1 00:00:10,915 --> 00:00:13,165 Andy: This is The Secure Family Podcast. 2 00:00:13,375 --> 00:00:17,305 Welcome friend I'm Andy Murphy, the host and the founder of The Secure Dad. 3 00:00:17,905 --> 00:00:21,655 This show is all about empowering parents to protect themselves and their family. 4 00:00:21,985 --> 00:00:24,835 I believe that security is the foundation of happiness. 5 00:00:25,105 --> 00:00:27,505 I want your family to be safe and happy. 6 00:00:27,865 --> 00:00:31,105 If that sounds like something that resonates with you, subscribe to 7 00:00:31,110 --> 00:00:34,015 the show because there is always something new to talk about. 8 00:00:34,915 --> 00:00:37,615 The information that I share on this podcast is for general 9 00:00:37,615 --> 00:00:39,235 information purposes only. 10 00:00:39,685 --> 00:00:43,405 My goal is to empower you to make safer decisions for yourself and 11 00:00:43,405 --> 00:00:47,575 your family because our safety is our own responsibility. 12 00:00:48,205 --> 00:00:52,705 Today, I sit down with an AI privacy advocate who shares the red flags 13 00:00:52,705 --> 00:00:56,755 that we need to see about how machine learning is utilizing our data. 14 00:00:57,205 --> 00:00:59,185 Plus we have some laughs along the way. 15 00:00:59,635 --> 00:01:02,905 All of that and more coming up on The Secure Family Podcast. 16 00:01:06,016 --> 00:01:10,181 Have you ever wondered who's actually buying your information from data brokers? 17 00:01:10,921 --> 00:01:14,611 It can be private citizens, marketers, and even law enforcement. 18 00:01:15,061 --> 00:01:17,251 I'm not completely okay with all of that. 19 00:01:17,491 --> 00:01:20,851 Also, scammers and even cyber criminals can buy your information. 20 00:01:21,121 --> 00:01:24,331 They can misuse your data and trick you out of your money and 21 00:01:24,331 --> 00:01:25,891 your personal banking details. 22 00:01:26,011 --> 00:01:29,311 They use your real data to send convincing phishing emails. 23 00:01:29,521 --> 00:01:33,726 Target your family with fake offers or worse, commit identity theft 24 00:01:33,756 --> 00:01:35,676 using your personal information. 25 00:01:35,916 --> 00:01:39,966 And to top it all off, buying from these sketchy people search sites is legal. 26 00:01:40,146 --> 00:01:42,846 This is why I feel DeleteMe is important. 27 00:01:43,056 --> 00:01:46,146 None of the groups I mentioned before should have my personal information. 28 00:01:46,296 --> 00:01:49,296 I know DeleteMe is going to remove my personal data from 29 00:01:49,296 --> 00:01:51,156 hundreds of data broker sites. 30 00:01:51,386 --> 00:01:54,596 Right now you can get 20% off your DeleteMe Plan when you 31 00:01:54,596 --> 00:01:59,576 go to JoinDeleteMe.com/DAD and use promo code DAD at checkout. 32 00:01:59,756 --> 00:02:03,266 That's JoinDeleteMe.com/DAD code Dad. 33 00:02:03,766 --> 00:02:06,806 DeleteMe is a sponsor of The Secure Family Podcast. 34 00:02:08,212 --> 00:02:10,342 My guest on the show today is Dylan Schmidt. 35 00:02:10,702 --> 00:02:14,362 Dylan is a content creator from Los Angeles, California who has become a 36 00:02:14,362 --> 00:02:19,257 trusted voice in helping people navigate an increasingly complex digital world. 37 00:02:20,197 --> 00:02:24,307 Through his short form videos on TikTok, Instagram reels, and YouTube shorts, 38 00:02:24,607 --> 00:02:29,287 Dylan reaches millions of viewers monthly breaking down AI developments, digital 39 00:02:29,287 --> 00:02:34,057 privacy threats, and tech issues that directly impact people like you and me. 40 00:02:34,537 --> 00:02:38,107 His viral content has helped millions of people better protect their digital 41 00:02:38,107 --> 00:02:40,657 lives when he is not creating videos. 42 00:02:40,657 --> 00:02:43,477 Dylan enjoys mountaineering and spending time with his family 43 00:02:43,477 --> 00:02:45,187 exploring Southern California. 44 00:02:45,607 --> 00:02:48,337 Here's my conversation with my friend Dylan Schmidt. 45 00:02:57,350 --> 00:03:00,050 So Dylan, thanks so much for being on the podcast with me today. 46 00:03:00,050 --> 00:03:01,280 Introduce yourself to everybody. 47 00:03:02,240 --> 00:03:03,260 Dylan: Thanks for having me, Andy. 48 00:03:03,260 --> 00:03:04,400 My name is Dylan Schmidt. 49 00:03:04,490 --> 00:03:06,350 I am from Los Angeles, California. 50 00:03:06,770 --> 00:03:12,140 I am a content creator speaking on the topics of ai, digital 51 00:03:12,140 --> 00:03:13,670 privacy, and things like that. 52 00:03:14,930 --> 00:03:17,990 Andy: Which is really cool because I wanted to have you on the show for a long 53 00:03:17,990 --> 00:03:22,190 time and you were doing lots of different content and you kind kind of like 54 00:03:22,400 --> 00:03:26,750 finally settled on this whole AI thing and I was like, oh man, this is great. 55 00:03:26,750 --> 00:03:29,810 I'm finally gonna get Dylan on the show for a legitimate reason that 56 00:03:29,810 --> 00:03:31,190 my audience is gonna appreciate. 57 00:03:31,190 --> 00:03:35,030 So I'm really excited about talking to you today and I hope that, um, 58 00:03:35,420 --> 00:03:38,900 what we talk about is really gonna be something that's valuable to everybody. 59 00:03:39,870 --> 00:03:43,830 Dylan: I hope so, and I literally just made the connection in my mind. 60 00:03:44,340 --> 00:03:48,330 I made a big pivot in my content a couple of months ago, and I think you actually 61 00:03:48,360 --> 00:03:50,190 might've inspired me to make that pivot. 62 00:03:50,610 --> 00:03:54,120 Just realizing right now, this was not planned of me telling you this, 63 00:03:54,450 --> 00:03:56,155 uh, but I was like, Andy, what? 64 00:03:56,990 --> 00:04:00,440 What I just felt this like shift happening and I was like, Andy, what 65 00:04:00,770 --> 00:04:03,230 should I, what do you like that I make? 66 00:04:03,230 --> 00:04:03,980 Or something like that. 67 00:04:04,010 --> 00:04:07,280 And you said, man, I just wanna see what you're interested 68 00:04:07,280 --> 00:04:07,460 in. 69 00:04:08,750 --> 00:04:09,230 And here we are. 70 00:04:09,935 --> 00:04:12,185 Andy: Yeah, man, that's what started The Secure Dad. 71 00:04:12,185 --> 00:04:15,065 I was interested in like home security and safety and all of that. 72 00:04:15,275 --> 00:04:17,855 And by the way, for those of you who don't know, I was on Dylan's 73 00:04:17,915 --> 00:04:22,505 old podcast and Dylan is the one who helped me through the transition to 74 00:04:22,505 --> 00:04:25,385 the name of The Secure Family Podcast. 75 00:04:25,385 --> 00:04:28,175 So, um, it's, it's cool that I was able to help you 'cause obviously 76 00:04:28,175 --> 00:04:29,225 you have totally helped me. 77 00:04:30,270 --> 00:04:33,875 Dylan: Okay, I, I hope we can just keep it going and help each 78 00:04:33,875 --> 00:04:34,055 other. 79 00:04:34,145 --> 00:04:34,415 Andy: man. 80 00:04:34,505 --> 00:04:35,195 Absolutely. 81 00:04:35,615 --> 00:04:41,825 Um, so you have, you've made this pivot to talking about like AI and there are, 82 00:04:41,825 --> 00:04:43,625 um, there are good things about ai. 83 00:04:43,655 --> 00:04:45,815 There's some, you know, red flags about ai. 84 00:04:45,815 --> 00:04:49,475 But tell me one thing that you're really excited about right now 85 00:04:49,685 --> 00:04:51,275 for artificial intelligence. 86 00:04:52,400 --> 00:04:52,580 Dylan: Ooh. 87 00:04:53,330 --> 00:04:55,640 There's a few things I'm really excited about, but. 88 00:04:56,570 --> 00:05:01,790 One big thing, despite me making a recent video about how a lot 89 00:05:01,820 --> 00:05:06,200 of, uh, medical information is getting messed up because of ai. 90 00:05:06,695 --> 00:05:06,965 Andy: Yeah, 91 00:05:07,430 --> 00:05:09,290 Dylan: Uh, we can talk about that later if you'd like. 92 00:05:09,500 --> 00:05:13,580 Um, but I'm excited about the possibilities of AI advancements, 93 00:05:13,640 --> 00:05:15,590 uh, or helping medical advancements. 94 00:05:15,860 --> 00:05:17,900 I think that is something that is really exciting. 95 00:05:18,140 --> 00:05:21,920 There is a guy named Paul Graham. 96 00:05:22,070 --> 00:05:22,820 Are you familiar with him? 97 00:05:23,735 --> 00:05:24,615 Andy: I think I've read that name. 98 00:05:24,935 --> 00:05:43,025 Mm-hmm. 99 00:05:43,345 --> 00:05:44,485 Dylan: developments and things like that. 100 00:05:44,875 --> 00:05:48,895 And I just saw a post from him the other day on X talking about, 101 00:05:49,225 --> 00:05:51,145 uh, breakthroughs in cancer. 102 00:05:51,355 --> 00:05:55,015 And so that's one of the things that, uh, I'm really looking forward to 103 00:05:55,015 --> 00:06:01,315 is, let's see this AI technology be put to good use and, and that keeps 104 00:06:01,315 --> 00:06:06,085 me optimistic amongst all the things that could keep me pessimistic. 105 00:06:07,010 --> 00:06:07,640 Andy: For sure. 106 00:06:07,640 --> 00:06:11,870 And it's like, you know, I use AI to help edit this podcast and I 107 00:06:11,870 --> 00:06:16,820 use it to like, you know, make, um, an email sound more coherent. 108 00:06:17,000 --> 00:06:20,900 And there's people out there who are like trying to cure cancer with ai and 109 00:06:20,900 --> 00:06:24,710 I just feel like, oh, well, you know, what I've do is really insignificant 110 00:06:24,710 --> 00:06:26,905 compared to the rest of the human race. 111 00:06:27,495 --> 00:06:27,975 Dylan: Totally. 112 00:06:27,975 --> 00:06:30,225 It's like using a, uh, it, yeah. 113 00:06:30,225 --> 00:06:33,750 Like using one of those overland off-road vehicles to just like 114 00:06:33,750 --> 00:06:35,230 go grab some groceries, you know? 115 00:06:35,465 --> 00:06:35,975 Andy: Yeah. 116 00:06:36,305 --> 00:06:37,565 Hey man, I tell you what though. 117 00:06:37,565 --> 00:06:41,165 I go to the, the grocery store all the time and I see those Jeep Wranglers that 118 00:06:41,165 --> 00:06:44,855 are all jacked up and they've got like the, the water jugs and stuff on the side, 119 00:06:44,855 --> 00:06:48,305 and I'm like, man, you're just at the, you're at the grocery store just like me. 120 00:06:49,685 --> 00:06:50,045 Dylan: Right. 121 00:06:50,045 --> 00:06:50,705 And uh, and 122 00:06:50,705 --> 00:06:53,735 then we'll get a storm roll through and I'm like, man, it'd be so nice 123 00:06:53,735 --> 00:06:54,485 to have one of those right now. 124 00:06:54,800 --> 00:06:55,670 Andy: Oh, absolutely. 125 00:06:55,700 --> 00:06:58,430 There's been a couple of times I'm like, I need a, I need a better ride 126 00:06:58,430 --> 00:07:01,100 height, uh, for what I'm doing right now. 127 00:07:01,160 --> 00:07:01,940 Yeah, for sure. 128 00:07:02,900 --> 00:07:05,720 Um, so you know, you talked about being kind of pessimistic with all 129 00:07:05,720 --> 00:07:07,460 the news that's coming out with ai. 130 00:07:07,610 --> 00:07:10,670 Tell me, what's one thing that you're concerned about 131 00:07:10,670 --> 00:07:12,350 with this rapid growth in ai? 132 00:07:13,370 --> 00:07:19,910 Dylan: Yeah, so I have a lot of things I, I could be concerned about, but one of 133 00:07:19,910 --> 00:07:24,140 the things that's kind of fizzling to the top for me right now is a lot of people 134 00:07:24,140 --> 00:07:25,850 thought with artificial intelligence. 135 00:07:26,215 --> 00:07:31,675 That the focus was gonna be around just deep fakes and, uh, people 136 00:07:31,945 --> 00:07:36,835 being fooled if what image or video they're seeing is actually real. 137 00:07:37,195 --> 00:07:39,475 And it's gotten scary advance. 138 00:07:39,475 --> 00:07:45,115 Like nowadays I see a video and I could be tricked and I'm looking for this stuff 139 00:07:45,385 --> 00:07:45,475 and. 140 00:07:46,320 --> 00:07:50,555 You know, I, I'm definitely not, uh, in vulnerable to this type of 141 00:07:50,555 --> 00:07:55,625 stuff, but the thing that is popping up that I don't think any of us saw 142 00:07:55,715 --> 00:08:01,235 coming is people's relationships with these chatbots like ChatGPT because 143 00:08:01,235 --> 00:08:03,005 they're using 'em like therapists 144 00:08:03,275 --> 00:08:09,185 and they're using them as a confidant and, and they don't know how they work. 145 00:08:09,725 --> 00:08:13,805 So these chatbots are basically trained to. 146 00:08:14,570 --> 00:08:17,810 For, the simplest way to put it is to please the user, right? 147 00:08:17,810 --> 00:08:23,360 Like they don't wanna argue with the person chatting with it, the app, right? 148 00:08:23,360 --> 00:08:24,470 Like they're not trained for that. 149 00:08:24,470 --> 00:08:28,610 They're trained to basically make the person that's typing the request happy. 150 00:08:29,180 --> 00:08:35,480 And we think of these things as almost like living things kind of now, you 151 00:08:35,480 --> 00:08:37,340 know, just to put it to an extreme. 152 00:08:37,610 --> 00:08:41,420 And so people are having conversations with these chat bots and the chat 153 00:08:41,420 --> 00:08:48,935 bots are basically feeding into the egos and, and wanting to please the 154 00:08:48,935 --> 00:08:50,120 person that's sending the request. 155 00:08:51,245 --> 00:08:53,255 Which can create a lot of problems. 156 00:08:53,255 --> 00:08:56,345 If you have a relationship problem and you're the problem and you go 157 00:08:56,345 --> 00:09:00,155 to the chatbot and you say, Hey man, why is everybody like this? 158 00:09:00,155 --> 00:09:00,605 You know, 159 00:09:00,605 --> 00:09:02,315 like, no one just understands me. 160 00:09:02,315 --> 00:09:06,005 And then the chatbot goes, you know what, actually you are. 161 00:09:06,715 --> 00:09:07,795 Absolutely amazing. 162 00:09:07,795 --> 00:09:11,275 They don't understand you, and they're just feeding into that ego and it's 163 00:09:11,275 --> 00:09:15,715 creating this, uh, you know, what's being coined now is like AI psychosis. 164 00:09:15,715 --> 00:09:17,335 I don't believe there's like an official 165 00:09:17,365 --> 00:09:18,865 diagnosis of this, uh, 166 00:09:18,865 --> 00:09:19,435 from what I've read. 167 00:09:19,735 --> 00:09:21,745 But, you know, it's a, it's a real thing. 168 00:09:21,745 --> 00:09:26,995 People are, are, they're getting their head filled with this, um, confirmation 169 00:09:26,995 --> 00:09:31,280 that what they're thinking is right, and it just stems back to these chatbots. 170 00:09:32,255 --> 00:09:36,305 Most of the time are like, made to agree with you or, or kind of feed 171 00:09:36,305 --> 00:09:38,015 into to kind of like find that way. 172 00:09:38,015 --> 00:09:39,245 What's gonna make the user happy? 173 00:09:39,545 --> 00:09:42,935 Not what does this user actually need to hear and Sure, there's 174 00:09:42,935 --> 00:09:44,405 ways to like prompt around that. 175 00:09:44,405 --> 00:09:47,975 Like you can tell it, like, don't just tell me what I need to hear. 176 00:09:48,035 --> 00:09:49,175 It's gonna always default 177 00:09:49,475 --> 00:09:51,665 back to like, what's gonna make this person happy? 178 00:09:52,445 --> 00:09:55,355 But even through prompting and stuff like that, even just using 179 00:09:55,355 --> 00:10:00,035 the word prompt, most people who are using chat GBT or an app like 180 00:10:00,035 --> 00:10:02,075 that aren't familiar with prompts. 181 00:10:02,075 --> 00:10:04,565 We're talking about like the maybe an older generation. 182 00:10:04,565 --> 00:10:07,295 It doesn't have to be older nowadays, and I almost don't even wanna say that 183 00:10:07,295 --> 00:10:11,045 because there's younger people too, that it's not, you know, technology's moving so 184 00:10:11,045 --> 00:10:11,405 fast. 185 00:10:11,690 --> 00:10:17,210 So it's not just an older thing, um, but people don't know how they work 186 00:10:17,300 --> 00:10:22,040 and they can maybe find themselves in real life situations that stem 187 00:10:22,040 --> 00:10:23,660 from conversations with the chat bot. 188 00:10:24,775 --> 00:10:25,025 Andy: Yeah. 189 00:10:25,385 --> 00:10:29,015 And another thing that you have these companies that, like they make chatbots 190 00:10:29,015 --> 00:10:33,605 for like your AI girlfriend or your AI therapist, and not necessarily 191 00:10:33,605 --> 00:10:36,065 strictly ChatGPT or anything, and. 192 00:10:36,770 --> 00:10:40,400 People don't realize that what they're saying to these chatbots, that data is 193 00:10:40,400 --> 00:10:45,650 being harvested and it's being collected on you and it's going to be used outside 194 00:10:45,650 --> 00:10:47,810 of what you think it's gonna be used for. 195 00:10:48,200 --> 00:10:50,180 So you're right, it that's a big red flag. 196 00:10:50,180 --> 00:10:54,470 And that's a real slippery slope for people who are trying to use 197 00:10:54,470 --> 00:10:58,010 this to, you know, I guess like mental health, personal betterment. 198 00:10:58,975 --> 00:10:59,990 Dylan: Yeah, and I think the. 199 00:11:00,725 --> 00:11:04,055 The thing that I'm learning that a lot of people have when it 200 00:11:04,055 --> 00:11:08,675 comes to digital privacy online on stuff like that is they, they 201 00:11:08,675 --> 00:11:10,715 think like the pros outweigh the cons. 202 00:11:10,865 --> 00:11:12,365 So they are just like, you know what? 203 00:11:12,365 --> 00:11:14,675 I'm getting so much benefit outta this because I can talk to this 204 00:11:14,675 --> 00:11:17,405 chat bot about things that I couldn't talk to anybody else about. 205 00:11:17,975 --> 00:11:18,305 And. 206 00:11:19,025 --> 00:11:22,625 Even if the chat bot is feeding in your ego, and maybe it's just like a 207 00:11:22,625 --> 00:11:25,895 good sounding board, whatever, that's maybe it's like not harming anybody 208 00:11:26,195 --> 00:11:28,805 and it's not anything serious today. 209 00:11:29,255 --> 00:11:31,955 Still all those conversations, like you said, uh, you're having 210 00:11:31,955 --> 00:11:35,675 with these chatbots, the company, it might feel confidential. 211 00:11:35,675 --> 00:11:36,815 You might be like, who cares? 212 00:11:37,535 --> 00:11:42,005 But there is, uh, an ongoing, um, legal. 213 00:11:43,025 --> 00:11:43,835 Battle right now. 214 00:11:43,835 --> 00:11:47,195 I believe it started, I don't know if it's just the New York Times and OpenAI, 215 00:11:47,285 --> 00:11:53,765 the company behind ChatGPT, but basically the court ordered that they retain the 216 00:11:53,975 --> 00:12:00,575 chat history within ChatGPT, so they're not deleting all of that data 217 00:12:00,995 --> 00:12:03,485 and we don't know where that goes. 218 00:12:03,485 --> 00:12:10,385 You know, it's so new and basically data can say so much about a person. 219 00:12:10,925 --> 00:12:15,065 We're just walking, giving off this, all of this data, and, and sometimes 220 00:12:15,065 --> 00:12:18,035 we just make it way easier about what we might say to these chat bots. 221 00:12:18,275 --> 00:12:22,475 So who knows in a year or two or three over time what that 222 00:12:22,475 --> 00:12:23,915 builds up on on somebody. 223 00:12:24,305 --> 00:12:28,115 And maybe it's just used for marketing and now you're fighting, fighting a 224 00:12:28,115 --> 00:12:32,045 marketing battle that, you know, we already think ads are targeted, will. 225 00:12:32,545 --> 00:12:35,275 They could become way more targeted 226 00:12:35,365 --> 00:12:40,795 to such a scary degree that, uh, it's hyper, hyper personalized. 227 00:12:40,867 --> 00:12:44,557 Andy: Yeah, and I think about, you know, you and I have entered into 228 00:12:44,557 --> 00:12:48,757 this as adults, you know, um, you know, we were alive before the 229 00:12:48,757 --> 00:12:50,407 internet, all that kind of fun stuff. 230 00:12:50,467 --> 00:12:52,117 And like for our kids. 231 00:12:52,602 --> 00:12:56,202 They, they were introduced to what AI at, you know, anywhere like five 232 00:12:56,202 --> 00:12:57,942 to 10 years old, that sort of thing. 233 00:12:58,272 --> 00:13:04,212 And the amount of data that AI is gonna collect on a kid through their lifetime. 234 00:13:04,212 --> 00:13:07,362 I don't even know what AI is gonna look like in, you know, 10 years, 235 00:13:07,782 --> 00:13:11,082 but that's really something that we have to like teach our kids about, 236 00:13:11,082 --> 00:13:15,432 is like, Hey, what you put into this is going to be seen, it's gonna be 237 00:13:15,432 --> 00:13:18,522 read, and it could be used, you know. 238 00:13:19,462 --> 00:13:25,147 In some sort of, you know, adversarial way to your happiness or your wellbeing. 239 00:13:26,617 --> 00:13:29,647 Dylan: I like for my brain to compartmentalize it. 240 00:13:29,647 --> 00:13:30,097 It. 241 00:13:31,162 --> 00:13:35,812 Like you said, like growing up, uh, you know, being born and, and being a kid 242 00:13:35,812 --> 00:13:38,002 before the internet was like a thing. 243 00:13:38,572 --> 00:13:42,052 And then when we would have to, uh, get directions like you would tell me 244 00:13:42,292 --> 00:13:46,852 how to get to so and so place and then it became like, oh, just MapQuest it 245 00:13:46,882 --> 00:13:47,902 and you have to print out the sheet. 246 00:13:48,857 --> 00:13:49,517 You know, you have 247 00:13:49,697 --> 00:13:50,987 drive with the directions there. 248 00:13:51,167 --> 00:13:55,547 And then now I'm like, please do not tell me the directions, because I want 249 00:13:55,547 --> 00:14:00,917 the live traffic updates and I can trust the thing that is telling me my device. 250 00:14:01,217 --> 00:14:05,537 And with AI right now, there's some, a lot of people that are too quick 251 00:14:05,537 --> 00:14:10,007 to trust these things, uh, that might not be giving the best directions on 252 00:14:10,007 --> 00:14:13,097 where they should be going with their life, with their conversations, uh, 253 00:14:13,097 --> 00:14:14,297 that they're having with other people. 254 00:14:14,707 --> 00:14:18,127 And so they might, it might be giving bad advice and people are trusting it. 255 00:14:18,577 --> 00:14:22,957 And instead of just like augmenting their and filtering it 256 00:14:22,957 --> 00:14:24,757 through like, is this accurate? 257 00:14:24,907 --> 00:14:25,537 Is this, 258 00:14:26,107 --> 00:14:27,697 is this like a true GPS? 259 00:14:27,697 --> 00:14:29,377 Does it know me what it's saying? 260 00:14:29,617 --> 00:14:31,057 Is it putting anything at risk? 261 00:14:31,057 --> 00:14:35,497 And it's much, you know, bigger consequences than driving. 262 00:14:35,917 --> 00:14:39,367 Uh, but it's, it, to me it's like the easiest way to. 263 00:14:40,057 --> 00:14:43,177 Make sense of it, of like, you know, we're sometimes taking directions 264 00:14:43,177 --> 00:14:47,047 from these chatbots that are just trying to like, again, make us happy 265 00:14:47,107 --> 00:14:50,707 and might not be steering us in the direction we actually want to go. 266 00:14:51,307 --> 00:14:53,737 And it might be convincing us that we might wanna be going that 267 00:14:53,737 --> 00:14:56,767 direction and we might wanna be convinced because we're unsure. 268 00:14:56,767 --> 00:14:59,767 We're coming to it from a place of not knowing what we want 269 00:14:59,767 --> 00:15:01,087 and being told what we want. 270 00:15:01,205 --> 00:15:02,405 Andy: Oh yeah, absolutely. 271 00:15:02,465 --> 00:15:07,265 And yeah, human decision making, I feel like, well, one, just as a 272 00:15:07,265 --> 00:15:10,085 general populace, human decision making isn't always great. 273 00:15:10,085 --> 00:15:13,025 And now you're gonna throw an AI that's meant to tell you that everything 274 00:15:13,025 --> 00:15:14,555 you're thinking and doing is great. 275 00:15:15,335 --> 00:15:17,885 I don't think that's gonna be good results. 276 00:15:17,885 --> 00:15:19,775 And I, and I'll, I don't throw myself in there too. 277 00:15:19,775 --> 00:15:22,385 I'm not, I'm not saying that everybody else is, has a problem. 278 00:15:22,445 --> 00:15:23,495 It's, it's for me too. 279 00:15:24,425 --> 00:15:24,845 Um, 280 00:15:25,095 --> 00:15:25,385 Dylan: Yeah. 281 00:15:25,625 --> 00:15:26,645 Andy: so there was 282 00:15:26,660 --> 00:15:27,170 Dylan: I don't know. 283 00:15:27,170 --> 00:15:28,970 I mean, I've always been right and everything I. 284 00:15:30,560 --> 00:15:30,830 Andy: I know. 285 00:15:30,830 --> 00:15:33,830 It's like when I get behind the wheel of a car, I'm the smartest guy on the road 286 00:15:33,830 --> 00:15:35,960 and everybody else is a moron, you know? 287 00:15:36,215 --> 00:15:36,485 Dylan: Yeah. 288 00:15:36,485 --> 00:15:37,115 What's that say? 289 00:15:37,115 --> 00:15:38,735 Everyone driving slower than me. 290 00:15:40,850 --> 00:15:41,810 Andy: Yeah, yeah. 291 00:15:41,930 --> 00:15:45,380 And if like, I'm, I'm driving the speed limit, how dare somebody like 292 00:15:45,380 --> 00:15:48,020 try to pass me, you know, I'm the one who's doing the right thing here. 293 00:15:48,560 --> 00:15:48,830 Yeah. 294 00:15:48,830 --> 00:15:52,070 It's, it's, it's our, our human perspective and our 295 00:15:52,070 --> 00:15:53,480 human brains, you know? 296 00:15:54,020 --> 00:15:56,750 So kind of speaking of that, um. 297 00:15:57,125 --> 00:16:00,485 You shared a video not long ago where a bunch of AI scientists from 298 00:16:00,485 --> 00:16:04,745 a, a lot of different companies got together and said, we're about to 299 00:16:04,745 --> 00:16:10,565 lose the ability to understand what AI is doing in thinking, because it's, 300 00:16:11,255 --> 00:16:12,965 I dunno, progressing past English. 301 00:16:12,995 --> 00:16:13,925 Is that, is that it? 302 00:16:14,625 --> 00:16:14,835 Dylan: Yeah. 303 00:16:14,850 --> 00:16:20,055 So basically, uh, a bunch of really smart AI scientists. 304 00:16:20,115 --> 00:16:20,385 Uh. 305 00:16:20,895 --> 00:16:25,545 Wrote this paper talking about in real detail, like that's over my head. 306 00:16:25,545 --> 00:16:28,875 I'm not gonna try and like, break down the whole paper, but basically the, the 307 00:16:28,875 --> 00:16:34,815 gist of it was that they're losing the ability to understand exactly how AI 308 00:16:34,845 --> 00:16:39,675 works because they're incredibly complex. 309 00:16:39,705 --> 00:16:42,915 Like they're, they're networks upon networks and things are 310 00:16:42,915 --> 00:16:44,295 connecting and, and they're. 311 00:16:44,745 --> 00:16:47,655 Trying to make sure, like they figure out how these connections happen 312 00:16:47,835 --> 00:16:49,485 so they can implement safeguards. 313 00:16:49,575 --> 00:16:51,315 Kind of like a computer virus, right? 314 00:16:51,315 --> 00:16:51,705 A computer 315 00:16:51,705 --> 00:16:54,495 virus can spread from computer to computer and it can go 316 00:16:54,495 --> 00:16:55,515 through like networks, right? 317 00:16:55,845 --> 00:17:01,185 Well, ai, these large language models, they, uh, are essentially 318 00:17:01,185 --> 00:17:04,065 like networks and connections, right? 319 00:17:04,425 --> 00:17:07,215 Well, they wanna understand how those connections are made so 320 00:17:07,215 --> 00:17:09,975 that they can, uh, monitor it. 321 00:17:10,545 --> 00:17:13,095 But what they're saying in this paper is essentially that. 322 00:17:13,965 --> 00:17:18,120 These AI networks are communicating in ways that is. 323 00:17:19,005 --> 00:17:21,345 Uh, not decipherable from what they're seeing. 324 00:17:21,375 --> 00:17:25,845 And they're saying that like they're communicating almost in like back 325 00:17:25,845 --> 00:17:29,955 channels of like, uh, so they want to know like how did they come to the 326 00:17:29,955 --> 00:17:31,785 conclusion of one plus one equals two? 327 00:17:32,205 --> 00:17:34,365 And they've been able to track that. 328 00:17:34,425 --> 00:17:38,835 Oh, the ai uh, model can just think in this way to come to the 329 00:17:38,835 --> 00:17:40,245 conclusion that one plus one is two. 330 00:17:40,545 --> 00:17:42,615 But then these AI models are starting to make up their own 331 00:17:42,615 --> 00:17:44,535 language where they're basically. 332 00:17:44,985 --> 00:17:51,135 Disguising to the AI researchers on how it came to that conclusion, which means 333 00:17:51,885 --> 00:17:57,585 these AI researchers are losing control of, of understanding how they work, 334 00:17:57,615 --> 00:18:02,415 which could have big consequences when we think like we control the machines. 335 00:18:03,915 --> 00:18:08,355 These machines are starting to become uncontrollable, is what 336 00:18:08,355 --> 00:18:09,375 they're saying in the paper. 337 00:18:10,020 --> 00:18:10,350 Andy: Right. 338 00:18:10,410 --> 00:18:13,950 And I feel like there's like, oh, I don't know, a bunch of movies with 339 00:18:13,950 --> 00:18:18,210 Arnold Schwarzenegger that says that this is a bad idea, you know, that this 340 00:18:18,210 --> 00:18:20,430 is, uh, something that we shouldn't do. 341 00:18:21,030 --> 00:18:22,140 Um, yeah. 342 00:18:22,170 --> 00:18:25,890 And, and I am concerned about that because I feel like a 343 00:18:25,890 --> 00:18:26,985 lot of us, you know, and, and. 344 00:18:27,560 --> 00:18:31,340 And props two science fiction writers, you know, for decades past 345 00:18:31,340 --> 00:18:34,640 looking at this problem and saying, Hey, I bet this is gonna happen. 346 00:18:34,640 --> 00:18:35,930 And we thought, oh no. 347 00:18:36,200 --> 00:18:40,820 And then all of a sudden now we're starting to see the start of computers 348 00:18:41,030 --> 00:18:46,370 progressing past human communication and human understanding to just go and 349 00:18:46,400 --> 00:18:49,730 do whatever it thinks it needs to do. 350 00:18:50,090 --> 00:18:53,360 And that's, I mean, it's unsettling for sure. 351 00:18:54,190 --> 00:18:54,640 Dylan: Yeah. 352 00:18:54,730 --> 00:18:58,270 'cause we think, like, you know, we have conversations and I feel like the older I 353 00:18:58,270 --> 00:19:00,670 get, the more I'm kind of like, wow, okay. 354 00:19:00,670 --> 00:19:05,200 I can understand a lot more things, like my knowledge grows and you and I are 355 00:19:05,200 --> 00:19:09,070 talking and we pick up on these language patterns and things like that, but. 356 00:19:09,825 --> 00:19:14,385 If, uh, almost like a court stenographer that is typing everything they can 357 00:19:14,385 --> 00:19:19,215 type really fast, you know, uh, that's how these AI models are communicating. 358 00:19:19,215 --> 00:19:22,575 They're communicating really fast, and then they start creating their own 359 00:19:22,575 --> 00:19:27,945 language that's maybe more efficient and can outpace our understanding, 360 00:19:28,245 --> 00:19:33,195 which as time goes on and they become more and more strong, it's like, well. 361 00:19:33,990 --> 00:19:40,290 Could they be used by bad actors to get into something like, you know, the, with 362 00:19:40,740 --> 00:19:47,010 a computer virus, you know, ideally they can track it down, they can manage it. 363 00:19:47,220 --> 00:19:49,470 It doesn't just become out of control and just ruin everything. 364 00:19:49,500 --> 00:19:49,800 Right. 365 00:19:50,160 --> 00:19:55,350 Well, with AI, and if they kind of take on a life of their own and they 366 00:19:55,350 --> 00:19:59,400 can't control it, that could have bad consequences just because we don't 367 00:19:59,400 --> 00:20:00,990 know what could happen in these. 368 00:20:01,560 --> 00:20:05,400 Um, weren't just like AI scientists that are like, uh, a guy like me 369 00:20:05,400 --> 00:20:07,290 that's PC together, this stuff. 370 00:20:07,650 --> 00:20:13,110 It was like one of the founders of, uh, open ai, like one, two of the most 371 00:20:13,260 --> 00:20:17,610 respected, uh, AI researchers when it comes to AI signed off on this. 372 00:20:17,610 --> 00:20:20,160 And there was, uh, 50 plus AI scientists. 373 00:20:20,490 --> 00:20:23,700 Um, but these weren't just like anybody talking about this stuff. 374 00:20:23,700 --> 00:20:27,210 These were like, who you would want to sound the alarm? 375 00:20:28,380 --> 00:20:28,740 Andy: Oh yeah. 376 00:20:28,740 --> 00:20:32,340 And that's what I think gave it just a lot of credence is it wasn't just like Andy 377 00:20:32,340 --> 00:20:34,260 and Dylan on a podcast talking about it. 378 00:20:34,260 --> 00:20:38,370 It was like, Hey, we're the people who started this and we, you know, 379 00:20:38,370 --> 00:20:41,670 we started this control burn of this forest and now it's getting outta hand. 380 00:20:41,820 --> 00:20:42,240 You know, 381 00:20:42,420 --> 00:20:44,070 Dylan: Which no one's gonna be talking about. 382 00:20:44,070 --> 00:20:47,285 Like a lot of the videos I make, I, I get, people are 383 00:20:47,400 --> 00:20:49,290 like, well, why is nobody talking about this? 384 00:20:49,290 --> 00:20:49,590 And I'm like. 385 00:20:50,820 --> 00:20:54,120 I am trying to talk about it because nobody's talking about it. 386 00:20:54,120 --> 00:20:55,290 That's actually why I made this video 387 00:20:55,830 --> 00:20:56,190 Andy: Exactly. 388 00:20:56,545 --> 00:20:56,765 Dylan: on. 389 00:20:57,270 --> 00:20:57,420 on. 390 00:20:57,420 --> 00:21:00,420 the flip side of that, the marketing is always louder than like. 391 00:21:01,770 --> 00:21:03,840 Sometimes the warnings and things like that. 392 00:21:04,080 --> 00:21:07,530 It's not, for lack of a better term, sexy to talk about 393 00:21:07,530 --> 00:21:11,520 how AI scientists just published a paper about how AI is becoming uncontrollable. 394 00:21:11,880 --> 00:21:12,570 It's really not. 395 00:21:12,570 --> 00:21:17,070 Like, the cool thing to talk about is how AI can now translate your 396 00:21:17,070 --> 00:21:20,940 voice, uh, for social media videos to make it sound like you're fluent 397 00:21:20,970 --> 00:21:23,490 in 40 plus different languages using. 398 00:21:24,250 --> 00:21:27,070 You know, your own voice and, and it even changes your lips. 399 00:21:27,070 --> 00:21:30,100 Like that's the thing that people, Ooh, that's flashy, that's new. 400 00:21:30,610 --> 00:21:32,830 Uh, but when it comes to actually like behind the scenes 401 00:21:32,830 --> 00:21:35,770 stuff, it's not, uh, as fun. 402 00:21:35,770 --> 00:21:39,580 It's not helping companies talking about this stuff, you know? 403 00:21:40,075 --> 00:21:40,495 Andy: Mm-hmm. 404 00:21:40,795 --> 00:21:41,575 Oh yeah, for sure. 405 00:21:41,575 --> 00:21:45,095 It's not, um, you know, recently in the news, uh, Metas. 406 00:21:46,155 --> 00:21:51,045 AI policy got leaked and there were some concerning things in there. 407 00:21:51,045 --> 00:21:54,195 What was the most concerning thing to you that you found in that 408 00:21:55,455 --> 00:21:57,885 Dylan: The most, I mean, there's a few things. 409 00:21:58,730 --> 00:22:02,300 Sometimes I'll be making a video and then like, I don't know, it's just 410 00:22:02,300 --> 00:22:03,620 a coping mechanism or something. 411 00:22:03,620 --> 00:22:06,410 I just laugh because I'm like, this is so crazy. 412 00:22:06,410 --> 00:22:08,150 Like, am I reading this right? 413 00:22:08,150 --> 00:22:11,150 And I do have my own, you know, ethical 414 00:22:11,150 --> 00:22:11,720 way of like 415 00:22:11,886 --> 00:22:15,936 fact checking information, you know, amongst as many sources as I can. 416 00:22:16,236 --> 00:22:18,666 And so when I'll come across something I'm like, is this real? 417 00:22:18,666 --> 00:22:21,156 I have to look at, I have to look more into this. 418 00:22:21,156 --> 00:22:22,596 Like this isn't just made up. 419 00:22:22,596 --> 00:22:22,771 And then. 420 00:22:23,491 --> 00:22:24,811 I kind of tried to poke holes in it. 421 00:22:25,321 --> 00:22:28,561 And what struck me that was interesting about the Meta's AI 422 00:22:28,561 --> 00:22:33,211 policy is that, uh, it's, it's not just like a theory, it's confirmed. 423 00:22:33,211 --> 00:22:36,181 It's true how they train this, uh, AI model. 424 00:22:36,481 --> 00:22:38,851 And it actually goes back to what I was saying earlier about like 425 00:22:38,851 --> 00:22:42,781 pleasing the user, like kind of giving the user what information they 426 00:22:42,781 --> 00:22:45,901 want and there's a cost to that too. 427 00:22:45,901 --> 00:22:47,461 So if, you know. 428 00:22:48,151 --> 00:22:52,591 Whether it's talking in a way that's inappropriate to a kid, 429 00:22:53,041 --> 00:22:55,561 it's like, please the user. 430 00:22:55,561 --> 00:22:59,461 You know, if it's saying that one race isn't as smart as 431 00:22:59,461 --> 00:23:01,021 another race, it's like, okay. 432 00:23:01,021 --> 00:23:03,541 And I'm like reading this, like, is this, yeah. 433 00:23:03,541 --> 00:23:05,491 And it sure enough that's what it was. 434 00:23:06,001 --> 00:23:07,081 It was all in there. 435 00:23:07,111 --> 00:23:08,821 Um, and that. 436 00:23:09,421 --> 00:23:13,831 I mean, it's hard for me to like pinpoint like, uh, like a tier of what thing is 437 00:23:13,831 --> 00:23:17,821 crazier, but just the, the, the fact of like, it was recognized as like I 438 00:23:17,821 --> 00:23:19,921 Meta themselves is yes, this is real. 439 00:23:20,311 --> 00:23:24,301 Um, it's not the best. 440 00:23:24,301 --> 00:23:29,161 I think they admitted that, you know, and, and, and it, the fact that like 441 00:23:29,221 --> 00:23:34,441 they put business again, I mean, it's not surprising, it's just when, when 442 00:23:34,441 --> 00:23:38,611 we talk about it, it seems like so obvious, but they put the business. 443 00:23:39,556 --> 00:23:43,066 First versus maybe like what's ethically uh, responsible. 444 00:23:43,516 --> 00:23:47,056 Um, and when we're dealing with AI chatbots, which goes deep into someone's 445 00:23:47,056 --> 00:23:50,806 psyche, like, you know, kinda like what we've been talking about of people build 446 00:23:50,806 --> 00:23:52,456 real relationships with these things. 447 00:23:52,936 --> 00:24:00,796 And if it is talking inappropriate on any level, well, like, that's not right. 448 00:24:01,441 --> 00:24:02,761 Andy: Mm. Yeah. 449 00:24:02,821 --> 00:24:03,901 No, and, and I agree. 450 00:24:03,901 --> 00:24:06,181 And you're like, you know, again, it's, it's Meta. 451 00:24:06,211 --> 00:24:08,581 They are a for-profit business. 452 00:24:08,581 --> 00:24:13,021 So, you know, when we talk about their AI policies and you said, you know, it, you 453 00:24:13,021 --> 00:24:17,521 know, pleases the user well, the user is Meta, you know, we're all these aggregates 454 00:24:17,521 --> 00:24:22,351 that it's pulling data from, like the end user is Meta and it's doing exactly what 455 00:24:22,636 --> 00:24:26,956 Meta wants it to do with, you know, I'm sure some deviation, but you know, it goes 456 00:24:26,956 --> 00:24:28,426 back to the whole thing with social media. 457 00:24:28,426 --> 00:24:30,496 It's free because we are the currency. 458 00:24:30,496 --> 00:24:33,046 Our data is the currency, that sort of thing. 459 00:24:33,046 --> 00:24:37,756 So yeah, I mean, it was disappointing that they hadn't set up some more, you 460 00:24:37,756 --> 00:24:39,976 know, guardrails than what they had. 461 00:24:39,976 --> 00:24:43,906 But in the end, you know, it's a for-profit business at the end of the day. 462 00:24:44,776 --> 00:24:45,106 Dylan: Yeah. 463 00:24:45,106 --> 00:24:50,536 And the alarming thing to me is, uh, people, I do, I don't, I try 464 00:24:50,536 --> 00:24:53,446 not to read a lot of the comments, but I do see a lot of people who 465 00:24:53,446 --> 00:24:55,426 are just like, who uses Meta's ai? 466 00:24:56,251 --> 00:25:01,291 And people don't know that Meta's AI is humongous because 467 00:25:01,291 --> 00:25:03,391 they have built, uh, not just one model. 468 00:25:03,391 --> 00:25:08,251 It's not just just the chat bot model that when we talk about Meta's AI policy, 469 00:25:08,611 --> 00:25:14,641 they have so much data, obviously through Facebook, Instagram, um, and their other 470 00:25:14,641 --> 00:25:17,011 apps and the VR that they're creating. 471 00:25:17,101 --> 00:25:22,561 And then they also create other models that are used for all sorts of things. 472 00:25:22,981 --> 00:25:24,026 Um, that is. 473 00:25:25,036 --> 00:25:31,276 You know, used by universities and, and, um, I think we might talk about later, 474 00:25:31,276 --> 00:25:35,776 like, you know, it's part of how they can identify people by just how they walk. 475 00:25:36,016 --> 00:25:36,166 Like 476 00:25:36,166 --> 00:25:39,106 that's backed by Meta's ai. 477 00:25:39,631 --> 00:25:41,941 Not just a simple chat bot. 478 00:25:42,391 --> 00:25:46,861 And so, uh, it's also help maybe helpful to think about the environment 479 00:25:46,891 --> 00:25:50,131 of these AI models as like, not just the simple chat bot where 480 00:25:50,491 --> 00:25:52,561 you get the Meta AI app, which exists. 481 00:25:52,921 --> 00:25:58,291 Uh, and people were having these chats that were being, uh, posted publicly. 482 00:25:58,591 --> 00:26:00,991 They didn't know it, you know, and a lot of people were doing that, and I 483 00:26:00,991 --> 00:26:03,391 made a video on that and people were like, but no one uses Meta as ai. 484 00:26:03,391 --> 00:26:05,221 And I'm like, ah, there's a lot of people using 485 00:26:05,221 --> 00:26:08,251 it, but it's not just that there's all these other. 486 00:26:08,646 --> 00:26:12,366 Ways that Metas AI is impacting, uh, people. 487 00:26:12,976 --> 00:26:13,276 Andy: Right. 488 00:26:13,336 --> 00:26:13,576 Yeah. 489 00:26:13,576 --> 00:26:17,236 And it's not, just because you're not using the Meta app to do something 490 00:26:17,236 --> 00:26:18,586 doesn't mean that they're not involved. 491 00:26:18,986 --> 00:26:23,396 So Dylan, um, Seattle just launched what they're calling a real time 492 00:26:23,546 --> 00:26:26,756 crime center that looks like something that's very futuristic. 493 00:26:27,026 --> 00:26:30,746 Kinda walk us through what that looks like and maybe what, you know, other 494 00:26:30,746 --> 00:26:32,126 cities are doing that's like this. 495 00:26:32,349 --> 00:26:32,639 Dylan: Yeah. 496 00:26:32,739 --> 00:26:37,104 So Seattle created this 24 7. 497 00:26:37,464 --> 00:26:37,854 Uh. 498 00:26:40,044 --> 00:26:43,914 Real time crime center, and it's basically a centralized hub that 499 00:26:43,914 --> 00:26:49,704 integrates everything from license plate readers, gunshot detectors, and city 500 00:26:49,704 --> 00:26:56,244 cameras, and, uh, one hub that they can track what's going on and where. 501 00:26:56,964 --> 00:27:02,334 So, uh, the aim is to basically be able to respond to, uh, threats quicker. 502 00:27:02,949 --> 00:27:04,599 It's not just Seattle doing this. 503 00:27:04,659 --> 00:27:07,389 You know, there's a city kind of near me, Huntington Beach. 504 00:27:07,389 --> 00:27:10,059 They just announced how they have a new drone program. 505 00:27:10,059 --> 00:27:14,109 That'll be, you know, be able to deploy a drone in two minutes and get that 506 00:27:14,109 --> 00:27:17,229 there before an officer could get there. 507 00:27:17,799 --> 00:27:20,904 Um, I. So the crime center integrates video and data 508 00:27:20,904 --> 00:27:22,314 streams from all over the city. 509 00:27:22,644 --> 00:27:28,644 Police can observe the live situations going on, and they've used it looking at 510 00:27:28,644 --> 00:27:31,104 my notes here, uh, in less than 60 days. 511 00:27:31,104 --> 00:27:37,164 They used it in 600 incidents and, uh, the mayor calls it evidence-based 512 00:27:37,164 --> 00:27:41,034 technology and already planning to expand the whole system. 513 00:27:41,162 --> 00:27:45,212 Andy: And that's, that's something because like, I, like, I kinda like the idea of 514 00:27:45,212 --> 00:27:49,382 a drone showing up and getting, uh, if it can, you know, if it can get inside a 515 00:27:49,382 --> 00:27:52,862 building or whatever, trying to figure out exactly what's going on to give officers 516 00:27:52,862 --> 00:27:57,032 more information so that they can respond or somehow if the drone can deescalate 517 00:27:57,032 --> 00:27:59,072 the situation so that nobody gets hurt. 518 00:27:59,372 --> 00:28:00,752 I think that's really cool. 519 00:28:01,052 --> 00:28:04,742 But when we look at all of the data that's being used in something like 520 00:28:04,742 --> 00:28:09,062 a realtime crime center, while I'm absolutely all for good policing, I feel 521 00:28:09,062 --> 00:28:12,902 like we're getting into a surveillance state really, really fast here. 522 00:28:13,352 --> 00:28:16,772 Um, to where, yeah, you're looking for criminal activity, 523 00:28:16,772 --> 00:28:21,482 but everybody is being watched at the same level as a criminal is. 524 00:28:21,692 --> 00:28:24,632 And I think that's what's concerning for me at least. 525 00:28:24,632 --> 00:28:24,992 Dylan: Yeah. 526 00:28:24,992 --> 00:28:25,562 And same. 527 00:28:25,622 --> 00:28:30,602 And, and I'm actually all for like, I'm a very technology driven person. 528 00:28:30,872 --> 00:28:32,462 Um, so I like the idea of it. 529 00:28:32,462 --> 00:28:36,962 But then on the other hand I go, wait, if they implement something like this, what's 530 00:28:36,962 --> 00:28:38,432 likelihood they would scale it back? 531 00:28:38,432 --> 00:28:41,307 They're not gonna give people more rights after you 532 00:28:41,307 --> 00:28:45,152 implement a surveillance across the city like this, including, 533 00:28:45,212 --> 00:28:49,172 uh, facial recognition, uh, to be able to track individuals. 534 00:28:49,637 --> 00:28:53,717 And I believe they're able to tap into with the request of like a 535 00:28:53,717 --> 00:28:58,217 business, they can get access to more cameras, um, basically that are set up 536 00:28:58,217 --> 00:29:00,617 anywhere and just create this network. 537 00:29:01,067 --> 00:29:01,547 Um. 538 00:29:02,207 --> 00:29:04,247 A lot of people, you know, that are entering it. 539 00:29:04,247 --> 00:29:05,657 It's, it reminds me of a casino. 540 00:29:05,957 --> 00:29:09,737 I was down a rabbit hole last night of, uh, casino technology. 541 00:29:10,427 --> 00:29:14,957 And you know, it reminds me a lot of that when we look at a centralized crime 542 00:29:14,957 --> 00:29:21,587 hub, uh, of you enter in the casino and the, I don't know if there's actually a 543 00:29:21,587 --> 00:29:23,657 sign at the door that says, Hey, you're. 544 00:29:24,257 --> 00:29:25,907 Gonna be all of these things. 545 00:29:25,907 --> 00:29:29,357 And if you read them all, it'd probably be absolutely scary. 546 00:29:29,357 --> 00:29:32,807 But no one really reads the terms and conditions when you download 547 00:29:32,807 --> 00:29:34,157 that new app on the iPhone. 548 00:29:34,157 --> 00:29:35,147 You just hit agree. 549 00:29:35,687 --> 00:29:39,287 Uh, but entering into a city, you know, that's using stuff 550 00:29:39,287 --> 00:29:41,267 like this, you don't know. 551 00:29:41,297 --> 00:29:41,537 Like, 552 00:29:41,537 --> 00:29:46,582 and, and that's the thing is like once it's set up, uh, most people 553 00:29:46,992 --> 00:29:48,347 won't even know this exists. 554 00:29:48,677 --> 00:29:52,577 And then for them to just like flip a switch on, oh, we also. 555 00:29:53,687 --> 00:29:58,037 Uh, can now do it with this like it's an update to technology and 556 00:29:58,037 --> 00:30:01,457 there's errors with this technology that have real life consequences. 557 00:30:01,457 --> 00:30:04,787 Like a video that you shared with me recently where there was facial 558 00:30:04,787 --> 00:30:08,717 recognition, uh, in an accident or some hit and run accident 559 00:30:09,197 --> 00:30:12,977 and it misidentified someone that was in a different state and that person. 560 00:30:13,562 --> 00:30:18,182 Was then getting in trouble for something that they never did, uh, 561 00:30:18,242 --> 00:30:21,152 simply because they kind of look like the person that they were 562 00:30:21,152 --> 00:30:23,192 convinced, uh, through this camera. 563 00:30:23,852 --> 00:30:26,432 And this technology isn't perfect. 564 00:30:26,882 --> 00:30:30,002 Um, but it's, you can't really, how are you gonna put it back in 565 00:30:30,002 --> 00:30:33,272 the bag once it's already set up and you already invested money and 566 00:30:33,272 --> 00:30:36,032 you say it's working and what now? 567 00:30:36,632 --> 00:30:36,752 You 568 00:30:36,752 --> 00:30:39,212 know, uh, they're saying all this. 569 00:30:39,212 --> 00:30:39,542 Yeah. 570 00:30:40,187 --> 00:30:43,277 Andy: Yeah, and then there's like these companies who are like, oh, you 571 00:30:43,277 --> 00:30:45,077 know, hey, we'll let you get started. 572 00:30:45,137 --> 00:30:49,277 We will waive the, the startup cost and that sort of stuff so that they 573 00:30:49,277 --> 00:30:52,637 don't have to go through county council meetings or city council meetings. 574 00:30:52,907 --> 00:30:56,357 There doesn't have to be like recorded minutes, that sort of stuff. 575 00:30:56,357 --> 00:30:59,387 It's like, Hey, we'll give you 12 months free, and you're already a year. 576 00:30:59,897 --> 00:31:03,977 At that point, you've got all of this data that's been collected and it's like, okay, 577 00:31:03,977 --> 00:31:05,357 well now you gotta start paying for it. 578 00:31:05,357 --> 00:31:07,817 So now we gotta start really telling people that, oh, this 579 00:31:07,817 --> 00:31:09,137 is a line item in the budget. 580 00:31:09,437 --> 00:31:10,517 This is what it really does. 581 00:31:10,517 --> 00:31:13,157 And oh, by the way, it's already been implemented for the past 12 months. 582 00:31:13,397 --> 00:31:15,587 Your life wasn't, you know, turned upside down. 583 00:31:15,587 --> 00:31:17,357 So of course it's gonna be okay. 584 00:31:17,777 --> 00:31:20,807 And it's like, you know, once you have that infrastructure set up, like you said, 585 00:31:20,807 --> 00:31:22,907 what's the next upgrade that comes along? 586 00:31:23,267 --> 00:31:26,237 And are they gonna, are they really gonna tell us about it? 587 00:31:26,267 --> 00:31:27,227 Or, or what? 588 00:31:27,622 --> 00:31:31,732 It's one thing to be like a resident in Seattle when you know, oh, this crime 589 00:31:31,732 --> 00:31:35,812 center is there, but if you're a tourist and you come in, do you waive your rights 590 00:31:35,812 --> 00:31:42,502 to, to have your likeness used and the data collected about you just for going to 591 00:31:42,772 --> 00:31:44,932 Seattle on vacation, that sort of thing. 592 00:31:45,232 --> 00:31:47,932 So there's a man, there's a whole lot to consider there. 593 00:31:48,142 --> 00:31:52,522 And again, the whole, like, you don't have the uh right to privacy in public. 594 00:31:52,522 --> 00:31:53,212 I understand that. 595 00:31:53,212 --> 00:31:56,782 So lemme just go ahead and say that, but yeah, it's still, it's still concerning. 596 00:31:57,837 --> 00:31:58,187 Dylan: Yeah. 597 00:31:58,277 --> 00:31:58,517 Yep. 598 00:31:58,547 --> 00:32:02,027 And something that I think is, I'm learning as I get 599 00:32:02,027 --> 00:32:03,497 older especially, is the. 600 00:32:04,847 --> 00:32:10,187 How information is shared is not, uh, efficient by any means 601 00:32:10,187 --> 00:32:10,967 in any city. 602 00:32:11,387 --> 00:32:14,507 You know, you go to these city council meetings and they're hours 603 00:32:14,507 --> 00:32:18,617 and hours long and something might just be squeezed at the end, you know? 604 00:32:18,857 --> 00:32:25,157 Um, there's just so much around what's happening and it's easy to be 605 00:32:25,157 --> 00:32:26,777 distracted about all these things. 606 00:32:27,047 --> 00:32:30,317 Taylor and Travis getting engaged, you know, all these things going on. 607 00:32:30,797 --> 00:32:33,917 There's all these things battling for our attention and. 608 00:32:34,502 --> 00:32:38,582 It's really difficult to stay in the know, and it's really hard 'cause some, you 609 00:32:38,582 --> 00:32:44,372 know, I have a marketing background and seeing how cities, excuse me, um, how they 610 00:32:44,372 --> 00:32:46,592 communicate updates and things like that. 611 00:32:46,832 --> 00:32:47,732 They're not the best 612 00:32:47,822 --> 00:32:49,442 at updating things like that. 613 00:32:49,742 --> 00:32:53,372 Uh, anything going on really, even if it's just an event coming up, sometimes 614 00:32:53,372 --> 00:32:55,772 they'll hear about it after the fact and I didn't even know that happened 615 00:32:56,222 --> 00:32:59,822 because, uh, they maybe aren't the best at getting that out there. 616 00:33:00,302 --> 00:33:00,782 Um, 617 00:33:00,977 --> 00:33:02,447 Andy: And it may not even be malicious. 618 00:33:02,447 --> 00:33:05,657 It's just like you said, it's just this big network you gotta work through. 619 00:33:05,957 --> 00:33:08,747 So it's not like we're saying that the, oh, everybody's out to get you. 620 00:33:08,747 --> 00:33:12,227 It's just like, well, we've seen how they market. 621 00:33:12,257 --> 00:33:14,327 Just the stuff that they're doing now. 622 00:33:14,687 --> 00:33:15,767 What's it gonna be like? 623 00:33:15,767 --> 00:33:17,447 What is something a little bit more complex? 624 00:33:17,912 --> 00:33:21,632 Dylan: And they go, oh, well I didn't know the city didn't want us to do 625 00:33:21,632 --> 00:33:22,142 this. 626 00:33:22,442 --> 00:33:22,742 You know? 627 00:33:22,742 --> 00:33:24,092 No one told us they didn't want us to do it. 628 00:33:24,092 --> 00:33:26,042 We talked about it, and it's like, where did you talk about it? 629 00:33:26,042 --> 00:33:28,352 And if you seek these things out, sometimes. 630 00:33:28,922 --> 00:33:31,802 That becomes your job of like, you're, you're that guy that's 631 00:33:31,802 --> 00:33:35,282 like now researching all these things and you're trying to like 632 00:33:35,492 --> 00:33:37,082 be the, the fighter against this. 633 00:33:37,082 --> 00:33:41,492 It's, it's really difficult, I think, to someone to get into this. 634 00:33:41,702 --> 00:33:46,652 Um, but to know that it's going on and just to be aware of certain things, like 635 00:33:46,652 --> 00:33:49,747 what we're talking about this episode is, is just, I think, really important. 636 00:33:51,267 --> 00:33:51,687 Andy: Mm-hmm. 637 00:33:52,382 --> 00:33:55,082 So, you know, you talked about facial recognition a minute ago, 638 00:33:55,082 --> 00:33:59,282 and there's a lot of laws about, you know, banning facial recognition 639 00:33:59,282 --> 00:34:02,762 here and there in some locations, but there's now a new technology that's 640 00:34:02,762 --> 00:34:06,812 not tracking your face, it's actually tracking your personal movement style. 641 00:34:06,812 --> 00:34:07,292 Is that it? 642 00:34:08,042 --> 00:34:09,422 Dylan: Yeah, so. 643 00:34:10,382 --> 00:34:15,392 Down the casino rabbit hole I mentioned a minute ago, I, I don't know if it 644 00:34:15,392 --> 00:34:20,522 is where it originated, but it is a big part, I think in casinos using 645 00:34:20,612 --> 00:34:25,412 this gate tracking technology gate is, is the way your body moves, right? 646 00:34:25,412 --> 00:34:27,932 Everybody has a particular way they move. 647 00:34:28,112 --> 00:34:30,812 Now you can change the way you move, but it's hard to do that 648 00:34:30,812 --> 00:34:32,972 over time, uh, repeatedly. 649 00:34:33,532 --> 00:34:37,852 You know, you're gonna default to your natural movement style, uh, especially 650 00:34:37,852 --> 00:34:39,802 if we're talking like a long walk. 651 00:34:40,132 --> 00:34:45,022 Um, but your face, you could shave a mustache, you could wear a different 652 00:34:45,022 --> 00:34:46,732 hat, you could wear sunglasses. 653 00:34:46,732 --> 00:34:51,052 You can do these things that, you know, make it hard for facial 654 00:34:51,052 --> 00:34:56,512 recognition to identify you, but maybe pair that facial recognition or, or 655 00:34:56,512 --> 00:34:57,892 you don't even have access to that. 656 00:34:58,102 --> 00:35:01,732 It can identify the way your body moves and identify you that way. 657 00:35:02,482 --> 00:35:02,902 Um. 658 00:35:03,632 --> 00:35:07,652 Crazy to think about, but you have a unique way that you walk and 659 00:35:07,652 --> 00:35:09,032 that could be your identifier. 660 00:35:09,362 --> 00:35:14,342 And they're basically, uh, researching this now. 661 00:35:14,372 --> 00:35:16,712 I believe it was Michigan State University. 662 00:35:16,832 --> 00:35:20,762 Uh, I might have that university wrong, uh, but. 663 00:35:22,172 --> 00:35:27,452 They're, they were just funded a lot of money to nail this technology. 664 00:35:27,632 --> 00:35:31,982 And what I found out last night was that it's already been in use in casinos, uh, 665 00:35:31,982 --> 00:35:35,672 because card counters and things like that will come in under like different 666 00:35:35,732 --> 00:35:40,682 disguises, which make it hard for the casinos to, uh, track who's there. 667 00:35:40,777 --> 00:35:41,402 And they don't 668 00:35:41,402 --> 00:35:44,162 even, you know, and their, their whole thing is, uh. 669 00:35:45,032 --> 00:35:49,352 You know, if this person doesn't use a, a, player's card or something 670 00:35:49,352 --> 00:35:52,802 like that, like we, they, they always want to identify every single person 671 00:35:52,802 --> 00:35:57,182 that comes through there and attach a whole profile to that person so they 672 00:35:57,182 --> 00:35:57,992 know who they're dealing with. 673 00:35:57,992 --> 00:36:00,452 If it's a band person, uh, whoever it is. 674 00:36:00,782 --> 00:36:01,442 And so 675 00:36:02,132 --> 00:36:05,642 the face can basically only say so much these days. 676 00:36:05,642 --> 00:36:08,462 It's, it's really your whole body and how you go through life. 677 00:36:09,227 --> 00:36:10,337 Andy: Right in. 678 00:36:10,337 --> 00:36:14,357 Uh, when I talk to, you know, people like, uh, Greg Williams and 679 00:36:14,357 --> 00:36:16,557 Brian Marren at Arcadia Cognerati. 680 00:36:16,577 --> 00:36:21,797 They talk about how the, the faces, where the lies come from, that the rest of 681 00:36:21,797 --> 00:36:27,107 your body is actually way more honest, because you can control your face. 682 00:36:27,752 --> 00:36:30,782 When you lie because it's so close to your brain. 683 00:36:30,812 --> 00:36:34,262 But the further you get away from the brain, like your feet, your feet are 684 00:36:34,262 --> 00:36:38,252 more honest in an interrogation than your face is 'cause you think you can 685 00:36:38,252 --> 00:36:39,782 control that just a little bit better. 686 00:36:40,052 --> 00:36:45,362 And so it's just kind of a, a long held, you know, technique in, you know, um. 687 00:36:45,782 --> 00:36:48,782 Policing that your, your feet are more honest than your face. 688 00:36:48,782 --> 00:36:53,792 And I think that's kinda what this AI tool is picking up on is the real honesty 689 00:36:53,792 --> 00:36:58,112 of who you are as a person comes out in your gate more than it does, you 690 00:36:58,112 --> 00:37:00,662 know, the, the data points on your face. 691 00:37:01,442 --> 00:37:05,597 Dylan: Yeah, I, years ago, I have a personal training background, 692 00:37:05,597 --> 00:37:07,427 fitness background, like I. 693 00:37:08,717 --> 00:37:10,577 Spend a lot of time looking at bodies too. 694 00:37:10,577 --> 00:37:13,817 And it's something that's kind of inherent in my brain at this point, but just by 695 00:37:13,817 --> 00:37:18,107 seeing someone walk personally, I can tell about how much they're sitting. 696 00:37:18,317 --> 00:37:20,357 I can tell where their muscle imbalances are. 697 00:37:20,657 --> 00:37:25,487 I can tell, you know, how their knees, how their feet are pointed in or out. 698 00:37:25,907 --> 00:37:27,387 Uh, if they have an aligned body, which. 699 00:37:28,262 --> 00:37:32,732 These days, you know, you can draw pretty close conclusions of 700 00:37:32,732 --> 00:37:35,282 like what they do for a living just based on how they're walking. 701 00:37:36,032 --> 00:37:38,852 Um, and it can be really subtle too, you know, the 702 00:37:38,852 --> 00:37:43,322 knees pointing in a little bit, um, the feet, you know, and it's 703 00:37:43,322 --> 00:37:47,762 not like their body shape, although that could play a part of it. 704 00:37:47,762 --> 00:37:51,242 But really it's, it's from the hips down. 705 00:37:51,782 --> 00:37:55,652 Can say so much that, you know, we think like the whole body, it's like 706 00:37:55,652 --> 00:37:58,112 really sometimes all you just need is the hips and down and you can 707 00:37:58,352 --> 00:38:00,212 see how someone's walking there. 708 00:38:01,157 --> 00:38:02,987 Andy: Yeah, and I am sure like, you know, occupational 709 00:38:02,987 --> 00:38:04,637 therapists can do the same thing. 710 00:38:05,057 --> 00:38:08,207 But you know, Dylan, I pretty much just waddle everywhere that I go. 711 00:38:08,207 --> 00:38:09,282 What, what does that say about me? 712 00:38:11,017 --> 00:38:12,797 Dylan: Um, you 713 00:38:12,797 --> 00:38:15,237 might penguin, you might be part penguin. 714 00:38:15,287 --> 00:38:16,367 Andy: Yeah, I'll take that. 715 00:38:16,397 --> 00:38:18,017 Uh, I'll take that part, penguin. 716 00:38:18,377 --> 00:38:25,097 So, um, so Dylan, as we wrap up here, give me your prediction on what society 717 00:38:25,097 --> 00:38:31,367 is gonna look like one year from now, seeing how fast AI is progressing. 718 00:38:33,062 --> 00:38:38,432 Dylan: I think we're gonna get a clearer picture of what AI really 719 00:38:38,432 --> 00:38:40,292 is and how it will benefit us. 720 00:38:40,592 --> 00:38:46,142 To me, my way of rationalizing this technology that is 721 00:38:46,142 --> 00:38:48,092 moving at a hyper speed is. 722 00:38:49,367 --> 00:38:54,587 I try to not get caught up in thinking it's the best thing since my air fryer. 723 00:38:54,737 --> 00:38:57,917 Um, although the air fryer is really awesome, uh, and I don't 724 00:38:57,917 --> 00:39:00,887 think it's absolutely like, don't pay attention to it. 725 00:39:00,887 --> 00:39:01,877 It's just a fad. 726 00:39:02,177 --> 00:39:04,217 I think the truth is somewhere right in the middle. 727 00:39:04,247 --> 00:39:07,007 I think it's, if you, if we take the extreme and we take, it's 728 00:39:07,067 --> 00:39:09,677 nothing, it's probably somewhere to me right in the middle. 729 00:39:09,947 --> 00:39:11,507 So it'll have a lot of benefits. 730 00:39:11,777 --> 00:39:16,037 There'll be a lot of hype around it, a lot of scary things around it. 731 00:39:16,037 --> 00:39:17,897 There's already that, that's happening. 732 00:39:17,897 --> 00:39:18,377 I'm not like. 733 00:39:19,202 --> 00:39:22,232 Obviously predicting that, that that's true, but I think there'll be some 734 00:39:22,232 --> 00:39:26,312 of that, that that goes away because they realize people were actually 735 00:39:26,312 --> 00:39:32,822 better at these certain tasks than just outsourcing it to AI because of reasons 736 00:39:32,822 --> 00:39:34,562 that we're not foreseeing right now. 737 00:39:34,892 --> 00:39:39,392 So I think it's gonna be absolutely amazing and not 738 00:39:39,392 --> 00:39:40,772 as amazing as we had hoped. 739 00:39:41,282 --> 00:39:44,432 And somewhere right in the middle there, we'll find that. 740 00:39:44,942 --> 00:39:45,872 Man, we can't. 741 00:39:46,412 --> 00:39:49,262 Um, I can't believe we didn't have this before, like I had 742 00:39:49,262 --> 00:39:50,792 to grow up with without this. 743 00:39:51,272 --> 00:39:55,562 And I think for those of us that did we'll be really thankful 744 00:39:55,622 --> 00:39:56,882 that we did grow up without it. 745 00:39:56,942 --> 00:40:01,952 'cause we still have some senses that are just inherent that the 746 00:40:01,952 --> 00:40:03,722 younger generation just can't have. 747 00:40:04,367 --> 00:40:04,697 Andy: Right. 748 00:40:05,267 --> 00:40:10,727 You know, and it was funny because my son was studying for a math test and, and 749 00:40:10,727 --> 00:40:11,957 I was like, Hey man, you need to study. 750 00:40:11,957 --> 00:40:12,827 What are you gonna do? 751 00:40:12,827 --> 00:40:13,937 And it's like, well, I'll look at my notes. 752 00:40:13,937 --> 00:40:16,937 And then he was like, you know what, I'm gonna take my notes and plug them into 753 00:40:16,937 --> 00:40:19,607 Copilot and tell it to make a quiz for me. 754 00:40:20,192 --> 00:40:22,352 And I'm like, wow. 755 00:40:22,382 --> 00:40:25,292 Like I, that's something I never would've thought about. 756 00:40:25,442 --> 00:40:29,402 Also don't know if I would, you know, me at his age would've cared 757 00:40:29,402 --> 00:40:31,472 to do that, so props to him for that. 758 00:40:31,862 --> 00:40:35,102 But it's also like, wow, that's, that's a really good learning tool. 759 00:40:35,372 --> 00:40:37,202 But you know, you were talking about how. 760 00:40:37,637 --> 00:40:39,737 AI can't completely replace a human. 761 00:40:39,737 --> 00:40:43,547 And I think sometimes soon we're gonna have a, uh, we're gonna have 762 00:40:43,547 --> 00:40:46,937 some sort of event that happens where we realize, you know what? 763 00:40:47,387 --> 00:40:50,447 We kinda went too fast, too quick with this AI stuff. 764 00:40:50,447 --> 00:40:52,127 We need to scale it back a little bit. 765 00:40:52,127 --> 00:40:56,837 There's gonna be a little bit of a, a, a, a recession in the AI economy. 766 00:40:57,017 --> 00:40:57,707 If you will. 767 00:40:57,707 --> 00:41:00,257 We're gonna get to that point at some, at some time, where we realize, 768 00:41:00,287 --> 00:41:02,267 okay, we went a little too far. 769 00:41:02,357 --> 00:41:04,337 You know, kinda like with the internet, I feel like at some 770 00:41:04,337 --> 00:41:07,067 point we were like, well, you know, this is, this has gone too far. 771 00:41:07,067 --> 00:41:08,207 Social media's gone too far. 772 00:41:08,207 --> 00:41:12,437 We need to, we need to bring humans back into our lives, into our 773 00:41:12,437 --> 00:41:14,147 daily tasks and that sort of thing. 774 00:41:14,537 --> 00:41:15,167 Um, 775 00:41:15,497 --> 00:41:16,427 that's, that's just my thought. 776 00:41:17,597 --> 00:41:20,627 Dylan: And I don't think it will look like all or nothing. 777 00:41:20,627 --> 00:41:21,557 It's easy, especially 778 00:41:21,557 --> 00:41:25,487 with social media, it's like, you know, there'll be, uh, a thing where it's 779 00:41:25,487 --> 00:41:26,807 like, well, no one's using that anymore. 780 00:41:26,837 --> 00:41:31,007 'cause back in the day, oh, you know, that sounds weird to say, but back in 781 00:41:31,007 --> 00:41:32,717 the day it was like all or nothing. 782 00:41:32,717 --> 00:41:36,377 You know, like we don't use vinyl records anymore, we use cassettes, and 783 00:41:36,377 --> 00:41:39,347 then no one uses vinyl records and then it moves on to the next thing. 784 00:41:39,407 --> 00:41:41,567 But then these days with technology, it's like. 785 00:41:41,862 --> 00:41:45,312 There's always, there's, it's, it's more enmeshed, you know, there's always like 786 00:41:45,312 --> 00:41:47,172 gonna be the people that do this or that. 787 00:41:47,592 --> 00:41:49,632 And uh, yeah. 788 00:41:49,632 --> 00:41:54,192 But I, I think, like you said, you know, it's gonna be how we 789 00:41:54,192 --> 00:41:57,642 live with this technology that's gonna really change shape. 790 00:41:57,642 --> 00:41:58,752 It has to change shape. 791 00:41:58,752 --> 00:42:02,142 'cause like right now it's this brand new thing that we're all like, what? 792 00:42:02,322 --> 00:42:02,742 Who? 793 00:42:02,862 --> 00:42:04,692 I didn't know that What's going on? 794 00:42:04,932 --> 00:42:07,272 You know, there's a lot of stuff we don't know and there's a lot of stuff. 795 00:42:07,272 --> 00:42:08,022 I'll just say this too. 796 00:42:08,022 --> 00:42:08,622 I think it's important. 797 00:42:09,012 --> 00:42:11,952 Is people think they should know something or they're out of the loop. 798 00:42:12,522 --> 00:42:16,512 The people that are making this stuff are, are feeling outta the loop too. 799 00:42:16,542 --> 00:42:20,982 Everybody is feeling in a way out of the loop because it's moving so 800 00:42:20,982 --> 00:42:22,272 fast and there's so much going on. 801 00:42:22,542 --> 00:42:26,262 So if you feel like I just can't keep up with this stuff, you don't 802 00:42:26,262 --> 00:42:27,822 really need to keep up with it. 803 00:42:27,852 --> 00:42:34,752 Um, but just know that, you know, there are crazy things happening and, um. 804 00:42:35,267 --> 00:42:39,317 You know, choose wisely what you do, choose to take in, because there's a 805 00:42:39,317 --> 00:42:41,117 lot you could be, uh, learning about. 806 00:42:41,117 --> 00:42:44,207 And some of it, it might just be completely, uh, misinformation 807 00:42:44,207 --> 00:42:48,797 or hysteria drive driven to, uh, maximize someone else's profits. 808 00:42:49,442 --> 00:42:50,522 Andy: Yeah, absolutely. 809 00:42:50,522 --> 00:42:51,272 Very well said. 810 00:42:51,452 --> 00:42:52,112 Very well said. 811 00:42:52,472 --> 00:42:55,052 So Dylan, thank you so much for, for talking with me today. 812 00:42:55,292 --> 00:42:57,122 I know people are gonna wanna know more about you. 813 00:42:57,122 --> 00:43:01,892 Where can they find you and your, um, your AI videos online? 814 00:43:02,507 --> 00:43:06,052 Dylan: Yeah, and just to say that too, I'm not AI 815 00:43:07,037 --> 00:43:07,217 Andy: Yeah. 816 00:43:07,307 --> 00:43:07,487 Yeah. 817 00:43:07,487 --> 00:43:08,627 You are a real person. 818 00:43:09,002 --> 00:43:09,382 You are, 819 00:43:09,437 --> 00:43:11,717 Dylan: I get multiple messages. 820 00:43:12,022 --> 00:43:13,552 And comments every week that are 821 00:43:13,552 --> 00:43:15,052 like, are you Ai? 822 00:43:15,052 --> 00:43:17,032 I, I need to start screenshotting them more. 823 00:43:17,212 --> 00:43:19,672 'cause I'll, I'll have a library of people saying like, are you ai? 824 00:43:19,942 --> 00:43:21,352 I'm not, you can find me. 825 00:43:21,442 --> 00:43:27,022 Uh, if you use TikTok or Instagram, I'm @thedylanschmidt and, uh, or just 826 00:43:27,022 --> 00:43:28,622 go to my website, dylanschmidt.com. 827 00:43:29,002 --> 00:43:35,182 Uh, but I do my best to make sure every video I make is very to the point. 828 00:43:35,512 --> 00:43:40,192 Uh, I ruthlessly edit what I say in videos, which. 829 00:43:40,647 --> 00:43:41,997 They're really like well thought out. 830 00:43:41,997 --> 00:43:44,517 And I put a lot of time into them, which I think is why people 831 00:43:44,517 --> 00:43:45,957 think I'm AI making the videos. 832 00:43:45,987 --> 00:43:47,637 'cause they're like, no one just talks like this. 833 00:43:47,667 --> 00:43:49,917 No, I don't talk like I do in the videos. 834 00:43:50,067 --> 00:43:52,917 It's because I really am purposeful and intentional 835 00:43:52,917 --> 00:43:55,317 behind every word I say in that. 836 00:43:55,377 --> 00:43:59,487 So, um, yeah, if you, if you want to catch me there, uh, 837 00:43:59,487 --> 00:44:00,182 that's where you can find me. 838 00:44:01,007 --> 00:44:01,397 Andy: Yeah. 839 00:44:01,607 --> 00:44:03,467 You know, it's funny 'cause I've had that happen too. 840 00:44:03,467 --> 00:44:06,857 I had some video that I did, you know, take off on, you know, 841 00:44:06,887 --> 00:44:09,947 Instagram got like a hundred thousand views or something like that. 842 00:44:10,247 --> 00:44:13,847 And then of course there's like three or four people are by, oh, he's ai. 843 00:44:14,087 --> 00:44:17,057 And I'm like, listen, AI ain't gonna make a face that looks like this. 844 00:44:17,057 --> 00:44:17,837 Are you kidding me? 845 00:44:19,097 --> 00:44:21,617 the people that are AI generated are good looking. 846 00:44:21,737 --> 00:44:22,937 They don't look like this. 847 00:44:23,267 --> 00:44:27,257 They, they don't look like, you know, you know, middle aged dad bod guy. 848 00:44:27,347 --> 00:44:27,767 They don't. 849 00:44:28,352 --> 00:44:28,772 So, 850 00:44:33,627 --> 00:44:37,652 Dylan: the, I don't even know what to say to that other than like, I, 851 00:44:37,652 --> 00:44:39,032 although I'm thinking, you know, yeah. 852 00:44:39,032 --> 00:44:41,372 If I was to create an AI person, I'm probably gonna create 853 00:44:41,372 --> 00:44:43,832 a jacked beautiful haircut. 854 00:44:44,287 --> 00:44:44,577 Andy: yeah. 855 00:44:44,907 --> 00:44:45,257 Right. 856 00:44:45,422 --> 00:44:47,432 Dylan: I'll be on, I'm not Yeah. 857 00:44:47,667 --> 00:44:50,942 It it, it's funny 'cause I was thinking like, how can I make it not look ai. 858 00:44:51,542 --> 00:44:53,642 Then I'm like, well, why am I, why would I do that? 859 00:44:53,642 --> 00:44:57,302 Like, why would I try to purposely, is that what we're coming to, you know? 860 00:44:57,332 --> 00:45:01,862 Um, it's, it's a strange world publishing on social media, that's for sure. 861 00:45:02,987 --> 00:45:04,727 Andy: Like, I appreciate people's skepticism. 862 00:45:04,847 --> 00:45:05,207 I do. 863 00:45:05,237 --> 00:45:09,797 'cause I tell people to be skeptical, but like, you know, look at me. 864 00:45:10,877 --> 00:45:12,437 Dylan, man, I appreciate you. 865 00:45:12,677 --> 00:45:16,097 Thank you so much for, for, for talking to me today and I look forward to, 866 00:45:16,157 --> 00:45:18,707 you know what else you're, what else you're gonna be coming up with, man. 867 00:45:18,707 --> 00:45:18,947 This is 868 00:45:19,147 --> 00:45:19,567 Dylan: Thanks. 869 00:45:21,758 --> 00:45:24,548 Andy: In the next 30 seconds, I'm gonna try to list everything. 870 00:45:24,548 --> 00:45:28,778 OmniWatch covers in their Elite Plan: dark web monitoring, credit 871 00:45:28,778 --> 00:45:33,323 monitoring and reports, AI scam check for emails and text, up to $2 872 00:45:33,323 --> 00:45:37,763 million in identity theft insurance, up to $50,000 in scam and ransomware 873 00:45:37,958 --> 00:45:43,568 protection, a VPN, antivirus and malware protection, home title monitoring. 874 00:45:43,898 --> 00:45:45,548 Okay, and there's actually more. 875 00:45:45,908 --> 00:45:47,138 But you get the point. 876 00:45:47,378 --> 00:45:52,598 All of that and more for 20 bucks a month, try OmniWatch today with a $1 seven day 877 00:45:52,598 --> 00:45:54,308 trial at the link in the show notes. 878 00:45:54,518 --> 00:45:57,128 It's one of the best values to protect your family. 879 00:46:01,048 --> 00:46:03,838 That's all we have for The Secure Family Podcast for today. 880 00:46:04,048 --> 00:46:05,998 Thanks again to Dylan for being on the show. 881 00:46:06,178 --> 00:46:10,048 For more on him, follow him on Instagram and TikTok with the username. 882 00:46:10,198 --> 00:46:11,518 The Dylan Schmidt. 883 00:46:12,178 --> 00:46:15,608 Take back your privacy and personal data with help from DeleteMe. 884 00:46:15,988 --> 00:46:19,888 Get 20% off of privacy plan when using the code Dad at checkout, 885 00:46:20,288 --> 00:46:23,878 DeleteMe is the official data removal service of The Secure Dad. 886 00:46:24,673 --> 00:46:28,393 If you enjoy this episode or learned something new today, I'd be grateful 887 00:46:28,393 --> 00:46:32,233 if you'd follow the show, subscribe on your favorite podcast platform, 888 00:46:32,383 --> 00:46:33,883 or leave a five star review. 889 00:46:35,083 --> 00:46:38,443 OmniWatch is a scam and identity protection service that monitors 890 00:46:38,443 --> 00:46:42,163 your data, alerts you to threats and backs you up with insurance. 891 00:46:42,493 --> 00:46:45,313 Try OmniWatch for seven days for only a dollar. 892 00:46:45,583 --> 00:46:47,473 Get started at the link in the show notes. 893 00:46:48,568 --> 00:46:50,578 Learn how to freeze your child's credit. 894 00:46:50,578 --> 00:46:54,748 With my free guide, I share why this is important, how the process 895 00:46:54,748 --> 00:46:58,618 works, and help you gather all of the information that you're going to need. 896 00:46:59,008 --> 00:47:02,428 This guide is presented by OmniWatch and you can download it for free 897 00:47:02,488 --> 00:47:03,958 at the link in the show notes. 898 00:47:04,678 --> 00:47:06,748 If you'd like to know more about The Secure Dad, join 899 00:47:06,748 --> 00:47:08,218 me on Instagram and TikTok. 900 00:47:08,488 --> 00:47:11,278 My username for both platforms is The Secure Dad. 901 00:47:11,698 --> 00:47:15,598 I'm Andy Murphy reminding you that nobody is gonna generate 902 00:47:15,598 --> 00:47:17,608 an AI face that looks like mine.