1 00:00:00,240 --> 00:00:00,640 Speaker 1: In pain. 2 00:00:00,960 --> 00:00:04,360 Speaker 2: Check out the Good Feet store in Roseville, Woodbury, Maple Grove, 3 00:00:04,440 --> 00:00:05,520 Speaker 2: and Burnsville today. 4 00:00:05,800 --> 00:00:08,880 Speaker 3: So this is madness voter ID. It's not about voter ID. 5 00:00:09,000 --> 00:00:10,200 Speaker 4: The save acts not about that. 6 00:00:11,200 --> 00:00:12,360 Speaker 3: It's about registration. 7 00:00:14,040 --> 00:00:17,840 Speaker 2: It's about proving your citizenship with a passport. 8 00:00:18,880 --> 00:00:23,640 Speaker 3: Not everyone has a passport. If you where I don't, 9 00:00:24,000 --> 00:00:25,320 Speaker 3: I don't know where I'm up. You know where your 10 00:00:25,320 --> 00:00:30,840 Speaker 3: pirth certificate is? I lost that at seven. I mean 11 00:00:30,880 --> 00:00:32,600 Speaker 3: I don't even know where to begin to get it back. 12 00:00:33,440 --> 00:00:36,280 Speaker 3: So these guys are not screwing around. 13 00:00:40,760 --> 00:00:40,879 Speaker 5: Now. 14 00:00:40,960 --> 00:00:46,200 Speaker 2: Was California Governor Gavin Newsom. There's a lot of things 15 00:00:46,240 --> 00:00:48,800 Speaker 2: that he can't get if he doesn't have his birth certificate. 16 00:00:51,200 --> 00:00:55,600 Speaker 3: First off, I don't believe him. But is this the 17 00:00:55,640 --> 00:00:59,000 Speaker 3: winning message that he is hoping for. 18 00:01:01,160 --> 00:01:05,480 Speaker 2: With his aspirations to be the twenty twenty eight Democrat nominee. 19 00:01:06,040 --> 00:01:09,679 Speaker 2: So in the course of days, he's said that he 20 00:01:09,800 --> 00:01:14,920 Speaker 2: had a bad SAT score in the thirty second to 21 00:01:15,000 --> 00:01:20,840 Speaker 2: fortieth percentile. He lost his birth certificate when he was 22 00:01:20,880 --> 00:01:23,520 Speaker 2: a child. He doesn't know how to read. 23 00:01:27,280 --> 00:01:30,199 Speaker 3: Twentin City's news Talk. My name is John Justice. 24 00:01:31,040 --> 00:01:33,480 Speaker 2: Glad you're with the show for a Tuesday in the 25 00:01:33,480 --> 00:01:36,240 Speaker 2: master control booth next door is a Sam Good. 26 00:01:36,080 --> 00:01:37,720 Speaker 3: Morning, Sam Warren, John. 27 00:01:38,640 --> 00:01:40,960 Speaker 2: David Cartzenstein Ross will talk a little AI. 28 00:01:41,319 --> 00:01:42,960 Speaker 3: We're gonna talk AI fears. 29 00:01:43,560 --> 00:01:45,160 Speaker 2: It's going to be the big topic when we have 30 00:01:45,319 --> 00:01:48,559 Speaker 2: David on the AI convenience trap. 31 00:01:49,000 --> 00:01:50,920 Speaker 3: No one warned Mom's about. 32 00:01:51,480 --> 00:01:55,600 Speaker 2: In the meantime AI entering the operating room, a rise 33 00:01:55,640 --> 00:02:00,600 Speaker 2: of botched surgeries, maybe all while AI leaders that open 34 00:02:00,680 --> 00:02:06,639 Speaker 2: AI and x AI are fleeing as doovesday scenarios arrive. 35 00:02:07,000 --> 00:02:14,240 Speaker 2: Much concern over AI becoming self aware like sky net. 36 00:02:14,320 --> 00:02:15,880 Speaker 2: We've also got a lot of frod talk, a lot 37 00:02:15,919 --> 00:02:17,519 Speaker 2: of ICE talk. We have a new whistleblower. Do you 38 00:02:17,560 --> 00:02:20,520 Speaker 2: hear about the whistleblower? Democrats are all about the whistleblower. 39 00:02:20,760 --> 00:02:27,960 Speaker 2: They found a whistleblower to go and vilify ICE. Really convenient. 40 00:02:28,120 --> 00:02:30,400 Speaker 2: They found one dude who had been on the job 41 00:02:30,760 --> 00:02:34,600 Speaker 2: for like five months who just happened to have a 42 00:02:34,680 --> 00:02:39,360 Speaker 2: list of complaints that he is revealing during his congressional 43 00:02:39,360 --> 00:02:44,480 Speaker 2: testimony that aligned perfectly with all of the Democrat talking 44 00:02:44,520 --> 00:02:48,359 Speaker 2: points and all of the criticisms by the anti ICE, 45 00:02:48,440 --> 00:02:52,600 Speaker 2: obstructionists and insurrectionists on the streets of Minnesota. It's just 46 00:02:52,639 --> 00:02:54,920 Speaker 2: it's amazing how that happens. 47 00:02:55,520 --> 00:02:59,440 Speaker 3: It's incredible. They have what's called a Trump derangement problem. 48 00:02:59,480 --> 00:03:00,960 Speaker 3: Have you heard of it problem? 49 00:03:01,040 --> 00:03:04,280 Speaker 2: Let's start off here, though, with what's been taking place 50 00:03:04,440 --> 00:03:08,200 Speaker 2: in Mexico. I told this story last night. I spoke 51 00:03:08,200 --> 00:03:12,240 Speaker 2: at a BPOU meeting up in in Blaine. Well, you 52 00:03:12,280 --> 00:03:15,800 Speaker 2: know what, speaking probably isn't the right way to describe 53 00:03:15,800 --> 00:03:16,240 Speaker 2: what I did. 54 00:03:16,280 --> 00:03:23,119 Speaker 3: It was more like a cohesive ramble. I didn't plan 55 00:03:23,200 --> 00:03:23,440 Speaker 3: on it. 56 00:03:23,600 --> 00:03:25,800 Speaker 2: I didn't plan and just like you know what, I 57 00:03:25,800 --> 00:03:27,560 Speaker 2: write stuff all the time when I go out in public, 58 00:03:27,560 --> 00:03:29,200 Speaker 2: and I'm a lot better when I just kind of 59 00:03:29,520 --> 00:03:34,200 Speaker 2: shoot from the hip. Yeah, twenty five minutes later, I 60 00:03:34,240 --> 00:03:35,840 Speaker 2: think you're done. Now, John, think you're done. 61 00:03:36,000 --> 00:03:37,960 Speaker 3: But I told the story. Didn't go over very well 62 00:03:37,960 --> 00:03:38,320 Speaker 3: with the crowd. 63 00:03:38,320 --> 00:03:40,600 Speaker 2: I probably didn't describe it correctly, but I'll share it 64 00:03:40,640 --> 00:03:44,240 Speaker 2: with you this morning, so I'm online. Yesterday Logan got 65 00:03:44,240 --> 00:03:46,000 Speaker 2: back from his trip from Alaska, went and saw the 66 00:03:46,000 --> 00:03:49,840 Speaker 2: Aurora borealis, which was incredibly Aurora Borealis saw the video footage. 67 00:03:49,840 --> 00:03:50,520 Speaker 3: It was incredible. 68 00:03:50,760 --> 00:03:53,000 Speaker 2: It was like everything you've seen in the movies and more. 69 00:03:53,040 --> 00:03:55,160 Speaker 2: It was nothing compared to what we've been able to 70 00:03:55,200 --> 00:03:59,160 Speaker 2: see here, but you know he's a pilot. So I'm 71 00:03:59,240 --> 00:04:03,400 Speaker 2: online doing and I've been fascinated by all the flight 72 00:04:03,560 --> 00:04:09,280 Speaker 2: radar images with all of the military hardware heading to 73 00:04:09,320 --> 00:04:11,760 Speaker 2: the Middle East, right because and we could see an 74 00:04:11,760 --> 00:04:15,000 Speaker 2: attack within the next you know, twenty four forty eight hours. 75 00:04:15,040 --> 00:04:17,960 Speaker 2: Although the conversation around has died down a bit, but 76 00:04:18,240 --> 00:04:21,919 Speaker 2: there's still is anticipation that we could strike Aron, you 77 00:04:21,920 --> 00:04:24,400 Speaker 2: know again anytime in the next the next forty eight hours. 78 00:04:24,480 --> 00:04:28,640 Speaker 2: So I saw this screen grab of flight radar showing 79 00:04:28,680 --> 00:04:32,320 Speaker 2: the path of a jet and the headline on it 80 00:04:32,480 --> 00:04:37,040 Speaker 2: was Kirkland F fifteen E heading for a port of Varta. 81 00:04:37,760 --> 00:04:40,960 Speaker 2: Now I'm in work mode, right, I'm just I'm looking 82 00:04:40,960 --> 00:04:41,320 Speaker 2: for a PIP. 83 00:04:41,360 --> 00:04:44,000 Speaker 3: I'm in work mode. I'm like, sure, wow, because we know. 84 00:04:43,960 --> 00:04:45,880 Speaker 2: There's all the I mean, you had twenty five members 85 00:04:45,880 --> 00:04:48,680 Speaker 2: of the National Guard. We're dead in aalis Goo, six 86 00:04:48,760 --> 00:04:52,640 Speaker 2: separate attacks after the killing of this new generation cartel 87 00:04:52,720 --> 00:04:56,159 Speaker 2: leader l Mensho. I mean, the violence is breaking out. 88 00:04:56,240 --> 00:04:58,960 Speaker 2: The tourists can't get out. ALFA News has some great 89 00:04:59,000 --> 00:05:01,840 Speaker 2: reporting on this at alt news dot org. They're telling people, 90 00:05:01,880 --> 00:05:03,120 Speaker 2: if you want to get out, you got to drive 91 00:05:03,160 --> 00:05:05,520 Speaker 2: north because they've canceled all the flights. So there's a 92 00:05:05,520 --> 00:05:07,359 Speaker 2: part of me that goes, well, I guess maybe we 93 00:05:07,400 --> 00:05:10,600 Speaker 2: could be sending some hardware down to Mexico. 94 00:05:10,800 --> 00:05:14,400 Speaker 3: You know, it's a show of force. Right, So I'm like, 95 00:05:14,440 --> 00:05:16,440 Speaker 3: what is a Kirkland F fifteen E. 96 00:05:19,400 --> 00:05:21,280 Speaker 2: Look at Logan and he's half paying attention to me 97 00:05:21,320 --> 00:05:24,479 Speaker 2: because he's watching Aurora Borealis videos on YouTube and he's 98 00:05:24,480 --> 00:05:27,320 Speaker 2: showing me subsequently, right, He's like, I don't know. I mean, 99 00:05:27,320 --> 00:05:29,240 Speaker 2: I know what a fifteen you know, I'm fifteen, you 100 00:05:29,279 --> 00:05:31,160 Speaker 2: know F fifteen E is, But I don't know Kirkland. 101 00:05:31,160 --> 00:05:34,080 Speaker 3: When am I still weird? So I actually googled it. Okay, 102 00:05:34,880 --> 00:05:35,680 Speaker 3: nothing came up. 103 00:05:36,279 --> 00:05:39,359 Speaker 2: The F fifteen came up, sure, but nothing attached to 104 00:05:39,360 --> 00:05:40,000 Speaker 2: Clerk Kirkland. 105 00:05:40,040 --> 00:05:40,640 Speaker 4: I'm like, just so. 106 00:05:40,640 --> 00:05:42,640 Speaker 3: Weird, and in the meantime, in the. 107 00:05:42,600 --> 00:05:44,520 Speaker 2: Back of my head, I'm going it sounds awfully familiar. 108 00:05:47,400 --> 00:05:49,400 Speaker 2: So what I didn't do was I didn't scroll further 109 00:05:49,440 --> 00:05:54,080 Speaker 2: on the post. Okay, underneath the flight radar picture capture 110 00:05:54,520 --> 00:05:57,400 Speaker 2: that showed the you know, the the track of the 111 00:05:57,440 --> 00:06:01,400 Speaker 2: F fifteen E was a screen grab of the fifteen 112 00:06:01,480 --> 00:06:07,599 Speaker 2: ME that was adorned in the colors of Costco with 113 00:06:07,640 --> 00:06:09,400 Speaker 2: the Costco label on the nose. 114 00:06:09,200 --> 00:06:09,480 Speaker 4: Of the. 115 00:06:12,880 --> 00:06:16,440 Speaker 3: You're fascinating to talk. I felt like such an idiot. 116 00:06:19,400 --> 00:06:22,800 Speaker 2: Cause they because they went after the Costco in port 117 00:06:22,800 --> 00:06:23,440 Speaker 2: of my Arta. 118 00:06:23,839 --> 00:06:29,360 Speaker 3: So they're bringing in the Kirkland fifteen. I get it. 119 00:06:29,400 --> 00:06:30,279 Speaker 3: I get it now. 120 00:06:31,040 --> 00:06:32,760 Speaker 6: I saw one of those in the parking lot at 121 00:06:32,800 --> 00:06:36,960 Speaker 6: the Costco in Burnsville. They there for sale at Kirkland fifteenth. 122 00:06:37,400 --> 00:06:39,960 Speaker 3: Can you yeah, what isle? What ile? Can you find 123 00:06:39,960 --> 00:06:41,600 Speaker 3: the Kirkland f fifteenth? 124 00:06:41,600 --> 00:06:45,479 Speaker 2: Though John Justice, Twin Cities News fantastic talk radio host, 125 00:06:45,520 --> 00:06:47,560 Speaker 2: I just figured I should probably play that until Laura 126 00:06:47,800 --> 00:06:49,520 Speaker 2: text me and says, can you stop playing that on 127 00:06:49,560 --> 00:06:52,760 Speaker 2: your show? I no longer agree with that assessment anymore, 128 00:06:53,279 --> 00:06:57,000 Speaker 2: so that made me laugh. Speaking of what's been taking 129 00:06:57,040 --> 00:07:00,279 Speaker 2: place down in Mexico, in all seriousness, the White House 130 00:07:00,320 --> 00:07:03,839 Speaker 2: did confirm that the US provided intelligence support to the operation. 131 00:07:04,760 --> 00:07:07,719 Speaker 2: No fifteen were involved as far as I know, although 132 00:07:07,720 --> 00:07:10,480 Speaker 2: I do feel bad for that Costco to capture the 133 00:07:10,560 --> 00:07:14,000 Speaker 2: cartel leader, and applauded Mexico's army for taking down a 134 00:07:14,000 --> 00:07:17,120 Speaker 2: man who was one of the most wanted criminals in 135 00:07:17,160 --> 00:07:20,680 Speaker 2: both countries. Elmncho was killed during the shootout in his 136 00:07:20,760 --> 00:07:23,840 Speaker 2: home state of Jalisco. As the Mexican military attempted to 137 00:07:23,880 --> 00:07:27,320 Speaker 2: capture him, the cartel members responded with violence across the country, 138 00:07:27,520 --> 00:07:30,800 Speaker 2: blocking roads and setting fire to vehicles. El Mencho I 139 00:07:30,800 --> 00:07:34,840 Speaker 2: don't think I brought this up yesterday, but he'd been 140 00:07:34,880 --> 00:07:39,600 Speaker 2: significantly involved in drug trafficking activities since the nineteen nineties. 141 00:07:40,240 --> 00:07:43,000 Speaker 2: In the US, he was convicted of conspiracy to distribute 142 00:07:43,000 --> 00:07:46,600 Speaker 2: heroin in northern California back in ninety four served nearly 143 00:07:46,640 --> 00:07:52,960 Speaker 2: three years in prison. After his release, Elmncho returned to 144 00:07:53,040 --> 00:07:57,760 Speaker 2: Mexico and joined another drug lord known as Nacho on 145 00:07:57,880 --> 00:08:00,520 Speaker 2: Coronelcho Coroner. 146 00:08:03,640 --> 00:08:05,320 Speaker 3: They were doing drug traffic at the time. 147 00:08:05,720 --> 00:08:11,760 Speaker 2: Following Nacho's death, El Mensho and L eighty five, another 148 00:08:11,840 --> 00:08:15,960 Speaker 2: drug lord, created the Jalisco New Generation Cartel around two 149 00:08:15,960 --> 00:08:19,400 Speaker 2: thousand and seven. Initially they had worked for the Sinaloa cartel, 150 00:08:19,960 --> 00:08:23,360 Speaker 2: but eventually split and for years the two Tarquelles cartels 151 00:08:23,560 --> 00:08:26,720 Speaker 2: have been battling for territory across Mexico. 152 00:08:26,920 --> 00:08:29,360 Speaker 3: By the way, this guy, Elmenshow. 153 00:08:28,800 --> 00:08:31,160 Speaker 2: Is a really great example of the type of individual 154 00:08:31,200 --> 00:08:34,120 Speaker 2: that anti Ice insurrectionists have been defending as they've been 155 00:08:34,120 --> 00:08:38,320 Speaker 2: getting away of ice on the streets Minnea apples much 156 00:08:38,320 --> 00:08:41,240 Speaker 2: smaller fish, obviously, but same mentality. 157 00:08:41,679 --> 00:08:43,440 Speaker 3: All right, Coming up, we'll give you a bit of 158 00:08:43,440 --> 00:08:47,920 Speaker 3: a preview of the fraud news that broke yesterday. 159 00:08:47,960 --> 00:08:51,040 Speaker 2: The new Program Integrity Director under Governor Tim Walls released 160 00:08:51,040 --> 00:08:54,440 Speaker 2: a fifty six page report, although Walls admittedly yesterday said 161 00:08:54,440 --> 00:08:55,160 Speaker 2: he didn't read it. 162 00:08:55,840 --> 00:08:58,480 Speaker 3: Why wouldn't you read it before he holds the press conference? 163 00:08:59,200 --> 00:09:03,800 Speaker 2: This is a report from a guy who you hired 164 00:09:03,960 --> 00:09:09,040 Speaker 2: to bring about integrity to the fraud that's cost Minnesotan's 165 00:09:09,120 --> 00:09:12,520 Speaker 2: billions of dollars. He has a press conference yesterday about 166 00:09:12,520 --> 00:09:14,160 Speaker 2: the report, and then the governor comes out and says, 167 00:09:14,200 --> 00:09:17,880 Speaker 2: I didn't read it, but I trust him, okay, And 168 00:09:17,880 --> 00:09:20,200 Speaker 2: then we'll talk with David Gartenstein Ross. If you have 169 00:09:20,200 --> 00:09:23,480 Speaker 2: any AI related questions, you can get those in early. 170 00:09:23,559 --> 00:09:26,800 Speaker 2: Just email me Justice at iHeartRadio dot com. Even, of course, 171 00:09:27,040 --> 00:09:29,280 Speaker 2: leave a question via the talkback. I see several of 172 00:09:29,320 --> 00:09:32,280 Speaker 2: you have already left comments via the iHeartRadio app brought 173 00:09:32,280 --> 00:09:34,400 Speaker 2: to you by Lyndahlrealty, and we will get to those 174 00:09:34,400 --> 00:09:36,800 Speaker 2: next right here on Twin Cities News Talk Am eleven 175 00:09:36,880 --> 00:09:38,360 Speaker 2: thirty and one oh three five FM. 176 00:09:38,440 --> 00:09:40,079 Speaker 5: Good morning, and I love your show. 177 00:09:46,679 --> 00:09:50,079 Speaker 7: Good morning, John Paul from Brooklyn Park. I remember wal 178 00:09:50,200 --> 00:09:52,200 Speaker 7: saying last week that he was the only one that 179 00:09:52,280 --> 00:09:55,079 Speaker 7: cares about fraud anymore. And now the guy won't take 180 00:09:55,120 --> 00:09:57,040 Speaker 7: time to read a fraud report from a guy he 181 00:09:57,160 --> 00:10:00,280 Speaker 7: hired to look into it. Wow, he stopped there. 182 00:10:00,320 --> 00:10:04,280 Speaker 3: You hurry, that's a really good point. Thank you for 183 00:10:04,320 --> 00:10:04,839 Speaker 3: the talk back. 184 00:10:05,360 --> 00:10:09,040 Speaker 8: Expect for the next eleven months for me to ride 185 00:10:09,080 --> 00:10:10,480 Speaker 8: you like you've never been ridden. 186 00:10:11,040 --> 00:10:13,960 Speaker 3: How's it going? By the way, are we still being 187 00:10:13,960 --> 00:10:17,200 Speaker 3: written by Walls? Did the writing start yet? 188 00:10:19,480 --> 00:10:22,520 Speaker 2: Twin City's News Talk Am eleven thirty one oh three 189 00:10:22,679 --> 00:10:25,320 Speaker 2: five FM. 190 00:10:25,960 --> 00:10:27,800 Speaker 3: My name is John Justice. I'm glad you're with the 191 00:10:27,800 --> 00:10:28,439 Speaker 3: show this morning. 192 00:10:28,760 --> 00:10:31,720 Speaker 4: I think has a good marketing opportunity. 193 00:10:31,800 --> 00:10:36,400 Speaker 2: They could make it el Montell favored Dorito Chips, limited time, thanks, 194 00:10:36,960 --> 00:10:39,079 Speaker 2: makes lots of money. I was thinking the same thing 195 00:10:39,120 --> 00:10:45,480 Speaker 2: with the other drug lord being named Natcho. I still 196 00:10:45,480 --> 00:10:48,440 Speaker 2: can't believe the Kirkland fifteen. I still I felt so 197 00:10:48,480 --> 00:10:51,120 Speaker 2: foolish for that one. Like I said in my defense, 198 00:10:51,160 --> 00:10:54,000 Speaker 2: I was, I was. I was locked in at the time, 199 00:10:57,520 --> 00:10:58,520 Speaker 2: so New York City. 200 00:10:58,360 --> 00:10:59,120 Speaker 3: Got a bunch of snow. 201 00:11:00,080 --> 00:11:04,959 Speaker 2: My conversation with Davide Gartensteinross. Right, so they've been trying 202 00:11:05,000 --> 00:11:06,880 Speaker 2: to figure out ways to go and clear the snow. 203 00:11:06,960 --> 00:11:10,440 Speaker 2: We played the clip yesterday of zohoron Mom Donnie talking 204 00:11:10,440 --> 00:11:14,680 Speaker 2: about how you need multiple IDs in order to borrow 205 00:11:14,720 --> 00:11:19,840 Speaker 2: a shovel. Okay, well here's a new one. Wages are 206 00:11:19,880 --> 00:11:22,880 Speaker 2: surging for anyone in New York City who wants to 207 00:11:22,920 --> 00:11:28,199 Speaker 2: sign up to shovel snow. Zohorn had a press conference yesterday. 208 00:11:28,559 --> 00:11:31,000 Speaker 2: He increased the hourly wage. 209 00:11:31,120 --> 00:11:32,120 Speaker 3: This is unbelievable. 210 00:11:32,360 --> 00:11:36,760 Speaker 2: He increased the hourgy wage for snow shovelers from nineteen 211 00:11:36,840 --> 00:11:40,200 Speaker 2: dollars and fourteen cents to thirty dollars an hour. 212 00:11:40,360 --> 00:11:41,680 Speaker 3: You're fascinating to talk to. 213 00:11:43,800 --> 00:11:47,839 Speaker 2: After forty hours, that rate jumps even higher to forty 214 00:11:47,880 --> 00:11:53,960 Speaker 2: five dollars an hour. Oh, how did they plan on 215 00:11:54,000 --> 00:12:00,160 Speaker 2: tracking that? How do they plan on tracking. 216 00:12:00,080 --> 00:12:00,920 Speaker 3: Tracking which part? 217 00:12:01,240 --> 00:12:03,280 Speaker 2: How many hours they're gonna be shoveling snow? Is that 218 00:12:03,320 --> 00:12:06,360 Speaker 2: going to be self reported? Like I if my wife 219 00:12:06,480 --> 00:12:09,280 Speaker 2: was charging me forty five dollars an hour to shovel 220 00:12:09,360 --> 00:12:12,080 Speaker 2: the driveway, yeah, Ohana, it's gonna take me two days. 221 00:12:15,840 --> 00:12:19,560 Speaker 2: I mean, it's just it is ripe for fraud. They're 222 00:12:19,600 --> 00:12:22,960 Speaker 2: not gonna have it. There's no there is no comprehensive way. 223 00:12:24,000 --> 00:12:24,800 Speaker 2: There is no. 224 00:12:26,559 --> 00:12:27,120 Speaker 3: Good way. 225 00:12:27,200 --> 00:12:29,240 Speaker 2: Let me make it easier. There is no good way 226 00:12:30,160 --> 00:12:36,480 Speaker 2: to track shoveling of snow in New York City without 227 00:12:36,600 --> 00:12:40,400 Speaker 2: just having it be you're gonna self report. I mean 228 00:12:40,440 --> 00:12:44,679 Speaker 2: the evidence would have to be there, right, But at 229 00:12:44,720 --> 00:12:47,160 Speaker 2: forty five dollars an hour, I mean, you and a 230 00:12:47,200 --> 00:12:50,760 Speaker 2: handful of your buddies could probably get yourself a little 231 00:12:50,800 --> 00:12:53,480 Speaker 2: tiny tractor, not tell anybody, clear out all. 232 00:12:53,400 --> 00:12:54,839 Speaker 3: The snow and then just put down. 233 00:12:54,880 --> 00:12:57,520 Speaker 2: Oh yeah, it took us eighty five hours to clear 234 00:12:57,559 --> 00:13:02,480 Speaker 2: all that snow. Now give me the cash before the 235 00:13:02,480 --> 00:13:05,480 Speaker 2: hour of your wage increase. The program reportedly failed to 236 00:13:05,520 --> 00:13:08,960 Speaker 2: attract any shovelers for hours at the New York Side. 237 00:13:09,000 --> 00:13:11,680 Speaker 2: City officials said they hoped to return with lazy people. 238 00:13:11,920 --> 00:13:17,280 Speaker 2: You look at even even twenty dollars an hour, I wouldn't. 239 00:13:17,280 --> 00:13:19,160 Speaker 3: I wouldn't pay my son's that again. If I did, 240 00:13:19,240 --> 00:13:20,760 Speaker 3: they'd be, oh, it's taking me so long. 241 00:13:21,320 --> 00:13:26,040 Speaker 2: Uh snow is so thick and heavy. City officials said 242 00:13:26,040 --> 00:13:29,080 Speaker 2: they hoped to attract a total of fourteen hundred public 243 00:13:29,120 --> 00:13:34,000 Speaker 2: shovelers by comparison in twenty fifteen, the city did attract 244 00:13:34,440 --> 00:13:37,920 Speaker 2: some six four hundred and fifty four shovelers. During the 245 00:13:37,960 --> 00:13:41,959 Speaker 2: press briefing, Zohoran reminded New York City property owners that 246 00:13:42,040 --> 00:13:44,720 Speaker 2: the mandate to clear a foot wide path along the 247 00:13:44,800 --> 00:13:48,920 Speaker 2: sidewalks remains in effect. When this story first broke about 248 00:13:48,960 --> 00:13:50,959 Speaker 2: the shovels, I just thought it was because of all 249 00:13:50,960 --> 00:13:53,800 Speaker 2: the pooh. I don't know if you saw the footage, 250 00:13:53,800 --> 00:13:56,400 Speaker 2: but prior to the snowstorm rolling in, a lot of 251 00:13:56,400 --> 00:13:58,720 Speaker 2: the snow had melted and the sidewalks were all covered 252 00:13:58,760 --> 00:14:03,880 Speaker 2: in pooh. Just really, it's really really disgusting. That's really gross. 253 00:14:04,400 --> 00:14:06,400 Speaker 6: I believe that last time I was, oh, sorry, last 254 00:14:06,400 --> 00:14:08,040 Speaker 6: time was to say, last time I was in New York, 255 00:14:08,120 --> 00:14:11,640 Speaker 6: there was I mean sort of the stereotype trash everywhere. 256 00:14:11,760 --> 00:14:13,720 Speaker 6: It was. It was a lot. And I was in 257 00:14:13,800 --> 00:14:15,320 Speaker 6: Queens kind of by the airport. 258 00:14:15,400 --> 00:14:18,320 Speaker 2: I have a I have a story later on today 259 00:14:18,640 --> 00:14:22,480 Speaker 2: out of Aurora, Colorado. So there's an editorial by some 260 00:14:22,600 --> 00:14:25,440 Speaker 2: Yahoo and the Star Tribute. Then I'll share that is 261 00:14:26,040 --> 00:14:28,000 Speaker 2: talking about just how wonderful it would be at the 262 00:14:28,000 --> 00:14:30,840 Speaker 2: city of Minneapolis won the Nobel Peace Prize. But I 263 00:14:30,840 --> 00:14:34,320 Speaker 2: found this story out of Aurora, Colorado, and really it 264 00:14:34,400 --> 00:14:38,240 Speaker 2: is a it's a cautionary tale, as Aurora serves kind 265 00:14:38,320 --> 00:14:43,000 Speaker 2: of as a sister city relating to corrupt and dangerous 266 00:14:43,040 --> 00:14:47,240 Speaker 2: Democrat policies. So we'll get into this much later in 267 00:14:47,360 --> 00:14:49,680 Speaker 2: the seven o'clock hour this morning. But if you're looking 268 00:14:49,720 --> 00:14:54,360 Speaker 2: to make a buck, fraudulently or legitimately, homp yourself on 269 00:14:54,400 --> 00:14:56,840 Speaker 2: a plane to New York City, where if you work 270 00:14:56,880 --> 00:14:59,920 Speaker 2: more than forty hours you can get paid forty five 271 00:15:00,480 --> 00:15:03,920 Speaker 2: forty five dollars an hour or two shovel to shovel snow. 272 00:15:04,880 --> 00:15:07,240 Speaker 2: Of course, that's after you present multiple IDs to go 273 00:15:07,320 --> 00:15:12,360 Speaker 2: and get the snow shovel. All right, coming up AI 274 00:15:12,480 --> 00:15:15,760 Speaker 2: convenience trap that no one warned moms about. Essentially, what 275 00:15:15,800 --> 00:15:19,240 Speaker 2: this amounts to is concerned that with all of the 276 00:15:19,320 --> 00:15:26,760 Speaker 2: conveniences that are given by AI, it also ends up 277 00:15:26,800 --> 00:15:29,240 Speaker 2: being a time suck for a lot of people because 278 00:15:29,280 --> 00:15:33,239 Speaker 2: of all of the ancillary things that end up occupying 279 00:15:33,280 --> 00:15:36,720 Speaker 2: your time that you perhaps wouldn't have found if you 280 00:15:36,760 --> 00:15:39,200 Speaker 2: weren't utilizing AI. I think most of this comes down 281 00:15:39,200 --> 00:15:42,800 Speaker 2: to personal responsibility, but we do have other concerns. 282 00:15:43,240 --> 00:15:44,720 Speaker 3: AI entering the operating room. 283 00:15:44,760 --> 00:15:52,400 Speaker 2: Reports are rising of boxed surgeries, misidentified body parts. Well, 284 00:15:52,400 --> 00:15:55,800 Speaker 2: there's some correlation between the ice protesters and their rubber 285 00:15:55,840 --> 00:15:58,400 Speaker 2: body parts and the misidentified and body parts of AI. 286 00:15:58,640 --> 00:16:00,920 Speaker 2: In the meantime, AI leaders at and AI and other 287 00:16:00,960 --> 00:16:05,240 Speaker 2: AI platforms are fleeing their jobs as doomsday scenarios that 288 00:16:05,440 --> 00:16:07,800 Speaker 2: increase the concerns grow via AI, and we're going to 289 00:16:07,840 --> 00:16:10,200 Speaker 2: talk about whether or not there's any legitimacy to them 290 00:16:10,200 --> 00:16:13,480 Speaker 2: with Dvid Gartenstein Ross the CEO, ad to expert theory, 291 00:16:13,520 --> 00:16:17,840 Speaker 2: and if you have any artificial intelligence related questions. It's 292 00:16:17,880 --> 00:16:19,720 Speaker 2: always kind of a free for all when it comes 293 00:16:19,760 --> 00:16:21,640 Speaker 2: to DVD. We'll talk about the stories that we have 294 00:16:21,680 --> 00:16:24,520 Speaker 2: in the stack, but we'll also take any AI related questions. 295 00:16:24,640 --> 00:16:27,000 Speaker 2: You can get those any email me Justice at iHeartRadio 296 00:16:27,040 --> 00:16:29,600 Speaker 2: dot com or leave a talk back on the iHeartRadio 297 00:16:29,640 --> 00:16:31,920 Speaker 2: app and we'll share those with David next here on 298 00:16:31,960 --> 00:16:33,960 Speaker 2: Twin City's News Talk Am eleven thirty and one o 299 00:16:34,040 --> 00:16:40,120 Speaker 2: three five FM. John Justice on Twin Cities News Talk 300 00:16:40,160 --> 00:16:42,800 Speaker 2: Am eleven thirty and one oh three five FM, streaming 301 00:16:42,800 --> 00:16:48,080 Speaker 2: worldwide on the iHeartRadio app. I'm very pleased to welcome 302 00:16:48,080 --> 00:16:51,520 Speaker 2: to the show once again the CEO at Expert Theory, 303 00:16:52,920 --> 00:16:57,200 Speaker 2: analyst and expert regarding all things artificial intelligence. Friend of 304 00:16:57,200 --> 00:17:00,760 Speaker 2: the show, David Gartenstein Ross, come on InVID. 305 00:17:01,320 --> 00:17:02,680 Speaker 4: Good morning job. Get you joined you? 306 00:17:02,960 --> 00:17:04,479 Speaker 2: Yeah, good to have you on. I got a lot 307 00:17:04,520 --> 00:17:06,840 Speaker 2: of questions that are already rolling in. Got a few 308 00:17:06,840 --> 00:17:09,000 Speaker 2: items in the stack that we will try to get 309 00:17:09,040 --> 00:17:12,720 Speaker 2: to as well this morning as we continue our artificial 310 00:17:12,760 --> 00:17:17,440 Speaker 2: intelligence discussions. I want to start here. Last week he 311 00:17:17,480 --> 00:17:19,800 Speaker 2: didn't have the opportunity to join us. There was an 312 00:17:19,880 --> 00:17:22,280 Speaker 2: article that I wanted to talk to you about, and 313 00:17:22,320 --> 00:17:26,840 Speaker 2: we can discuss it briefly. It made it made some 314 00:17:26,960 --> 00:17:30,040 Speaker 2: waves about two or three weeks ago. It was a 315 00:17:30,040 --> 00:17:33,600 Speaker 2: substack article an author I'm unfamiliar with but has been 316 00:17:33,720 --> 00:17:39,520 Speaker 2: utilizing AI. Glenn Beck actually read a large portion of 317 00:17:39,560 --> 00:17:43,960 Speaker 2: this substack article on his show and the writer, the 318 00:17:44,000 --> 00:17:48,840 Speaker 2: author was basically laying out the concerns that he had 319 00:17:48,920 --> 00:17:53,400 Speaker 2: because of how quickly artificial intelligence has advanced, and he 320 00:17:53,520 --> 00:17:57,800 Speaker 2: used an example of how he had gone to create 321 00:17:57,840 --> 00:18:01,919 Speaker 2: an app and based off of almost the prompt alone. 322 00:18:01,920 --> 00:18:04,080 Speaker 2: And feel free to v because I know you've gone 323 00:18:04,080 --> 00:18:07,159 Speaker 2: through this piece to fill in any blanks as as 324 00:18:07,160 --> 00:18:09,560 Speaker 2: I handed over to you, But he had he had 325 00:18:09,640 --> 00:18:12,159 Speaker 2: put together the prompt to create this app, and the 326 00:18:12,200 --> 00:18:15,600 Speaker 2: AI had created the app went so far as to 327 00:18:15,680 --> 00:18:18,560 Speaker 2: test the app to work out any so called bugs 328 00:18:19,040 --> 00:18:23,960 Speaker 2: before it ended up handing this individual a completed product. 329 00:18:24,280 --> 00:18:26,000 Speaker 2: It was interesting to me to v just as a 330 00:18:26,000 --> 00:18:29,360 Speaker 2: bit of a background. Prior to you know, our dear 331 00:18:29,359 --> 00:18:32,240 Speaker 2: friend Drew passing away, we had, along with a few 332 00:18:32,240 --> 00:18:36,320 Speaker 2: other individuals, actually developed an app and we went through 333 00:18:36,320 --> 00:18:39,440 Speaker 2: the process and it was a complicated process, working with 334 00:18:39,480 --> 00:18:41,440 Speaker 2: a with a company that took a lot of time 335 00:18:41,480 --> 00:18:45,040 Speaker 2: to create this app. Unfortunately, that company was ultimately hacked 336 00:18:45,040 --> 00:18:48,199 Speaker 2: and everything regarding our app was destroyed, destroyed, and that 337 00:18:48,320 --> 00:18:50,800 Speaker 2: was the end of that. So all that being said, 338 00:18:50,880 --> 00:18:53,879 Speaker 2: this guy was basically laying out his concerns about how 339 00:18:54,000 --> 00:18:56,800 Speaker 2: quickly AI was advancing and what it's going to mean 340 00:18:56,840 --> 00:19:00,240 Speaker 2: for society moving forward. Last thing on this I thought 341 00:19:00,280 --> 00:19:02,520 Speaker 2: it was interesting because I sent this to you and 342 00:19:02,560 --> 00:19:05,960 Speaker 2: you had replied very calmly and directly, which I always 343 00:19:05,960 --> 00:19:06,880 Speaker 2: appreciate from you. 344 00:19:06,880 --> 00:19:09,040 Speaker 3: That yes, AI codes well. 345 00:19:09,720 --> 00:19:12,200 Speaker 2: So I wanted to hold off on any more commentary 346 00:19:12,240 --> 00:19:14,879 Speaker 2: from you regarding what this individual had to say. But 347 00:19:15,160 --> 00:19:17,399 Speaker 2: he had a lot of concerns in that piece, and 348 00:19:17,440 --> 00:19:20,320 Speaker 2: I'm wondering if you thought any of those concerns were 349 00:19:20,359 --> 00:19:23,400 Speaker 2: warranted or if it was just an example of how 350 00:19:23,520 --> 00:19:26,399 Speaker 2: well AI is able to code. 351 00:19:26,600 --> 00:19:28,560 Speaker 4: Oh, no, the concerns are warranted. 352 00:19:28,840 --> 00:19:31,720 Speaker 1: So to provide a little bit more color, this is 353 00:19:32,040 --> 00:19:37,480 Speaker 1: by Matt Schumer, And definitely you know your audience members 354 00:19:37,600 --> 00:19:41,359 Speaker 1: have probably come across this, but if not, we should 355 00:19:41,400 --> 00:19:42,919 Speaker 1: post it to x just so they can take a 356 00:19:42,920 --> 00:19:48,840 Speaker 1: look at it, to provide color. He is an he's 357 00:19:48,880 --> 00:19:53,679 Speaker 1: a developer, he's an engineer, right. He writes code and 358 00:19:53,720 --> 00:19:57,960 Speaker 1: he's good at it, and he's reading the alarm because 359 00:19:58,760 --> 00:20:05,080 Speaker 1: AI is way better than he is now at being 360 00:20:05,119 --> 00:20:09,119 Speaker 1: able to write code, and not just writing code, but 361 00:20:09,640 --> 00:20:14,040 Speaker 1: testing an entire app with what seems to him like 362 00:20:14,119 --> 00:20:17,360 Speaker 1: good judgment, the kind of thing that AI isn't supposed 363 00:20:17,400 --> 00:20:21,520 Speaker 1: to have. And so to read a piece for like 364 00:20:21,840 --> 00:20:25,440 Speaker 1: a portion of his essay, just to make clear why 365 00:20:25,480 --> 00:20:28,760 Speaker 1: he's ringing the alarm, he writes, in twenty twenty two, 366 00:20:29,000 --> 00:20:32,960 Speaker 1: AI couldn't do basic arithmetic reliably. It would confidently tell 367 00:20:33,000 --> 00:20:36,639 Speaker 1: you that seven times eight equals fifty four. By twenty 368 00:20:36,640 --> 00:20:39,440 Speaker 1: twenty three, it could pass the Bar exam. By twenty 369 00:20:39,480 --> 00:20:41,919 Speaker 1: twenty four, it could write work you software and explain 370 00:20:42,000 --> 00:20:45,639 Speaker 1: graduate level science. By late twenty twenty five, some of 371 00:20:45,680 --> 00:20:47,800 Speaker 1: the best engineers in the world said they had handed 372 00:20:47,840 --> 00:20:51,280 Speaker 1: over most of their coding work to AI. On February fifth, 373 00:20:51,280 --> 00:20:54,680 Speaker 1: twenty twenty six, new models arrived that made everything before 374 00:20:54,720 --> 00:20:56,000 Speaker 1: them feel like a different era. 375 00:20:57,160 --> 00:21:01,040 Speaker 4: So it's putas moving fast. It's moving in code first. 376 00:21:01,520 --> 00:21:07,679 Speaker 1: Why because AI companies are very, very code heavy, and 377 00:21:07,720 --> 00:21:10,680 Speaker 1: if they could perfect AI code first, it's going to 378 00:21:10,720 --> 00:21:15,439 Speaker 1: help them more than anything else. The argument Matt Schuer 379 00:21:15,440 --> 00:21:18,680 Speaker 1: makes is that this is coming to every job sector 380 00:21:19,359 --> 00:21:24,560 Speaker 1: and it is destabilizing professionally in a way that nothing 381 00:21:24,600 --> 00:21:25,679 Speaker 1: that came before it was. 382 00:21:26,320 --> 00:21:28,040 Speaker 4: All of this is legitimate. 383 00:21:27,600 --> 00:21:30,960 Speaker 1: And I definitely think it is worth a read. 384 00:21:31,280 --> 00:21:34,320 Speaker 2: Well, is there any relatability to I have a piece 385 00:21:35,280 --> 00:21:38,919 Speaker 2: out of Axios This morning. Top AI experts at OpenAI, 386 00:21:39,080 --> 00:21:42,879 Speaker 2: Anthropic and other companies warn of the rising dangers of 387 00:21:42,880 --> 00:21:47,600 Speaker 2: their technology, with some quitting in protest or going public 388 00:21:47,640 --> 00:21:50,360 Speaker 2: with grave concerns. And it goes through and it lists 389 00:21:50,680 --> 00:21:53,040 Speaker 2: some of the different researchers some of the comments that 390 00:21:53,040 --> 00:21:57,080 Speaker 2: they've made. I finally feel the existential threat that AI 391 00:21:57,359 --> 00:22:01,000 Speaker 2: is posing. Another tech investor and co host of a 392 00:22:01,040 --> 00:22:05,000 Speaker 2: podcast said, I've never seen so many technologists to state 393 00:22:05,040 --> 00:22:09,439 Speaker 2: their concerns so strongly frequently with such concern as I 394 00:22:09,560 --> 00:22:12,520 Speaker 2: have with AI. And I guess one question that will 395 00:22:12,520 --> 00:22:15,320 Speaker 2: pop up with this deviat is if these individuals are 396 00:22:15,320 --> 00:22:18,760 Speaker 2: so concerned, there's just going to be somebody else that's 397 00:22:18,800 --> 00:22:21,920 Speaker 2: going to step in to continue to push the technology forward. 398 00:22:22,280 --> 00:22:24,679 Speaker 2: Why wouldn't you stay in get now that you know 399 00:22:24,720 --> 00:22:26,920 Speaker 2: what these individuals are thinking, But I guess I'm questioning 400 00:22:27,160 --> 00:22:31,080 Speaker 2: why wouldn't you stay engaged to keep fundamental checks in 401 00:22:31,119 --> 00:22:35,400 Speaker 2: place for AI as opposed to just abandoning it all together. 402 00:22:36,760 --> 00:22:40,600 Speaker 1: You can't really advocate for fundamental checks when you're employed 403 00:22:40,640 --> 00:22:43,080 Speaker 1: by open AI, at least not fundamental checks that we 404 00:22:43,200 --> 00:22:46,000 Speaker 1: cross the business. I would wager that most of the that, 405 00:22:46,160 --> 00:22:51,080 Speaker 1: like the people who are quitting, have one of two ideas. 406 00:22:51,720 --> 00:22:54,399 Speaker 1: What is simply they view this as an existential threat 407 00:22:54,440 --> 00:22:56,639 Speaker 1: and don't want to be a part of that system, 408 00:22:56,960 --> 00:22:59,119 Speaker 1: or idea too will be We'll see some of them 409 00:22:59,160 --> 00:23:02,800 Speaker 1: re emerge at you know, nonprofits or others that are 410 00:23:02,840 --> 00:23:04,400 Speaker 1: pushing for AI regulation. 411 00:23:05,520 --> 00:23:07,600 Speaker 2: So what do you think I mean, how how you know, 412 00:23:07,720 --> 00:23:11,000 Speaker 2: how how grave are these concerns these individuals have when 413 00:23:11,040 --> 00:23:14,240 Speaker 2: you see a story like this, do you sort of understand? 414 00:23:14,520 --> 00:23:16,000 Speaker 2: You know, I don't want to say agree, but I'm 415 00:23:16,000 --> 00:23:18,520 Speaker 2: just curious your thoughts as to the concerns that are 416 00:23:18,520 --> 00:23:20,760 Speaker 2: being presented by these individuals that are at the core 417 00:23:20,800 --> 00:23:21,679 Speaker 2: of this technology. 418 00:23:22,160 --> 00:23:25,000 Speaker 1: Oh yeah, I mean I understand them and agree. Like 419 00:23:25,280 --> 00:23:30,479 Speaker 1: my past hat, you know, before founding expert theory, I 420 00:23:30,560 --> 00:23:32,360 Speaker 1: was in the counter terrorism sphere for. 421 00:23:33,920 --> 00:23:36,400 Speaker 4: You know, a little over two decades. 422 00:23:37,280 --> 00:23:40,600 Speaker 1: I actually testified before Congress last year, if I recall 423 00:23:40,680 --> 00:23:45,159 Speaker 1: John about terrorist use of artificial intelligence, and there I 424 00:23:45,200 --> 00:23:49,359 Speaker 1: was explained all of the ways terrorists could use AI. Now, 425 00:23:49,520 --> 00:23:53,040 Speaker 1: so there are now new ways that terrorists or other 426 00:23:53,400 --> 00:23:56,440 Speaker 1: adversaries could use AI. What are the things that they're 427 00:23:56,440 --> 00:24:00,600 Speaker 1: wringing the alarm about is AI and the way that 428 00:24:00,640 --> 00:24:05,760 Speaker 1: it can help people to fashion biological weapons. There are 429 00:24:05,760 --> 00:24:08,800 Speaker 1: other things related to AI. You know, if the safety 430 00:24:08,800 --> 00:24:12,200 Speaker 1: controls aren't in place, AI can walk you through how 431 00:24:12,200 --> 00:24:15,000 Speaker 1: to assassinate somebody. There's a lot of things that it 432 00:24:15,080 --> 00:24:19,120 Speaker 1: can do that are deeply, deeply disturbing, and it's accelerating 433 00:24:19,440 --> 00:24:24,760 Speaker 1: learning curves all around. If you zoom out, not all 434 00:24:24,760 --> 00:24:28,520 Speaker 1: of this will touch on AI. It won't necessarily fundamentally 435 00:24:28,560 --> 00:24:31,439 Speaker 1: relate to AI or fundamentally be driven by AI, but 436 00:24:31,480 --> 00:24:34,960 Speaker 1: it all touches on AI. Cartels at this point are 437 00:24:35,080 --> 00:24:39,960 Speaker 1: using drones, you know, unmanned aerial vehicles in an extraordinarily 438 00:24:39,960 --> 00:24:45,480 Speaker 1: effective way. There are places where criminal organization's use of 439 00:24:45,560 --> 00:24:49,760 Speaker 1: drones in Latin America can be deeply destabilizing. 440 00:24:49,760 --> 00:24:51,400 Speaker 4: Colombia is one of those countries. 441 00:24:52,800 --> 00:24:55,800 Speaker 1: You know, Terrorist groups the world over are using artificial 442 00:24:55,840 --> 00:25:02,160 Speaker 1: intelligence in a variety of ways, you know the I mean, 443 00:25:02,440 --> 00:25:06,760 Speaker 1: if you zoom out, the problems are are significant, and 444 00:25:07,760 --> 00:25:12,960 Speaker 1: technological leaps forward are out pacing any sort of attempt 445 00:25:13,080 --> 00:25:19,160 Speaker 1: to put safety features into play, and that creates a 446 00:25:19,280 --> 00:25:22,280 Speaker 1: system that's dangerous. I think we talked about this on 447 00:25:22,320 --> 00:25:24,680 Speaker 1: a number of occasions, right including if you go back 448 00:25:24,720 --> 00:25:27,040 Speaker 1: ten fifteen years ago, Like this is something I was 449 00:25:27,080 --> 00:25:27,919 Speaker 1: talking about then. 450 00:25:28,280 --> 00:25:30,600 Speaker 4: When it wasn't really on people's radar. 451 00:25:30,640 --> 00:25:34,000 Speaker 1: But at this point in time, I think that almost 452 00:25:34,080 --> 00:25:39,959 Speaker 1: everybody in AI recognizes there's an existential risk, and no 453 00:25:40,000 --> 00:25:43,840 Speaker 1: one really will stop it, right, Like, no one has 454 00:25:43,880 --> 00:25:46,520 Speaker 1: the ability to do so, because it's a system that 455 00:25:46,640 --> 00:25:49,399 Speaker 1: is moving faster than any of them can control. And 456 00:25:49,480 --> 00:25:52,800 Speaker 1: even if we were able to perfectly regulate AI in 457 00:25:52,880 --> 00:25:57,040 Speaker 1: the West, there's this AI race between the US and China, 458 00:25:57,560 --> 00:26:01,640 Speaker 1: which means that we can't even in our own sphere 459 00:26:02,080 --> 00:26:04,840 Speaker 1: regulate away the issues because it's coming from somewhere that 460 00:26:04,880 --> 00:26:06,560 Speaker 1: we have no regulatory control over. 461 00:26:07,680 --> 00:26:13,000 Speaker 2: Talking with David Gartenstein, Ross AI expert and analyst and 462 00:26:13,119 --> 00:26:15,720 Speaker 2: CEO at Expert Theory, you mentioned, of course, you know 463 00:26:15,760 --> 00:26:19,760 Speaker 2: your expertise in counter terrorism complete sidebar devide. It just 464 00:26:19,840 --> 00:26:22,199 Speaker 2: provides me an opportunity to bring something up because you 465 00:26:22,280 --> 00:26:24,600 Speaker 2: mentioned drones a moment ago, and then we'll get right 466 00:26:24,640 --> 00:26:26,680 Speaker 2: back to AI. I don't know if you spend any 467 00:26:26,720 --> 00:26:29,439 Speaker 2: time in looking into this, but I went down a 468 00:26:29,520 --> 00:26:33,080 Speaker 2: rabbit hole yesterday of the drone warfare that's been taking 469 00:26:33,119 --> 00:26:37,000 Speaker 2: place between Russia and Ukraine and the fact that these 470 00:26:37,080 --> 00:26:41,480 Speaker 2: drones are using this fiber optic cable for communication to 471 00:26:41,520 --> 00:26:43,720 Speaker 2: the drones, so the drones can't be hacked. But this 472 00:26:43,800 --> 00:26:47,960 Speaker 2: has now left just miles and miles of fiber optic 473 00:26:48,080 --> 00:26:51,359 Speaker 2: cable across the landscape in Ukraine. I've seen just a 474 00:26:51,400 --> 00:26:53,800 Speaker 2: couple of different videos regarding this. It is one of 475 00:26:53,880 --> 00:26:56,439 Speaker 2: the wildest things to v that I think I have 476 00:26:56,520 --> 00:26:59,320 Speaker 2: seen in a long long time, and you had mentioned 477 00:26:59,320 --> 00:27:00,440 Speaker 2: in to me an. 478 00:27:00,359 --> 00:27:01,800 Speaker 3: Opportunity to bring it up briefly. 479 00:27:02,440 --> 00:27:07,359 Speaker 1: No, I appreciate that it's I'm following those events relatively 480 00:27:07,400 --> 00:27:12,080 Speaker 1: closely in Ukraine because we're going to see a lot 481 00:27:12,119 --> 00:27:17,560 Speaker 1: of the innovations that are being showcased in Ukraine in 482 00:27:17,880 --> 00:27:19,480 Speaker 1: a number of other places in the world. 483 00:27:19,640 --> 00:27:22,200 Speaker 2: Unfortunately, how much of those Just as a side note, 484 00:27:22,440 --> 00:27:25,159 Speaker 2: bringing it back to AI, do you know, I mean, 485 00:27:25,200 --> 00:27:27,320 Speaker 2: how much of those AIS are being I mean, excuse me, 486 00:27:27,320 --> 00:27:29,400 Speaker 2: those drones are being guided by AI. I know they're 487 00:27:29,480 --> 00:27:32,120 Speaker 2: using sort of traditional fiber optic cable to keep them 488 00:27:32,119 --> 00:27:35,080 Speaker 2: from being hacked, But are those being is AI being 489 00:27:35,160 --> 00:27:38,080 Speaker 2: utilized in that drone warfare in the way that they 490 00:27:38,160 --> 00:27:40,160 Speaker 2: are using those drones to attack each other. 491 00:27:40,920 --> 00:27:44,639 Speaker 1: I don't know the technical specifications. AI is certainly touches 492 00:27:44,680 --> 00:27:50,280 Speaker 1: on it. My guess is that AI. Look, AI is 493 00:27:50,280 --> 00:27:52,480 Speaker 1: now a part of almost every system we have, right 494 00:27:52,640 --> 00:27:55,680 Speaker 1: like any new car, AI is a part of the car, 495 00:27:56,119 --> 00:27:59,879 Speaker 1: even if it's not like the new Tesla's fully self driving. 496 00:28:01,040 --> 00:28:04,920 Speaker 1: Like cars are now machines, they're not are differently cars 497 00:28:04,960 --> 00:28:07,880 Speaker 1: are now computers. They've always been machines, but cars are 498 00:28:07,880 --> 00:28:11,919 Speaker 1: now computers. 499 00:28:10,720 --> 00:28:12,240 Speaker 4: So AI touches it. 500 00:28:13,040 --> 00:28:15,520 Speaker 1: We don't yet have, Like there's a lot of talk 501 00:28:15,560 --> 00:28:19,280 Speaker 1: about kind of drovee swarms, which a droug swarm is 502 00:28:19,320 --> 00:28:23,280 Speaker 1: literally drogs that swarm autonomously, where AI is guiding them 503 00:28:23,560 --> 00:28:26,800 Speaker 1: rather than human operators. Right, we, as far as I know, 504 00:28:27,640 --> 00:28:30,320 Speaker 1: the world still has not seen a true drovee swarm. 505 00:28:31,080 --> 00:28:33,359 Speaker 4: But AI is a part of every drone system. 506 00:28:34,440 --> 00:28:36,400 Speaker 2: Let's get into some of the talkbacks that have rolled 507 00:28:36,440 --> 00:28:39,200 Speaker 2: in questions for our AI expert de Vd Gartenstein Rossen 508 00:28:39,240 --> 00:28:39,840 Speaker 2: will start here. 509 00:28:40,520 --> 00:28:43,800 Speaker 9: Big question for David, I haven't heard anybody even talk 510 00:28:43,880 --> 00:28:49,960 Speaker 9: about the AI not necessarily being Internet based but just 511 00:28:50,080 --> 00:28:53,440 Speaker 9: my phone or just my laptop, me being able to 512 00:28:53,480 --> 00:28:55,720 Speaker 9: tell my laptop that I wanted to copy a file 513 00:28:55,800 --> 00:28:58,200 Speaker 9: over or do this or do that, and then just 514 00:28:58,240 --> 00:29:03,840 Speaker 9: be on my on my computer itself and not necessarily 515 00:29:04,400 --> 00:29:07,160 Speaker 9: for just searching the Internet for answers. 516 00:29:07,560 --> 00:29:09,280 Speaker 3: I guess this kind of goes right into what you 517 00:29:09,320 --> 00:29:10,640 Speaker 3: were just talking aboutda VD. 518 00:29:10,600 --> 00:29:14,040 Speaker 1: Right, Yeah, I mean the answer there is a simple one, 519 00:29:14,080 --> 00:29:18,280 Speaker 1: which is yes, like AI could be under a computer 520 00:29:18,360 --> 00:29:21,000 Speaker 1: without any sort of connectivity to the Internet. It's sort 521 00:29:21,000 --> 00:29:24,640 Speaker 1: of like, you know, these days, most people connect to 522 00:29:24,680 --> 00:29:29,520 Speaker 1: like Microsoft Office, like you know word those files through 523 00:29:29,520 --> 00:29:32,840 Speaker 1: a share Point, meaning that they're on computers or they're 524 00:29:32,840 --> 00:29:33,560 Speaker 1: on the Internet. 525 00:29:33,960 --> 00:29:36,080 Speaker 4: But you know, Microsoft Word. 526 00:29:35,880 --> 00:29:39,200 Speaker 1: Could exist as an independent app, like an artificial intelligence 527 00:29:39,240 --> 00:29:41,719 Speaker 1: could easily exist on your computer without any sort of 528 00:29:41,720 --> 00:29:44,800 Speaker 1: Internet connectivity or needed to connect to the Internet to 529 00:29:44,800 --> 00:29:45,280 Speaker 1: be guided. 530 00:29:46,080 --> 00:29:49,080 Speaker 2: Let's go here to the iHeart Radio app. Talkbacks are 531 00:29:49,080 --> 00:29:51,160 Speaker 2: brought to you by Lyndahl Realty. As we continue our 532 00:29:51,200 --> 00:29:52,480 Speaker 2: conversation with Devid. 533 00:29:52,920 --> 00:29:56,040 Speaker 8: Hey John Frank from some Future. Yeah, one of the 534 00:29:56,080 --> 00:29:58,200 Speaker 8: other questions that we're going to ask is is this 535 00:29:58,280 --> 00:30:00,120 Speaker 8: what we're going to see on the political right? And 536 00:30:00,280 --> 00:30:04,120 Speaker 8: as AI takes over more and more of these coding activities, 537 00:30:04,960 --> 00:30:09,160 Speaker 8: I could see a democratic push or universal basic income 538 00:30:09,920 --> 00:30:10,880 Speaker 8: in this next election. 539 00:30:11,440 --> 00:30:13,040 Speaker 3: They're going to be talking about it a lot. 540 00:30:13,320 --> 00:30:14,920 Speaker 8: That's what I think there's going to be one of 541 00:30:14,960 --> 00:30:19,200 Speaker 8: the outcomes of all this AI advancement. 542 00:30:19,720 --> 00:30:21,840 Speaker 2: I really, you know, David, you've brought this up the 543 00:30:21,960 --> 00:30:25,280 Speaker 2: UBI and you know, I wonder I question whether or 544 00:30:25,320 --> 00:30:28,880 Speaker 2: not this is actually going to come up in the 545 00:30:28,920 --> 00:30:33,120 Speaker 2: most you know, in the upcoming election maybe twenty twenty eight, 546 00:30:33,240 --> 00:30:35,120 Speaker 2: But I don't know how much you've thought about a 547 00:30:35,160 --> 00:30:37,520 Speaker 2: sort of timeline. But you've had Elon Musk and others 548 00:30:37,520 --> 00:30:39,120 Speaker 2: that have been mentioning this, and I know you've brought 549 00:30:39,120 --> 00:30:41,360 Speaker 2: this up as well, regarding to the number of jobs 550 00:30:41,360 --> 00:30:44,040 Speaker 2: at AI will be taking and a potential need for 551 00:30:44,080 --> 00:30:44,600 Speaker 2: a UBI. 552 00:30:45,440 --> 00:30:48,680 Speaker 1: Yeah, I mean, it depends on how much how much 553 00:30:48,720 --> 00:30:51,280 Speaker 1: of the job market is cut into, but there definitely 554 00:30:51,320 --> 00:30:54,880 Speaker 1: is going to be a push for a UBI. My expectation, John, 555 00:30:55,040 --> 00:30:57,600 Speaker 1: is that UBI ends up not being a political edge, 556 00:30:57,680 --> 00:31:00,480 Speaker 1: but rather we end up with a concent just for 557 00:31:00,600 --> 00:31:02,240 Speaker 1: UBI between the two parties. 558 00:31:02,680 --> 00:31:04,440 Speaker 4: And more than anything. 559 00:31:04,160 --> 00:31:07,680 Speaker 1: Is of it's due to the massive job disruption that's 560 00:31:07,760 --> 00:31:11,680 Speaker 1: being created, because you need some way to cushion people 561 00:31:12,320 --> 00:31:16,760 Speaker 1: against job loss. I think that's just kind of a fact. Like, 562 00:31:16,840 --> 00:31:20,080 Speaker 1: and it may well be a wedge in the near term, right, 563 00:31:21,120 --> 00:31:24,480 Speaker 1: and there are different visions for UBI. Right, there's very 564 00:31:24,480 --> 00:31:27,000 Speaker 1: different visions between the right and the left when it 565 00:31:27,040 --> 00:31:32,040 Speaker 1: comes to economics. But I think that, like my guess 566 00:31:32,080 --> 00:31:35,920 Speaker 1: is that in the longer term, there ends up being 567 00:31:36,240 --> 00:31:40,200 Speaker 1: a massive push for UBI with different visions for what 568 00:31:40,320 --> 00:31:41,240 Speaker 1: UBI entails. 569 00:31:41,240 --> 00:31:43,720 Speaker 4: That's the way I see it. Well, we'll see how. 570 00:31:43,640 --> 00:31:46,040 Speaker 1: It shakes out, but I don't think it certainly won't 571 00:31:46,040 --> 00:31:47,360 Speaker 1: be in the twenty twenty sixth election. 572 00:31:47,760 --> 00:31:49,120 Speaker 4: I don't see that push there yet. 573 00:31:49,600 --> 00:31:51,680 Speaker 2: All right, let's go back to the iHeartRadio app. Got 574 00:31:51,680 --> 00:31:55,520 Speaker 2: a lot of questions this morning for DVD Gartensteinraans Can. 575 00:31:55,400 --> 00:31:56,760 Speaker 5: You ask dev this question? 576 00:31:57,080 --> 00:31:57,280 Speaker 4: You can? 577 00:31:58,680 --> 00:32:01,160 Speaker 5: Was on Joe Rogan's podcast than he had said, if 578 00:32:01,200 --> 00:32:05,480 Speaker 5: the wrong people are the ones programming AI, they could 579 00:32:05,480 --> 00:32:10,080 Speaker 5: wipe out humanity. I'm just curious specifically, how would that happen, 580 00:32:10,680 --> 00:32:14,400 Speaker 5: What would it be drone strikes on people? Or I 581 00:32:14,440 --> 00:32:16,800 Speaker 5: can't wrap my head around how wipe out humanity? 582 00:32:17,400 --> 00:32:18,440 Speaker 1: Sorry for the dark question. 583 00:32:18,720 --> 00:32:21,000 Speaker 3: Thanks, No, I think it's a relevant question. I've heard 584 00:32:21,000 --> 00:32:21,560 Speaker 3: those comments. 585 00:32:21,800 --> 00:32:24,640 Speaker 2: Those comments as well, to beat your thoughts before I 586 00:32:24,640 --> 00:32:25,440 Speaker 2: share any of mine. 587 00:32:26,080 --> 00:32:31,800 Speaker 1: In multiple ways, one is providing the guidance needed to 588 00:32:32,160 --> 00:32:37,080 Speaker 1: release a massive biological agent which is designed to kill humans, 589 00:32:38,000 --> 00:32:40,720 Speaker 1: to kind of an AI getting into its mind that 590 00:32:40,840 --> 00:32:44,440 Speaker 1: humans are you know, a real problem and need to 591 00:32:44,480 --> 00:32:48,840 Speaker 1: be dealt with. And from there, you know if you 592 00:32:48,920 --> 00:32:51,920 Speaker 1: have it being a. 593 00:32:51,680 --> 00:32:53,120 Speaker 4: Dominantly powerful AI. 594 00:32:53,320 --> 00:32:57,600 Speaker 1: There's multiple ways that AI can kill human beings or 595 00:32:57,760 --> 00:33:02,240 Speaker 1: reduce them to captivity. This is something This is that 596 00:33:02,280 --> 00:33:04,440 Speaker 1: Elon Musk has been talking about for a while. Right, 597 00:33:04,480 --> 00:33:09,400 Speaker 1: he actually ended his friendship with Larry Page and loose 598 00:33:09,480 --> 00:33:11,040 Speaker 1: Larry Page and one of the Google cofatders. It might 599 00:33:11,000 --> 00:33:14,400 Speaker 1: have been Sergey Brandon instead. But over this question of 600 00:33:14,600 --> 00:33:17,920 Speaker 1: AI wiping out humanity, like it's an existential risk that's 601 00:33:17,960 --> 00:33:20,200 Speaker 1: been seen for a while. I know I'm providing like 602 00:33:20,800 --> 00:33:24,280 Speaker 1: not like a great deal of guidance here, but basically, like, 603 00:33:24,360 --> 00:33:26,280 Speaker 1: let me take a step back and just provide the scenario. 604 00:33:27,080 --> 00:33:29,040 Speaker 4: An AI AI that. 605 00:33:29,160 --> 00:33:32,840 Speaker 1: Is able to get onto the Internet and function autonomously 606 00:33:33,360 --> 00:33:37,120 Speaker 1: in a way that the previous caller talked about, is 607 00:33:37,160 --> 00:33:40,000 Speaker 1: able to interact with a lot of systems, Like we 608 00:33:40,040 --> 00:33:42,800 Speaker 1: already know that a lot of our utilities have been hacked. 609 00:33:43,080 --> 00:33:45,760 Speaker 1: An AI that can shut down utilities, that can shut 610 00:33:45,760 --> 00:33:50,520 Speaker 1: down guidance systems on planes, that can launch nuclear weapons. Right, 611 00:33:50,760 --> 00:33:53,280 Speaker 1: we can go on and suddenly it becomes clear that 612 00:33:53,360 --> 00:33:56,640 Speaker 1: there's a lot that a hyper powerful AI with the 613 00:33:56,680 --> 00:34:00,240 Speaker 1: ability to get onto the Internet to hack into you know, 614 00:34:00,360 --> 00:34:02,880 Speaker 1: passwords that we think are secure and the like, there's 615 00:34:02,920 --> 00:34:04,920 Speaker 1: a lot it would be able to do to try 616 00:34:04,920 --> 00:34:05,880 Speaker 1: to destroy humanity. 617 00:34:06,120 --> 00:34:08,920 Speaker 2: Yeah, and the other question, like starting at the beginning, 618 00:34:08,960 --> 00:34:13,160 Speaker 2: I would be I would like somebody to ask Elon 619 00:34:13,600 --> 00:34:15,680 Speaker 2: if they ever get into a conversation like this again, 620 00:34:16,200 --> 00:34:19,600 Speaker 2: what parameters is he using the term wiping out humanity? 621 00:34:19,640 --> 00:34:23,680 Speaker 2: Because that could mean various things depending on you know 622 00:34:23,719 --> 00:34:24,400 Speaker 2: who you're talking to. 623 00:34:24,800 --> 00:34:26,520 Speaker 3: When you talk about job loss. 624 00:34:26,239 --> 00:34:27,680 Speaker 2: I mean you could talk about, you know, wiping out 625 00:34:27,760 --> 00:34:30,520 Speaker 2: humanity because AI has taken over all the jobs and 626 00:34:30,560 --> 00:34:32,040 Speaker 2: you've got a bunch of people that don't have, you know, 627 00:34:32,160 --> 00:34:33,320 Speaker 2: jobs and the like. 628 00:34:33,400 --> 00:34:35,160 Speaker 3: So that's kind of where my mind went on a DevD. 629 00:34:35,920 --> 00:34:38,200 Speaker 1: I'm sure, but I feel like if the answer is 630 00:34:38,200 --> 00:34:40,600 Speaker 1: like five percent of humanity would still survive or we'd 631 00:34:40,600 --> 00:34:43,719 Speaker 1: only be in prison and not all killed, it still 632 00:34:43,760 --> 00:34:45,719 Speaker 1: is not necessarily a future I would like. 633 00:34:45,719 --> 00:34:48,839 Speaker 3: Case in point. Yeah, Yeah, that's what I mean. 634 00:34:48,840 --> 00:34:51,760 Speaker 4: You know, five percent of us survive. That's that's better 635 00:34:51,800 --> 00:34:52,600 Speaker 4: than a zero percent. 636 00:34:52,640 --> 00:34:54,440 Speaker 3: There's still some of humanity left, right, we. 637 00:34:54,440 --> 00:34:58,000 Speaker 4: Get the exist in a zoo under benevolent AI overlord. 638 00:34:58,080 --> 00:34:59,879 Speaker 2: I don't know, man, I like being at home now. 639 00:35:00,000 --> 00:35:01,680 Speaker 2: I'm not so sure that would be so bad. I 640 00:35:01,719 --> 00:35:04,080 Speaker 2: just had a conversation with Melinda about this last night. 641 00:35:04,280 --> 00:35:05,880 Speaker 2: Hey to that point, let's go ah here to this 642 00:35:06,120 --> 00:35:08,120 Speaker 2: comment from the iHeartRadio app. 643 00:35:09,960 --> 00:35:13,400 Speaker 3: Okay, let's be honest here for just a minute. 644 00:35:14,160 --> 00:35:17,080 Speaker 4: Are we truly more likely to end up in the 645 00:35:17,120 --> 00:35:24,279 Speaker 4: matrix or wall e? I would go for the latter well. 646 00:35:24,239 --> 00:35:26,759 Speaker 2: Based off our conversation, I would think we would be 647 00:35:26,840 --> 00:35:30,000 Speaker 2: closer to Wally, especially if we're talking about things like 648 00:35:30,080 --> 00:35:32,800 Speaker 2: UBI in the future and having to you know, shore 649 00:35:32,960 --> 00:35:36,239 Speaker 2: up job loss because of AI. But I don't know 650 00:35:36,280 --> 00:35:40,080 Speaker 2: how deep we've gone into the movie AI conversation. I 651 00:35:40,080 --> 00:35:43,080 Speaker 2: feel like one segment one day de v just need 652 00:35:43,120 --> 00:35:45,280 Speaker 2: to be devoted to AI and films. 653 00:35:45,320 --> 00:35:49,000 Speaker 3: But your thoughts on the talkbacks comments. 654 00:35:49,480 --> 00:35:53,000 Speaker 1: It's a great question. I guess Wally would be my answer. 655 00:35:55,320 --> 00:35:56,600 Speaker 1: I'd have to give a little bit more thought to 656 00:35:56,640 --> 00:35:59,360 Speaker 1: that though. But this is gosh, this is an awfully 657 00:35:59,640 --> 00:36:00,680 Speaker 1: depressed conversation. 658 00:36:00,800 --> 00:36:03,960 Speaker 4: It's been about your job loss and how AI can 659 00:36:04,000 --> 00:36:06,759 Speaker 4: destroyer enslave us and humans in the zoo and maybe 660 00:36:06,840 --> 00:36:09,359 Speaker 4: becing a zoo isn't that bad? Are you able to 661 00:36:09,480 --> 00:36:11,160 Speaker 4: end on a positive note? 662 00:36:11,719 --> 00:36:14,279 Speaker 2: Probably not, not, based off of the talkbacks that I'm 663 00:36:14,320 --> 00:36:16,759 Speaker 2: looking at it in front of me. I will say though, 664 00:36:16,800 --> 00:36:20,080 Speaker 2: as a side note, One more movie related item. I 665 00:36:20,120 --> 00:36:24,560 Speaker 2: did go see with my wife and my son Good Luck, 666 00:36:24,920 --> 00:36:30,520 Speaker 2: Have Fun, Don't Die, which is a really fun and interesting. 667 00:36:30,080 --> 00:36:32,760 Speaker 3: Take on our current society. AI. 668 00:36:33,280 --> 00:36:35,400 Speaker 2: It gets fan it gets into, you know, sort of 669 00:36:35,440 --> 00:36:39,040 Speaker 2: fantastical elements of it. But it really was an enjoyable watch, 670 00:36:39,120 --> 00:36:42,200 Speaker 2: especially if you're interested at all in AI. 671 00:36:42,360 --> 00:36:44,719 Speaker 3: I would I would recommend, I would recommend going and 672 00:36:44,760 --> 00:36:45,120 Speaker 3: seeing it. 673 00:36:45,840 --> 00:36:47,600 Speaker 4: Cool. That's positive. Note. 674 00:36:47,800 --> 00:36:49,799 Speaker 1: It may destroy us all, but it's produced some good 675 00:36:49,800 --> 00:36:50,560 Speaker 1: movies in the process. 676 00:36:50,640 --> 00:36:53,279 Speaker 2: Yeah, it's been entertaining so far, especially the videos that 677 00:36:53,360 --> 00:36:57,279 Speaker 2: get made. All right, let's go here. We got a 678 00:36:57,320 --> 00:36:59,880 Speaker 2: little bit of time left. Good morning, gentlemen. 679 00:37:00,600 --> 00:37:03,359 Speaker 10: On the topic of AI, I'm going to convention this 680 00:37:03,440 --> 00:37:08,800 Speaker 10: weekend with Gary V and he's talking about AI and technology, 681 00:37:09,360 --> 00:37:14,399 Speaker 10: as is another lady, a national speaker, and she said 682 00:37:14,440 --> 00:37:17,759 Speaker 10: something that was very compelling. That was something along the 683 00:37:17,800 --> 00:37:22,880 Speaker 10: lines of those who don't embrace and use AI and 684 00:37:22,920 --> 00:37:24,800 Speaker 10: are afraid it will replace them are going to be 685 00:37:24,840 --> 00:37:27,560 Speaker 10: the ones that suffer the most, and that AI. 686 00:37:28,600 --> 00:37:31,200 Speaker 2: Well, I think this is a good place to wrap. 687 00:37:31,280 --> 00:37:33,120 Speaker 2: What are your thoughts on that those that don't embrace 688 00:37:33,160 --> 00:37:35,600 Speaker 2: AI and maybe you know and are afraid it will 689 00:37:35,640 --> 00:37:37,879 Speaker 2: replace them are the ones that may be the most 690 00:37:37,960 --> 00:37:41,120 Speaker 2: vulnerable to AI. Your thoughts to be Yeah, absolutely, that 691 00:37:41,160 --> 00:37:46,400 Speaker 2: ties back in a I agree, and b it ties 692 00:37:46,440 --> 00:37:48,640 Speaker 2: back in with the Matt Humor piece that we led with, 693 00:37:50,400 --> 00:37:55,200 Speaker 2: right it is this is directly the advice that he 694 00:37:55,280 --> 00:37:59,080 Speaker 2: gives given those job disruptions. What he writes is this 695 00:37:59,160 --> 00:38:03,440 Speaker 2: might be the most important year of your career work Accordingly, 696 00:38:03,920 --> 00:38:05,879 Speaker 2: I don't see that to stress you out, I said, 697 00:38:06,000 --> 00:38:08,640 Speaker 2: because right now there's a brief window where most people 698 00:38:08,640 --> 00:38:11,399 Speaker 2: at companies are still ignoring this. The person who walks 699 00:38:11,400 --> 00:38:13,440 Speaker 2: into me and says I used AI to do this 700 00:38:13,480 --> 00:38:16,160 Speaker 2: analysis in an hour instead of three days is going 701 00:38:16,200 --> 00:38:19,200 Speaker 2: to be the most valuable person in the room, not eventually, 702 00:38:19,520 --> 00:38:23,120 Speaker 2: right now. And he goes on, But like what your 703 00:38:23,800 --> 00:38:29,360 Speaker 2: listener is putting their finger on is there's this inevitability 704 00:38:29,600 --> 00:38:33,960 Speaker 2: to AI and those who start to use it and 705 00:38:34,160 --> 00:38:37,400 Speaker 2: understand how it can intersect with their workflow, that is 706 00:38:37,440 --> 00:38:41,080 Speaker 2: an important part of having economic value in the future. 707 00:38:41,880 --> 00:38:46,240 Speaker 2: Tavi Gartenstein Ross and CEO and expert theory really enjoyed 708 00:38:46,239 --> 00:38:49,680 Speaker 2: the conversation. As always, thank you for the time this morning, 709 00:38:49,719 --> 00:38:51,520 Speaker 2: and hopefully we can do it again next week. 710 00:38:52,560 --> 00:38:55,000 Speaker 4: Likewise, John look forward to it coming up. 711 00:38:56,160 --> 00:38:59,440 Speaker 2: An examination of the root causes of fraud. A fifty 712 00:38:59,560 --> 00:39:04,120 Speaker 2: six page roadmap for fraud prevention submitted to Governor Tim Walls, 713 00:39:04,120 --> 00:39:07,120 Speaker 2: although he said yesterday he hadn't read it, and we 714 00:39:07,200 --> 00:39:11,040 Speaker 2: may have what will most likely be the official talking 715 00:39:11,080 --> 00:39:14,839 Speaker 2: point for the DFL as they avoid any sort of scrutiny, 716 00:39:15,120 --> 00:39:18,319 Speaker 2: accountability or responsibility for the fraud in Minnesota. I'll tell 717 00:39:18,360 --> 00:39:20,359 Speaker 2: you what it is next here on Twin City's News 718 00:39:20,400 --> 00:39:22,880 Speaker 2: Talk AM eleven thirty and one oh three five FM.