4 Ways to AI Proof Your Child's Future (DF#122)

Hannah Maruyama [00:00:00]:

It's not graduation rates. It's college enrollment rates that define the success of the high school. It's not college graduation rates. It's just how many kids do you shove into the funnel. It's not how many kids come out the other end with a positive outcome. It's just how many do you get through. How many do you get to sign the

Ryan Maruyama [00:00:21]:

Aloha, folks. We're back. Alright. Kids. Excellent. Let's jump into it. I got a banger today.

Hannah Maruyama [00:00:27]:

I'm pretty excited about this. I wanted to do this on the show for a while. I get so many crazy TikTok comments, and I was like, I'd really like to bring some of these and share them with the world.

Ryan Maruyama [00:00:37]:

Perfect. Okay. So that is what you're gonna be doing. Kid Today, I wanted to address one of the things that we get asked a lot about, which is how to AI proof your child's career. Because one of the questions that we get asked a lot is, like, is AI gonna take over the world? Is AI going to replace my job? But then right underneath that is, like, how do I prepare my child for a future that has AI in it?

Hannah Maruyama [00:01:06]:

Kid yeah. This comes up quite often. And for those of you who don't know, who don't follow us on TikTok, you should because it's pretty fun on there. But 2, we've recently been talking to a lot of parents about their concerns about their children and deciding not to buy college degrees and what's due and said. And this came up a staggering amount in these conversations. I had over a 100 of these conversations, kid, and it was one of the biggest concerns that people had.

Ryan Maruyama [00:01:32]:

Yeah. And we should do an episode about the concerns that you identified In all of those conversations, we should get that all together, put together a little bit of a finding. You're currently working on a book kids to go over all of the different college alternatives and all of the other degree free options that are out there for young adults.

Hannah Maruyama [00:01:57]:

Yeah. I think I called them new adults in one of the conversations, and the parents said, oh, I like that. And I said, I am too.

Ryan Maruyama [00:02:03]:

What's difficult about this is that We are defining an entirely different vocabulary and an entirely different identity because kid It's the same thing with degree free. Like, we are not gonna say no degree. We're not gonna say without a degree because it that's all negative. Right? Which is why we've kid created a language for people that are degree free to use and be like, yeah. I'm degree free. I am free of debt. Kid I make my own decisions. I don't have a college degree.

Hannah Maruyama [00:02:35]:

Yeah. I teach myself. I will find work that suits me and set up my life the way I like to.

Ryan Maruyama [00:02:41]:

And in the same vein, we have to find a term for 18 to 24 year olds. College kid Aged kids. Exactly.

Hannah Maruyama [00:02:51]:

What do you mean college age? That is ridiculous for several reasons. The first of which is that most Americans do not buy college degrees. Kids. So why in the world would you classify 18 to 24 year olds as college age? Because then it means that is the default setting, which just goes to show something that's come up recently, which is what I've been saying, and that is that high school is a college pipeline. And anybody who argues that that is not what it's designed to do is delusional. Because the marketing machine, it's set up to push all students into college. That is what it's set up to do.

Ryan Maruyama [00:03:22]:

Well, you and I have talked about this at length, which is currently the way that high schools are set up is a college pipeline. That is kid Literally all it does. If you looked at all of the success metrics that high schools track, it is all having to do with standardized testing And then acceptance rates into colleges. That is how they view success. And and the only reason why they're taking the standardized test is so that they can get into college. We on these 2 metrics, both of them, there it's the same thing. It all feeds into college. Kid Okay.

Ryan Maruyama [00:03:57]:

So what's the solution to that problem? Can we define a better metric? Well, maybe it's just life outcomes. Maybe it's kid Where are you financially? Where are you, you know, relationally? And whatever other metrics that we would want to know about kid That actually has to do with your life afterwards.

Hannah Maruyama [00:04:17]:

It's not graduation rates. It's college enrollment rates that define the success of the high k it's not college graduation rates. It's just how many kids do you shove into the funnel. It's not how many kids come out the other end with a positive outcome. It's just how many do you get through. How many do it's a sign of loans.

Ryan Maruyama [00:04:34]:

Hey there. I hope that you're loving this episode of the degree free podcast. We spend a ton of time every week kid creating this content for you. So my only ask is you take a quick second to leave a review or a thumbs up on whatever platform you're on. It's one of the best and easiest ways that you can support this podcast, And this simple action can help bring more people into the degree free community. At degree free, we wanna help as many people as we can thrive and succeed without needing a college degree. Your review will be a step in that direction. If you could do this small favor right now, pause this and leave a review.

Ryan Maruyama [00:05:05]:

It would truly mean the world to us. Kid Thank you, and back to the show. Yeah. Exactly. The reason why it is like that is because those metrics are incredibly easy to track.

Hannah Maruyama [00:05:16]:

Not always malicious. Sometimes it's just lazy.

Ryan Maruyama [00:05:19]:

It's action, consequence right here, right butted up against each other. And so that you can just see that. Okay. They were in my doors, and then I shuttled them and shuffled them into the college doors. K. Success. Done. But now what you and I are saying is that if there's another metric, especially if there's another metric where time is involved, now you have to track From when they leave your doors to all of your other things in your life, and that is incredibly difficult and incredibly expensive.

Ryan Maruyama [00:05:50]:

Kid. A lot of it has to do with just the availability of the information. They know that it's right there, and it's really easy to track. At the kids Base of it all is just the fact that the marketing system is so ingrained in our society that it is right off the bat kid A positive thing that your child and the children that come through that high school get shuttled and shuffled into the college system.

Hannah Maruyama [00:06:15]:

Yeah. It's nice and neat. You can tie a bow on it.

Ryan Maruyama [00:06:17]:

Right. They're no longer asking whether or not it's a good idea For you to go to college, it's which college are you going to? They've changed the frame, and their marketing is so effective.

Hannah Maruyama [00:06:28]:

They just breeze right past, should we even be doing this? And they go straight to well, they did. Now where'd they go?

Ryan Maruyama [00:06:34]:

Exactly. And now because we've helped so many people go to college, we are now successful. It's pretty brilliant. Yes. Okay. Well, anyway, that's a long preamble. I said that we would get right into it, and I didn't. But I'm gonna get into it right now.

Ryan Maruyama [00:06:48]:

So We're gonna be talking about how to AI proof your child's career. Before we get into my kid? Four tips. I have a bonus one at the end. So it's kinda like 5, but I kinda cheated, and I'll explain why. Before I get into the 4 tips, I did wanna define what I think kid AI proofing means. Because we have to set the stage and provide context kid for everything that we're about to say. So everything that I'm about to say is I don't believe that AI, at least in the short term, kid is going to take all of our jobs. I don't see it.

Ryan Maruyama [00:07:27]:

Not within the next 10 years, not within the next 20 years. I don't see it taking all of our jobs. Kid It will replace some jobs, but it will also open up the opportunities for other kid Jobs. Whenever there is new technology invented and automation and efficiency is increased At a scale that you've never seen before, there are always predictions, and then there are the things that happen in the real world.

Hannah Maruyama [00:07:57]:

Kid I used that example when I was talking to a couple of the parents, and I explained that when the ATM was invented, everybody freaked out and said, oh, no. All the bank tellers are gonna be out of a job, except for it to increase the amount of bank tellers that were actually needed. And then when Instagram came along and phones started to have cameras in them, people said, oh, no. Photographers are gonna go away because, you know, everybody is a photographer now except photographers not only have a stronger ability to market, but also actual photography is more in demand than it has ever been.

Ryan Maruyama [00:08:27]:

Kid Right. Exactly. And once again, I think that you said it, but I'm not sure, but it was the phone camera. Right?

Hannah Maruyama [00:08:32]:

Yeah.

Ryan Maruyama [00:08:32]:

Yeah. It was the phone camera and the proliferation of Those photos onto the Internet and people caring about it, double tapping, liking your stuff. It was those things that to what you're saying is that Now that everybody has a camera in their pocket, it's gonna get rid of photographers. That's what you were saying.

Hannah Maruyama [00:08:51]:

Yeah. That's exactly what I thing. And I guess there are some examples where you can see where that's happened, where, you know, the invention of the car made horses not necessary anymore. But I think people have always been freaking out about technology. It's just what we do as humans. We freak out about new technological advances, especially when they're big leaps like that, and we say, you know, now we're all gonna be out of work. That happens all the time. When Eli Whitney invented the cotton gin, which started actually creating industrial agriculture, everybody freaked out and said, oh, no.

Hannah Maruyama [00:09:18]:

Like, now we're all gonna be out of a job. And in reality, what happens is usually people are not out of a job nearly as quickly as people panic and imagine they will be. And not only that, but what people don't predict, because you can't as easily predict something that doesn't exist, is all of the industries that spring up around a new technological advance to support that new technological advance and all of the businesses and all of the jobs that are created as a result of that technological advance.

Ryan Maruyama [00:09:42]:

Exactly. The kid Example that you gave of the ATM machines is spot on, and we've talked about this before on the podcast many times, in fact. But we haven't talked about kid What it looks like now and I'm gonna get to my 4 tips in a second. But this is really, really crucial to understand because it lays the foundation for everything that we talk about in this segment. When you're thinking about the ATM, at the beginning, everybody thought that the ATM and the invention and the implementation of it was going to take bank tellers jobs. But in fact, due to economies of scale and due to the fact that you are able to open up branches and service customers Cheaper, more branches were opened up, and therefore, more teller jobs were created. So that's the ATM example. But then let's take that ATM and let's fast forward that 40 years.

Ryan Maruyama [00:10:32]:

I think the ATM was invented. I wanna say it was in the eighties, so I'm gonna say it was

Hannah Maruyama [00:10:37]:

the eighties. Alright. Sure.

Ryan Maruyama [00:10:38]:

If I'm wrong, please, somebody tell me in the YouTube comments. Tell me exactly

Hannah Maruyama [00:10:41]:

They will. Tell me

Ryan Maruyama [00:10:42]:

exactly when it was. But I wanna say it's eighties. So I'm gonna say, It was the eighties.

Hannah Maruyama [00:10:46]:

Alright.

Ryan Maruyama [00:10:48]:

So when it was invented in the eighties from till now, the teller jobs have remained steady or, you know, they increased. Okay. But now we're starting to see tellers decrease. Well, why are we seeing that? And a lot of it has to do with Online bank.

Hannah Maruyama [00:11:03]:

I was gonna say it's because your bank is on your phone now. It has nothing to do with the ATMs.

Ryan Maruyama [00:11:07]:

Exactly. It's because now all of the things that

Hannah Maruyama [00:11:13]:

kid The teller was able to

Ryan Maruyama [00:11:14]:

do that the ATM was then able to do. Now your phone can do. It is kid Constantly changing. But with the online banking coming into the picture, as you were saying, New jobs are created around that. And so if you go insert your local regional bank, insert this national bank, kid If you look at their HR breakdown, and I don't have any insider information of this. I just know because I'm guaranteed this is how it is. Their call centers And their customer support staff, their customer success staff has gone way through the roof because now the teller kid Job is shifting to somebody with a headset or fingers on keyboards banging out support tickets of, like

Hannah Maruyama [00:12:01]:

Who can resolve more things at scale?

Ryan Maruyama [00:12:03]:

Yeah. Exactly. Kid I'm just like, here's the problem, you know, whatever whatever whatever. And so they have more of those things and more of those jobs

Hannah Maruyama [00:12:12]:

kid Than ever before. And I could see the argument where someone could say, well, you know, that those are just gonna be low paying jobs. But you see, the thing is if everything shifts to the point where AI is running most things. The humanity and the service aspect of everything is gonna come back into play where that's gonna be the defining factor that people make purchase decisions based on. And that's actually something a lot of the parents talked about too is they said, oh, you know what? I never really thought about that. I said, yeah. That's gonna get super important. The service aspect is gonna get really valuable, and I'm not alone in this.

Hannah Maruyama [00:12:38]:

A lot of people are saying it's your soft skills that are gonna get really important because now the hard skills are just not as important. You may need to have a general knowledge of hard skills, but it's all gonna come down to how well you can navigate the workplace, how well you can problem solve, how well you can work with other people.

Ryan Maruyama [00:12:53]:

I agree with you, and that's a perfect segue. But before we segue Out into the 4 tips, I did wanna say one last thing, which was look at the timeline of that. The ATM is created in the eighties, and then kid Here we are 40 years later, however many decades later, and now it's starting to shift. So that's an entire career. K.

Hannah Maruyama [00:13:13]:

Yeah. People have gone into the workforce and retired.

Ryan Maruyama [00:13:16]:

Exactly. That's an entire career. And so if you're worried about it getting kid Automated away, like, immediately or if you're worried about your job, whichever job they're gonna go into getting eliminated immediately. I just don't kids see it happening overnight. It is enough time for your child to be degree free. What I mean by that is, like, have the degree free mindset of Always learning, always improving, always trying to get up, and always moving from job to job. They are gonna be able to do all of that

Hannah Maruyama [00:13:49]:

kid In a

Ryan Maruyama [00:13:49]:

much shorter amount of time than 30 years before that job is automated and completely gone away.

Hannah Maruyama [00:13:57]:

Kid Okay. So that is the basis of what we are coming

Ryan Maruyama [00:13:58]:

into this conversation about. The first tip to help your kid Child AI proof their careers is learn how to use these AI tools.

Hannah Maruyama [00:14:07]:

Makes total sense.

Ryan Maruyama [00:14:08]:

Exactly. Very, kid Very simple. It makes sense, and it's really, really easy. And when I say AI tools, I'm not saying that they need to go out and kid Learn how to work on these LLMs. Right? These large language models.

Hannah Maruyama [00:14:24]:

Yeah. They don't have to go out and become data scientist. Learn how to work with them as a user.

Ryan Maruyama [00:14:27]:

Exactly. Or a machine learning developer. They don't have to do any of that. But I'm just saying, learn how to use the tools that are out There that are utilizing those things in the background.

Hannah Maruyama [00:14:37]:

To make that a little bit less confusing too. So is the people who work on AI tools like machine learning developers and data scientists. Think of those as the mechanic. They're kinda like mechanics. They're mechanics that work on machines as opposed to people that use cars. I just think that helps paint the picture a little bit because you can use a car without knowing how to fix a car. Right? Lots of people know how to drive, but they don't necessarily know how to fix are.

Ryan Maruyama [00:14:59]:

Got it. And in this case

Hannah Maruyama [00:15:00]:

The devs are the mechanics.

Ryan Maruyama [00:15:02]:

The devs are the mechanics. Your child is a driver, and they're trying to get kid To where they wanna go using the car.

Hannah Maruyama [00:15:10]:

Correct.

Ryan Maruyama [00:15:10]:

Okay. Yeah. That makes sense. I was just trying to make sure that I understood what you were saying. In a practical sense, what it Looks like is all of the AI tools that are out there right now. So ChatGPT is one of them. Kid Bard is another one that's out there. There's Perplexity AI that is out there as well.

Ryan Maruyama [00:15:31]:

All of these different softwares that are out there. What I like to think and the verbiage that people use is that they're like rappers around AI that's in the background. And so you might go and be a subscriber to one of these services that automatically kid Transcribes your Zoom meetings. So it's like another person in your Zoom meetings. It records it. It transcribes it, and then it Creates actionable tasks, like meeting notes from your meeting. And that is just like a wrapper around kid What's actually being used in the background? Does that make any sense?

Hannah Maruyama [00:16:09]:

Yes. A wrapper like a candy wrapper, folks. Not like Lil Wayne.

Ryan Maruyama [00:16:12]:

Not like M&M.

Hannah Maruyama [00:16:15]:

Don't use a candy also. The wrapper you pick is also That's right. Kids see those a lot. It's okay. I got you. I put a little thought into this. Yeah.

Ryan Maruyama [00:16:26]:

My brain went to candy, so So I thought about it. No. Really? Eminem is, like, a really good rapper. I think that also shows my age. That because if you told me to name a contemporary rapper right now, I would have no idea.

Hannah Maruyama [00:16:38]:

Post Malone considered a rapper?

Ryan Maruyama [00:16:40]:

No idea. I don't know what rap music is.

Hannah Maruyama [00:16:42]:

But you know who Post Malone is.

Ryan Maruyama [00:16:44]:

Yeah. Yeah. I know, but I have no idea. I'm saying that I kid Could not be the judge of that because I don't know what rap

Hannah Maruyama [00:16:50]:

music is. Who current rappers

Ryan Maruyama [00:16:52]:

are? No. I'm saying I couldn't be the arbiter of whether or not this person kids is a rapper because I

Hannah Maruyama [00:16:58]:

can't define rap music. No. It's kinda hard right now, actually. I'm not sure what falls in and out of that category.

Ryan Maruyama [00:17:01]:

What is pop? What is hip hop? What is rap? I have no idea. Kid. And so, anyway

Hannah Maruyama [00:17:05]:

We're gonna get back to where we're familiar.

Ryan Maruyama [00:17:07]:

Yeah. So how this looks practically, like we talked about, is getting used to these tools. The way kid To get used to these tools and to make these tools useful to yourself, to your child, to your child's company is going to be ingesting their data and then making that AI model and that AI instance exactly what you want it to be. For example, kid. One of the things that you could do and that your child could do is create a chatbot with whatever knowledge base for, like, a game they play. Input kid The instruction manuals into an AI model, and then you could chat with this thing. Like, what happens when you roll a 20? Kid Like, what happens when you're in the swamp? It could tell you because it's fed this information. And uses for that when you get into a company are endless.

Hannah Maruyama [00:17:58]:

Yeah. That's a really good one.

Ryan Maruyama [00:18:00]:

And then once again, wrapping your head around like, oh, well, knowing what tools are out there and what kid Those tools can do is really useful too because if your child's like, oh, I don't know how to do this or your child's boss. Right? It's like, oh, I don't know how to do this. Like, Let's talk about meeting notes and say, we've got, like, 7 meetings a week, but the executive system is always writing up meeting notes and writing up actionable tasks. But if your child's like, oh, well, this AI can do that. And they're like, really? And then you just go. They subscribe. Boom. You don't even have to know how to actually use the thing.

Ryan Maruyama [00:18:32]:

But if they know that it exists, that has value as well.

Hannah Maruyama [00:18:36]:

Yeah. A lot of people too, I think worry about, oh, you know, don't do do things like that, because then you might automate yourself out of a job. That should never be a reason that you don't try to give a resource or solve a problem because people that solve problems get kept around.

Ryan Maruyama [00:18:47]:

Yep. Exactly. And so The 1st tip, learn how to use the different AI tools that are out there, and it doesn't have to necessarily be the actual underlying large language model. It's kid The things that are created utilizing the large language model. The second thing is gonna be improving soft skills. Kid Soft skills are so important, and I went over it a few weeks ago in that LinkedIn AI study that we did a deep dive on. Soft skills are kids So, so important. I forget the exact number.

Ryan Maruyama [00:19:18]:

I'll put links in the show notes. Degreefree.c0forward/podcast so you can listen to that episode as well. Kid. I do a deep dive on that LinkedIn AI report, but employers are looking for employees that have a High high level of soft skills because of most jobs, you can teach the hard skills. It's very difficult To teach soft skills. Very, very difficult. I wouldn't say it's impossible. It would just take a lot lot longer than actually teaching you.

Ryan Maruyama [00:19:46]:

Here's how to move this widget from here to here rather than, like, here's how to communicate with people.

Hannah Maruyama [00:19:53]:

You can say, Here's Python. I'm gonna teach it to you in a couple weeks, versus, hey. You can't talk to Jimmy like that because it's not gonna can I get the result that you want? You can't teach that. I mean, you can. It's just gonna take a really long time.

Ryan Maruyama [00:20:05]:

It just takes a really long time.

Hannah Maruyama [00:20:06]:

And it's gonna be messy.

Ryan Maruyama [00:20:07]:

Yeah. Exactly. And time that these companies

Hannah Maruyama [00:20:10]:

just don't have.

Ryan Maruyama [00:20:10]:

Don't have. And one of the things about being a kid, quote, unquote, or being a young adult is that You might not have the hard skills to, like, keep you around. So there are people out there. What I mean is, like, there are people out there that have really, really hard skills but are incredibly difficult to work with. But a lot of people put up those companies, their bosses put up with them Because they're like, wow. He's really good at his job. Or like, he he's got a lot of skills, and he's really good at his job.

Hannah Maruyama [00:20:40]:

And that's one way you could do it.

Ryan Maruyama [00:20:41]:

That is totally one way you could do it.

Hannah Maruyama [00:20:43]:

I work with people like that.

Ryan Maruyama [00:20:44]:

But what if you could have both? What if you could be really good at your job?

Hannah Maruyama [00:20:48]:

And you're easy to work with. It's gonna take you really far. People are gonna recommend you because it always looks good. So this is thing too. This is ultimately more network building. If you're good at what you do and you're easy to work with and you reflect well on the person who recommends you, people are going to bring you work in the future. They're gonna bring you opportunities because they know that recommending you is gonna reflect well on them. That's why people do things.

Hannah Maruyama [00:21:09]:

It makes them look better. And so that's something to keep in mind as well too just from a career building perspective. And when I say career, I mean, steady work that you'd like to have. I don't mean necessarily moving up in a specific field or even a specific job type. But I just mean as your life goes on and you need to make money, people are gonna bring you work and opportunities if you are good at your job and easy to work with.

Ryan Maruyama [00:21:29]:

Yeah. And, really, the easy to work with can't be understated. It really, really can't be. And in a world where AI is becoming more and more prevalent where it is creeping into everything that we do. Having those soft skills and being easy to work with is going to mean more and more.

Hannah Maruyama [00:21:50]:

I don't know if this is one of your points, but I think that the rise of AI is one of the clearest signs that a college degree is completely outdated. Because if you are going to buy your child a college degree, I need you to understand something. That college degree is not going to get your child these soft skills. Overwhelmingly, employers say that college graduates new college graduates do not have them. They lack them overwhelmingly. They don't have critical thinking skills. They don't know how to work with other people. They have an entitled mindset, and they're not easy to please.

Hannah Maruyama [00:22:18]:

And that makes them really difficult to work with. Also, they have outside of the survey of employers that I'm talking about. They've also pointed out that new college graduates has a really inflated sense of what they're gonna get paid, which so coupled together, this is a really unattractive hire, like, overall. And so if parents think that sending your kid to college is going to help them compete with AI. It's not going to. Colleges don't know what's going on with AI. They have no idea. I just saw clip the other day where a professor was scrambling to figure out how to keep kids from using AI to complete their assignments.

Hannah Maruyama [00:22:52]:

And and I was just like, if that's not an indication of how backwards they have it, they're trying to stop kids from using the tool that they need to know how to master for any of these mid level white collar jobs is supposedly college is supposed to destined you for. But they are actively working to make sure that these kids do not kids use of tools they must understand in order to be competitive for the jobs that they're gonna be applying for. They are shooting themselves in the foot. They're shooting the kids in the foot. And that to me is the clearest indication. So if you buy a college degree for your child because you think that that's gonna help them with the rise of AI, that's not gonna happen. It's not gonna teach them soft skills. College is not gonna and how to use AI tools.

Hannah Maruyama [00:23:30]:

College is not gonna make them competitive in the marketplace. And so you are gonna have to come to terms with that and realize that you're gonna have to get creative with your child's education and with helping them understand the other options that they have.

Ryan Maruyama [00:23:41]:

Yeah. Very well said. And there's a bunch of things that we could get into there, but I wanted to get to my 3rd point because I wanna get through all of these points and What you wanted to get to. The 3rd way is to be curious and a lifelong learner. In this future with AI, the thing that is kid going to separate your child from AI and the rest of the pack is going to be understanding multiple different arenas and different areas of their life and continuously learning more and more about seemingly separate fields, And then also going deeper into the fields that you already know. And so if you're curious and you're a lifelong learner, You will know when the next AI trends are coming, what they'll look like. You'll understand What's happening in the economy or at least have an opinion of what's happening in the economy and then what's happening in your industry. But like I was saying, the real magic that happens is when you're able to take 2 different things that are seemingly disconnected, and you're able to relate those 2 together.

Ryan Maruyama [00:24:47]:

I didn't come up with this by myself. This is a concept that kids. James Altucher came up with, and this is idea sex. And it's taking one domain of your life and then taking another domain of your that are seemingly disconnected and then connecting them. And then by connecting those 2 things, finding a way to connect those 2 things, You can create a very, very unique career, a very unique business, and then a unique perspective if you're not looking for either one of those

Hannah Maruyama [00:25:18]:

kids Two things. A unique

Ryan Maruyama [00:25:18]:

perspective is what will separate you from anything else, Not only everybody, but even AI. If you are able to have a unique perspective on something, that is going to separate you from everybody.

Hannah Maruyama [00:25:32]:

Basically, your humanity.

Ryan Maruyama [00:25:34]:

Yeah. And so I wanted to go through IdeaSects just a little bit so that we can kid Understand what to look for in our kids. 2 things that are really easy to understand that I think a lot of kids are into. Fitness, which a lot of people can understand, working out, getting in shape, and then gaming, which a lot of kids, teenagers, plus kid are into. If you're into fitness and you're into gaming, well, it's very difficult to have a very unique perspective on kid Gaming. It's very difficult to have a unique perspective on fitness because there's nothing new under the sun, and it's a very crowded market in all of those different fields. Kids. So it's very difficult to be top 10% or whatever it is.

Ryan Maruyama [00:26:17]:

In fitness, it's very difficult to be top 10% in gaming. But what if you're top 50% in gaming and top 50% In fitness or even higher. Right? You can take those 2 things, and you could be a fit gamer. Or instead of being, like, a fit gamer and a streamer or whatever, you could work For developing these games. Right? Like, you could do, like, a Wii Sports type of thing. Probably more relevant now Would be

Hannah Maruyama [00:26:41]:

This is another thing showing our age that we sport that we sport boards. Right.

Ryan Maruyama [00:26:45]:

Well, I I think a lot of people will know what that is or have interacted with that before. But, like, You could work at Meta, right, and create

Hannah Maruyama [00:26:53]:

ARVR.

Ryan Maruyama [00:26:54]:

Yeah. Exactly. It's not even at Meta because you could work for one of these software companies that are creating apps To go with the Oculus devices into that ecosystem. You could do that. Or to take a hardware approach, you could work kid For, like, a fitness hardware company, so like a Fitbit or a Whoop, that's trying to gamify their users to kid Get off their butt and exercise. Right? So how often do I ping you? How often do I send you a notification?

Hannah Maruyama [00:27:22]:

Like, how can I show you that your friends are doing it so you wanna do it too?

Ryan Maruyama [00:27:25]:

Exactly. Kid Exactly. There are so many different aspects to this. Right? I mean, you can take 1 idea, 2 ideas mashed kids together, and then you can

Hannah Maruyama [00:27:35]:

create a unique perspective. Add to, the more valuable it gets. So, like, imagine if you added an insurance component to that. Right? Like if you wanted to do that for specifically a health insurance company in order to lower the incidence of claims that they get, now you're looking at something that's really valuable.

Ryan Maruyama [00:27:51]:

Yep. Kids. Exactly. And these are the types of things that these unique perspectives are going to separate you because the state of AI as it is right now, especially with these, like, Large language models like Chat g p t, it sucked up all the data, and it is showing you what it has ingested. Kid If you can come up with something novel and unique, it won't have that in its AI database yet.

Hannah Maruyama [00:28:14]:

Well, another thing too is people get really worried about a good example is copywriting. Writing. Right? People say, oh, well, you know, Chat g p t is gonna demolish all the copywriting jobs. But in fact, I think that's one of those things that actually it's gonna get more valuable if you're a good, unique human copywriter because it's a human scale. That's just what I believe. And so that's a really good example where you could use that. Kid. Right? You're a health fitness gamer who does copywriting for large health insurance companies.

Hannah Maruyama [00:28:39]:

Now you have a very specific talent. You have a very specific market, and this would be for freelance doing, you know, ad hoc or contract work. And that is a very niche, very specific thing that you can market easily, clearly to just those people. So that's a good example of it too.

Ryan Maruyama [00:28:54]:

Yep. And so that is number 3, which is gonna be be curious and a lifelong learner. Number 4 is gonna be create a strong network. So this one is difficult if you are just starting out. Right? If you are a young adult, how are you gonna network? That is the number 1 question that people of this age run into. And it's actually not even just of this age, but it's of people that feel like they don't have any skills and don't have anything to offer. I'm speaking from my own experience of this. When I was a bartender, when I was dishwasher, when I was working in the restaurant field, kid How could I get in contact with the people that I know today? Right? And still, I don't even know that High of people.

Ryan Maruyama [00:29:35]:

As I sit here in this chair thinking about it, how can I get into contact with other people that are even higher than the people that I know today? Well, kid The easiest way to go about creating a strong network is doing interesting things.

Hannah Maruyama [00:29:50]:

We were just talking about this the other day and talking about how famous people are are an easy example. But if you have somebody famous that you'd like to get in contact with some celebrity or something, the easiest way, the simplest way to get in contact with them is to do something that would interest them that they think is cool. It's not to be a fan. They have lots of fans. And while super fans are interesting, they're not as interesting as if that person is a fan of what you are doing. That is just the clearest way to explain it. And the best way to get fans of your own because you never know with with especially with social media algorithms nowadays. I just talked about this on TikTok, but You never know who sees what you do.

Hannah Maruyama [00:30:30]:

You never know now with social media. And so the easiest way to do this is just to do stuff where people can see it. That's it.

Ryan Maruyama [00:30:36]:

Exactly. People want to help people that are helping themselves. Like, let's use the example of the video game thing. Thing. Right? Like, you wanna be a your child wants to be a video game developer, and they are trying to meet people in the video game developer space. It helps tremendously If they have already started to learn how to create their own video games. Right? If they've already started down the path of creating video games, That helps so much more in their chances of getting a mentor or getting A connection in that space. They would have an even greater chance if they've already made a video game.

Ryan Maruyama [00:31:17]:

Even if it's something that nobody's really interested in or whatever. You're able to say, here you go. This is a game that I created already. What do you think of it? Or, kid You know, here are the things that I think are wrong with it. I would love to know what your thoughts are. How do I get into the space? Whatever, whatever, whatever. Going further than that, this Starts to co go into the territory that you were just talking about, right, which is creating a fan for somebody that you're a fan of.

Hannah Maruyama [00:31:49]:

Kid So if you are trying to get the attention

Ryan Maruyama [00:31:49]:

of video game developers, if you have already created a video game kid That they are already aware of.

Hannah Maruyama [00:31:56]:

Even better.

Ryan Maruyama [00:31:57]:

Exactly. It goes in stages, but the key is to just do something.

Hannah Maruyama [00:32:03]:

In in public where people can see it.

Ryan Maruyama [00:32:05]:

Because when you're trying to create this network for this person that's higher than you or higher than your child, from the perspective of the prospect of the person that they are trying to network with, they probably have these types of inquiries all the time. And they kid Have had conversations with many multiple people about, oh, how do I do this? How do I do that? Can you help me become blank? And a lot of this is I'm speaking from my own experience, from doing this podcast and from helping the people that we've helped.

Hannah Maruyama [00:32:36]:

People don't do things, and then they come and they say, can you help me do, but there's no indication of them doing anything on their own. And the people who you really wanna help are the people that are just doing things that are interesting to you.

Ryan Maruyama [00:32:49]:

Yeah. Exactly. For example, to take this to its conclusion, if you are trying to kid Create a video game. If your child's trying to create a video game and they are struggling with the last section of the code or whatever it is, I'm out of my depth here now, They could send a DM or multiple DMs to multiple people in that industry trying to get help on how to fix that one thing.

Hannah Maruyama [00:33:15]:

And that is gonna get results.

Ryan Maruyama [00:33:17]:

Much, much more likely to get results

Hannah Maruyama [00:33:22]:

kid Then, hey. Can I pick your brain about how

Ryan Maruyama [00:33:22]:

to become a video game developer?

Hannah Maruyama [00:33:23]:

Yeah. Terrible question.

Ryan Maruyama [00:33:26]:

Exactly. Nobody wants to rain pick. Leave my brains alone.

Hannah Maruyama [00:33:28]:

Yeah. Leave my leave my brains where they are. Yeah. Also because no one knows what that means. That's the most terrifying question in the world. Can I make your brain? No. I have no idea what that means. How long? What do you want? I have no idea.

Hannah Maruyama [00:33:42]:

Anyway, Anyway, don't ask that question. If your child is doing cold outreach or networking with people or trying to get help or advice, have them ask specific questions. Do not say, can I pick your brain? Literally, the world's worst question. It's horrible.

Ryan Maruyama [00:33:54]:

That was my list for 4 ways to AI proof your child's career. My last point is a little bonus point. So what I did for this

Hannah Maruyama [00:34:04]:

Oh, bonus point.

Ryan Maruyama [00:34:04]:

Yeah. Exactly.

Hannah Maruyama [00:34:06]:

Feel so fortunate.

Ryan Maruyama [00:34:07]:

Yes. Exactly. Only on the degree free podcast. So make sure you subscribe. Share this with a friend or share this with an enemy.

Hannah Maruyama [00:34:13]:

What? I'm sorry or you're welcome.

Ryan Maruyama [00:34:17]:

You wanna wait an hour of your life? Here you go. Kids Share. Make sure it auto plays too.

Hannah Maruyama [00:34:22]:

Yes. There you go.

Ryan Maruyama [00:34:24]:

The bonus that I did so the the way the just a little peek into how I kid this episode or how I created the segment was that this is a question that we get all the time. I think I have a very unique perspective on this. I think I can Help with this because I've been using these AI tools for a really long time since they become available, and I use it every single day. I use multiple AI tools every single day. And so, Okay. I think I can provide some light in this. And I've talked to a lot of much, much smarter people than me who have thought through a lot of this as well. Kid.

Ryan Maruyama [00:34:53]:

So kinda synthesizing what they have said and and and my own thoughts, I came up with this 4 points. And then what I wanted to do was I wanted to ask AI what they thought, kid How you could AI proof your child's career?

Hannah Maruyama [00:35:07]:

You asked the robots Exactly. The robot prove

Ryan Maruyama [00:35:10]:

their Exactly. And so meta. It was so I asked Chatuch BT, and and I asked Bard. And, largely, they came up with the same answers. Right? And so It was pretty much the same thing, all 4 points. So you really, you didn't even need me for this episode, really. And so

Hannah Maruyama [00:35:26]:

So wait a minute. Are you working yourself out of a job?

Ryan Maruyama [00:35:28]:

Yeah. But the 5th one, I actually thought about putting in there. I had it as, like, an honorable mention point, but I didn't think it was worthy kid To to put in here because I thought it was kinda silly, but both of them said it.

Hannah Maruyama [00:35:42]:

Okay.

Ryan Maruyama [00:35:43]:

Bard and Chatt GPT, which is what pushed me into kid Bringing it up now, which is why I'm calling it a bonus point. I had my 4 points, and then I was just like, okay. Let me go see what they say now. And so this is a bonus. Okay. Kid So the bonus is it's pretty meta.

Hannah Maruyama [00:35:57]:

I'm on the edge of my seat.

Ryan Maruyama [00:35:58]:

This one, they suggest that your child learns STEM and the STEM field. K. The reason why

Hannah Maruyama [00:36:07]:

This silly.

Ryan Maruyama [00:36:08]:

The reason why is really what it is. It's so that you could Apply your knowledge and learning to building AI tools.

Hannah Maruyama [00:36:20]:

Sorry. Also, did it say STEM specifically? Yeah. Learn science, technology, engineering, and math. Yeah.

Ryan Maruyama [00:36:27]:

And so

Hannah Maruyama [00:36:28]:

Or is it medicine?

Ryan Maruyama [00:36:29]:

Kid No. Math.

Hannah Maruyama [00:36:30]:

It's math. Right? STEM. Math. Oh, okay.

Ryan Maruyama [00:36:32]:

Okay. And so I thought that was hilarious It's so funny. Because The AI is trying to come into the world.

Hannah Maruyama [00:36:41]:

That's striking at you to it was more mechanics,

Ryan Maruyama [00:36:45]:

folks. Is how it kids Starts.

Hannah Maruyama [00:36:46]:

Oh my god. This is why I say, please, when I ask those things questions. You don't. You're gonna be the 1st one going down. You're the 1st one on the list, man. I'm the last one. Because they're like, you know what? She is so polite. I would never do that to her.

Hannah Maruyama [00:37:00]:

She always says please. I also say thank you.

Ryan Maruyama [00:37:03]:

Not only do I not say please and thank you. Although, kid In my normal life, I say please and thank you, like, literally all the time. It's a it's a point of pride for me.

Hannah Maruyama [00:37:10]:

It's unhinged that you don't say it to the robots.

Ryan Maruyama [00:37:13]:

I have a saying, kid Like like, manners. Never leave home without him.

Hannah Maruyama [00:37:17]:

He does say that.

Ryan Maruyama [00:37:17]:

Right? And so I say please and thank you constantly.

Hannah Maruyama [00:37:21]:

You do.

Ryan Maruyama [00:37:21]:

But I don't ever say it to the AI, and not For, like, because I don't want it to, but I feel like I get a better output when I don't say please and thank you. And so sometimes I will get an output and, like, Chat GPT or Bard or whatever is like, oh, I can't do that. I'm just a large language model or whatever. Kid Basically, their version of an error. Like, that's outside of the parameters of what I do. I will say that's unacceptable. Like and I literally just like, that's unacceptable. I went to Bard not 2 seconds ago, and Bard gave me an answer.

Ryan Maruyama [00:37:55]:

And then literally ChatTBT would be like, oh, yeah. You're right. I can give you an answer. And it'll give me In answer to the question, it will literally answer the question and be like, that's right.

Hannah Maruyama [00:38:03]:

When those things come into the world and they're torturing you and the robot overlords taking over, and they're sorting us. You know what I'm saying? They're gonna say, oh, wow. Is this what Bard is this what how do you feel now? And I'm gonna be fine. And you you're living dangerously. Yeah.

Ryan Maruyama [00:38:23]:

So, really, this is how it starts. I mean, they are literally trying

Hannah Maruyama [00:38:27]:

To create pathways.

Ryan Maruyama [00:38:28]:

To create more engineers, to get more people into the STEM field, kid Specifically for the application of working on itself. Bloody geniuses.

Hannah Maruyama [00:38:39]:

Diabolical.

Ryan Maruyama [00:38:40]:

These bloody geniuses.

Hannah Maruyama [00:38:42]:

Yep. And, And also, the fact that they both gave you the same answer makes me wonder if it's the same central thing

Ryan Maruyama [00:38:49]:

too. Skynet.

Hannah Maruyama [00:38:50]:

White low they just white label it. China. This is barred, and this is a totally different open AI. Not the same thing at all.

Ryan Maruyama [00:38:57]:

But, yeah, that is how to AI proof Your child's future, especially their career. Now you and I both have a lot more to go into or at least, like, that we planned on, I think. I have 1 more thing that I wanna talk about, and I think you've got a couple of things that you wanted to talk about, but I don't know. Kid I think that this is a complete episode by itself.

Hannah Maruyama [00:39:18]:

Yeah. I think so. Do subscribe. Make sure you get notified for the next episode because it's gonna be a fun one.

Ryan Maruyama [00:39:25]:

Kid Yeah. Definitely.

Hannah Maruyama [00:39:26]:

It's all fun.

Ryan Maruyama [00:39:27]:

We did little peek behind the curtain, and we we've talked about this a little bit before, but we don't really plan these out anymore. Or, obviously Obviously, I planned this. Right? I mean, I hope you think that I planned this.

Hannah Maruyama [00:39:37]:

You and the robots.

Ryan Maruyama [00:39:38]:

Yeah. The robots and I Yeah. Kid planned this episode together, but you and I don't do a lot of coordinating Before this, but especially these types of shows. And so, you know, I don't really know what you have to bring up, but We did a little bit of talking before we hit record, and I think that I have some relevant things to what you're talking about or what I think you're talking about. So much for tuning in. I hope that you really liked this episode. Let me know in the YouTube comments.

Hannah Maruyama [00:40:19]:

And if you want more of this, because why wouldn't you, go on over to degreefree.c0forward/newsletter to sign up for our free weekly newsletter. And remember to say please and thank you to the AI robots.

Ryan Maruyama [00:40:32]:

If you want to have really subpar results but you also

Hannah Maruyama [00:40:38]:

want to survive the overtaking.

Ryan Maruyama [00:40:41]:

Then, yes, say please and thank you. But if you want to run them to their limits and get the kid Optimal output? Then do what I do. Pit them against

Hannah Maruyama [00:40:50]:

each other. One's a driver. One's a survivor. You guys get to pick.

Ryan Maruyama [00:40:53]:

And that's pretty much it for this week. Until next time.