1 00:00:00,480 --> 00:00:03,920 Speaker 1: You're listening to KFI AM sixty on demand. 2 00:00:04,800 --> 00:00:07,160 Speaker 2: It was a big day where the President claims he's 3 00:00:07,200 --> 00:00:12,559 Speaker 2: following through in his threats. Trump administration officials preparing sweeping 4 00:00:12,640 --> 00:00:18,439 Speaker 2: layoffs across all those liberal federal agencies as part of 5 00:00:18,480 --> 00:00:25,119 Speaker 2: the broader plan to shrink the government. Some are describing 6 00:00:25,120 --> 00:00:28,000 Speaker 2: this as one of the largest federal downsizing pushes in decades, 7 00:00:28,080 --> 00:00:32,239 Speaker 2: or at least in months. It could affect tens of 8 00:00:32,240 --> 00:00:35,840 Speaker 2: thousands of employees. Supporters say they're cutting bureaucracy. Critics say, 9 00:00:35,880 --> 00:00:39,800 Speaker 2: now you're gutting essentials. Oh, it's the same arguments we 10 00:00:39,880 --> 00:00:43,800 Speaker 2: had with DOJE. Here's what we know about it. The 11 00:00:43,840 --> 00:00:47,320 Speaker 2: president will fire people, people will sue, people will get 12 00:00:47,360 --> 00:00:49,479 Speaker 2: their jobs back. Then they're gonna get laid off. Then 13 00:00:49,479 --> 00:00:51,520 Speaker 2: they're gonna sue, then they're gonna get their jobs back. 14 00:00:53,240 --> 00:00:53,640 Speaker 3: It's a. 15 00:00:55,400 --> 00:00:59,680 Speaker 2: Giant wisdem time money, but it makes for wonderful political theater. 16 00:01:00,480 --> 00:01:03,480 Speaker 4: Reporting the White House official and telling me tonight that 17 00:01:03,520 --> 00:01:06,160 Speaker 4: thousands of federal employees are being fired, and we're just 18 00:01:06,200 --> 00:01:09,560 Speaker 4: getting that all confirmed. These new numbers confirmed in a 19 00:01:09,640 --> 00:01:14,600 Speaker 4: DOJ court filing. It specifies seven federal agencies conducted a 20 00:01:14,640 --> 00:01:19,800 Speaker 4: reduction in force today, firing over four thousand federal employees. Wow, 21 00:01:20,360 --> 00:01:22,320 Speaker 4: if we take a closer look, here at the numbers 22 00:01:22,319 --> 00:01:26,600 Speaker 4: at the agencies, the Education, Energy, Commerce, Department of Homeland Security, 23 00:01:26,680 --> 00:01:28,640 Speaker 4: also Housing an Urban Development department. 24 00:01:29,000 --> 00:01:34,360 Speaker 2: I'm kind of surprise they cut anybody from DHS. It 25 00:01:34,400 --> 00:01:38,720 Speaker 2: doesn't surprise me at Energy and Hud got cut like 26 00:01:39,280 --> 00:01:42,560 Speaker 2: doesn't that seem like the sort of silly nonsense that 27 00:01:42,760 --> 00:01:45,399 Speaker 2: Americans don't need. We certainly don't need any sort of 28 00:01:45,520 --> 00:01:48,280 Speaker 2: energy planning. Not with these data centers. They're going to 29 00:01:48,320 --> 00:01:50,200 Speaker 2: take care of everything and use up all the power. 30 00:01:50,240 --> 00:01:53,640 Speaker 2: We don't need any of that regulation. Be damned and Hud, 31 00:01:53,760 --> 00:01:55,760 Speaker 2: why you want to make sure that people have homes? 32 00:01:55,760 --> 00:01:56,840 Speaker 3: Not in my America. 33 00:01:57,640 --> 00:01:59,960 Speaker 2: But I am surprised that Trump would cut from dha 34 00:02:00,120 --> 00:02:01,160 Speaker 2: US firings. 35 00:02:01,200 --> 00:02:04,280 Speaker 4: Those range from around one hundred to five hundred employees. 36 00:02:04,320 --> 00:02:05,760 Speaker 4: You see that on your screen. 37 00:02:05,480 --> 00:02:07,840 Speaker 3: There, it's radio. I can't see anything on the screen. 38 00:02:08,680 --> 00:02:11,839 Speaker 4: Well hh s. The Health and Human Services Department cut 39 00:02:11,919 --> 00:02:14,560 Speaker 4: up to twelve hundred jobs now the largest. 40 00:02:14,600 --> 00:02:15,720 Speaker 3: Now that stands to reason. 41 00:02:15,800 --> 00:02:18,720 Speaker 2: Right, one thing that we know about this country is 42 00:02:18,720 --> 00:02:26,000 Speaker 2: we don't need health or human services. It's not my job. 43 00:02:26,840 --> 00:02:28,720 Speaker 2: My job is not to make sure that you live 44 00:02:29,320 --> 00:02:39,160 Speaker 2: and don't die, which sounds like the same thing but. 45 00:02:41,560 --> 00:02:42,240 Speaker 3: Could be. 46 00:02:43,680 --> 00:02:48,200 Speaker 2: More nuanced. It's not my job to do that. Why 47 00:02:48,200 --> 00:02:50,000 Speaker 2: would my tax dollars go to such a thing? 48 00:02:50,320 --> 00:02:51,120 Speaker 3: What are you gonna do with that? 49 00:02:51,919 --> 00:02:57,720 Speaker 2: Develop vaccines like RFK Junior said during his confirmation hearing No, No, 50 00:02:57,840 --> 00:03:00,440 Speaker 2: we're gonna cut it, and then we're gonna when we're 51 00:03:00,440 --> 00:03:03,560 Speaker 2: gonna stop vaccines like RFK Junior did once he got 52 00:03:03,600 --> 00:03:05,000 Speaker 2: into the position he's in. 53 00:03:05,680 --> 00:03:07,239 Speaker 3: That's the America we're in now. 54 00:03:07,360 --> 00:03:11,280 Speaker 4: Put though, impacted the Treasury Department with over four fourteen 55 00:03:11,400 --> 00:03:15,359 Speaker 4: hundred employees fired. Here is the president explaining, Oh, we. 56 00:03:15,320 --> 00:03:17,680 Speaker 2: Cut the Treasury Department. Does that mean we don't have 57 00:03:17,680 --> 00:03:22,320 Speaker 2: to turn in our taxes? We cut Treasury? I think 58 00:03:22,360 --> 00:03:24,400 Speaker 2: there were some IRS cuts. Does that mean we don't 59 00:03:24,440 --> 00:03:25,320 Speaker 2: have to do taxes now? 60 00:03:26,800 --> 00:03:27,680 Speaker 3: Oh? This is great? 61 00:03:28,880 --> 00:03:31,480 Speaker 2: I mean what I even use the taxes for? Not 62 00:03:31,520 --> 00:03:36,000 Speaker 2: like I can get any sort of Freddie Mac Fanny May, 63 00:03:36,360 --> 00:03:40,520 Speaker 2: Fanny Mack and Freddie May. You know they swap. We 64 00:03:40,520 --> 00:03:42,280 Speaker 2: wouldn't even need taxes any longer. 65 00:03:42,600 --> 00:03:44,320 Speaker 3: This is great. I love it. 66 00:03:44,480 --> 00:03:50,040 Speaker 2: No more taxes, everybody, No more taxes and since the 67 00:03:50,040 --> 00:03:53,680 Speaker 2: government shut down. But we're mandating that the that the 68 00:03:54,080 --> 00:03:57,560 Speaker 2: military show up for work even though we don't pay them. 69 00:03:57,920 --> 00:04:01,840 Speaker 3: This is saving us a fortune. We should have more 70 00:04:01,880 --> 00:04:02,240 Speaker 3: of this. 71 00:04:03,160 --> 00:04:05,240 Speaker 2: Mark. What's that called when you get somebody and you 72 00:04:05,320 --> 00:04:07,440 Speaker 2: and you force them to work for you, but you 73 00:04:07,480 --> 00:04:08,200 Speaker 2: don't pay them. 74 00:04:08,320 --> 00:04:09,920 Speaker 5: I feel like there's a word for that, and it's 75 00:04:09,920 --> 00:04:11,320 Speaker 5: just it's on the tip of my tongue. 76 00:04:11,600 --> 00:04:14,040 Speaker 2: There's precedent in this country for it. I just have 77 00:04:14,120 --> 00:04:17,680 Speaker 2: to remember what that is. Yeah, we just we just 78 00:04:17,960 --> 00:04:22,320 Speaker 2: we'll just grab people from their homes, will we'll we'll 79 00:04:22,600 --> 00:04:26,080 Speaker 2: we'll take them to wherever we need them to do 80 00:04:26,160 --> 00:04:29,240 Speaker 2: the work, and we'll just make them work for us 81 00:04:29,480 --> 00:04:30,000 Speaker 2: for free. 82 00:04:30,920 --> 00:04:33,160 Speaker 3: That would really save us a lot of money in taxes. 83 00:04:34,080 --> 00:04:36,400 Speaker 3: In fact, think of the economic boom. 84 00:04:36,080 --> 00:04:37,880 Speaker 2: That that would make for the people who actually own 85 00:04:37,960 --> 00:04:42,040 Speaker 2: those companies that are you know what's again? 86 00:04:42,240 --> 00:04:45,120 Speaker 3: Uh uh? When they're when the workers. 87 00:04:45,160 --> 00:04:48,520 Speaker 2: Are there but not getting paid, but they can't go home, 88 00:04:49,040 --> 00:04:52,159 Speaker 2: and if they even try to go home, you know, 89 00:04:52,279 --> 00:04:54,839 Speaker 2: if they try to go home, I mean we could 90 00:04:54,839 --> 00:04:58,839 Speaker 2: probably like shackle their legs to a giant log or something. 91 00:04:59,040 --> 00:05:01,560 Speaker 5: Listen, Chris, work that makes us free. I think I 92 00:05:01,600 --> 00:05:03,560 Speaker 5: saw that on a sign in Germany somewhere. 93 00:05:03,640 --> 00:05:10,240 Speaker 3: Yes, yes, our bias to mocks fry. Thank you. We're 94 00:05:10,279 --> 00:05:11,839 Speaker 3: finally catching up to the rest of the warld. 95 00:05:12,000 --> 00:05:16,320 Speaker 4: Yeah, finally there is the President explaining moments ago the 96 00:05:16,360 --> 00:05:17,600 Speaker 4: reasoning behind these cuts. 97 00:05:18,640 --> 00:05:20,960 Speaker 1: It'll be a lot, and we'll announce the numbers over 98 00:05:21,000 --> 00:05:22,720 Speaker 1: the next couple of days, but it'll be a lot 99 00:05:22,760 --> 00:05:24,839 Speaker 1: of people, all because of the Democrats. 100 00:05:25,200 --> 00:05:29,280 Speaker 3: There you go, Democrats, Why did you make him do that? 101 00:05:30,800 --> 00:05:36,760 Speaker 2: Why did you? Why did you make him hurt people? Democrats? 102 00:05:37,960 --> 00:05:38,720 Speaker 1: Why what? 103 00:05:39,040 --> 00:05:39,640 Speaker 3: Democrats? 104 00:05:39,800 --> 00:05:42,520 Speaker 2: Why did you do things that the President didn't like 105 00:05:42,600 --> 00:05:46,160 Speaker 2: that you knew was going to make him seek vengeance. 106 00:05:46,560 --> 00:05:51,839 Speaker 2: You did this, You did it, and there's no excuse. 107 00:05:52,520 --> 00:05:57,080 Speaker 2: And you will not be welcomed at the shelter. You 108 00:05:57,120 --> 00:06:00,880 Speaker 2: will not be given safe passage. You will be sent 109 00:06:01,120 --> 00:06:05,000 Speaker 2: right back right back to the White House of your abuser. 110 00:06:05,200 --> 00:06:08,159 Speaker 3: That's what you will do. And the more you push him, 111 00:06:08,440 --> 00:06:09,760 Speaker 3: the more people that. 112 00:06:09,800 --> 00:06:12,479 Speaker 2: He's going to fire, unless he needs them to work 113 00:06:12,520 --> 00:06:14,719 Speaker 2: for him, in which case they will not be fired. 114 00:06:14,920 --> 00:06:17,040 Speaker 2: They will be made to show up for work but 115 00:06:17,120 --> 00:06:19,880 Speaker 2: will not be paid. And if they try to escape, 116 00:06:19,880 --> 00:06:25,160 Speaker 2: we will shackle them and then if another company or 117 00:06:25,240 --> 00:06:29,400 Speaker 2: another government agency wants that person or feels like they 118 00:06:29,480 --> 00:06:34,520 Speaker 2: need that person to do work in their company or sector, 119 00:06:34,960 --> 00:06:40,360 Speaker 2: then they can compensate us accordingly, and we will then 120 00:06:40,880 --> 00:06:44,160 Speaker 2: sell the services of that individual to the other company, 121 00:06:44,160 --> 00:06:46,400 Speaker 2: where they will then be moved whether they like it 122 00:06:46,520 --> 00:06:52,280 Speaker 2: or not, and put in that service. And if they 123 00:06:52,279 --> 00:06:53,640 Speaker 2: think they're going to vote their way out of this, 124 00:06:54,400 --> 00:06:56,479 Speaker 2: we will not give them any sort of right to vote, 125 00:06:56,560 --> 00:06:59,120 Speaker 2: or if we do, at the very least will give 126 00:06:59,160 --> 00:07:01,600 Speaker 2: them like three fifths of a vote because we can't 127 00:07:01,600 --> 00:07:04,200 Speaker 2: have them voting for their own freedom. I think that's fair. 128 00:07:05,720 --> 00:07:09,480 Speaker 2: Things are shaping up well. This is going over splendidly. 129 00:07:10,680 --> 00:07:17,480 Speaker 2: Is there any way that anyone who's not rabid sees 130 00:07:17,560 --> 00:07:21,840 Speaker 2: this as the Democrat's fault? This is not going to 131 00:07:21,840 --> 00:07:25,040 Speaker 2: play out well in the margins. No one's going to 132 00:07:25,040 --> 00:07:27,440 Speaker 2: look at this and say, oh, the government shut down, 133 00:07:27,760 --> 00:07:29,240 Speaker 2: even if you were blaming the Democrats. 134 00:07:29,280 --> 00:07:32,720 Speaker 3: And I think I think the Democrats are the ones 135 00:07:32,720 --> 00:07:34,640 Speaker 3: who are or who are stop sticking this. 136 00:07:36,280 --> 00:07:38,160 Speaker 2: Budget here. And I know I'm actually in the minority 137 00:07:38,160 --> 00:07:39,680 Speaker 2: on this. I know that the polls say that most 138 00:07:39,680 --> 00:07:41,840 Speaker 2: people are blaming the president and the Republicans. 139 00:07:42,280 --> 00:07:43,800 Speaker 3: But even if you think that the. 140 00:07:43,760 --> 00:07:47,520 Speaker 2: Democrats are responsible for it, there is nobody that's going 141 00:07:47,560 --> 00:07:50,880 Speaker 2: to say, well, the Democrats fired four thousand people. Because 142 00:07:50,920 --> 00:07:54,960 Speaker 2: the Democrats didn't fire four thousand people. The President fired 143 00:07:54,960 --> 00:07:59,920 Speaker 2: four thousand people. That's like saying Elon Musk is running doge. 144 00:08:00,040 --> 00:08:04,679 Speaker 2: Can you believe Chuck Schumer doged everybody? No, it doesn't 145 00:08:04,720 --> 00:08:08,440 Speaker 2: work that way, and nobody's buying it. Meanwhile, you do 146 00:08:08,520 --> 00:08:11,119 Speaker 2: have troops that want to get paid, and you've got 147 00:08:11,760 --> 00:08:17,960 Speaker 2: family members who need those paychecks. ABC seven was highlighting 148 00:08:18,800 --> 00:08:23,200 Speaker 2: a se span a conversation that the House Speaker Mike 149 00:08:23,240 --> 00:08:27,560 Speaker 2: Johnson was having and a military mom pleaded. 150 00:08:27,120 --> 00:08:28,000 Speaker 3: With him personally. 151 00:08:28,080 --> 00:08:31,480 Speaker 6: This morning, new pressure on Republicans in the government shutdown 152 00:08:31,520 --> 00:08:34,400 Speaker 6: as federal workers face a second week without pay. 153 00:08:34,640 --> 00:08:37,520 Speaker 7: As a Republican, I'm very disappointed in my party, and 154 00:08:37,559 --> 00:08:40,000 Speaker 7: I'm very disappointed in you, because you do have the 155 00:08:40,040 --> 00:08:42,800 Speaker 7: power to call the House back. You did that or 156 00:08:42,920 --> 00:08:45,000 Speaker 7: you refuse to do that just for a show. 157 00:08:45,760 --> 00:08:49,920 Speaker 2: This is a Republican calling c SPAN, which is still 158 00:08:49,920 --> 00:08:52,800 Speaker 2: on the air until President Trump hears about this, and 159 00:08:53,080 --> 00:08:56,559 Speaker 2: telling Mike Johnson, Dude. 160 00:08:57,080 --> 00:09:01,319 Speaker 7: I'm begging you to pass this legislation Mike hits could die. 161 00:09:01,480 --> 00:09:04,400 Speaker 6: House Speaker Mike Johnson faced fierce criticism on Live TV 162 00:09:04,520 --> 00:09:07,160 Speaker 6: on Thursday as a woman claiming to be a military 163 00:09:07,200 --> 00:09:09,880 Speaker 6: spouse accuses him of putting her children at risk. 164 00:09:10,320 --> 00:09:12,920 Speaker 7: You could stop this and you could be the one 165 00:09:13,080 --> 00:09:16,040 Speaker 7: that could say military is getting paid. And I think 166 00:09:16,080 --> 00:09:18,880 Speaker 7: that it is awful and the audacity of someone who 167 00:09:18,920 --> 00:09:22,320 Speaker 7: makes six figures a year to do this to military family. 168 00:09:22,960 --> 00:09:28,360 Speaker 3: Wow, that hits hard. That hits hard. 169 00:09:30,520 --> 00:09:34,880 Speaker 2: That's probably going to be used in a number of commercials. 170 00:09:35,360 --> 00:09:41,640 Speaker 2: Just just predicting here, thinking that's going to happen. Deportations 171 00:09:41,640 --> 00:09:45,439 Speaker 2: continue on. We've got We've got, of course, that the 172 00:09:45,520 --> 00:09:48,160 Speaker 2: National Guard from Texas is ready to enforce the. 173 00:09:48,160 --> 00:09:51,000 Speaker 3: Law in in tech Oh no, not in Texas. 174 00:09:51,120 --> 00:09:54,760 Speaker 2: No, the Texas National Guard is ready to enforce the 175 00:09:54,840 --> 00:10:01,920 Speaker 2: law in not Texas, but in Texas. They just deported 176 00:10:01,960 --> 00:10:06,400 Speaker 2: somebody who got a huge tie to a Republican president. 177 00:10:06,480 --> 00:10:08,440 Speaker 3: I'll tell you who that is next. I'm Chris Maryldon. 178 00:10:08,640 --> 00:10:11,960 Speaker 1: You're listening to KFI AM sixty on demand. 179 00:10:12,080 --> 00:10:13,040 Speaker 3: You know what I did last year? 180 00:10:13,040 --> 00:10:15,000 Speaker 2: You remember when we were running those ads for Bartiesian 181 00:10:16,080 --> 00:10:19,120 Speaker 2: I finally I got one really yeah, we're running for 182 00:10:19,360 --> 00:10:22,160 Speaker 2: you know, they were advertising with us a lot last 183 00:10:22,320 --> 00:10:24,240 Speaker 2: last Christmas time or whatever. 184 00:10:24,280 --> 00:10:26,000 Speaker 5: And so the premise of that was, if you're too 185 00:10:26,080 --> 00:10:28,200 Speaker 5: lazy to make a cocktail on your own, here's a 186 00:10:28,200 --> 00:10:30,040 Speaker 5: more expensive one that's. 187 00:10:29,880 --> 00:10:32,680 Speaker 3: Already it's basically Kourig for booze. 188 00:10:32,760 --> 00:10:35,439 Speaker 2: Yeah, that's right exactly. And so I got it. Well, 189 00:10:35,480 --> 00:10:37,360 Speaker 2: I say I got one. I got it for my wife. 190 00:10:37,800 --> 00:10:40,160 Speaker 2: And I was like, oh, I hope she likes this 191 00:10:41,720 --> 00:10:43,680 Speaker 2: home run with the wife. 192 00:10:43,800 --> 00:10:47,040 Speaker 3: Really. Oh, she loves it. What's the best one. 193 00:10:47,720 --> 00:10:50,720 Speaker 2: She'll do, like just margarita, she'll do for her. She 194 00:10:50,840 --> 00:10:53,760 Speaker 2: just likes it's super convenient. It's just super easy because 195 00:10:53,960 --> 00:10:56,320 Speaker 2: she likes, for instance, a Long Island iced tea, right, 196 00:10:56,440 --> 00:10:57,840 Speaker 2: that takes a while to make. 197 00:10:58,280 --> 00:10:58,640 Speaker 3: This thing. 198 00:10:58,640 --> 00:11:00,839 Speaker 2: You just put the pod and you're pushing a right, 199 00:11:01,320 --> 00:11:02,440 Speaker 2: and she's like, this is great. 200 00:11:02,520 --> 00:11:04,280 Speaker 3: I there's all these different drinks or whatever, and she 201 00:11:04,400 --> 00:11:05,280 Speaker 3: loves that. And so. 202 00:11:06,760 --> 00:11:08,520 Speaker 2: Turn into I don't want to turn into commercial. It's 203 00:11:08,520 --> 00:11:10,360 Speaker 2: not like they're paying me or anything. They should. Yeah, 204 00:11:10,360 --> 00:11:14,040 Speaker 2: but she loves it. And and plus it's like you're 205 00:11:14,120 --> 00:11:16,080 Speaker 2: right about everything you said about, Oh, I don't have 206 00:11:16,120 --> 00:11:16,920 Speaker 2: to make my own drink. 207 00:11:16,960 --> 00:11:19,120 Speaker 3: Now it's gonna do it. That's the ultimate laziness. Yeah. 208 00:11:19,120 --> 00:11:21,200 Speaker 2: But if I were to have everything I wanted for 209 00:11:21,280 --> 00:11:24,560 Speaker 2: Manhattan and then have everything I wanted for for Tequila Sunrise, 210 00:11:24,600 --> 00:11:26,600 Speaker 2: and have everything I wanted for you know what, you know, 211 00:11:26,800 --> 00:11:29,000 Speaker 2: you name it, then it's like, Okay, Now I gotta 212 00:11:29,040 --> 00:11:31,080 Speaker 2: have orange peels from over here. I gotta have bitters, 213 00:11:31,080 --> 00:11:33,240 Speaker 2: and then I gotta have it's there. 214 00:11:33,320 --> 00:11:36,400 Speaker 5: All you need from Manhattan is bourbon, some sweet fromouth, 215 00:11:36,480 --> 00:11:37,240 Speaker 5: and cherries. 216 00:11:37,280 --> 00:11:38,720 Speaker 3: That's it. It's not complicated. 217 00:11:38,800 --> 00:11:41,280 Speaker 2: Okay, But then I got cherries in my fridge, and 218 00:11:41,280 --> 00:11:43,320 Speaker 2: then I gotta have I gotta have like orange twists 219 00:11:43,400 --> 00:11:45,679 Speaker 2: for for my old fashion, and I gotta have you. 220 00:11:45,640 --> 00:11:47,960 Speaker 3: Know, it's just you know, it's just a lot. 221 00:11:48,120 --> 00:11:51,240 Speaker 5: Well, okay, I support whatever you need to make drinking 222 00:11:51,320 --> 00:11:52,520 Speaker 5: easy for easier for you. 223 00:11:52,720 --> 00:11:53,080 Speaker 3: It's fine. 224 00:11:53,160 --> 00:11:58,199 Speaker 2: Got me some, yeah, Mark, it got me some high fives. 225 00:11:58,360 --> 00:12:02,120 Speaker 2: Let me let me reiterate, it got me some. 226 00:12:02,480 --> 00:12:04,640 Speaker 5: If your old lady needs a long island to be 227 00:12:04,760 --> 00:12:06,200 Speaker 5: with you, more power to you both. 228 00:12:06,520 --> 00:12:09,559 Speaker 2: Does it matter to the end, result is the same 229 00:12:09,640 --> 00:12:15,079 Speaker 2: for me and me. Our love is built and mild alcoholism. 230 00:12:16,480 --> 00:12:20,240 Speaker 2: That's exactly what it is. Oh, there's news out of 231 00:12:20,280 --> 00:12:22,120 Speaker 2: the failed Republic of Texas. 232 00:12:22,800 --> 00:12:27,480 Speaker 3: If we might sad news, throw that beautiful bean footage. 233 00:12:27,760 --> 00:12:30,199 Speaker 3: It's Bush's chef. See what I did. 234 00:12:30,200 --> 00:12:34,319 Speaker 2: There's bushes, bushes, deep cut bushes. 235 00:12:34,520 --> 00:12:34,840 Speaker 3: Chef. 236 00:12:35,200 --> 00:12:41,640 Speaker 2: George W. Bush's chef was deported. It's his secret was revealed. 237 00:12:43,040 --> 00:12:46,360 Speaker 3: Saragio Garcia, not the golfer, was a caterer for George W. 238 00:12:46,440 --> 00:12:49,240 Speaker 2: Bush in the early two thousands, and then he opened 239 00:12:49,280 --> 00:12:51,600 Speaker 2: up a Mexican food truck and he opened up restaurants 240 00:12:51,640 --> 00:12:55,960 Speaker 2: in Waco. Well, then ICE did some double checking, because 241 00:12:56,600 --> 00:12:59,240 Speaker 2: nothing's better than a nice, high profile arrest, and they did. 242 00:13:00,160 --> 00:13:02,880 Speaker 3: So they nabbed him, and then they deported him. 243 00:13:03,679 --> 00:13:09,320 Speaker 2: And so he's been deported, but his his children, and 244 00:13:09,360 --> 00:13:12,720 Speaker 2: his wife are still here. So he and his family 245 00:13:12,760 --> 00:13:16,840 Speaker 2: spent years trying unsuccessfully to secure legal status. What in America. 246 00:13:18,080 --> 00:13:20,600 Speaker 2: Residents of Waco are shocked. They say he was a 247 00:13:20,640 --> 00:13:23,360 Speaker 2: pillar in the community. You keep hearing more and more 248 00:13:23,360 --> 00:13:25,840 Speaker 2: stories like this from different communities. And I have seen 249 00:13:25,880 --> 00:13:31,320 Speaker 2: this before where enough community outrage leads to. 250 00:13:34,679 --> 00:13:38,640 Speaker 3: Leads to I don't know what, a national cards, it 251 00:13:38,720 --> 00:13:39,680 Speaker 3: leads to national card. 252 00:13:39,720 --> 00:13:40,320 Speaker 1: Yes, that's it. 253 00:13:40,360 --> 00:13:42,440 Speaker 3: That's what I was after yeah, I was after national card. 254 00:13:42,440 --> 00:13:47,200 Speaker 2: No, it leads to leniency and at least maybe not 255 00:13:47,440 --> 00:13:53,640 Speaker 2: immediate deportation, but they might actually listen to that immigration attorney. 256 00:13:54,000 --> 00:13:59,640 Speaker 3: That's all. Yeah, that's all. So anyway, that sucks. 257 00:14:01,280 --> 00:14:04,320 Speaker 2: You saw that Apple had the uh they pulled the 258 00:14:04,360 --> 00:14:08,000 Speaker 2: ICE app. It was the Ice tracking app. Yes, so 259 00:14:08,040 --> 00:14:12,480 Speaker 2: they pulled that, which I thought, that's that's Apple trying 260 00:14:12,480 --> 00:14:16,840 Speaker 2: to avoid conflict with the White House. Apple doesn't need 261 00:14:16,880 --> 00:14:18,679 Speaker 2: to pull out there's nothing wrong with the app. But 262 00:14:18,720 --> 00:14:22,960 Speaker 2: that's that's what it is. It's a Trump leveraging his 263 00:14:23,080 --> 00:14:25,840 Speaker 2: power and tech companies going, we just don't even want 264 00:14:25,840 --> 00:14:28,160 Speaker 2: to deal with it. But I did see New Yorker 265 00:14:28,240 --> 00:14:32,920 Speaker 2: ran a story about some people here that are what 266 00:14:33,000 --> 00:14:36,640 Speaker 2: they call them ricky, what they call these guys. There 267 00:14:36,680 --> 00:14:42,840 Speaker 2: was a name for these guys. Oh, he's looking it up. Uh, 268 00:14:43,480 --> 00:14:45,320 Speaker 2: they had a they had a name for like their uh, 269 00:14:46,120 --> 00:14:46,880 Speaker 2: their group here. 270 00:14:47,120 --> 00:14:50,000 Speaker 3: I'll find it anyway. 271 00:14:50,000 --> 00:14:53,120 Speaker 2: They follow national they follow ICE members and National Guard 272 00:14:53,160 --> 00:14:55,760 Speaker 2: members and Border Patrol members around and then they basically 273 00:14:55,760 --> 00:14:58,040 Speaker 2: tell everybody where they are and where they've been going. 274 00:14:58,680 --> 00:15:03,680 Speaker 2: And so they're trying to get the word out even 275 00:15:03,720 --> 00:15:06,640 Speaker 2: though they you know, obviously the it's not working on 276 00:15:06,680 --> 00:15:09,480 Speaker 2: the apps, but there are people out there who are 277 00:15:09,640 --> 00:15:17,200 Speaker 2: just watching. Uh oh, Peace patrol is that it Peace patrol? 278 00:15:17,320 --> 00:15:20,600 Speaker 2: Is it like a golf gallery kind of okay? And 279 00:15:20,640 --> 00:15:23,760 Speaker 2: they just follow them from from a rest location to 280 00:15:23,800 --> 00:15:26,640 Speaker 2: a rest location and then they they basically radio to everybody. 281 00:15:26,640 --> 00:15:28,000 Speaker 3: Here's here's where it's going on. 282 00:15:28,440 --> 00:15:32,640 Speaker 2: And I'm guessing that they're just posting it on Oh oh, 283 00:15:32,720 --> 00:15:34,760 Speaker 2: I just saw a piece of the story that it's conniving. 284 00:15:35,040 --> 00:15:36,600 Speaker 3: They're posting it on social media. 285 00:15:36,840 --> 00:15:38,520 Speaker 2: I've seen this happen a number of places where all 286 00:15:38,520 --> 00:15:40,240 Speaker 2: of a sudden it will be you know, an Instagram 287 00:15:40,320 --> 00:15:43,800 Speaker 2: live or somebody's doing doing talk live or whatever, and. 288 00:15:43,760 --> 00:15:44,280 Speaker 3: They're posting it. 289 00:15:44,320 --> 00:15:47,600 Speaker 2: They're like ice spotted here, Border patrol here, that kind 290 00:15:47,600 --> 00:15:50,400 Speaker 2: of thing. Uh, this is interesting. Federal agents have become 291 00:15:50,400 --> 00:15:53,080 Speaker 2: aware of the patrollers. Some agents will attempt to hide 292 00:15:53,120 --> 00:15:54,440 Speaker 2: their faces as they pass. 293 00:15:54,840 --> 00:15:55,000 Speaker 3: Well. 294 00:15:55,040 --> 00:15:58,280 Speaker 2: The patrollers have dubbed the shy shoulder. Here's where it 295 00:15:58,280 --> 00:16:02,160 Speaker 2: gets conniving. Others will try to disguise their unmarked cars 296 00:16:02,200 --> 00:16:04,800 Speaker 2: with things like Coexist bumper stickers. 297 00:16:05,040 --> 00:16:11,440 Speaker 3: Oh, how dare you triggering? You can't do that. 298 00:16:12,800 --> 00:16:15,120 Speaker 2: You can't put a Coexist bumper stick around and then 299 00:16:15,200 --> 00:16:16,440 Speaker 2: arrest people and deport them. 300 00:16:18,320 --> 00:16:21,400 Speaker 3: That's too sneaky. That's wrong. 301 00:16:22,560 --> 00:16:27,920 Speaker 2: That's like, uh, that's decoy, that's entrapment. You can't do 302 00:16:27,960 --> 00:16:31,360 Speaker 2: those sorts of things. That's like when people go deer 303 00:16:31,440 --> 00:16:35,760 Speaker 2: hunting and they rub like dough pheromones all over their 304 00:16:35,920 --> 00:16:38,040 Speaker 2: hunting gear to try to lure the bucks in, and 305 00:16:38,040 --> 00:16:39,560 Speaker 2: then the bucks get shot and they're. 306 00:16:39,360 --> 00:16:40,560 Speaker 3: Like, what the eugh. 307 00:16:42,200 --> 00:16:42,720 Speaker 7: Not fair? 308 00:16:43,600 --> 00:16:47,080 Speaker 3: E h conning. 309 00:16:47,160 --> 00:16:49,000 Speaker 2: Anyway, these guys are keep an eye on there's it's 310 00:16:49,000 --> 00:16:51,600 Speaker 2: in the New Yorker if you're interested in that article. Uh, 311 00:16:52,200 --> 00:16:55,840 Speaker 2: we have something going on in this country where the 312 00:16:55,960 --> 00:17:00,680 Speaker 2: bots are trying to turn yourr little darling. 313 00:17:00,600 --> 00:17:04,120 Speaker 3: Boys into macho dumb Jim bros. 314 00:17:04,640 --> 00:17:08,560 Speaker 2: And it's working. How they're doing it is next. I'm 315 00:17:08,600 --> 00:17:09,160 Speaker 2: Chris Merrill. 316 00:17:09,880 --> 00:17:13,280 Speaker 1: You're listening to KFI AM six forty on demand. 317 00:17:13,920 --> 00:17:16,400 Speaker 2: Hopefully you're ready for the weekend. I know I am, 318 00:17:17,640 --> 00:17:19,800 Speaker 2: and I appreciate you being a part of the program tonight. 319 00:17:20,160 --> 00:17:22,920 Speaker 2: I'm Chris Merril, and you would listen anytime on demand 320 00:17:22,920 --> 00:17:23,840 Speaker 2: on the iHeartRadio app. 321 00:17:23,880 --> 00:17:25,520 Speaker 3: The show is going to be available as soon as 322 00:17:25,520 --> 00:17:26,240 Speaker 3: we wrap up here. 323 00:17:26,280 --> 00:17:30,480 Speaker 2: It's in the featured segments podcast area of KFI AM 324 00:17:30,480 --> 00:17:31,520 Speaker 2: six forty dot. 325 00:17:31,280 --> 00:17:33,280 Speaker 3: Com and then would love it if you could join 326 00:17:33,320 --> 00:17:34,240 Speaker 3: me on Sunday. 327 00:17:34,760 --> 00:17:37,040 Speaker 2: If you're in town, you're driving around, or maybe you're 328 00:17:37,119 --> 00:17:40,400 Speaker 2: hanging out in your garage, whatever, just turn on the radio, 329 00:17:40,440 --> 00:17:42,960 Speaker 2: turn on your app, whatever it is, and I'll be 330 00:17:43,000 --> 00:17:44,040 Speaker 2: there four o'clock. 331 00:17:44,760 --> 00:17:45,640 Speaker 3: So good stuff. 332 00:17:46,160 --> 00:17:49,200 Speaker 2: Next week it is Andy Reesemeyer is going to be 333 00:17:49,280 --> 00:17:50,600 Speaker 2: in on Monday. 334 00:17:50,640 --> 00:17:53,320 Speaker 3: Monday, Monday, and Andy is such a good dude. 335 00:17:53,320 --> 00:17:55,119 Speaker 2: I'm so glad that he's part of the team here 336 00:17:55,160 --> 00:17:58,320 Speaker 2: at KFI now, so make sure you join us on 337 00:17:58,760 --> 00:18:04,280 Speaker 2: Monday for Andy Reesmeyer hosting. The algorithms are turning alpha, 338 00:18:05,840 --> 00:18:08,880 Speaker 2: so you've got a lot of teenagers. 339 00:18:09,320 --> 00:18:11,000 Speaker 3: They're not even looking for. 340 00:18:10,840 --> 00:18:14,240 Speaker 2: The posts on the social media is the algorithms are 341 00:18:14,320 --> 00:18:22,000 Speaker 2: serving up macheesemo and unfortunately it's turning into loneliness insecurity 342 00:18:22,040 --> 00:18:24,640 Speaker 2: and a rather warped sense of self. Here's what's happening. 343 00:18:25,320 --> 00:18:32,120 Speaker 2: It's an algorithmic alpha crisis. They call it digital masculinity. 344 00:18:32,800 --> 00:18:35,960 Speaker 2: Three quarters of boys between eleven and seventeen years old 345 00:18:36,200 --> 00:18:41,760 Speaker 2: are regularly being fed digital masculinity content. So what does 346 00:18:41,760 --> 00:18:44,920 Speaker 2: that mean? So these are gonna be like fight videos? 347 00:18:46,160 --> 00:18:50,160 Speaker 2: Some call it muscle worship. Just think Jim Bros. Flexing 348 00:18:50,200 --> 00:18:54,520 Speaker 2: in front of the mirror. I scroll quickly through that crap, 349 00:18:54,520 --> 00:18:56,120 Speaker 2: but some people are like, I want to look like that. 350 00:18:56,920 --> 00:19:01,480 Speaker 2: The hustle culture and how to be a real man tutorials. 351 00:19:02,840 --> 00:19:06,359 Speaker 2: None of it, however, talks about how to you know, 352 00:19:07,280 --> 00:19:10,760 Speaker 2: be a be true to yourself, care about your community, 353 00:19:12,240 --> 00:19:15,560 Speaker 2: feel emotions, ask for help when you need it. Nope, 354 00:19:16,400 --> 00:19:22,720 Speaker 2: this is going Supermachi's mo. And honestly, it's feeling a bit. 355 00:19:23,280 --> 00:19:25,200 Speaker 2: Uh what's that? 356 00:19:27,320 --> 00:19:30,159 Speaker 3: What's that? What's that term that they've got for when 357 00:19:30,200 --> 00:19:30,480 Speaker 3: you have to. 358 00:19:30,480 --> 00:19:34,000 Speaker 2: Be a suit not alpha male? But uh, it's it's 359 00:19:34,119 --> 00:19:36,439 Speaker 2: escaping the right now, I'll come up with it. So 360 00:19:36,520 --> 00:19:38,720 Speaker 2: the boys, here's the deal on this too. The boys 361 00:19:38,760 --> 00:19:43,399 Speaker 2: themselves aren't even searching for this stuff. The algorithms are learning. 362 00:19:43,880 --> 00:19:46,040 Speaker 3: Who you are. And you have already experienced this. 363 00:19:46,080 --> 00:19:48,200 Speaker 2: If you're online at all, you've already experienced that the 364 00:19:48,240 --> 00:19:51,879 Speaker 2: algorithms have got you figured out, and especially if you're. 365 00:19:51,760 --> 00:19:52,600 Speaker 3: A young user. 366 00:19:53,200 --> 00:19:55,919 Speaker 2: So the young users are you know, they're using the 367 00:19:55,960 --> 00:19:59,520 Speaker 2: chat GPT, they're using the search engines, they're using the 368 00:19:59,520 --> 00:20:02,400 Speaker 2: the the social media, and they're searching for different videos, 369 00:20:02,560 --> 00:20:04,520 Speaker 2: and then the videos, based on what they're searching for, 370 00:20:05,240 --> 00:20:09,320 Speaker 2: figure out who they are. It might be broad brush, 371 00:20:09,440 --> 00:20:12,480 Speaker 2: but the more they search, the more they can narrowly 372 00:20:12,560 --> 00:20:16,960 Speaker 2: tailor those types of videos, videos that they think that 373 00:20:16,960 --> 00:20:19,199 Speaker 2: that individual will like. 374 00:20:20,480 --> 00:20:22,639 Speaker 3: Some of these algorithms are very aggressive. 375 00:20:23,000 --> 00:20:25,280 Speaker 2: For instance, I have this issue, and I've mentioned this 376 00:20:25,320 --> 00:20:28,280 Speaker 2: before in the air, I have this issue with threads. 377 00:20:28,800 --> 00:20:31,439 Speaker 3: You guys use threads. I like threads, yeah, but you 378 00:20:31,480 --> 00:20:35,040 Speaker 3: also use bing. Bing is the best? What else would 379 00:20:35,080 --> 00:20:35,400 Speaker 3: you use? 380 00:20:36,080 --> 00:20:38,480 Speaker 5: You're not the only person I've ever heard say that, Yeah, 381 00:20:38,560 --> 00:20:41,919 Speaker 5: you bing it. Yeah, just bing away, bing to your 382 00:20:41,920 --> 00:20:44,719 Speaker 5: heart's content. So I like threads. 383 00:20:44,760 --> 00:20:47,720 Speaker 2: If you're unfamiliar, Threads is like the Twitter alternative, but 384 00:20:47,760 --> 00:20:50,480 Speaker 2: it's under It's under meta, which is Facebook and Instagram. 385 00:20:50,800 --> 00:20:55,040 Speaker 2: So they said, okay, Elon Musk is running this Twitter 386 00:20:55,080 --> 00:20:56,760 Speaker 2: into the ground. We're going to create an alternative, and 387 00:20:56,800 --> 00:20:59,280 Speaker 2: they did, and it's Threads. And I like threads, but 388 00:20:59,400 --> 00:21:03,280 Speaker 2: the the algorithm is very aggressive. And by that I 389 00:21:03,359 --> 00:21:09,000 Speaker 2: mean thread sees that I like a puppy video on Instagram, right, 390 00:21:09,080 --> 00:21:11,399 Speaker 2: and the meta is all intertwined. So for instance, I 391 00:21:11,440 --> 00:21:16,720 Speaker 2: follow Conway on Instagram, and Conway's got a If you're 392 00:21:16,720 --> 00:21:19,399 Speaker 2: not following him, you should. It's a wonderful variety of 393 00:21:19,440 --> 00:21:21,639 Speaker 2: different videos. Some of the stuff is from the station. 394 00:21:21,880 --> 00:21:23,920 Speaker 2: Some of it is, you know, things happening in La. 395 00:21:24,320 --> 00:21:26,280 Speaker 2: It could be it could be a riot. It could 396 00:21:26,320 --> 00:21:29,879 Speaker 2: be people protesting Ice. It could be you know, the 397 00:21:29,920 --> 00:21:32,880 Speaker 2: Dodgers win. It could be you know, it's good, it's bad, 398 00:21:33,000 --> 00:21:34,720 Speaker 2: it's news, it's it's topical. 399 00:21:35,160 --> 00:21:37,440 Speaker 3: It could be Conway at the racetrack. 400 00:21:38,600 --> 00:21:41,040 Speaker 2: But he also has a bunch of flick you know, 401 00:21:41,119 --> 00:21:45,840 Speaker 2: animals doing sweet things videos. So I tend to like 402 00:21:45,920 --> 00:21:49,080 Speaker 2: those sorts of things. I find that to be a 403 00:21:49,119 --> 00:21:51,359 Speaker 2: bit of a palate cleanser from my brain. It's not 404 00:21:51,440 --> 00:21:51,840 Speaker 2: so heavy. 405 00:21:51,920 --> 00:21:53,840 Speaker 3: I like it. So I like those videos. 406 00:21:54,359 --> 00:21:58,040 Speaker 2: And then Threads goes, oh, he likes pet videos, so 407 00:21:58,119 --> 00:21:59,240 Speaker 2: I get more pet videos. 408 00:21:59,320 --> 00:22:01,200 Speaker 3: That's fine with me. I'm okay with that. 409 00:22:01,520 --> 00:22:05,040 Speaker 2: I'm very happy to see pet videos. But then I'll 410 00:22:05,040 --> 00:22:07,040 Speaker 2: get a video, or I'll get a I'll get a 411 00:22:07,040 --> 00:22:10,960 Speaker 2: post on Threads that will be about somebody saying goodbye 412 00:22:11,000 --> 00:22:16,439 Speaker 2: to their pet, and I feel bad. Oh and I 413 00:22:16,480 --> 00:22:18,960 Speaker 2: click the like button, which of course is a heart. 414 00:22:19,240 --> 00:22:21,280 Speaker 3: So in my mind, I'm. 415 00:22:21,080 --> 00:22:24,520 Speaker 2: Just simply showing support for this person going through difficult time, 416 00:22:26,080 --> 00:22:28,399 Speaker 2: and I'm one of. 417 00:22:28,400 --> 00:22:29,600 Speaker 3: Those obnoxious pet owners. 418 00:22:29,640 --> 00:22:32,400 Speaker 2: I love my I love my dogs like they're my kids, right, 419 00:22:32,800 --> 00:22:35,439 Speaker 2: not my kids, but more like yeah, kind of like 420 00:22:35,440 --> 00:22:37,919 Speaker 2: my kids, Like like I raised them and then they 421 00:22:37,960 --> 00:22:39,560 Speaker 2: turned into somebody I really like, and then they become 422 00:22:39,600 --> 00:22:40,200 Speaker 2: my best friend. 423 00:22:40,760 --> 00:22:41,000 Speaker 3: You know. 424 00:22:41,160 --> 00:22:43,800 Speaker 2: It's like those really good father son relationships where the 425 00:22:43,840 --> 00:22:47,000 Speaker 2: father and son end up becoming very close and it's like, 426 00:22:47,040 --> 00:22:49,840 Speaker 2: that's my best friend, you know. That's how I am 427 00:22:49,840 --> 00:22:52,840 Speaker 2: with dogs. So I see somebody that's saying goodbye to 428 00:22:52,840 --> 00:22:56,719 Speaker 2: their their dog and I like it. And then all 429 00:22:56,760 --> 00:22:59,320 Speaker 2: of a sudden, threads goes, oh, he liked that. Here's 430 00:22:59,320 --> 00:23:01,600 Speaker 2: somebody else saying by of their dog. Okay, I like 431 00:23:01,600 --> 00:23:03,399 Speaker 2: that one too, because I want to send support. I 432 00:23:03,440 --> 00:23:04,639 Speaker 2: like that one too. I like that one too. I 433 00:23:04,680 --> 00:23:07,679 Speaker 2: like that one too. And then the next thing, you know, 434 00:23:09,600 --> 00:23:12,960 Speaker 2: more than half of the posts in my suggested for 435 00:23:13,040 --> 00:23:17,440 Speaker 2: you feed is dead dogs. All of a sudden, the 436 00:23:17,480 --> 00:23:19,680 Speaker 2: algorithm thinks I love dead dogs. 437 00:23:20,160 --> 00:23:22,920 Speaker 3: No, I do not love dead dogs. 438 00:23:23,440 --> 00:23:25,040 Speaker 2: And then I felt guilty and I had to start 439 00:23:25,040 --> 00:23:27,600 Speaker 2: scrolling past it. And here's the funniest thing is that 440 00:23:27,800 --> 00:23:31,720 Speaker 2: I actually ran across a thread of someone saying, I'm 441 00:23:31,800 --> 00:23:34,439 Speaker 2: really sorry if you are losing your pet, but I 442 00:23:34,560 --> 00:23:38,320 Speaker 2: have to scroll past your post because the algorithm thinks 443 00:23:38,400 --> 00:23:41,159 Speaker 2: I love dead dogs and all of my posts are 444 00:23:41,680 --> 00:23:43,680 Speaker 2: Everything in my feed is dead dogs, and I thought 445 00:23:44,240 --> 00:23:47,760 Speaker 2: that's me. I'm not the only one experiencing this, So 446 00:23:47,800 --> 00:23:49,840 Speaker 2: that one's very aggressive. So imagine if you're a fifteen 447 00:23:49,920 --> 00:23:53,440 Speaker 2: year old boy and and you're you know, you look 448 00:23:53,560 --> 00:23:57,119 Speaker 2: for a video about what happened at Summer Slam, you know, 449 00:23:57,320 --> 00:24:00,320 Speaker 2: WWE SummerSlam, and you're like, oh cool, this happened, and 450 00:24:00,359 --> 00:24:03,440 Speaker 2: you like it. Now the algorithm's like, oh, he likes 451 00:24:03,720 --> 00:24:06,879 Speaker 2: he likes macho wrestling stuff. Here's more, here's more, And 452 00:24:06,920 --> 00:24:09,560 Speaker 2: then it says, if he likes macho wrestling stuff, I 453 00:24:09,600 --> 00:24:12,160 Speaker 2: bet that he likes weight training. And if he likes 454 00:24:12,160 --> 00:24:14,640 Speaker 2: weight training and he likes wrestling, I bet he likes 455 00:24:15,320 --> 00:24:16,120 Speaker 2: fight videos. 456 00:24:16,920 --> 00:24:18,040 Speaker 3: I bet he likes those things. 457 00:24:18,040 --> 00:24:19,960 Speaker 2: And if he likes all of that stuff, I bet 458 00:24:20,000 --> 00:24:22,600 Speaker 2: that he is this kind of person and the algorithms 459 00:24:22,840 --> 00:24:26,399 Speaker 2: help feed into it, and then they feed into the 460 00:24:26,440 --> 00:24:31,840 Speaker 2: misogynistic tropes. They feed into this hole. Don't be weak, 461 00:24:32,640 --> 00:24:38,120 Speaker 2: be an alpha. It is emotional constipation that they are 462 00:24:38,240 --> 00:24:42,959 Speaker 2: shoving down the throats of your teenage boys, and it 463 00:24:43,000 --> 00:24:46,280 Speaker 2: is leading to higher rates of loneliness, It is leading 464 00:24:46,320 --> 00:24:49,639 Speaker 2: to insecurity, it is leading to lower self esteem. So 465 00:24:49,760 --> 00:24:52,560 Speaker 2: while your son is learning how to win, they're actually 466 00:24:52,640 --> 00:24:58,159 Speaker 2: falling apart. And the algorithms reinforce this day in and 467 00:24:58,280 --> 00:25:00,600 Speaker 2: day out, and your kids are online and they're on 468 00:25:00,640 --> 00:25:03,639 Speaker 2: social media for seven, eight, ten hours a day, and 469 00:25:03,680 --> 00:25:08,560 Speaker 2: it starts to target him with content, reinforcing this toxicity. 470 00:25:08,720 --> 00:25:11,000 Speaker 2: And it's the business model because they keep coming back 471 00:25:11,040 --> 00:25:14,400 Speaker 2: for more and as a result exactly this kind of thing. 472 00:25:14,600 --> 00:25:16,639 Speaker 2: You've got different countries that are saying we got to 473 00:25:16,640 --> 00:25:18,800 Speaker 2: put bands on it, different states that are saying that's it. 474 00:25:18,840 --> 00:25:21,760 Speaker 2: No social media for anybody under sixteen, or under fifteen, 475 00:25:21,840 --> 00:25:25,439 Speaker 2: or under whatever it is. They said, this is what 476 00:25:25,440 --> 00:25:28,040 Speaker 2: we're gonna do. But it doesn't matter because teenagers know 477 00:25:28,040 --> 00:25:33,439 Speaker 2: how to get around everything, including your parental controls. And 478 00:25:33,480 --> 00:25:36,560 Speaker 2: if you think they're not doing it, you probably should 479 00:25:36,600 --> 00:25:41,840 Speaker 2: double check. If you think your kid is not exploring 480 00:25:41,880 --> 00:25:46,080 Speaker 2: the world via the Internet and social media, I'm not 481 00:25:46,080 --> 00:25:48,959 Speaker 2: going to tell you that you're naive, but there's a 482 00:25:49,000 --> 00:25:52,639 Speaker 2: good chance that you haven't found it. Yet maybe you 483 00:25:52,760 --> 00:25:54,200 Speaker 2: got that one kid that doesn't do it, that would 484 00:25:54,200 --> 00:25:57,399 Speaker 2: be amazing. Good job. It's a parenting win. But for 485 00:25:57,520 --> 00:26:01,119 Speaker 2: most of us, and I raised three of them, we 486 00:26:01,160 --> 00:26:03,600 Speaker 2: didn't get so lucky. We had to had to clamp 487 00:26:03,640 --> 00:26:08,119 Speaker 2: down still to come. While you've got kids trying to 488 00:26:08,119 --> 00:26:10,840 Speaker 2: figure out how to be adults, we have the inverse 489 00:26:10,840 --> 00:26:14,639 Speaker 2: happening in the business world. Adults are trying to figure 490 00:26:14,640 --> 00:26:18,480 Speaker 2: out how to be kids, and HR is backing the play. 491 00:26:18,560 --> 00:26:20,840 Speaker 3: I'll tell you why next, Chris Meryldon. 492 00:26:20,640 --> 00:26:24,000 Speaker 1: You're listening to KFI AM six on demand. 493 00:26:24,680 --> 00:26:29,160 Speaker 2: Coming up here after nine o'clock. We have lost America's 494 00:26:29,560 --> 00:26:35,000 Speaker 2: greatest none and your favorite Laker could be out hundreds 495 00:26:35,080 --> 00:26:36,840 Speaker 2: of dollars. You'll find out why that is coming up 496 00:26:36,840 --> 00:26:40,119 Speaker 2: here again after nine o'clock. I realized the term I 497 00:26:40,160 --> 00:26:41,359 Speaker 2: was looking for in the last segment. If you were 498 00:26:41,359 --> 00:26:42,760 Speaker 2: listening to the last segment, I was talking about this 499 00:26:42,800 --> 00:26:46,600 Speaker 2: digital masculinity and the influence that's that's happening over these 500 00:26:46,960 --> 00:26:51,600 Speaker 2: these teenage boys, and the algorithms are shoving this digital masculinity, 501 00:26:51,640 --> 00:26:53,680 Speaker 2: Like if you're a man, you gotta watch the fight 502 00:26:53,800 --> 00:26:56,000 Speaker 2: videos and you gotta you gotta buff up and you. 503 00:26:55,960 --> 00:27:00,320 Speaker 3: Gotta you gotta you be a real man, right, And it. 504 00:27:00,320 --> 00:27:02,320 Speaker 2: Just reminds me I was looking for the term it's 505 00:27:02,320 --> 00:27:07,120 Speaker 2: that groper movement, which is like that white nationalist it's 506 00:27:07,200 --> 00:27:10,160 Speaker 2: kind of inceel adjacent kind of thing. 507 00:27:10,320 --> 00:27:13,960 Speaker 3: Isn't that specific to Nick Fuentis. That's his deal. Yeah, 508 00:27:14,000 --> 00:27:16,159 Speaker 3: I mean, that's that's He's the key figure of that. 509 00:27:16,240 --> 00:27:19,800 Speaker 2: But it just reminded me of all that, you know, 510 00:27:19,920 --> 00:27:21,960 Speaker 2: the gropers, like you could be a man, you could 511 00:27:22,000 --> 00:27:24,240 Speaker 2: be like this and you find yourself a good trad wife. 512 00:27:24,680 --> 00:27:27,879 Speaker 3: Okay, all right, enough of that nonsense. 513 00:27:28,680 --> 00:27:34,560 Speaker 2: Just unfortunately, that's when when young men are impressionable and 514 00:27:34,560 --> 00:27:36,400 Speaker 2: and they don't have the experience to learn that it's 515 00:27:37,080 --> 00:27:39,200 Speaker 2: usually just morons trying to manipulate them. 516 00:27:39,760 --> 00:27:40,239 Speaker 3: No, they're not. 517 00:27:40,960 --> 00:27:46,800 Speaker 2: Okay, Eventually they grow out of it, we hope, and 518 00:27:46,840 --> 00:27:48,400 Speaker 2: we hope it's before they do something that they can't 519 00:27:48,440 --> 00:27:48,880 Speaker 2: take back. 520 00:27:49,600 --> 00:27:50,000 Speaker 3: All Right. 521 00:27:51,000 --> 00:27:54,560 Speaker 2: While we've got young boys that are trying to navigate 522 00:27:54,600 --> 00:27:58,160 Speaker 2: how to become men, we also have grown ups trying 523 00:27:58,160 --> 00:28:00,720 Speaker 2: to figure out how to become children. And HR is 524 00:28:00,800 --> 00:28:04,240 Speaker 2: backing that play. Adults are turning in their power points, 525 00:28:04,880 --> 00:28:10,200 Speaker 2: they're picking up the potato sacks. It's field day for work. 526 00:28:11,840 --> 00:28:19,440 Speaker 2: Corporate synergy is trying to be found through mandated fun. 527 00:28:20,200 --> 00:28:23,439 Speaker 2: Nothing says fun like you will participate there it is. 528 00:28:23,760 --> 00:28:26,760 Speaker 2: Companies are using sack races, egg and spoon relays in 529 00:28:26,840 --> 00:28:32,240 Speaker 2: human knots to fix the corporate culture. They're trying to 530 00:28:32,320 --> 00:28:36,360 Speaker 2: find human connection at work. So when you have those 531 00:28:36,400 --> 00:28:43,720 Speaker 2: mandated return to office orders, don't worry. You might also 532 00:28:43,720 --> 00:28:46,840 Speaker 2: get to stay late so that you can participate in 533 00:28:46,840 --> 00:28:49,320 Speaker 2: three legged races. That's not gonna end in a sexual 534 00:28:49,360 --> 00:28:54,880 Speaker 2: harassment suit. We the games are being rebranded with names 535 00:28:54,920 --> 00:29:01,600 Speaker 2: like Executive Relay and Strategic water Balloon Toss. We're just 536 00:29:01,840 --> 00:29:04,840 Speaker 2: we're throwing corporate buzzwords on it, and then you can 537 00:29:04,880 --> 00:29:08,400 Speaker 2: expense it, so you got that going for you. The 538 00:29:08,440 --> 00:29:11,000 Speaker 2: goal is to break down barriers, to build trust and 539 00:29:11,160 --> 00:29:14,440 Speaker 2: remind Karen from accounting that she's not just a spreadsheet machine. 540 00:29:14,480 --> 00:29:21,760 Speaker 2: She's a sack hopin' champion. It's terrible, all of it 541 00:29:21,800 --> 00:29:23,960 Speaker 2: to try to make work feel less like work. But 542 00:29:24,040 --> 00:29:25,920 Speaker 2: of course the games are supposed to teach teamwork and 543 00:29:25,920 --> 00:29:30,360 Speaker 2: communication and resilience, and they are actually they're actually teaching 544 00:29:30,400 --> 00:29:33,080 Speaker 2: people they don't want to spend more time with their coworkers. 545 00:29:34,200 --> 00:29:37,120 Speaker 2: I don't know about you, guys, but I work with 546 00:29:37,160 --> 00:29:39,040 Speaker 2: people that I would love to spend more time with. 547 00:29:39,600 --> 00:29:41,200 Speaker 2: I also work with people I do not want to 548 00:29:41,200 --> 00:29:44,640 Speaker 2: spend another second with the idea that we're all gonna 549 00:29:44,640 --> 00:29:47,280 Speaker 2: get together and play is not all that appealing. 550 00:29:47,280 --> 00:29:49,360 Speaker 3: And I know you hr people are gonna say yeah, 551 00:29:49,360 --> 00:29:49,959 Speaker 3: but you don't know. 552 00:29:50,200 --> 00:29:52,920 Speaker 2: Maybe you're gonna learn something about that person that you 553 00:29:52,960 --> 00:29:57,640 Speaker 2: didn't know before. I work with this gal. She's twenty two, 554 00:29:57,800 --> 00:30:01,680 Speaker 2: and she is by far the smartest person she will 555 00:30:01,720 --> 00:30:05,320 Speaker 2: ever meet. Every day she gets up in the mirror 556 00:30:05,320 --> 00:30:08,200 Speaker 2: and she she she she looks at herself and she says, 557 00:30:09,080 --> 00:30:11,680 Speaker 2: you're gonna have to deal with all of these morons. 558 00:30:12,120 --> 00:30:14,640 Speaker 3: They're just not as smart as you. But don't worry. 559 00:30:15,240 --> 00:30:17,480 Speaker 2: You can show them all just how smart you are 560 00:30:17,720 --> 00:30:22,600 Speaker 2: by correcting everything they say. You ever work with somebody 561 00:30:22,640 --> 00:30:24,760 Speaker 2: like that, I have no idea what you're talking. It 562 00:30:24,800 --> 00:30:27,560 Speaker 2: doesn't matter what you say. They're gonna tell you you're wrong. 563 00:30:28,280 --> 00:30:31,240 Speaker 2: They're gonna tell you that's not how it is, okay, whatever, 564 00:30:32,520 --> 00:30:35,600 Speaker 2: God cannot stand. I've got a niece like this too, 565 00:30:35,880 --> 00:30:39,400 Speaker 2: and I just want to smack her my niece. One time, 566 00:30:40,120 --> 00:30:42,760 Speaker 2: she was in high school and she was she was 567 00:30:42,800 --> 00:30:45,479 Speaker 2: saying something, and I said something like, don't you think 568 00:30:45,520 --> 00:30:49,560 Speaker 2: you might wanna consider, you know, like working on some 569 00:30:49,600 --> 00:30:52,320 Speaker 2: extracurricular activities out she was a big softball player. I said, 570 00:30:52,360 --> 00:30:54,480 Speaker 2: do you ever think about other extracurricular activities? 571 00:30:54,520 --> 00:30:55,840 Speaker 3: She goes, I don't need to. 572 00:30:56,040 --> 00:30:57,840 Speaker 2: This is gonna get me my scholarship so I can 573 00:30:57,880 --> 00:31:00,240 Speaker 2: be a heart surgeon. I'm not gonna waste my life, 574 00:31:00,280 --> 00:31:03,080 Speaker 2: and something like radio was like there you go. 575 00:31:03,400 --> 00:31:07,360 Speaker 3: Well, okay, yeah, all right. I hope you'll remember to 576 00:31:07,400 --> 00:31:07,880 Speaker 3: thank her. 577 00:31:08,240 --> 00:31:11,720 Speaker 2: Oh do you know how much I celebrate every failure 578 00:31:11,840 --> 00:31:16,560 Speaker 2: she has. She lost her scholarship, she dropped out of college, 579 00:31:17,200 --> 00:31:21,840 Speaker 2: she married an old guy with three kids. She's working 580 00:31:21,880 --> 00:31:27,200 Speaker 2: as like a dental assistant now, and she's like, I'm 581 00:31:27,200 --> 00:31:28,600 Speaker 2: gonna be a dentist now. I don't want to be 582 00:31:28,600 --> 00:31:31,000 Speaker 2: a heart surge of it. And she keeps getting fired 583 00:31:31,040 --> 00:31:33,960 Speaker 2: from entry level jobs because they can't stand her. And 584 00:31:34,000 --> 00:31:37,600 Speaker 2: for me, I'm like, oh that's too bad. This is great. 585 00:31:37,800 --> 00:31:39,600 Speaker 2: I love it so much. So I work with a 586 00:31:39,600 --> 00:31:43,440 Speaker 2: person like this. She makes me nuts. I do not 587 00:31:43,560 --> 00:31:46,720 Speaker 2: want to spend another second with this individual. And I 588 00:31:46,760 --> 00:31:48,480 Speaker 2: understand at some point she's going to grow up and 589 00:31:48,520 --> 00:31:51,120 Speaker 2: she's gonna run into somebody just like herself, and either 590 00:31:51,160 --> 00:31:56,240 Speaker 2: they're going to self distruct or hopefully she matures. I 591 00:31:56,280 --> 00:31:58,360 Speaker 2: don't think she's going to, but I'm hoping that she 592 00:31:58,400 --> 00:32:00,720 Speaker 2: will mature. That's at some point she's gonna kind of, 593 00:32:01,120 --> 00:32:03,400 Speaker 2: you know, come to her senses. But I don't need 594 00:32:03,440 --> 00:32:05,400 Speaker 2: to spend any more time. I'm too old for that crap. 595 00:32:06,080 --> 00:32:08,040 Speaker 2: She tells me how old out of touch I am. 596 00:32:09,560 --> 00:32:11,560 Speaker 2: She tells me how dumb it is that I don't 597 00:32:11,600 --> 00:32:15,880 Speaker 2: know what sigma means, And I'm like, sigma, you mean 598 00:32:15,920 --> 00:32:24,080 Speaker 2: like the Greek letter? Like g all right, okay, Betchie, 599 00:32:24,080 --> 00:32:24,880 Speaker 2: what a sigma? 600 00:32:26,560 --> 00:32:27,600 Speaker 3: You know? I don't even know? 601 00:32:28,080 --> 00:32:32,400 Speaker 8: I okay, stupid, No, Like I am so dumb. I 602 00:32:32,440 --> 00:32:34,520 Speaker 8: tune into like my nieces and nephews to keep me 603 00:32:34,560 --> 00:32:37,400 Speaker 8: updated on these trends that I have zero idea sigma. 604 00:32:37,480 --> 00:32:40,520 Speaker 8: I have no idea there. No, I'm barely learning riz 605 00:32:41,080 --> 00:32:43,360 Speaker 8: so h on the side right. 606 00:32:44,040 --> 00:32:46,560 Speaker 2: And one thing I know is that maybe one or 607 00:32:46,560 --> 00:32:48,800 Speaker 2: two of the words that are popular at this very 608 00:32:48,840 --> 00:32:52,600 Speaker 2: moment will will stick for more than a year or two. 609 00:32:53,000 --> 00:32:55,800 Speaker 2: But for the most part they all fall apart. It's 610 00:32:55,840 --> 00:32:57,400 Speaker 2: not like it's not like we're all gonna be calling 611 00:32:57,400 --> 00:33:01,960 Speaker 2: each other Sigma in fifteen years, because Jen Alpha will 612 00:33:01,960 --> 00:33:04,960 Speaker 2: have developed their own and they will start ridiculing gen 613 00:33:05,080 --> 00:33:07,960 Speaker 2: Z for saying things like Sigma and how old and 614 00:33:08,040 --> 00:33:08,880 Speaker 2: dumb they sound. 615 00:33:09,520 --> 00:33:11,080 Speaker 3: I agreed, that's what happens. 616 00:33:11,480 --> 00:33:14,560 Speaker 2: I know, because I was one of the raddest dudes 617 00:33:14,560 --> 00:33:16,920 Speaker 2: in the eighties and anybody that thought differently could eat 618 00:33:16,960 --> 00:33:17,520 Speaker 2: my shorts. 619 00:33:17,560 --> 00:33:23,480 Speaker 5: Man, don't have a cow. Anybody else get that? Please 620 00:33:23,480 --> 00:33:25,200 Speaker 5: tell me I'm not alone. No, no, you sound like 621 00:33:25,200 --> 00:33:30,000 Speaker 5: a real square to me. Daddy, Thank you, daddy. You're 622 00:33:30,040 --> 00:33:31,200 Speaker 5: the be's knees my man. 623 00:33:32,920 --> 00:33:33,200 Speaker 3: All right. 624 00:33:33,280 --> 00:33:35,680 Speaker 2: She lived to one hundred and six. She outlasted generations 625 00:33:35,680 --> 00:33:39,080 Speaker 2: of players. She stole the spotlight. The world's most popular 626 00:33:39,160 --> 00:33:42,520 Speaker 2: nun is now headed off to meet her maker, and 627 00:33:42,560 --> 00:33:44,480 Speaker 2: it's hitting harder than most buzzer beaters. 628 00:33:44,480 --> 00:33:45,160 Speaker 3: That is next 629 00:33:45,600 --> 00:33:48,160 Speaker 1: Kfi A six on demand