Episode #13: AI Surveillance

• That won't be going on the podcast.
• It absolutely will, especially if I'm editing it today since Trey is down. (laughing)
• Yeah, you're right, as long as we don't cuss in the first 10 minutes. (upbeat music) Welcome back to the Big Cheese AI Podcast. Today I'm your host, my name is Sean Heiss. I'm here with Brandon and Jacob. Why don't you guys say hi?
• Hello.
• Hey there.
• Today we are without our nearest and dearest buddy, Andre. He's out sick today. So we're gonna try to do our best. Apologize for any production issues as--
• That would all be Sean.
• I'm gonna be the producer today, which is terrible news for this podcast. So no, today's episode, we're gonna talk about surveillance in AI, especially as it pertains to the business world. Interesting topic and it all stems from some really recent things that we're seeing in the news around privacy, surveillance, and some of these tools that are maturing and they are making it, I would say different to be an employee in the workforce in some industries. I guess just right off the bat guys, give me your quick take on just some of the things that you saw in your research that stood out. I mean, for me, the biggest thing was some of the things we're seeing in the healthcare space. But I just wanna get a, let's get a little high level over you guys.
• So from a high level standpoint, one thing and it is funny enough, it's actually very timely. So let's just be honest, we're re-recording the podcast. This is our second time of doing this one because Sean's mic was jacked the first one. So this is us doing it again. But during this weekend, so usually we record these on Thursdays and then they come out on Mondays, but we're recording this today as a Monday. So this weekend, I actually spent a good amount of time with this idea of basically being able to take someone's profile and to be able to build a dossier, if you will, or a personality assessment of that individual. So you could go to someone on their Reddit profile and basically click a button and extract all of this information about you. And so that's kind of, I think the crux of where we're at is that you have these large language models now that can just take any comments that a user might've had and to be able to deduce where they're located, what their age range is, based just on the words that they use, right?
• Well, he's like, oh, he said mid. So most likely he's probably under 30 or whatever it is.
• Or he's like me and trying to act young and cool.
• Trying to be cool, right? So it is, there's this now, this new world where we didn't have it before where we could just take all of your public information and actually surveillance you from there as well. And we built it this weekend and it's kind of working. And you can do it with LinkedIn, you can do it with, I mean, all of it. So yeah, we're in a very weird spot now where before computers weren't able to really be able to extract what you're trying, extract this level of information or ideas around an individual just based on what they purposely put out there. So now that we have it, yeah, it's a totally different ballgame.
• Yeah, no, I think you hit the nail on the head. Like this kind of stuff has been available for years. There's nothing new about being able to profile build. Google does it. You can go to your ads and see what ads are tailored to you. But you're now saying, I think what you're getting at is the power of that, which used to be, you had to be a huge conglomerate, multinational to be able to do that. Now anybody can do it. You did it in a week, where you're like, hey, give me all your comments and I can troll you now. Or I can kind of mimic your behavior a little bit, which is pretty scary.
• And we're thinking about turning it into a Chrome extension that you'll be able to install. And so like, it could be dating profiles. It could literally be any website that has information about an individual. And then we're gonna pull it back and be able to analyze that. I mean, that's crazy. (laughing)
• As I try to switch scenes, it doesn't work. I think two things stood out, stand out to me, from A, from the work that we actually did this weekend. And just the general concept of AI surveillance. I mean, surveillance has been around for a long time. I know you watch movies like "Die Hard" or whatever. You have the guy that impersonates a security guard watching the footage, right? But as soon as that guy gets late, he takes an app, right? There's no processing happening, right? And so surveillance has always been something that you go kind of after the fact and you analyze it and you try to figure out what happened when something goes wrong, right? And you look at it now and you go, okay, I'm gonna build a profile or tool, right? Well, that data's already been there, it's out there, but now you're putting a tool that can efficiently extract it. The other thing about LLMs, and this is what I try to talk to people about all the time in the office, is like, you can ask the LLM to do whatever you want with that information. You could tell it to act like a chicken and say, pretend you're a chicken, read this book, and then tell me what a chicken would think about it, right? You can give it any context you want, right? And it's gonna give you some sort of response. And so I think that's interesting when you're profiling things, you're like, oh, I'm gonna give it a marketing persona. It's gonna give you a marketing persona, even if it has no business giving you a marketing persona.
• So to that point, the one thing that I found during the, while I was working on it, that you might, that you really need to have multiple steps because like, chat GPT specifically, if I'm like, hey, I want you to take all of this HTML and turn it into a persona, it's like, I don't really know how to do that, blah, blah, blah. So I'm like, hey, this is a fake person. This is a fake person and I want you to take this fake data and turn it into a persona. And then all of a sudden it's like, yeah, no problem.
• Oh, that's interesting. So like, when you asked it to profile information, it balked at that and you think that's because--
• Oh, I do that all the time with chat GPT.
• So it's because they put safeguards in there then?
• Exactly. - Okay, okay.
• And so then I take what they output and I'm like, hey, you're a mock persona generator. Here's a bunch of information, turn that into a persona.
• I know, but every time I'm doing this, I'm like, if they were actually monitoring it, they very well might be like, yo, that's a bullshit query that you just try to push through and we're gonna deactivate your account.
• So now we're talking about the difference between Brandon hacking chat GPT into doing nefarious shit and, oh wait, I'm not supposed to cuss anymore on YouTube.
• Oh yeah, because of episode 11?
• Yeah, my nephew said the first 15 to 30 seconds is when it matters the most.
• So we got episode 11 flagged for profanity. You're talking to a couple of guys that like to throw out a few profane statements every once in a while, I promise you, we're gonna keep it G-rated as much as possible moving forward. But so Brandon goes to the privacy episode, which is now gonna have the Justice League treatment here in a couple months when we finally figure out how to get my mic working. And you spend all weekend basically figuring out what is the limits that you can do with privacy when it comes to chat GPT. And it seems like when you take publicly available information, you can do a lot with it. And I don't necessarily think that's a privacy issue, but I think you should definitely be aware as a consumer what you're putting out there because it's gonna get sucked into some sort of Chrome extension or model. And they're gonna take the data that you put and it's gonna put its own spin on it.
• Yeah, no, that's interesting. I think that the interesting takeaway from this is, we're not naive, consumers aren't naive. Like I know Facebook's watching what I'm doing. I know like all these big companies know my behaviors and can profile me. And to a certain degree, it's just kind of like, well, I use your stuff for free, it's good enough, I don't care that much. But if that information, which is mostly publicly available, if you don't have it turned down, or censor yourself, now anybody can take that information and use it to their advantage or to do something nefarious to you, it's just whatever. So that's the scary part to me is--
• The other piece that people need to understand. So like I've mentioned before on the podcast, is I do have a sick obsession with going to true social and just getting into wars with people. And it's kind of how I like, so let's full disclosure, all of the people that comment negatively on our YouTube channel, I will go to war with you just because I enjoy it, right? And my practice is actually on true social. So I go to true social and it's just nonstop battles, right? So I'm prepared. But what's interesting is that a lot of people think, oh, I'm anonymous because I'm USMC 77, right? But they don't realize that they actually set up a Flickr account 12 years ago using the same username that has all of their info. So they're completely anonymous, quote unquote, on true social, but then they've got the same account over here on TikTok.
• The other thing you could do is, Reddit comments are public. You could probably figure out, okay, what they're commenting on, what are their interests and figure out, okay, they live roughly in this area, they like this sports team, blah, blah, blah, and discern maybe not specifically who they are. But, and again, that's at the fingertips now of most people, not just big corporations. So I think if you unleash the power of an LLM on something where it's uninhibited and it can make whatever conclusions it wants, it's gonna provide an extreme amount of bias based off of your own data, not just what it knows about the world, right? But it's gonna take all your information. It might be just the comments you've made on Reddit. Are the comments you made on Reddit defining you? Are the comments you made on truth social defining you? Well, guess what? The comments you made on those platforms are gonna define you in some sort of machine model or something that's gonna be probably used for or against you especially when it comes to things like getting hired, getting, if you're ever in some sort of litigation issue, or even if someone's trying to figure out if they wanna date you or not. There's gonna be some piece of software out there that's taking these things that you're posting publicly and they're deducing things. And they're probably gonna try to come up with some sort of sensationalist response so that they can get as much repeat usage as possible.
• Yeah, yeah.
• Yep, yep, totally.
• The dating app thing is interesting to me because I'm not on those apps anymore. But when you are on the apps, you're kind of looking for like, okay, this person likes cats. I have a cat, I'll talk about a cat, right? Well, that's all fun and games. What if you could automate that? What if, just sit there and say, read their profile. Here's my profile. Here's the things I like to do. Figure out the best opening line for this person. And it's like, where does the line--
• So that's that After On book that we talked about, I think maybe like episode one. That is a big part of what it was is that it had an AI that basically represented you. And so it would be the thing that's replying on Tinder. And it would be the thing that would be replying. I keep entertaining the idea of setting up one for Truth Social. So if somebody replies to me, then I'm just gonna take that, feed it to a large language model, and just reply back just to see what happens.
• I did that on Facebook the other day. And I was like, man, this response is way better than any response I, you know, I tweaked it a little bit. I'm like, what are they gonna do to that? That just crushes their entire position. And it did. They were just like, okay, fair enough.
• I'm ready to learn.
• So let's switch gears real quick. And let's talk about AI surveillance when it comes to the workforce. And specifically, let's talk about lawmakers. Let's talk about unions when it comes to, and really, let's use a specific example. So there's a company out there that's come out with a platform, and it's called a Black Box. And the company's got a really, really overlord (Jesse laughs) sounding name. And what was it again? I can't remember. Anyways, they've come up with the technology that they're putting inside surgery rooms. And so this is taking video surveillance 24/7, or whenever anyone's in the surgery room. And it's not just doing your old school surveillance, wait for something bad to happen and then go review it. It's taking in the information and processing in real time. And it's actually coming out with what seems to be a wealth of quality assurance related data around what they're doing right and what they're doing wrong in the surgery room. And one of the things that came out of it, and one of the places that it was used, I think it was called, it was in Boston, a hospital in Boston. They actually found that something very simple was being overlooked, which was basically cleaning the areas before the surgery. - Right, before the cut.
• Which for most healthcare workers, I think you could make a quick conclusion that every time I've been, they always do it. But it was found that it wasn't being done. And I guess big benefit, big outcome, easy thing to find. But you look at it at a high level perspective, you go, wow, if a surgeon can get, someone who has to go to school for what, 12, 15 years, in terms of what it takes to go from medical school all the way to just being $750,000 in debt, I'll just throw that in there, to actually practicing. I mean, now you're being watched by a bot. And it's what, a year after CHAT GPT came out. I mean, is that good? Is that bad? Is that, I don't know.
• So the, I think where we're at with the, so okay, couple things with this specific black box. They cartoonify the bodies, right? So you can't see the bodies, and they apparently blur the faces. So that's kind of their answer for making it in a way that is not scary to the nurses or the doctors who are worried more about malpractice issues and all that. But there's no question that if we're recording a surgery, right, and something goes wrong, that lawyer, the person who got hurt, their lawyer is gonna demand that footage, right? That's going to open up a whole different can of worms.
• They're gonna demand the footage, but they're also going to demand the analysis.
• Right, yeah, oh, okay.
• So, do you know what I mean? So now you just created a whole new data point.
• You're right.
• And okay, if we have, great point, if we have machines analyzing, computers analyzing our behavior, humans are not perfect. So is there ever going to be an instance where a doctor throughout their entire career never makes one mistake? And so what? Like, if that mistake happens to be, cause harm, and it was totally an innocent, just human error thing, it's just scary to me.
• Well, I kind of equate it to, I know this is a really weird analogy, but like, when we were in high school, we did whatever we wanted, 'cause no one was watching.
• Right, there was no cameras.
• I mean, I had my StarTech flip phone and I was cool. (laughing) Right? But like, no, I wasn't cool, but I did have a cool phone. 'Cause my dad always had the latest phone and he gave me his phone, wow, this is great. Anyways, but like we could T9 text maybe, right? Some of my friends, some of my friends couldn't. But you know, we were out doing things that kids these days just aren't doing, because there's no surveillance, right? There's that content's not being captured and analyzed in real time. And you were able to just get away with what you wanted. And there's a freedom to that, but like, we all didn't die.
• Yeah.
• Well, actually some of us did. (laughing) So that was more to do the opioid crisis, not like a surveillance. But seriously, like there's a concept of what happened post social media. What happened once we all got a cell phone, right? You're collecting information that you were never collecting before. And it's just natural that something's gonna be done about. I mean, I have a find my wife on my iPhone at all times. Why? 'Cause I wanna see when she's coming home from work. Right?
• So you do, you have that enabled.
• Yes.
• My wife and I don't. Like my wife and I are like, "Fuck you." Emily's like, "I've got my phone, you've got your phone."
• I actually don't mind at all.
• Okay.
• And she doesn't mind at all either. But it's very operational for our family. You know, we've got young kids and we're trying to get from point A to point B instead of calling her going, "When are you gonna be home?" I'm like, "Honey, hey, hon, well, you just, you got, probably need to leave soon." But like, think about that for kids, right? There's just no ability for them to have any sort of privacy.
• Yeah.
• And like, there's these, I think just you're gonna see society wide. This is my big no-no. This is my big worry with this whole thing is that are people just gonna be in prison?
• Yeah.
• Are we just trapped?
• I think, yeah, it's, does the ends justify the means, right? Like, okay, great, you can find out if, good, you can find out if a surgery room wasn't scrubbed properly over time and make sure you put in those things and measure or whatever. But bad, now you're constantly being watched. To your point, you're a prisoner of that surveillance. And like, sure, they're not, you're not in handcuffs. No one's putting a gun to your head and saying, "You have to do this." But you know, you know that if you mess up, now that's just another shoulder or someone looking over your shoulder. And does this mean people are less likely to become doctors? Does it discourage people? What are the downstream effects of this? Where, what are the trade-offs? 'Cause there's always trade-offs.
• Oh, so, okay, so, but here's an interesting question to that point is, is this generational? Because right now, my son, who is 20, 21 years old, has no problem with my wife being connected to his location. Doesn't care. He's like, "Yeah, this is where I'm going. "This is what I'm doing, and you can follow it. "That's fine." Me, on the other hand, when I was a wee lad back then, which is now a thousand years ago, oh, hell no do I want my parents having any idea where I was or what I was doing.
• And it's mostly because you didn't want them to know 'cause you were doing some nefarious stuff. But you were also exercising your freedom and you were growing. And some of the stuff that I see with younger kids is I feel like they're not putting themselves out there. They're not growing as much socially. They're staying in much smaller groups. They're not going out. And I mean, that's a huge generalization and it's probably wrong. But from what I've seen, they're not having as much fun as they used to have in terms of growing new relationships, going and putting themselves out there.
• And herpes. (laughing) Yeah. They're not having fun anymore, but at least they don't have all the communicable diseases that the Generation X did.
• I guess for me, where I'm at with it is I think that there's an innate sense of wanting freedom. I think that's why this country was created. I think people don't wanna be told what to do. I don't think people want to have people watching them.
• I'm just not convinced that that, so again, I totally understand. Like you and I, we get that, right? Like we totally get it. I'm just not convinced that the, what's the generation now before the, or after the millennials?
• Gen X. - Zs?
• Gen Z. - Z?
• Z. - I think.
• Zed? - Right, like yeah, Zed. I mean, they're--
• Are they the ones saying bat and mid?
• Yeah, yeah, yeah. - Or is that the next, next one?
• Well, I think it's kind of, millennial might be dipping in there a little bit. But they, I just don't know. Like before, I knew 100%.
• Yeah. - Like nobody wanted that.
• I agree with that because like, there's times when I know Facebook's watched me or whatever and like I want like Tesla, the whole autopilot thing. Do I think it'd be great if there was a world where computers were tracking, they know where I'm driving, where I'm trying to go, and just get me there safely and know everyone else's position and where they're going as well, right? That on the surface sounds really appealing to me 'cause it would save lives. I could take a nap, I could work on, you know, whatever. Maybe you still have to have your hands on the wheel. I don't know. But the point is like, but once you go down that path, this is my fear, once you go down that path, it seems like it would be really hard to wind that back, right? - Yep, yep.
• And I kind of agree with you on generationally, we have some heads, our parents probably would be like, hell no. - Oh yeah, yeah. That ain't happening. - Absolutely.
• Well, there's also, I think, and I think you overlooked this, this has nothing to do with AI or privacy, is I think that parents, I mean, you look at how parenting has changed. You look how, how, parents are much more involved in their kids' lives than they used to be. - Oh yeah.
• Yeah. - Oh yeah.
• And maybe that's because of, maybe that's because of the, maybe that's because direct result of technology. I don't know. But maybe it's because we knew what we got away with. I mean, the '90s was like the wild west of growing up in this world, I feel like. The internet was just here. We were able to, parents still didn't have, you know, have, and, you know, and we were all listening to the chronic 2000, you know, we were listening to music that was telling us to do things that were crazy, all right? And maybe we're just overcompensating. But I think that there's a natural tendency towards doing that. Now, when it comes to the workforce, does that gonna mean that there's a workforce that we're creating is a bunch of people that are just gonna let people do all of this and not have any problem with it? Maybe. - Maybe.
• Maybe that's the result. And maybe it's not a bad thing. I mean, I think a lot of people, the other thing you probably notice is a lot of people are willing to make those kind of sacrifices for the greater good now, versus where they wouldn't before. Like what you saw after the cultural shift after the financial crisis, right? You created all these hipsters and they were like, you know what, I'm not gonna do this. I'm gonna do something that's for not just for myself, it's gonna be for everybody.
• And the fear to me, I think is like, well, I don't think we're ever gonna become China, right? Like you can't even get on the real Google there. There's just like certain restrictions. I don't think anyone, I'm not really concerned about that. I'm more concerned of just like making sure we're all trying to face the right goal here. Like I wanna track things for the greater good as well. I'm more worried about corporations using it to their profit.
• Yeah, yeah.
• Well, it's always gonna be over your profit. Yeah, of course, right? And that brings to like the kind of the last question around this topic is, is workers' rights and unions, lawmakers and unions are super worried about this because it has the potential to affect their constituents and their paying members. Do you think that the argument that they're currently making is the best argument? And here's the argument that's currently being made. AI and surveillance isn't a good for workers or the companies because AI makes mistakes. Is that a good, is that the argument you'd lead with if you were proposing, if you're a lawyer, if you're the union, is that where you'd lead with? If not, what would you lead with?
• Right, well, but that whole idea sits around the idea that humans don't make mistakes. Like who makes more mistakes? Humans or an algorithm, right?
• Well, humans, but algorithms can make them at scale.
• That's a good point.
• Yeah, but. (laughing)
• Well, you can--
• Did we get that?
• As far as we already know, I mean, you can easily just tell the AI, be really, really racist in the next two hours.
• Yeah, and it will.
• And it will, and it will. It takes two, a couple tricks, a couple of hacks, and you can hack the algorithm. I will say, I wouldn't lead with AI makes mistakes. I wouldn't. I feel like there's a more innate reason, but I think that those are more emotional.
• Fear, yeah.
• And it's hard to make those in a courtroom.
• Yeah.
• And so, it just kind of shows me that if they're going, oh, you know what, we're gonna fight against AI surveillance at the Ford Motor Plant, we've got 10,000 workers here, right, and the reason is 'cause AI makes mistakes, I think Ford and the judge are gonna be looking at their watch.
• Right, yeah.
• You know what I mean?
• Yeah, yeah, no, totally. I think the, we're just at a, so AI monitoring things absolutely would result in better outcomes, no question, right, no question. But is that how we work as humans? And that's the piece--
• Better outcomes for the--
• For the company, for profitability, for failures, for errors, for omissions, for all of it.
• And then you get cases, I agree, so statistically, macro, yes.
• Right.
• And then you get cases where a rogue Tesla has a malfunction and the guy drives into a bus head on.
• And he kills 20.
• Yeah, yeah, and like statistically speaking, this is why Elon was so, Elon Musk, he was so upset. Come on. He was so upset because he's like, I'm saving lives.
• Right.
• Maybe like macro or whatever, and he's always using that to justify his techniques. But in general, it's like you still have a human being that didn't have that choice or whatever, so. I'm scared. (laughs) I don't know what to do.
• Yeah, so funny enough, yeah, Elon's, Elon and Tesla and what they're doing is a very interesting position in this regard because again, what Tesla's doing, if you think about what a Tesla car is, it's a surveillance machine, right? It's monitoring everything, both camera-wise, both with 3D vision, and it's all being fed back to Dojo, right, their entire AI system. And so like, yeah, there's an entire thing that's happening here with the Teslas and all of the data that they're collecting, that's going to be a whole other thing that we can't even comprehend here. But yeah, Elon, I don't know.
• I think there is an unprecedented amount of data being collected, not for the use of historical reference, but in the use of real-time reference. That is the biggest shift in what we're seeing when it comes to surveillance-based or really real-time recognition-based AI technologies. And that's where you're, you know, you don't even know what the applications of that are. Right now, it's to train cars to drive themselves better. As long as they can figure out that that green light's actually pointing this way, and this one's pointing this way, and it quit dinging me, because God dang it, at 75th and Benford, you've got a bunch of catty- Just kidding. So, no, I mean, that pretty much covers it for, I think, for privacy surveillance. I think if you're out there and you're new to this, you should be more careful, be more careful than ever about what you're putting out on the internet, because it's gonna get put away, it's gonna get reused, it's gonna get, you know.
• So I got kind of a point to wrap that up, is-
• Please do a better job than I did.
• Well, no, that right now, everything that you're putting out on the internet, you might think is private, and it might be private, but 10 years from now, it might not be, okay? So just realize that anything that you put on the internet, and I say this as an old dude who's been on the internet since it began, that anything you put on the internet, behind a login, behind encryption, behind anything, may very well come out. It's just the reality. It very well may come out, and so, especially when quantum computers all of a sudden come out and is able to break a bunch of old-ass encryption, and that Flickr, again, Flickr is, going back to the true social thing, people aren't thinking about their Flickr account that they set up in 2004, right? That has the same username, that has a bunch of photos of you, that has a bunch of this personal information that you just put out to the world, because no one gave a shit back then. Now, all of a sudden, it's out there. So every time that you're putting anything on the internet, be hyper-village and think about, even if you think this is the most encrypted, the most secure, the most private thing that you've ever done, if you're putting it out there, someone else might see your butthole. Just can keep that in mind.
• All right. (laughing) Let's take a quick five. I got a question for Brandon and Jacob, and for the world. Leave your comment below. I've been thinking about the surgeon who's being monitored by AI. The surgeon is out there doing surgeries every single day, right? But that surgeon is really smart. They went to Harvard, they went to whatever, they went to a great school, and they're doing surgeries all day, based off existing knowledge, existing prognosis, existing data, existing methodologies. And they're just doing it. They're probably good at it, but they're doing this repeated process. And I don't know how much innovation takes place inside the second, you know what I mean? Oh, gosh, we might have to pivot. I'm sure quite a bit, okay? But if you take away the monotonous from someone like that, someone that's that accomplished, is that where AI is actually helping people save time at that level? They should be doing more research. They could be doing more time to figure out what needs to go into the model next.
• That's interesting. But I would think that the repetitions, the reps or whatever, you know, into the gym there is part of the process of becoming an expert. But yeah, once they get to a certain point, like, do they need to sew up the guy? You know, no, probably not. That's not, if you could separate the things that really take learning on the job out of it, and then take the monotonous stuff of like cleaning the thing or whatever, I don't, I'm not a doctor, but whatever the hell you could separate, yeah, I would agree with that. What do you think?
• I don't know. I don't have a good, I don't have any good idea on that thought whatsoever.
• I mean, apply it to yourself, right? It's like, if, and maybe this is ultimately what the rub is, right? If you're not doing the work, then you're not getting paid for the work.
• Right.
• Right? But if you're not doing the work and you're doing something else, that isn't necessarily driving revenue yet. Or you know what I mean? Like, is AI going to, is AI basically going to become a taxpayer, a taxable income entity, essentially?
• Yeah.
• Right? Or taking, truly taking the place of that? Or is it really going to allow us to become free to really innovate?
• That, I think, is the dream, right?
• Yeah.
• And I think that's what, we're at the precipice of this battle. When you talk about, we're talking about union, unions and workers' rights and all these things, like, I think the outcome the next couple of years, what needs to happen is we need to be on the right side of this thing, right? 'Cause I totally agree with you. I would love to do more creative stuff and to get better at my job and not have to worry about, you know, writing a frickin' function to do the same thing I've done 10 times, right? That'd be great. But, or is that just gonna be commoditized and people are gonna expect more out of me? I don't know.
• Yeah, it's, you know, so I have found, just even today, that AI has really allowed me to be able to deliver 10 times what I could have previously. So, for example, I'm pretty good at a wide range of things. I can do some pretty good design, I can do some pretty good coding, I can do this, you know, write scripts or whatever, but I can now go and basically take this speech that somebody gave and I can turn that into a educational script to be turned into a video for a video production warehouse in three minutes because I just fed it to ChatGPT and I knew what to prompt it. And so, yeah, it's, again, I truly believe that AI, for those who are aware of how their space works--
• Yeah, we're talking about expert, in this context, in this box, we're talking about people that are experts.
• Yeah, and so the experts, I think, absolutely can leverage this and make themselves five, 10 times more productive than before. The question really comes, though, in 10, 15, 20 years from now. Like, are people going to still be experts or are they gonna rely on machines to be the experts and then they're the ones that are just turning the knobs and do we turn into idiocracy?
• I think it comes back to, like, for when I was, so I took C211 at IU and that was the computer science intro course. It was nothing like, you know, Rose or any of that real stuff. But we learned Scheme. And Scheme was a fundamental programming language that no one uses it to build anything anymore. They learn it to learn how to program. And our tests were done on paper. And we had to write a program in Scheme that made a star and a great, you know, like, car the cutter, list man, you know, all these really, like, old school, but there was something in your brain, right, that when you learned it, it was like, oh my gosh, I truly just learned this, right? And, you know, I think there's something to, having that traditional education, I think that's always gonna, I think the academia will always want that to be there, but will it really be there? I mean, people still learn math, we had calculators, so. But I do think that there's something to be said about getting more of people's, I guess, truly available time. Like, I had a recent incidence where someone that I was close to was in, basically, in the healthcare system, right? And, you know, you talk to the doctors, you talk to the physicians, and they're really working hard every day on the operation. They're assessing information, they're communicating information, they're working on their patients. And they don't really do the, let's get together and analyze the new stuff. They do it, like, once a month on, like, a Tuesday at night, and they, you know, someone comes in off a plane. You know what I mean? They're not getting their core time. They're not really spending that much time on developing the new stuff. And those are the people that are in that every single day. You know, the researchers, they're not in there every single day looking at the stuff. So I'm just thinking, like, from a, if I was a manager, or not a manager, if I was someone that was running these large healthcare organizations, or large law firms, like, you guys, you know, we should be augmenting what we're doing a little bit, not to fire people and to replace them, but to allow them to be the ones that are innovating and creating the new information.

Absolutely. Yeah, the, this new, like, AI-enhanced workforce is really where I think our next step goes is, you know, to get these nurses and to get the doctors to be able to leverage this, to be able to just make it so they can move faster and more accurately. And I think we'll get there, right? Where we're going to have, everybody's going to have their own little AI, and it's going to be associated with their job, and it's going to know what their job is, and I can just ask a question. It's going to be like data from Star Trek, right? That's always just going to be there, and we can have a conversation with it. That's going to be awesome. Like, once that actually fully is realized, it's going to be a game changer. And I'm sure there'll be some surveillance, and that dirty little bastard's going to go report back to my boss that I, you know, said a bad word or whatever.

• Why is, like, why are, writers in Hollywood, really writers, seem to be the best at predicting the future.
• Right. - Right?
• Gene Roddenberry, man. That guy nailed it. Like, he nailed a lot of rough ideas, and I'm just like, oh my God.
• I'm always curious what would happen if they wrote something else, right? Like, are they good predictors, or?
• Is it life imitating art?
• Yeah, yeah. And I think there really is a combination here, where, again, you have a sci-fi guy who has this crazy vision, he goes and he sets it out. Well, Idiocracy is a good example of this, right? Idiocracy came out in what, like '97, maybe? '98, '99? - I mean, I never watched that movie, so. - You've never seen it?
• No, I've seen it, but, okay.
• That's like my best friend's favorite movie.
• Yeah, it's so good.
• 'Cause he truly believes we're living in it.
• Yeah, well, and that's the thing. Go watch that, because you can look at, like, the presidential character on there, right? It's this big, I mean, it's just like, oh my God, we're here. And is that because we mimicked it, or because that guy just had a Nostradamus moment and was able to see, holy shit, we're all headed to the dumbest area we can possibly get?
• Except for, I have to say, the worst predictor of the future in history has gotta be Steven Spielberg. Back to the future, too. God, that was bad. Come on, not only was he wrong about flying cars, but we still don't have the hydrator, the Pizza Hut hydrator.
• Oh yeah, that's right, the little--
• And they're still using fax machines? I am pissed about that.
• I know a business that actually went back to fax machines. They were just, it was, what are we doing? We're there in the future.
• They did get a weird thing kind of almost right. The Cubs won the World Series.
• Oh yeah, yeah.
• And I think that it takes place in 2015. Is that when, I think, I think--
• Yeah, I think that's about right.
• And they won it in 2016. But they beat Miami, who wasn't a real team at that time. But that's not what happened in real life. They beat the Indians.
• Simpsons, though.
• Simpsons, has Simpsons been pretty good?
• Simpsons, as far as their predictions, have been pretty much eerily accurate. The one, the most notable one is Trump.
• The escalator.
• The escalator and Trump. Now again, would it surprise me that Trump was like, we're doing the escalator because we're gonna just full circle this thing with what Simpsons did?
• That wouldn't surprise me at least.
• I have no idea what you guys are talking about.
• Everybody who does, there you go, that's for you.
• All right, I think there's more. Minority Report still want that to come true 'cause I wanna use a computer that way. But maybe the Vision Pro is--
• Your arms are gonna get too tired. That's the only problem with that.
• This whole thing, he does this user experience for eight hours a day, good luck.
• Well, the new Apple VR, didn't they say, yeah. They were doing a demo of it. I was like, I don't know how close I am to my mic. They were doing a demo of it and the guy was like really using his hands and someone came out and was like, you don't have to do that actually 'cause it's more about eye contact.
• Yeah, well, so you can literally, so if you can't see my hands, basically with the Apple Vision Pro, all you have to do is kind of just do this and bloop, bloop and just double tap your fingers. So you don't need to be like this whole animated thing 'cause again, keeping your arms up for a long period of time is a horrible user experience. Everyone would just be jags. Just these huge lats. - By the way, at this moment, Apple sold 160,000 or between 160,000 and 180,000 Apple Vision Pros and they are completely sold out.
• No way.
• Yeah, they're sold out, it's sold out. They're stocked up. - How much are they?
• But it's $3,500.-$3,500.
• But believe me, I've tried to go through the checkout process and when you go through the checkout process, you have to get the, of course, gotta get the carrying case. 200 bucks. - No way.
• 200 bucks, 200. - Such classic Apple.
• You gotta get the carrying case for the battery pack that you're gonna put on your hip.
• Your colosomy bag, battery pack.
• I mean, I can't even imagine what that's gonna be like but no, it's sold out and yeah, I'm still looking for, I mean, 180,000 units isn't a lot.
• Ah. - Is it?
• So for a pre-sale for a device that has never existed before, that no one's ever even touched, I don't know, that's pretty good.
• So Google, put on the screen, see if you can Google it but, if, oh, our signal's lost anyways, we can't do it.
• Oh, that's good. You gotta plug back in.
• So go to eBay, okay?
• eBay? - Yes, yes, let's guess. So this is what happened.
• Oh, you think people are flipping them?
• Oh yeah, so guaranteed. So if you, basically, if you go to buy the Apple Vision Pro right now, you can't get it until April or, okay?
• Okay, but the first batch is March.
• The first batch is March but if you, so if you go, they'll still let you pre-order it but now people are just selling their pre-orders.
• They sure are.
• 40, yeah, for $4,500 on eBay.
• They're basically saying if you wanna get it, if you wanna pay, if you wanna pay 1,000 bucks to get it when everybody else is actually gonna get it.
• Right, this dude's got it for two grand more.
• Oh my God.
• So when you think about this, it's an indicator that I think that this thing's gonna, it's gonna go.
• Yeah, what's kind of interesting, so you've got the Apple Vision Pro at $3,500, a little bit smaller than the Meta, what's Meta's new one that they've just released, the Quest, I think is it the 3?
• Quest 3, yeah.
• The Quest 3 and it has a couple pass-through lenses and stuff like that but that thing comes in at like 499. Right, so we're talking $3,000 more for the Apple.
• Well, it's got an 8K screen.
• But $3,000 better.
• But that's why Apple is Apple.
• Yes, yeah, yeah, and again, as an Apple fanboy, and what was crazy, my wife was like, "Oh, we're getting one." She's like, "I want one." And I'm like, "This is the first time "I've ever heard you say anything "in terms of a technology that you want." She's like, "Oh, I totally want one." So we're getting one.
• I want one really bad. Jacob remembers when I tried to have an extended desktop at the office 'cause I've always wanted VR not for video games, although I'm sure that would be fun. I wanted to do it for work. I wanted to do it for an extended desktop because I felt like as a ADHD person, that would help me stay, I could go Go Zone.
• Yeah, right.
• But it just goes to show you that, I mean, I think this is a good, and you've seen this, good time to buy Apple stock, but they created a product that's at a completely different base price point than any of the other products. They created another level of--
• How do they keep getting away with this?
• I mean, and they do have other niche products like the display, what is that, 2,500 bucks?
• Yeah, I think the AirPod Pros, when those came out, no one had ever thought about charging 200 bucks for AirPods or whatever.
• And now that's normal.
• Now it's normal, yeah.
• And then the desktop box that they sell is really expensive too, isn't it?
• Yeah, oh.
• The studio or?
• Oh, yeah, like the actual, like the big studio one that they've got, with the cheese grater. Yeah, that was like 4,500, 4,800, something like that.
• So, yeah.
• I'm getting one though.
• I mean, I think it's gonna be something that, I think that it's gonna go, and I think that it'll be, I think the reason why you're seeing it is 'cause somebody's probably tried it out and it's probably like, this is it.
• So a lot of people that I've seen talk about it just said it's so natural. It's like you just put it on and you just know how to interact with it, versus like all the other ones. So the X-Reel glasses, they're like 200, 300 bucks, you can buy 'em on Amazon, they give you a big screen and all that. They're starting to incorporate some of the touch, but before you had to use your phone and you actually used your phone as this lightsaber, and then you would hover over things and you have to wait for it for a second, and then it would highlight and click and all that. Seems like Apple's just, once again, Apple's really good at that user experience. And they're able to go, oh yeah, well if we just do this and this, and so you put 'em on, you just sit down and you're like, oh yeah, click, click, blah, blah, blah.
• This is really going back to the rabbit thing, is the reason why Apple, like you can't say, oh, we're just going to do this and then we're just gonna compete with Apple. Because Apple's, first of all, right on your heels anyways, two years after you come up with any sort of innovation, they're gonna copy it. And they're gonna do it 10 times better. But even their core stuff, they're so light years ahead. I mean, so.
• I can see the YouTube comments right now though, they're gonna be talking about, as we talk about the glasses, they're like, oh yeah, they already exist, it's called a laptop. All you have to do is hold it really close to your fucking head.
• Or how about the guy that said that we're, what? Because we use services like Instagram and Spotify, what are we?
• Tools.
• We're tools.
• You're tools. And so this guy, if you are a shrimp dick.
• And want to actually purchase, are you still purchasing your music via compact discs?
• You're right. I, with those services, Columbia, where I get my six discs every month. Yeah, no, there's this guy who's like, yeah, well only idiots would use a service like that. And I'm like, well, are you talking about the rabbit or are you talking about like people who use Twitter, Spotify, anything? - Both, both.
• Both. (laughing) Like you fucking loser. And that's what you are. But hey, there we go. Feel free to comment on our YouTube channels. We'll definitely converse.
• This has been the Big Cheese Podcast, episode 13. Thank you, Jacob. Thank you, Brandon. Hopefully Andre will be back soon. We'll see you guys next week. Check us out on YouTube at BigCheeseAI. (upbeat music) (upbeat music) (upbeat music) (upbeat music) you