you can just call a car up and it's cheaper to own, you're not gonna own a car anymore. So maybe you might shift that towards owning your own humanoid robot, which should be interesting.
Makoto Kern:And if they could get that price down to like $50,000 you're like, okay, let me get a robot that can I don't need to hire a babysitter? I don't need to hire a chef or this or that or cleaner. I mean, then the ROI starts to be like, okay, I'd rather own my own robot versus a car. That just gets me from here and there once in a while.
Brynley Evans:Exactly. And it's going to be wild when you start seeing more and more robots actually entering society. It's really like the sort of sci fi that we've grown up watching, and it's going to be here. And I think looking at some of the ones, know that fourth wave eventually was sort of five to seven years from now.
Makoto Kern:I'm curious. In video games, cheat codes let you skip months of grinding to unlock special abilities instantly. Have you ever wished for something similar for your software challenges? What if there's a way to instantly access twenty plus years of specialized expertise instead of developing it all internally? What if you could solve in weeks what might otherwise take months or years?
Makoto Kern:Would you agree that most organizations faced a steep learning curve when implementing new software solutions? At my company, Impact, we serve as that cheat code for companies looking to transform complex software into intuitive experiences that users love and that drive real business results. Would it be valuable to explore, and how might this work for your specific situation? Visit impact.io for a free strategy session focused on your unique challenges.
Brynley Evans:I wanted to just touch on some of the things like ten, fifteen, twenty years, which is interesting, and sort of seeing how that looks as well. So looking at two thousand and thirty five, ten years from now, as a potential job disruption tipping point. So you start seeing entire roles just vanishing. So not just the tasks anymore. Not just, we can do all these tasks and you still need people, so you've got entire roles just being automated.
Brynley Evans:And a kind of convergence of blue and white colored workers, so things like warehouse work, logistics, factory roles, all autonomous or mostly autonomous. And you've got your sort of middle skilled jobs are completely hollowed out, so creating a social pressure for policies that a lot of people think are inevitable. So the universal basic income or things like AI dividends. So kind of in that time, seeing job shifts of a decline in your sort of customer service agents, your truck drivers, your radiologists, your analysts, and, you know, a rise in some automated supervisors or robotic maintenance, all things that are, I guess, a lot of more human driven. Because also if you look at, well, what are the characteristics that are potentially going to make a job safe?
Brynley Evans:So you think things like, you know, creativity, you know, your sort of judgment, your adaptability, but then you come down to empathy. You think empathy is something that you want to express even with a customer service agent. If you've got someone really good that can empathize with, you know, with how you're feeling, or if you have a medical consultant, you know, and you're suffering with an illness, you've got that sort of empathy. But that's probably short term safeguards, you know, if you've got those qualities. But what does it mean when you start looking ten years out and you've got robots that are pretty good at actually expressing what seems like empathy, and you feel like they're heard, and they're always available?
Brynley Evans:And then you start looking at fifteen years from now, so 02/1940, so you look at potentially things like governments and companies are being forced to rethink their economies. You may see things like some nations pioneering four day work weeks or job sharing or even things like citizen work credits. That's going to be felt on the the most advanced countries. So The States, maybe United Kingdom, Japan, China, all the sort of very first world are going to probably have to solve these first. And then looking at things like most services are AI enabled.
Brynley Evans:So you've got your personalized education, your virtual doctors, your AI legal aid. And then really, at that stage, your creativity and how you handle relationships or interpersonal skills probably becomes core to what it means to have a job, because it's not doing things. And that's what I found I'm busy reading the psychology of money. And it's just so interesting how they say, if you look at work in the fifties, sixties, more of the sort of times when you were working to output something, you know, that was your job. You worked, let's say, on a manufacturing plant and you built cars, and you were there and you're working your eight hour shift and you were measured by how much you output.
Brynley Evans:And then slowly it shifted more and more an immeasurable one, you know, which are all more difficult to measure in terms of, you know, how much you're processing mentally, you know, things like creative jobs or even management. You start thinking about those and, you know, it's not as quantifiable as what you built, you know, 50 cars this month. It's like, no, no, you helped create this idea or push this business strategy. And I think that's probably what's, you know, it's becoming more and more, well, what it means to have a job then in fifty years is how good are you at being creative or at dealing with people, making things work and connecting people together. So that's pretty interesting.
Makoto Kern:I like what Joe's point about working in groups on a project. I think that's a very important thing where I've seen and I've, you know, we've homeschool our kids, we've thought about, and I've done like project based learning where you see alternative schools, they do that and they push that where you're working on teams and you're trying to realize, you know, who's doing what, who's a good person at being very niche at some certain tasks, very OCD, very organized. You got some that are the thinker, you got the ones that are the leaders. So you kind of see who kind of like comes together and you see the dynamics of the group. And I think that being able to hone in on that and whatever you do and teaching that is so important.
Makoto Kern:Because whenever I put my kids on a task and how they work together, how they fight, how they get along, how they're not, it's just, it's a little dynamic that you see. But the ability also, I mean, obviously now we got, the big thing is AI agents. And I think it's probably along the same, I think it was Sequoia who had this big AI conference or it's a small one within their group, but it was very interesting where they talk about the AI agents where you're gonna have now maybe the one person trillionaire or trillion dollar unicorn. And all he has is, or she has is AI agents running all these different things and tasks. They're able to work together.
Makoto Kern:They almost become their own neural network working together. I don't know how far along that's in the future, but being able to do that and create those things would be interesting to see.
Brynley Evans:It is interesting, though, just how you can see profit margins coming down. So, you know, it becomes things become so much more competitive. Because as you say, if you have one person running a company that is, you know, a lot of AI agents doing the work. Previously, you had to let's say it's a development company. You would have a handful of developers.
Brynley Evans:You'd have a marketing person, you know, a designer. Now they're all just agents. So that industry becomes, you can get a custom built app for a hundredth of the price that you could before. It's going to be interesting to see how that you know, shapes it and also It's like manufacturing.
Joe Kraft:As you mentioned earlier, it's just gonna come down to creativity again. Right? Because, like, anyone can now run a company and have these AI agents that sort of bold out some software But, you know, okay, great. You know, you can build out something that would have taken, you know, a year of development with 20 people. Now you can do it yourself in, a month or a week.
Joe Kraft:Mhmm. But it's still just, you know, is that product have any value? Because there's other 50 other people can do the same now, and so the the drive of that product goes way down. Now, again, it comes back to what you're saying, but around creativity, you can't just sort of the value isn't you being able to create the thing anymore. It's what's special about it.
Joe Kraft:Like, what's unique about it? Why is it solving that nothing else is solved yet? And as you both have sort of mentioned, yeah, it's gonna come back to that sort of human approach of, yeah, being able to sort of be creative and encompass those novel ideas more than just the pure output of of something. Exactly. Way of sort of approaching approaching things.
Joe Kraft:Like, hard work isn't gonna be the driving factor anymore of being successful in in a traditional sort of way.
Brynley Evans:I guess it raises a question, and we could ask, is soft skill skill mastery the new hard skill? And you think you go and you study things or you work on creating hard skills. How do you do this process? What are the skills you need? But, you know, are the soft skills that we need to master things like empathy, communication, leadership?
Brynley Evans:And it's so interesting, coming back to this book, Psychology of Money, it looks at also how you take certain sort of skills or talent. So you think smart people, you have one smart person in the town, this is fifty years ago, and they can do incredibly well because they're the smartest person there. But now, you know, with the internet, things are expanded, so maybe now you start competing about, you know, are you the smartest business owner in your certain state that you're in? And now it's global. Are you the smartest person?
Brynley Evans:It's like, no, there are lots of smart people. They're a dime a dozen because you have access to a global pool of talent, but it's all those other soft skills that make them particularly effective. Are they a good leader? Are they a good team player? And it suddenly becomes there are all these other skills that are being sort of amplified.
Brynley Evans:If we had to say, What should you be focusing on to future proof your job? It's, you know, How good are you at all those other pieces? Not necessarily the hard skills, those soft skills.
Joe Kraft:I guess if you're the sort of person who feels like their job is, you know, I go to work, I just greet one or two people, I sit down in front of my computer, I work all day with headphones on, don't talk to anyone, you know, barely communicate, leave at the end of the day, and job well done.
Makoto Kern:You might be absolutely.
Joe Kraft:Yeah, you may have gotten away with that to this point, but yeah, as you guys say, and I agree, if you're doing that kind of work, that means that work can be automated in some way or could be easily AI driven because it doesn't require any kind of human skills to do it. It's definitely a risk.
Brynley Evans:So I wanted to jump to go ahead, go ahead.
Makoto Kern:No, was gonna say if we wanna jump to another thing is the actual recommended university majors that maybe we can kinda bring up.
Brynley Evans:Well, Libby, I would mind just doing finishing off with the twenty years. We did the, like, ten,
Makoto Kern:fifteen. Yeah.
Brynley Evans:Twenty years is is really interesting and and looking at something like a post work transition. So you look at AI is general enough to do pretty much anything. You know, it performs any, at least, knowledge tasks better, faster, cheaper than, you know, any one human can. What does that mean? I mean, does it mean that something like a new social contract would emerge where, you know, you've got universal basic income and work is going to be optional for many.
Brynley Evans:But people that contribute, it's really about doing something for the sake of doing for its purpose that it offers you, for its meaning and the creativity as well, and those things taking center stage. So, you know, people working with AI to focus on things like climate resilience or philosophy or exploration or even improving care for people and the human experience. It's so interesting to think that in two decades time, we could be looking at a landscape where jobs aren't compulsory to survive anymore, and they're optional to contribute something that you feel is something you were born to contribute. It's going to be really interesting to see that.
Joe Kraft:Yeah. I'm just I'm very it's gonna be very interesting to see how governments react, though. Right? Because when you're talking about universal basic income and and things like that, that means that people are gonna have to be supported inherently to a certain degree by their governments. Right?
Joe Kraft:Very very socialist in a way. And, you know, you know, traditionally, that's always been a lot of controversy around that, but, you know, what's the alternative? Like, a capitalist society just, you know, will it even still be able to function in a world where jobs just the value of them has been driven down so low that kappas can't be held up by, you traditional sort of workforces anymore? I don't know what the answer is.
Brynley Evans:I almost feel like we're gonna see the the pioneers come out of I always think a lot of the European countries, whether it's Switzerland, Sweden, they're often pioneering, especially with education. Wouldn't be surprised if we start seeing some new economies emerge in those countries.
Makoto Kern:My prediction is that they have a reproduction issue. I forgot the exact number, but if you have less than, I think two and a half kids in your country, your population will be diminishing and that's happening almost everywhere. And so are we gonna get to a point where people are just not gonna have kids? We become less social, no more kids, we create androids or little robots that are running around or is it we become a space faring technology and everybody just starts space mining, exploration, things like that because now you can send out robots and AI to do that. And it doesn't matter if it gets hurt, injured or destroyed or whatever.
Makoto Kern:I think that's a whole another industry within like twenty five years that should be something that is emerging. And I think that will be interesting to see where a career is going in that respect. But It's a mixed other topics with that one. But I think jumping to university majors, because that's really what, if anybody's listening, what should they get into? And that's where you're blending some technical proficiency with human centric skills.
Makoto Kern:So some of the ones that obviously are computer science and artificial intelligence, if you wanna be into tech and you wanna get into it, great, get into that. That's the bare bones basic things that you need to get into. You could study how things think and create neural networks and whatnot, and then how to program those things. I think that'd be really cool to get into if you're that aspect of it. Data science analytics, always numbers crunching, seeing where those things are, using that with AI, that's always interesting.
Makoto Kern:Economics, whatever, I think that might be something to If you really have a thing for numbers and how they work, think that's something they really get into. Cybersecurity, that's something where we actually have clients that are in cybersecurity as well. And you just see whether it's the amount of crappy vibe coding or vibe coded applications are out there that probably could be easily hacked. It's probably gonna accelerate. I think that fight in the future is going to be so key.
Makoto Kern:And
Joe Kraft:I don't Yeah. Know attack vectors, right? So, you know, people using AI to penetrate security systems is gonna become bigger too. So it's gonna be a bit of an AI arms race in terms of just security alone.
Makoto Kern:For sure. I don't
Joe Kraft:know if
Makoto Kern:you heard just in the news. I thought I read that Spain, their entire mobile network just went down after having a huge power outage a
Joe Kraft:few Wow. Weeks
Makoto Kern:don't know if that's true. I'm curious if that was a hack, but yeah. The entire mobile network supposedly went down across the country. Wow. There's solar flare, it could be whatever, but yeah, having the ability to protect the infrastructures is key.
Makoto Kern:And so, yeah, the next one is biomedical engineering, combining the engineering principles and medical science. That was really interesting because biomimicry is something that I've been kind of following and I love hearing about that where they're taking things that haven't been evolving for years and years, hundreds or thousands of years with animals. And then combining that with like, I saw one where they took a look at a whale's fin and how it has ridges and adding that to a windmill fan. Do you normally think of it being smooth, but actually when you have ridges, it increased the efficiency and being able to combine They those used an engineer, somebody who's aerodynamic or wind engineer or a plane engineer somebody who's very creative and just thought about like, Hey, I took a look at that and saw like, why are there ridges on a whale's fin? And it was pretty interesting.
Makoto Kern:I said, Oh, if you can do that stuff, that would be really cool.
Joe Kraft:Yeah, definitely.
Makoto Kern:Environmental science and sustainability. We know that there's pollution everywhere, plastics, whatever, you name it. That's always a great cause to see if you can somehow get rid of those things and then really clean up the things that are happening out there. And I think these next ones are really important, especially around like business administration with a focus on technology management. So you're preparing students for leadership roles in tech driven industries.
Makoto Kern:Yeah, knowing how do you manage all these different aspects of it? Is that Jack of all trades type of dock connector? And then education tech, you see teachers now, mean with my kids now, I've always asked my kids like, how is the teachers integrating AI other than saying you can't use it because you're cheating on the test? I actually tell my kids, hey, use it to learn how to prompt it because I feel like that's so important. It's like using a calculator or a spreadsheet or a computer or Google Agreed.
Brynley Evans:Yeah, exactly.
Makoto Kern:And so I encourage that with them. But then
Brynley Evans:as a teacher,
Makoto Kern:oh, go ahead.
Joe Kraft:No, just thinking about that, like, yeah, banning AI material. If you're given a task and you can produce the required output for that task, does it matter how you got it or generated it as long as you still did it if you used AI to do it or went to a library and took out a book or Google searched? I mean, I don't know, just kind of from an education perspective, I always just wonder about that.
Brynley Evans:It's probably changing the criteria that it's assessed on. Instead of saying, Oh, you just generated this straight from AI, it's like, Did you generate it in a way that actually answered the question? Or is there superfluous information in it? Maybe the tone is incorrect. It's almost like, did you manage to correctly generate what was needed?
Brynley Evans:As I the question, it should almost be Because whether you're, again, like you're saying, how did we do it? If we had to answer something, you would look through encyclopedias or textbooks, and then you would summarize that information. And you know, as long as you're doing it in a way that you're not just verbatim adding it, even if you are generating it, you've generated it in a way that is potentially answering the question under that. Ted, something
Joe Kraft:you I guess the assignments I guess the assignments themselves need to, like, go up to the next level too. You can't just ask your students to, like, you know, write me a report on Christopher Christopher Columbus, whatever the case is, right, and get a report on, you know, this year, he did this, and then he went here, and then he went there, and end of report. Like, that's you can generate in two seconds. You're gonna have to start asking them to give you reports that show that they have maybe more understanding. Like, okay.
Joe Kraft:What were the implications of what he did, and what are your thoughts? Do you think it was right or wrong what he did, or, you know, the things that, you know, you know, do you think history should look funny on him more negatively? Like, maybe just trying to, like, get a bit more, like, thinking involved and not just outputting the report.
Brynley Evans:Exactly.
Joe Kraft:So that, you know, generation alone, once you get you there, you kind have have your own opinions about things. I think that's way more important than just content alone going forward.
Makoto Kern:That's such a good point because it's like, well, instead of asking who Christopher Columbus was, say, if you were him and you were back in those days, what route would you take to maximize your costs and whatever, really get it down into those specifics?
Joe Kraft:If you had modern day technology, how could you do it differently? Just get them to think out the box and things like that.
Makoto Kern:That would be really cool actually to do that. And you know, it's interesting again to see the different levels of teaching now that my kids are they all went to school this year and to see the different types of teachers, some who embrace tech, some that just, hey, all they do is teach directly from a book, completely gonna be obsolete. But then you've got teachers that are managing a big classroom and some kids learn at a faster rate than others. And it's like, if you had an AI agent saying, hey, this kid is asking these types of questions to AI, there's something that they're not quite getting. And there's this group of kids that are maybe more visual learners to other ones that are more analytical.
Makoto Kern:So they're able to accelerate this way or they're able to learn through video versus just talking. These are things that if you have something as a teacher trying to manage twenty, thirty, 40 students or more
Joe Kraft:Yeah.
Brynley Evans:But you see that Exactly. But I think what you'll find from good teachers as well is that it's those interpersonal skills coming in. Because if you're teaching multiple groups of students so let's say you take seven or eight lessons a day. You've got a range of different age groups, and you've got a completely different group dynamic, especially in public schools where the bigger class sort of numbers. You've got a completely different dynamic from one class to the next with certain people that will want to trigger the teacher or certain people that want to learn faster.
Brynley Evans:So being able to understand that, I think just coming back to those points of what makes you really good at something is being able to understand those students and then apply, as you're saying, Makoto, the technology to help each of them uniquely, but also to satisfy that unique group dynamic that that class, that combination of kids together presents itself as.
Makoto Kern:It's interesting too, because I do let my kids, again, I tell them to use it. I have them use multiple AIs, and even my son now is able to pattern recognize outputs from certain AI's. He's like, oh, this is, you can tell it's AI generated because the amount of repeat of certain ways in which it says sentences, he's like, oh, that's, you know, Chad GPT. And so they can recognize right away whenever something is AI generated and they immediately dismiss it as being less value, which is kind of funny.
Brynley Evans:Yeah, that is interesting.
Makoto Kern:I think the other final thing is on university majors is psychology and human factors. And human factors, we had this discussion about the AI pin and having this kind of AI friend. This is just like less than a year ago that we had this conversation and how that was weird and gets into the movie Her. I'm sure now, I mean, with the different I mean, Grok has different personality traits and you can start programming these things and the ability to Was it the Turing test to actually pass that at a higher rate. So yes, there's probably areas in which you can talk to it and maybe it'll help out certain people, but I think there's gotta be that combination of an actual person and that human touch and factor, But then you can somehow leverage AI into making quicker diagnosis or somehow visually seeing their body language or something to help you maybe focus on diagnosing somebody with whatever or understanding human behavior while you're having this AI help you with other things that are harder to maybe detect.
Brynley Evans:Yeah, agreed. Yeah, it's gonna be fascinating, though. I think I always say that, but where it's headed, even just preparing for these podcasts and looking through projections, it's fascinating. I mean, we're living through such a revolution, I think, that it's kind of like stay tuned, let's see what's gonna happen.
Makoto Kern:For sure. Cool. I think unless you have anything else to bring up, I think this is probably a good place to end this podcast. Sounds Appreciate everybody's time. Again, like and subscribe.
Makoto Kern:And if you have any ideas on what education or questions on what you should go after or what you're into and how AI can help you, reach out and leave a comment. But thanks again for joining and talk to you next time. Take care.
Brynley Evans:Go well.
Joe Kraft:Cool. Thanks.
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