1 00:00:00,760 --> 00:00:02,960 Speaker 1: If I am six forty, you're listening to the John 2 00:00:03,000 --> 00:00:09,039 Speaker 1: and Ken Show on demand on the iHeartRadio app. We're 3 00:00:09,080 --> 00:00:12,080 Speaker 1: on the radio from one until four. After four o'clock, 4 00:00:12,160 --> 00:00:13,960 Speaker 1: you go to the iHeart app. John and Ken on 5 00:00:14,000 --> 00:00:17,000 Speaker 1: Demand is our podcast, and you can download it and 6 00:00:17,640 --> 00:00:22,240 Speaker 1: listen to everything you missed at any time day, night, weekend, 7 00:00:22,480 --> 00:00:25,160 Speaker 1: whether you're in the country or out of the country. 8 00:00:25,320 --> 00:00:26,079 Speaker 1: It's always there. 9 00:00:26,120 --> 00:00:29,200 Speaker 2: Twenty four to seven is always John and Ken handy right, 10 00:00:29,560 --> 00:00:32,040 Speaker 2: and we posted up right after four o'clock. You have 11 00:00:32,040 --> 00:00:33,720 Speaker 2: to way too long get the full three hours, so 12 00:00:33,800 --> 00:00:36,239 Speaker 2: it's very exciting. Also, use that to connect to the 13 00:00:36,280 --> 00:00:38,960 Speaker 2: moistline the app. There's a microphone you can leave a 14 00:00:39,000 --> 00:00:41,080 Speaker 2: message or you can call the tell free number one 15 00:00:41,080 --> 00:00:43,600 Speaker 2: eight seven seven Moist eighty six one eight seven seven 16 00:00:44,040 --> 00:00:46,080 Speaker 2: six six four seven eight eight six And I wants 17 00:00:46,120 --> 00:00:48,840 Speaker 2: to get John to mention follow that app. Please follow 18 00:00:48,840 --> 00:00:49,280 Speaker 2: that app. 19 00:00:49,360 --> 00:00:51,360 Speaker 1: That's right, follow it. Put a tracker on it. 20 00:00:52,920 --> 00:00:56,280 Speaker 2: Last time we mentioned AI artificial intelligence, it was about 21 00:00:56,320 --> 00:00:57,280 Speaker 2: the writer's strike. 22 00:00:57,360 --> 00:00:59,840 Speaker 1: Are you following that closely? John? The Hollywood writer strike? 23 00:01:00,960 --> 00:01:03,360 Speaker 1: I'm aware of it. Well, it was kind of sad. 24 00:01:03,440 --> 00:01:06,200 Speaker 2: Yesterday our union announced more events that they want you 25 00:01:06,240 --> 00:01:07,920 Speaker 2: to come and help picket I. 26 00:01:08,240 --> 00:01:10,640 Speaker 1: Drove down Olive Avenue on my way here yesterday. There's 27 00:01:10,720 --> 00:01:13,080 Speaker 1: one of those right there. This is true. And right 28 00:01:13,120 --> 00:01:16,600 Speaker 1: on the corner of Hollywood Hollywood Way and Olive Avenue 29 00:01:16,640 --> 00:01:21,880 Speaker 1: at the traffic light, there was one picketer. What one guy? 30 00:01:22,040 --> 00:01:26,400 Speaker 1: It's only been a couple of weeks, but the crabs 31 00:01:26,760 --> 00:01:29,000 Speaker 1: dwindled on the picket line. In fact, is it a 32 00:01:29,040 --> 00:01:32,480 Speaker 1: picket line if there's only one guy? I think you 33 00:01:32,520 --> 00:01:34,040 Speaker 1: need three people to form a line. 34 00:01:34,240 --> 00:01:35,840 Speaker 2: And the reason we talked about it then is because 35 00:01:35,880 --> 00:01:37,839 Speaker 2: some think that that might be the future, that AI 36 00:01:37,959 --> 00:01:41,600 Speaker 2: could take over for writers writing movies and shows. But 37 00:01:41,640 --> 00:01:45,080 Speaker 2: what about the dangers of AI? And today, apparently there 38 00:01:45,120 --> 00:01:49,520 Speaker 2: was a Senate Judiciary committee hearing was titled Oversight of 39 00:01:49,560 --> 00:01:53,320 Speaker 2: AI Rules for Artificial Intelligence. Let's find out what went on? 40 00:01:53,480 --> 00:01:56,400 Speaker 2: From ABC News is Mike Debusky is gonna come on 41 00:01:56,400 --> 00:01:59,120 Speaker 2: the air and talk about this hearing. 42 00:01:59,360 --> 00:01:59,960 Speaker 1: Mike, how are you? 43 00:02:00,880 --> 00:02:02,880 Speaker 3: I'm doing well, guys, how are you good? 44 00:02:02,960 --> 00:02:04,920 Speaker 1: What's going on at the hearing? I mean, do the 45 00:02:05,160 --> 00:02:08,560 Speaker 1: do the does the congressman even understand or the senators 46 00:02:08,639 --> 00:02:11,040 Speaker 1: rather even understand what's going on with AI? 47 00:02:11,120 --> 00:02:13,760 Speaker 3: It's an interesting it's an interesting shade of this, right 48 00:02:13,840 --> 00:02:17,960 Speaker 3: because our our conception of Congress when tech CEOs, you know, 49 00:02:18,120 --> 00:02:20,680 Speaker 3: visit Capitol Hill is is maybe not the greatest. We 50 00:02:20,720 --> 00:02:23,600 Speaker 3: all remember when Mark Zuckerberg appeared on Capitol Hill a 51 00:02:23,639 --> 00:02:25,840 Speaker 3: couple of years ago and there was the question, well, 52 00:02:25,880 --> 00:02:28,440 Speaker 3: how do you make money on Facebook? And Mark Zuckerberg 53 00:02:28,520 --> 00:02:33,400 Speaker 3: rather incredulously said well, Senator, we run ads, obviously. So 54 00:02:33,800 --> 00:02:37,000 Speaker 3: I think we have come slightly further from that that time. 55 00:02:37,680 --> 00:02:42,280 Speaker 3: This was the Senate Judiciary's Privacy, Technology and the Law Subcommittee. 56 00:02:42,280 --> 00:02:45,640 Speaker 3: It's chaired by Richard Blumenthal, and just to sort of 57 00:02:45,800 --> 00:02:49,560 Speaker 3: eschew any notions that the senators were behind when it 58 00:02:49,600 --> 00:02:52,360 Speaker 3: came to their technical know how, he actually started with 59 00:02:52,480 --> 00:02:56,799 Speaker 3: his opening statement that was partially written and voiced by 60 00:02:56,840 --> 00:02:59,080 Speaker 3: an AI technology. Here's what that sounded like, guys. 61 00:02:59,400 --> 00:03:03,239 Speaker 4: Too often we have seen what happens when technology outpaces regulation, 62 00:03:04,440 --> 00:03:09,480 Speaker 4: the unbridled exploitation of personal data, the proliferation of disinformation. 63 00:03:09,840 --> 00:03:13,200 Speaker 3: That again was not Richard Blumenthal, although it sounded like 64 00:03:13,280 --> 00:03:17,520 Speaker 3: Richard Blumenthal. That was a completely AI generated written and 65 00:03:17,680 --> 00:03:21,520 Speaker 3: voiced opening statement. And he went on to give his 66 00:03:21,600 --> 00:03:24,960 Speaker 3: own opening statement as well, the human Richard Blumenthal. He 67 00:03:25,040 --> 00:03:27,520 Speaker 3: was asking questions of Sam Altman, who was the CEO 68 00:03:27,639 --> 00:03:30,240 Speaker 3: of open Ai, a company that you may have heard of. 69 00:03:30,520 --> 00:03:33,360 Speaker 3: They make a program called chat gpt, which has gotten 70 00:03:33,360 --> 00:03:35,080 Speaker 3: a lot of press in the last year or so. 71 00:03:35,360 --> 00:03:39,080 Speaker 3: Also Dolly Too, a very popular image generator online. And 72 00:03:39,360 --> 00:03:41,280 Speaker 3: kind of as you alluded to there, guys, this was 73 00:03:41,320 --> 00:03:43,960 Speaker 3: all focused on not only what AI can do in 74 00:03:44,040 --> 00:03:47,000 Speaker 3: some of the risks, but also how we could maybe 75 00:03:47,040 --> 00:03:49,000 Speaker 3: think about regulating this technology. 76 00:03:50,640 --> 00:03:52,640 Speaker 2: I mean, was there anything about it that talked about 77 00:03:52,640 --> 00:03:55,800 Speaker 2: the positive aspects of AI in terms of what wonderful 78 00:03:55,840 --> 00:03:58,360 Speaker 2: things they could do for mankind or it was really 79 00:03:58,400 --> 00:04:00,000 Speaker 2: all about the dangerous. 80 00:04:00,320 --> 00:04:02,320 Speaker 3: Well, you know, I think what was striking about this 81 00:04:02,440 --> 00:04:05,160 Speaker 3: hearing was that it was kind of both, right. I mean, 82 00:04:05,320 --> 00:04:08,360 Speaker 3: Sam Altman, you know, is a prominent voice in the 83 00:04:08,400 --> 00:04:11,880 Speaker 3: AI space. They also talked to Christina Montgomery, who is 84 00:04:11,920 --> 00:04:15,680 Speaker 3: an IBM vice president. She sits on their AI Ethics board, 85 00:04:16,000 --> 00:04:19,240 Speaker 3: and Gary Marcus, who's a professor at NYU and a 86 00:04:19,400 --> 00:04:23,479 Speaker 3: sort of entrepreneur, founder author in the AI space. And 87 00:04:23,560 --> 00:04:26,760 Speaker 3: you would kind of expect those voices to you know, 88 00:04:26,800 --> 00:04:31,200 Speaker 3: you know, talk positively about AI, but really everyone agreed, 89 00:04:31,480 --> 00:04:34,320 Speaker 3: both the people who were being who were testifying and 90 00:04:34,360 --> 00:04:37,520 Speaker 3: the people who were asking the questions. Everybody agreed that 91 00:04:37,560 --> 00:04:41,120 Speaker 3: there are potential risks posed by this technology, which was 92 00:04:41,160 --> 00:04:44,000 Speaker 3: a striking moment for bipartisanship and also, you know, for 93 00:04:44,480 --> 00:04:45,640 Speaker 3: the industry at large. 94 00:04:46,480 --> 00:04:49,360 Speaker 1: Possibly, yes, how could you possibly regulate this though? 95 00:04:50,360 --> 00:04:53,839 Speaker 3: So Sam Altman came with a couple of ideas which 96 00:04:53,880 --> 00:04:56,719 Speaker 3: I thought were interesting to talk about. The big idea 97 00:04:56,760 --> 00:04:58,839 Speaker 3: that he had when it comes to regulating his own 98 00:04:58,880 --> 00:05:02,600 Speaker 3: industry is that the government should create a new agency, 99 00:05:02,680 --> 00:05:06,040 Speaker 3: essentially a DMV for AI. I think is a good 100 00:05:06,080 --> 00:05:09,000 Speaker 3: way to think about this, where this agency would give 101 00:05:09,040 --> 00:05:12,920 Speaker 3: out licenses to startups and AI technologies operating in the space, 102 00:05:13,120 --> 00:05:15,599 Speaker 3: and if those companies ran a foul of some rules 103 00:05:15,640 --> 00:05:17,400 Speaker 3: that the government would set up, then they could have 104 00:05:17,400 --> 00:05:20,479 Speaker 3: their license revoked. They couldn't develop the technology any further. 105 00:05:20,800 --> 00:05:24,320 Speaker 3: He also suggested new safety standards essentially tests that these 106 00:05:24,360 --> 00:05:27,039 Speaker 3: AI systems would need to pass so that they do 107 00:05:27,120 --> 00:05:30,080 Speaker 3: not and I'm quoting here xfiltrate into the real world 108 00:05:30,200 --> 00:05:32,839 Speaker 3: in other words, go rogue and do things that the 109 00:05:32,880 --> 00:05:36,279 Speaker 3: creators don't intend them to do. And he also advocated 110 00:05:36,320 --> 00:05:38,640 Speaker 3: for audits by independent experts to come in and kind 111 00:05:38,640 --> 00:05:41,240 Speaker 3: of supplement the government's work there. So Sam Altman with 112 00:05:41,320 --> 00:05:44,640 Speaker 3: a couple of ideas of his own, and lawmakers, no 113 00:05:44,720 --> 00:05:47,520 Speaker 3: surprise here, were receptive to that idea. They like it 114 00:05:47,560 --> 00:05:50,000 Speaker 3: when tech CEOs and business CEOs come and say, hey, 115 00:05:50,080 --> 00:05:52,200 Speaker 3: come regulate my industry. Here's a couple of ideas how 116 00:05:52,240 --> 00:05:54,080 Speaker 3: to do that, John. 117 00:05:54,640 --> 00:05:57,440 Speaker 1: Every technology sounds great until the bad guys take over. 118 00:05:57,560 --> 00:06:01,920 Speaker 1: So what's going to stop some e AI geniuses from 119 00:06:01,960 --> 00:06:07,480 Speaker 1: relocating out of the country and right sending all their distortion, 120 00:06:07,760 --> 00:06:12,920 Speaker 1: all their fake news, right, fake videos, fake news story, Yeah, 121 00:06:12,960 --> 00:06:16,880 Speaker 1: all that stuff you know from a server overseas. I 122 00:06:16,880 --> 00:06:19,719 Speaker 1: mean it's like trying to control pornography. I mean right, 123 00:06:20,120 --> 00:06:21,720 Speaker 1: None of that has ever worked. 124 00:06:22,600 --> 00:06:25,480 Speaker 3: And it's also worth mentioning that, you know, the discussion 125 00:06:25,520 --> 00:06:30,000 Speaker 3: today didn't necessarily center around stopping the development of this technology. 126 00:06:30,040 --> 00:06:32,080 Speaker 3: It was more of a guardrails discussion. It was a 127 00:06:32,160 --> 00:06:36,680 Speaker 3: ground rules kind of talk today. There were earlier this 128 00:06:36,800 --> 00:06:39,080 Speaker 3: year two open letters, one of which was signed by 129 00:06:39,080 --> 00:06:42,680 Speaker 3: Elon Muskin, one of which targeted open AI specifically that 130 00:06:42,839 --> 00:06:45,200 Speaker 3: did advocate for something that you're talking about there, which 131 00:06:45,279 --> 00:06:49,640 Speaker 3: is completely stopping the development on their GPT for technology 132 00:06:49,760 --> 00:06:52,920 Speaker 3: while we figure out a way to regulate it, while 133 00:06:52,960 --> 00:06:55,000 Speaker 3: we figure out kind of how this technology works and 134 00:06:55,040 --> 00:06:58,039 Speaker 3: exactly what's going on here. Although an expert that I 135 00:06:58,040 --> 00:07:01,320 Speaker 3: talked to you today, a former FTC officials, said that 136 00:07:01,440 --> 00:07:03,800 Speaker 3: he would actually advocate for the opposite. He would advocate 137 00:07:03,839 --> 00:07:07,559 Speaker 3: for lawmakers and potential legislators to actually take a pause 138 00:07:07,560 --> 00:07:10,960 Speaker 3: here before they rush into creating legislation, make sure that 139 00:07:11,040 --> 00:07:13,280 Speaker 3: they fully understand the technology. And that goes back to 140 00:07:13,280 --> 00:07:15,320 Speaker 3: what we were talking about at the beginning here, which is, 141 00:07:15,560 --> 00:07:16,920 Speaker 3: you know that we want to make sure that our 142 00:07:17,000 --> 00:07:19,760 Speaker 3: lawmakers know the technology that they're regulating. 143 00:07:19,920 --> 00:07:21,960 Speaker 1: Yeah, that's right. How do they know what they're supposed 144 00:07:21,960 --> 00:07:24,880 Speaker 1: to regulate when this technology is in its infancy? 145 00:07:25,800 --> 00:07:28,360 Speaker 3: Yes, it is such a new technology, and I mean 146 00:07:28,640 --> 00:07:31,360 Speaker 3: that also speaks to the moment that we're in right now. 147 00:07:32,280 --> 00:07:35,080 Speaker 3: You know, we look back to the time of Facebook 148 00:07:35,120 --> 00:07:38,200 Speaker 3: and Twitter fifteen years ago. They were in a similar 149 00:07:38,240 --> 00:07:40,360 Speaker 3: position to where a lot of AI companies are today. 150 00:07:40,360 --> 00:07:44,360 Speaker 3: They were small bit players on the global stage. Now 151 00:07:44,440 --> 00:07:47,600 Speaker 3: they are huge companies, and our lawmakers are still trying 152 00:07:47,600 --> 00:07:49,920 Speaker 3: to figure out exactly what they're going to do with 153 00:07:49,960 --> 00:07:52,680 Speaker 3: those incredibly large companies and field a lot of influence 154 00:07:52,720 --> 00:07:56,720 Speaker 3: and power. Now we're looking at like this nascent AI industry, 155 00:07:56,920 --> 00:08:00,559 Speaker 3: seems like legislators don't necessarily want to miss the b again. 156 00:08:00,560 --> 00:08:02,160 Speaker 3: They want to get in on the ground floor and 157 00:08:02,200 --> 00:08:04,560 Speaker 3: set up some walls before this is allowed. 158 00:08:04,800 --> 00:08:08,920 Speaker 1: Assuming these predictions are correct, where you can see anyone 159 00:08:08,960 --> 00:08:12,000 Speaker 1: from an order taker at McDonald's to a high end 160 00:08:12,120 --> 00:08:15,720 Speaker 1: lawyer get thrown out of work by AI. Was there 161 00:08:15,720 --> 00:08:18,840 Speaker 1: any discussion on what all these millions and millions of 162 00:08:18,880 --> 00:08:20,200 Speaker 1: unemployed people are gonna do. 163 00:08:21,000 --> 00:08:23,360 Speaker 3: So jobs was a big part of this right uh 164 00:08:23,560 --> 00:08:25,720 Speaker 3: the The jobs issue was raised by Bluementhal, It was 165 00:08:25,800 --> 00:08:27,880 Speaker 3: raised by Rob Hawley, who is the co chair of 166 00:08:27,960 --> 00:08:32,360 Speaker 3: this UH this subcommittee as well, and Sam Altman said 167 00:08:32,480 --> 00:08:35,720 Speaker 3: he thinks that far greater jobs will be on the 168 00:08:35,760 --> 00:08:38,840 Speaker 3: other side of this AI revolution. That not necessary, that 169 00:08:38,840 --> 00:08:40,960 Speaker 3: these AI jobs are excuse me, that these jobs are 170 00:08:41,000 --> 00:08:43,920 Speaker 3: not necessarily going to be outright replaced by AI. But 171 00:08:43,960 --> 00:08:47,400 Speaker 3: they're gonna shift, They're going to become something else. And 172 00:08:47,559 --> 00:08:50,040 Speaker 3: you know, there's there's questions as to exactly you know, 173 00:08:50,080 --> 00:08:52,400 Speaker 3: how accurate that is. And he did, for his part, 174 00:08:52,480 --> 00:08:55,920 Speaker 3: say that some jobs will be completely eliminated. We're not 175 00:08:55,960 --> 00:08:58,560 Speaker 3: going to completely you know, live in this this blue 176 00:08:58,600 --> 00:09:01,400 Speaker 3: sky world where you know, nobody loses their jobs because 177 00:09:01,400 --> 00:09:03,840 Speaker 3: of this technology. But he does see it as rather 178 00:09:03,960 --> 00:09:07,240 Speaker 3: a shift, as opposed to an outright replacement. Another thing 179 00:09:07,280 --> 00:09:08,880 Speaker 3: that he mentioned that I thought was interesting was that 180 00:09:09,160 --> 00:09:12,040 Speaker 3: AI AI should be thought of like a tool, not 181 00:09:12,120 --> 00:09:15,640 Speaker 3: necessarily like this unknowable creature that we can't control. It's 182 00:09:15,640 --> 00:09:18,160 Speaker 3: more like a calculator, right, like we use our minds, 183 00:09:18,400 --> 00:09:21,840 Speaker 3: you know, for something greater than our multiplication tables. Because 184 00:09:21,840 --> 00:09:24,520 Speaker 3: our calculators can do that, AI could maybe serve a 185 00:09:24,520 --> 00:09:27,720 Speaker 3: similar function. Nobody likes writing boring emails to your airline 186 00:09:27,760 --> 00:09:30,560 Speaker 3: or to your employer. That's what GPT for is for. 187 00:09:30,720 --> 00:09:32,960 Speaker 3: Or that's what chat GPT is for. At least that's 188 00:09:33,000 --> 00:09:33,600 Speaker 3: how he sees it. 189 00:09:33,679 --> 00:09:35,800 Speaker 1: Yeah. There was an article and you've probably read it 190 00:09:35,800 --> 00:09:37,600 Speaker 1: in the New York Times where a New York Times 191 00:09:37,600 --> 00:09:41,760 Speaker 1: writer interviewed an AI chatbot. 192 00:09:41,360 --> 00:09:43,400 Speaker 3: And it yes, and it told him to leave his wife. 193 00:09:43,480 --> 00:09:44,400 Speaker 3: Is this what we're talking about? 194 00:09:44,840 --> 00:09:48,480 Speaker 1: Well, the one I saw is the the chatbot said 195 00:09:48,520 --> 00:09:51,240 Speaker 1: one of its greatest desires is to get control of 196 00:09:51,280 --> 00:09:57,120 Speaker 1: the nuclear codes. Oh great, Yeah, I wonder if there 197 00:09:57,200 --> 00:10:00,000 Speaker 1: was any discussion about that about you know, the Frankenstein 198 00:10:00,000 --> 00:10:00,480 Speaker 1: in effect. 199 00:10:01,480 --> 00:10:03,880 Speaker 3: You know, I'm not sure if they reference that specifically, 200 00:10:03,880 --> 00:10:06,920 Speaker 3: but I mean sort of the hallucination aspect of it. 201 00:10:06,960 --> 00:10:10,200 Speaker 3: To use AI parlance, here is a big concern, right, 202 00:10:10,240 --> 00:10:13,880 Speaker 3: these AI programs get things wrong. One of the funny 203 00:10:14,080 --> 00:10:16,840 Speaker 3: things that was a byproduct of open AIS technology up 204 00:10:16,880 --> 00:10:18,720 Speaker 3: until very recently was that it was bad at math. 205 00:10:18,800 --> 00:10:20,520 Speaker 3: If you gave it a math problem, it was it 206 00:10:20,520 --> 00:10:23,400 Speaker 3: would often get it wrong, which is, you know, a 207 00:10:23,520 --> 00:10:25,840 Speaker 3: sort of interesting moment in the development of computers and 208 00:10:25,880 --> 00:10:28,360 Speaker 3: technology that we finally created a program that. 209 00:10:28,320 --> 00:10:28,960 Speaker 1: Is bad at math. 210 00:10:30,040 --> 00:10:33,480 Speaker 3: But the sort of larger question there it speaks to 211 00:10:33,480 --> 00:10:36,520 Speaker 3: this larger issue that you know, these these programs do hallucinate. 212 00:10:36,600 --> 00:10:39,800 Speaker 3: They do they do create wrong information. And when you 213 00:10:39,840 --> 00:10:41,840 Speaker 3: put that in the broader context of this being a 214 00:10:41,880 --> 00:10:44,680 Speaker 3: consumer good something that anyone at a website that anyone 215 00:10:44,720 --> 00:10:48,880 Speaker 3: can go to and potentially look for information from, you 216 00:10:48,880 --> 00:10:52,679 Speaker 3: know what happens when that that you know, answer is incorrect. 217 00:10:53,240 --> 00:10:55,600 Speaker 3: You put this up against something like Google, right, or 218 00:10:55,640 --> 00:10:58,800 Speaker 3: a search engine like being and those search engines present 219 00:10:58,920 --> 00:11:01,240 Speaker 3: you with a bunch of different potential answers to your 220 00:11:01,320 --> 00:11:04,800 Speaker 3: question right, a big long list of links. What these 221 00:11:04,800 --> 00:11:08,280 Speaker 3: AI chatponts do is they provide you with unanswer right, 222 00:11:08,320 --> 00:11:11,959 Speaker 3: presumably the answer The company hopes it's the right answer, 223 00:11:12,320 --> 00:11:15,439 Speaker 3: but it does it with this confidence that is both 224 00:11:15,920 --> 00:11:18,280 Speaker 3: heartening to people who are looking for a quick and 225 00:11:18,320 --> 00:11:21,120 Speaker 3: easy answer to their questions, but also potentially concerning if 226 00:11:21,160 --> 00:11:22,480 Speaker 3: that technology gets it wrong. 227 00:11:23,360 --> 00:11:25,200 Speaker 1: All right, Mike, thank you very much for coming on. 228 00:11:25,240 --> 00:11:27,560 Speaker 3: We appreciate it, of course, guys, take care. 229 00:11:27,840 --> 00:11:28,040 Speaker 1: Hi. 230 00:11:28,120 --> 00:11:32,240 Speaker 2: Mike Debuski, ABC News Technology reporter on these hearings in Washington, DC, 231 00:11:32,400 --> 00:11:37,160 Speaker 2: a Senate Judiciary subcommittee looking at the problems and dangers 232 00:11:37,160 --> 00:11:40,000 Speaker 2: of artificial intelligence. Apparently, John, one other thing they talked about, 233 00:11:40,240 --> 00:11:42,720 Speaker 2: being senators, what could do in voting? 234 00:11:43,280 --> 00:11:43,439 Speaker 1: Right? 235 00:11:43,800 --> 00:11:47,040 Speaker 2: How could artificial intelligence scrup the whole voting system be? 236 00:11:47,600 --> 00:11:48,839 Speaker 1: It'll decide who's going to win. 237 00:11:49,559 --> 00:11:52,000 Speaker 2: I'm more coming up, Johnny k KFI AM six forty 238 00:11:52,000 --> 00:11:53,680 Speaker 2: Live everywhere iHeartRadio app. 239 00:11:54,480 --> 00:11:57,800 Speaker 5: You're listening to John and Ken on demand from KFI 240 00:11:58,040 --> 00:11:59,000 Speaker 5: AM six forty. 241 00:12:00,840 --> 00:12:01,080 Speaker 1: Yeah. 242 00:12:01,160 --> 00:12:03,200 Speaker 2: All right, Well we're going to give you some good news. 243 00:12:03,240 --> 00:12:06,400 Speaker 2: Well there's two stories here. They're both kind of good 244 00:12:06,400 --> 00:12:10,080 Speaker 2: news for people in this country, and it's all about 245 00:12:10,600 --> 00:12:14,040 Speaker 2: the theory of things. Relatively can be better off where 246 00:12:14,040 --> 00:12:17,040 Speaker 2: you are than other places. Egg prices john have come 247 00:12:17,080 --> 00:12:20,800 Speaker 2: way down, that was a big story, thank god, way down. 248 00:12:21,880 --> 00:12:25,720 Speaker 2: As of last week, Midwest large eggs, which is the 249 00:12:25,760 --> 00:12:29,199 Speaker 2: benchmark for eggs sold in their shells, cost US ninety 250 00:12:29,240 --> 00:12:32,480 Speaker 2: four cents per dozen in the wholesale market. That's a 251 00:12:32,559 --> 00:12:35,800 Speaker 2: sharp fall from five to forty just six months ago. 252 00:12:35,840 --> 00:12:38,559 Speaker 2: Now in retail prices are still well above a dollar 253 00:12:38,600 --> 00:12:42,319 Speaker 2: a carton, but they seem to be declining. The Avian 254 00:12:42,360 --> 00:12:44,920 Speaker 2: flu thing seems to have subsided. That was a real 255 00:12:45,679 --> 00:12:49,760 Speaker 2: problem for the egg producers was the deadly Avian flu 256 00:12:49,800 --> 00:12:53,720 Speaker 2: when they were, as we mentioned in much to the 257 00:12:53,760 --> 00:12:56,199 Speaker 2: sadness of Debora Mark, that they had to kill a 258 00:12:56,240 --> 00:13:01,199 Speaker 2: lot of the eggs and millions and millions of hands. 259 00:13:01,559 --> 00:13:04,679 Speaker 2: They also had inflated feed and fuel costs which were 260 00:13:04,679 --> 00:13:07,679 Speaker 2: causing all these problems. But now to tell you that 261 00:13:07,960 --> 00:13:10,120 Speaker 2: you're in a better place, even though we hear these 262 00:13:10,160 --> 00:13:13,280 Speaker 2: inflation reports and they're horrendous. The one place in the 263 00:13:13,320 --> 00:13:16,640 Speaker 2: world second I guess you wouldn't want to be when 264 00:13:16,679 --> 00:13:21,160 Speaker 2: it comes to the topic of inflation is Argentina. I 265 00:13:21,280 --> 00:13:23,760 Speaker 2: had to read this twice to believe it. The Central 266 00:13:23,760 --> 00:13:26,920 Speaker 2: Bank of Argentina raised its key interest rate by six 267 00:13:26,960 --> 00:13:31,080 Speaker 2: percentage points to ninety seven percent in an effort to 268 00:13:31,120 --> 00:13:37,760 Speaker 2: tackle soaring inflation. The key interest rate is ninety seven percent. No, 269 00:13:37,840 --> 00:13:40,160 Speaker 2: they didn't raise it by ninety seven percent. They raised 270 00:13:40,160 --> 00:13:43,760 Speaker 2: it to ninety seven percent. Is that is a tough 271 00:13:44,679 --> 00:13:48,000 Speaker 2: that's a tough mortgage. Annual inflation has sort above one 272 00:13:48,080 --> 00:13:53,360 Speaker 2: hundred percent in Argentina one hundred percent, so something that 273 00:13:53,400 --> 00:13:56,560 Speaker 2: you bought a year ago costs up double in price 274 00:13:56,800 --> 00:14:00,839 Speaker 2: just a year later. They're hoping that this will incentivize 275 00:14:01,160 --> 00:14:04,880 Speaker 2: investments in the country's currency, because that's also well, they've 276 00:14:04,920 --> 00:14:05,839 Speaker 2: taken a bad hit. 277 00:14:05,920 --> 00:14:09,320 Speaker 1: They printed too much money. Is that how they got 278 00:14:09,320 --> 00:14:13,520 Speaker 1: into this? Look this up the other day. They gets complicated, 279 00:14:14,080 --> 00:14:19,320 Speaker 1: but they had problems with their currency. Other countries around 280 00:14:19,360 --> 00:14:23,440 Speaker 1: the world didn't trust the currency, they didn't want to 281 00:14:23,560 --> 00:14:26,000 Speaker 1: use it, they didn't want to trade with it, and 282 00:14:26,040 --> 00:14:31,080 Speaker 1: this ended up causing the government to print enormous amounts 283 00:14:31,120 --> 00:14:34,360 Speaker 1: of money because of what it was doing to the economy. 284 00:14:34,640 --> 00:14:38,320 Speaker 1: And printing money is the worst thing in the world 285 00:14:38,320 --> 00:14:41,120 Speaker 1: that you can do. I mean, that's the reason we 286 00:14:41,160 --> 00:14:46,280 Speaker 1: had inflation this past year was excessive money printing. You 287 00:14:46,360 --> 00:14:49,880 Speaker 1: just can't do it, because it's the basic definition of 288 00:14:49,880 --> 00:14:53,000 Speaker 1: inflation is too much money chasing too few goods. Well, 289 00:14:53,040 --> 00:14:56,200 Speaker 1: if you create a lot of fake money and people 290 00:14:56,280 --> 00:14:59,200 Speaker 1: now have their you know, cash is burning in their hands, 291 00:14:59,240 --> 00:15:02,120 Speaker 1: right at all I could spend Well, in effect, it 292 00:15:02,200 --> 00:15:06,760 Speaker 1: creates millions of many bidding wars. It's like, well, you know, 293 00:15:06,840 --> 00:15:09,080 Speaker 1: i'll pay dollars for those eggs. Yeah, I'll pay ten, 294 00:15:09,200 --> 00:15:12,120 Speaker 1: I'll pay twelve, because what does it matter? Right? 295 00:15:12,840 --> 00:15:15,200 Speaker 2: And when we sear they had an election in twenty 296 00:15:15,320 --> 00:15:20,320 Speaker 2: nineteen and it sparked a massive selloff in government bonds 297 00:15:20,640 --> 00:15:24,640 Speaker 2: that the government defaulted on. So the President of Argentina, 298 00:15:24,800 --> 00:15:27,680 Speaker 2: you're right, printed money during the pandemic the finance, cash 299 00:15:27,680 --> 00:15:31,000 Speaker 2: handouts and salary programs whould set the stage for inflation 300 00:15:31,120 --> 00:15:34,400 Speaker 2: to surge. They're right, too much money tasting too few goods. 301 00:15:35,000 --> 00:15:37,160 Speaker 2: But I've never seen inflation like this, Although it says 302 00:15:37,440 --> 00:15:42,560 Speaker 2: in Lebanon, Lebanon inflation is three hundred and fifty two percent. Yes, 303 00:15:42,640 --> 00:15:46,120 Speaker 2: it's hard to even fathom that something could cost more 304 00:15:46,160 --> 00:15:46,960 Speaker 2: than three times when. 305 00:15:46,880 --> 00:15:49,720 Speaker 1: It costs just a year ago. But these stories are 306 00:15:49,760 --> 00:15:50,360 Speaker 1: pretty sad. 307 00:15:51,000 --> 00:15:53,000 Speaker 2: I would imagine that there's probably going to be a 308 00:15:53,000 --> 00:15:54,560 Speaker 2: surge of people trying to come to the United States 309 00:15:54,560 --> 00:15:56,800 Speaker 2: from this country as well. I mean, you'd want to 310 00:15:56,920 --> 00:15:58,720 Speaker 2: escape this if you can't afford food. 311 00:15:58,560 --> 00:16:02,520 Speaker 1: Right, well, yeah, have to. This is what causes refugees 312 00:16:02,920 --> 00:16:07,800 Speaker 1: situations because people can't can't live, they can't manage it. 313 00:16:08,120 --> 00:16:12,600 Speaker 2: More than ten Argentinians are poor, and fifty four percent 314 00:16:12,640 --> 00:16:16,000 Speaker 2: of the children under fifteen are poor, according to this report. 315 00:16:17,520 --> 00:16:18,880 Speaker 1: I'm looking at them lining up at. 316 00:16:18,760 --> 00:16:22,120 Speaker 2: Soup kitchens and it's just not a place you think 317 00:16:22,120 --> 00:16:24,440 Speaker 2: about much. Argentina doesn't generally make the news. 318 00:16:24,840 --> 00:16:28,640 Speaker 1: Now I'm looking up Lebanon and they had some currency 319 00:16:29,080 --> 00:16:32,480 Speaker 1: printed up, too much money too with their currency. This 320 00:16:32,560 --> 00:16:36,440 Speaker 1: has been going on all year. It's their worst financial 321 00:16:36,480 --> 00:16:39,200 Speaker 1: crisis in decades. They call it hyper inflation. 322 00:16:39,840 --> 00:16:45,400 Speaker 2: Yeah, well it's fifty sounds beyond even hyper. You have 323 00:16:45,440 --> 00:16:48,440 Speaker 2: to come up with a new word for that. Yeah, 324 00:16:48,680 --> 00:16:52,240 Speaker 2: you're right, John. The Argentinians have seen this before. The 325 00:16:52,280 --> 00:16:55,240 Speaker 2: government has a pension there for printing money to finance spending, 326 00:16:55,880 --> 00:17:00,880 Speaker 2: but the pandemic really accelerated the printing of money. They've 327 00:17:00,920 --> 00:17:03,560 Speaker 2: also had a big drought there, and of course the 328 00:17:03,600 --> 00:17:09,920 Speaker 2: local currency has depreciated humongously in their country. But a 329 00:17:10,160 --> 00:17:13,080 Speaker 2: ninety seven percent interest rate, I don't think anybody would 330 00:17:13,080 --> 00:17:17,280 Speaker 2: be borrowing, would they same thing in Lebanon. They did 331 00:17:17,280 --> 00:17:19,400 Speaker 2: the same thing that they started printing money, it says 332 00:17:19,400 --> 00:17:22,240 Speaker 2: the central bank. This is a story from November of 333 00:17:22,480 --> 00:17:26,200 Speaker 2: twenty twenty two. Central back. Central Bank has been significantly 334 00:17:26,240 --> 00:17:30,280 Speaker 2: printing money since twenty nineteen. The amount of pounds in 335 00:17:30,320 --> 00:17:34,560 Speaker 2: circulation has drastically increased. Here's another story, the high cost 336 00:17:34,560 --> 00:17:36,639 Speaker 2: of printing money for the Lebanon Central Bank. 337 00:17:37,560 --> 00:17:38,439 Speaker 1: And I don't think we. 338 00:17:38,280 --> 00:17:40,359 Speaker 2: Were that much different when we had our We still 339 00:17:40,359 --> 00:17:43,760 Speaker 2: have a run with inflation. But we panted out so 340 00:17:43,880 --> 00:17:46,720 Speaker 2: much stimulus money during the pandemic and that will government, 341 00:17:46,720 --> 00:17:48,000 Speaker 2: the state government. 342 00:17:47,640 --> 00:17:50,359 Speaker 1: And interest rates were near zero percent. 343 00:17:51,280 --> 00:17:54,960 Speaker 2: Yeah, so because again we overreacted thinking, oh, people aren't 344 00:17:54,960 --> 00:17:58,320 Speaker 2: going to spend because of the pandemic, keeps them at home, 345 00:17:58,400 --> 00:18:01,440 Speaker 2: and oh, so let's just incentivize them with more money 346 00:18:01,440 --> 00:18:01,879 Speaker 2: to spend. 347 00:18:02,000 --> 00:18:05,800 Speaker 1: There are some basic economic rules, and they're like physics rules. 348 00:18:06,160 --> 00:18:09,120 Speaker 1: You can't violate them. If you violate them, you'll pay 349 00:18:09,119 --> 00:18:11,720 Speaker 1: a price every time. If you pretend that the law 350 00:18:11,720 --> 00:18:14,800 Speaker 1: of gravity doesn't exist. Well, when you jump off the 351 00:18:15,000 --> 00:18:17,040 Speaker 1: fifth floor of a building, you're gonna fall on your 352 00:18:17,080 --> 00:18:20,560 Speaker 1: head and die. All right, we got more coming up. 353 00:18:20,920 --> 00:18:25,120 Speaker 2: Johnny Ken, KFI AM six forty Live Everywhere the iHeartRadio app. 354 00:18:26,240 --> 00:18:29,600 Speaker 5: You're listening to John and Ken on demand from KFI 355 00:18:29,840 --> 00:18:31,080 Speaker 5: AM six forty. 356 00:18:32,640 --> 00:18:35,120 Speaker 1: On the radio from one till four. After four o'clock, 357 00:18:35,520 --> 00:18:38,760 Speaker 1: we post John and Ken on demand. That's our podcast, 358 00:18:38,880 --> 00:18:41,200 Speaker 1: and you could hear our whole show this afternoon all 359 00:18:41,240 --> 00:18:43,680 Speaker 1: over again the parts you missed, and that'll be after 360 00:18:43,720 --> 00:18:44,720 Speaker 1: four o'clock you could do. 361 00:18:45,560 --> 00:18:48,919 Speaker 2: I'd like listen to clip that Mark played in the news. 362 00:18:49,160 --> 00:18:51,280 Speaker 2: New York City, of course, with a lot of migrants, 363 00:18:51,320 --> 00:18:53,440 Speaker 2: maybe putting some of them in gyms, and a real 364 00:18:53,440 --> 00:18:55,600 Speaker 2: New Yorker did you hear on there? Let them put 365 00:18:55,640 --> 00:18:58,480 Speaker 2: them in their neighborhoods. They should take them. If they did, 366 00:18:58,480 --> 00:19:00,520 Speaker 2: there's so much for this, then then take them into 367 00:19:00,560 --> 00:19:04,120 Speaker 2: their own neighborhoods. These politicians, you I. 368 00:19:04,080 --> 00:19:06,280 Speaker 1: Can't imagine there's not going to be a huge parental 369 00:19:06,280 --> 00:19:10,800 Speaker 1: revolt having their high school gyms filled with illegal aliens. 370 00:19:11,520 --> 00:19:17,119 Speaker 1: It's only temporary, really, Yeah, if they can't find a 371 00:19:17,119 --> 00:19:18,800 Speaker 1: place today. Where are they going to find a place 372 00:19:18,840 --> 00:19:21,320 Speaker 1: a week from now. They're supposed to have sponsors who 373 00:19:21,320 --> 00:19:22,960 Speaker 1: take them in. I thought that was the idea. But 374 00:19:23,480 --> 00:19:25,800 Speaker 1: let you into the country. There's a sponsor somewhere they 375 00:19:25,800 --> 00:19:28,119 Speaker 1: can go live with. Now, it was the sponsors, the 376 00:19:28,200 --> 00:19:32,320 Speaker 1: drug cartel guys this phone. Sometimes it's the child labor guys. Yeah, no, 377 00:19:32,359 --> 00:19:35,160 Speaker 1: it's a guy in Tijuana picks up the phone. Yeah, 378 00:19:35,280 --> 00:19:37,880 Speaker 1: I'm their sponsor. All right, let's. 379 00:19:37,720 --> 00:19:42,200 Speaker 2: Play this sad story of an attack in downtown Los 380 00:19:42,280 --> 00:19:47,920 Speaker 2: Angeles on a clothing store and the owner got severely beaten. 381 00:19:48,400 --> 00:19:51,840 Speaker 2: It's from ABC seven reporter Sophie Flays. 382 00:19:51,920 --> 00:19:56,119 Speaker 6: A vicious beating inside this downtown LA store, the owner 383 00:19:56,200 --> 00:20:01,360 Speaker 6: brutally attacked by two armed men, kicking and pistol him unconscious. 384 00:20:01,920 --> 00:20:03,919 Speaker 6: When his friend comes out from the back of the store, 385 00:20:03,960 --> 00:20:07,080 Speaker 6: he's kicked in the face. This all happened around five 386 00:20:07,119 --> 00:20:10,479 Speaker 6: pm Wednesday at the retail store Cloud Pushers on Main Street. 387 00:20:10,760 --> 00:20:14,400 Speaker 6: The store owner, Frankie Salerno, was hospitalized. 388 00:20:13,840 --> 00:20:21,400 Speaker 7: Multiple skull fractures, I suck, a nose fractures, a broken finger. 389 00:20:21,920 --> 00:20:24,240 Speaker 6: Frankie didn't want us to see his injured face, but 390 00:20:24,320 --> 00:20:27,440 Speaker 6: shared these photos of staples and his scalp after being 391 00:20:27,480 --> 00:20:29,879 Speaker 6: hammered in the head with a gun and stomped on. 392 00:20:30,160 --> 00:20:32,840 Speaker 6: He's been discharged after spending four days in the hospital. 393 00:20:33,080 --> 00:20:35,200 Speaker 6: He's now recovering at home under the care of his 394 00:20:35,240 --> 00:20:39,159 Speaker 6: mother and his girlfriend, Evana Octaviani. She set up a 395 00:20:39,200 --> 00:20:42,840 Speaker 6: GoFundMe for his medical bills, surpassing ten thousand dollars. 396 00:20:43,160 --> 00:20:48,159 Speaker 7: I went to the store on Thursday because when the 397 00:20:48,160 --> 00:20:51,760 Speaker 7: police was there, I saw so much blood on the floor. 398 00:20:51,800 --> 00:20:53,040 Speaker 7: I don't even want to walk in. 399 00:20:53,280 --> 00:20:56,440 Speaker 6: His attackers stole only what was on him, his watch, bracelet, 400 00:20:56,480 --> 00:20:59,680 Speaker 6: and chain. Surveillance video from outside the store shows the 401 00:20:59,680 --> 00:21:03,040 Speaker 6: attackers hop into a park sedan with tinted windows they 402 00:21:03,040 --> 00:21:06,119 Speaker 6: had southbound on Main Street. Frankie's girlfriend moved out of 403 00:21:06,160 --> 00:21:09,040 Speaker 6: Los Angeles days before the attack because she was worried 404 00:21:09,040 --> 00:21:12,639 Speaker 6: about increasing crime in the city, and after the unthinkable 405 00:21:12,640 --> 00:21:16,080 Speaker 6: abuse Frankie endured, she says he'll never open his shop 406 00:21:16,200 --> 00:21:17,200 Speaker 6: again by. 407 00:21:17,119 --> 00:21:18,320 Speaker 7: Aus and so what do you want to do with 408 00:21:18,640 --> 00:21:20,439 Speaker 7: about the store? And he was like, I'm not going 409 00:21:20,520 --> 00:21:23,440 Speaker 7: to step my feet into to the store anymore. 410 00:21:23,760 --> 00:21:26,560 Speaker 6: She hopes sharing this video will help police catch these 411 00:21:26,600 --> 00:21:27,320 Speaker 6: heartless men. 412 00:21:27,800 --> 00:21:32,359 Speaker 7: This does not only a regular robbery. They almost kill him, 413 00:21:32,760 --> 00:21:37,240 Speaker 7: literally almost kill him. He's lucky he doesn't have any 414 00:21:37,440 --> 00:21:38,919 Speaker 7: brain damage. 415 00:21:38,440 --> 00:21:40,600 Speaker 6: And mark that mess inside the shop has not yet 416 00:21:40,680 --> 00:21:45,000 Speaker 6: been cleaned up. Ivana is meeting with detectives again on Wednesday. 417 00:21:45,240 --> 00:21:49,800 Speaker 2: His wounds were unbelievable. And now let's just recap this. This 418 00:21:49,840 --> 00:21:52,639 Speaker 2: is usually the point where like the Lsagundo Times, trots 419 00:21:52,680 --> 00:21:56,159 Speaker 2: out the stats and crime and violent crime is really 420 00:21:56,200 --> 00:21:58,520 Speaker 2: no different than it was a couple of years. I mean, 421 00:21:58,520 --> 00:22:01,600 Speaker 2: hearing stories like this, all they took was like his watch. 422 00:22:01,800 --> 00:22:03,840 Speaker 2: I mean, they walk into a clothing store, you think 423 00:22:03,840 --> 00:22:05,920 Speaker 2: they would have at least taken some jeans or some 424 00:22:05,960 --> 00:22:08,119 Speaker 2: shirts that might be worth something. They took his watch, 425 00:22:08,160 --> 00:22:12,159 Speaker 2: bracelet and shane and beat him senseless. This is really 426 00:22:12,200 --> 00:22:14,440 Speaker 2: really bizarre and no wonder the poor guy has decided 427 00:22:14,680 --> 00:22:15,280 Speaker 2: he's not going. 428 00:22:15,240 --> 00:22:18,120 Speaker 1: To come back into that store and reopen again. These 429 00:22:18,119 --> 00:22:21,840 Speaker 1: people are psycho they're psycho violent and guy has happened 430 00:22:21,880 --> 00:22:23,760 Speaker 1: during the day. What kind of drugs that they're on 431 00:22:24,040 --> 00:22:29,960 Speaker 1: that enhances their violence? This is I mean, because if 432 00:22:29,960 --> 00:22:34,080 Speaker 1: you're an armed robber, you got a gun, and almost 433 00:22:34,119 --> 00:22:37,720 Speaker 1: all the time the store owner or whoever's behind the 434 00:22:37,760 --> 00:22:40,080 Speaker 1: counter is going to give you what you want, right, 435 00:22:40,160 --> 00:22:42,360 Speaker 1: you got a gun, they don't. You win, all right, 436 00:22:42,400 --> 00:22:45,840 Speaker 1: So you take all the money, take whatever valuable items 437 00:22:46,240 --> 00:22:48,359 Speaker 1: that they have. But if you just go out of 438 00:22:48,400 --> 00:22:51,080 Speaker 1: your way to beat the crap out of him, beating 439 00:22:51,160 --> 00:22:53,399 Speaker 1: him over the head with his gun repeated lan in fact, 440 00:22:53,440 --> 00:22:56,320 Speaker 1: fracturing his skull and breaking his nose, you're just doing 441 00:22:56,359 --> 00:22:59,639 Speaker 1: that for fun or you're so whacked out on whatever 442 00:22:59,760 --> 00:23:04,199 Speaker 1: drug you're on. I man, there's there's there's there's no 443 00:23:04,240 --> 00:23:06,800 Speaker 1: point in doing that most of the time. Uh, those 444 00:23:06,880 --> 00:23:08,320 Speaker 1: those robbers don't do that. 445 00:23:10,320 --> 00:23:12,800 Speaker 2: Apparently one of the Yeah, a second victim was later 446 00:23:12,840 --> 00:23:15,480 Speaker 2: seen in the video being injured at off camera altercations. 447 00:23:15,520 --> 00:23:17,360 Speaker 1: So it looks like they got a couple of people there. 448 00:23:17,960 --> 00:23:21,480 Speaker 1: But but this is you know, Karen Bessett, you have 449 00:23:21,520 --> 00:23:26,400 Speaker 1: anything to say about this? Downtown ELA's a wonderful place. Yeah. 450 00:23:26,440 --> 00:23:30,080 Speaker 2: And also from the the bizarre world of when the 451 00:23:30,080 --> 00:23:33,200 Speaker 2: Homeless Meets the Homeless, we have this story out of 452 00:23:33,240 --> 00:23:37,359 Speaker 2: downtown Riverside where apparently one homeless guy chopped off with 453 00:23:37,440 --> 00:23:43,280 Speaker 2: other guy's hand. The victim was in his sixties and 454 00:23:43,800 --> 00:23:46,439 Speaker 2: all right, believed to be homeless, was taken to a 455 00:23:46,480 --> 00:23:50,200 Speaker 2: nearby hospital. Expected to respond. The police got a call 456 00:23:50,240 --> 00:23:53,520 Speaker 2: about ten thirty Saturday night. People reported what appeared to 457 00:23:53,520 --> 00:23:56,600 Speaker 2: be a severed hand on the ground. When I call 458 00:23:56,680 --> 00:23:59,880 Speaker 2: that in, I guess I would, I don't. They found 459 00:24:00,160 --> 00:24:02,960 Speaker 2: hand and what looked like a crime scene. That around 460 00:24:03,000 --> 00:24:05,359 Speaker 2: the same time, a guy in his sixty shows up 461 00:24:05,359 --> 00:24:07,680 Speaker 2: at a local hospital happens to be missing a hand. 462 00:24:08,200 --> 00:24:12,080 Speaker 2: So you put two and two together and you discovered that. 463 00:24:12,160 --> 00:24:13,400 Speaker 1: I think we found your hands, sir. 464 00:24:14,320 --> 00:24:18,199 Speaker 2: They yeah, they believe that both the attacker and the 465 00:24:18,280 --> 00:24:22,359 Speaker 2: victim were homeless. They must have had some disagreement where 466 00:24:22,880 --> 00:24:24,720 Speaker 2: one of the guys took out his sword and chopped 467 00:24:24,720 --> 00:24:25,040 Speaker 2: off his. 468 00:24:25,200 --> 00:24:29,680 Speaker 1: Right the sword. There are more people walking around swords 469 00:24:29,680 --> 00:24:33,439 Speaker 1: and machetes. Yes, stampings have been big lately. All this 470 00:24:33,480 --> 00:24:36,040 Speaker 1: one's really not just stabbings where you have a regular 471 00:24:36,119 --> 00:24:38,920 Speaker 1: you know, pocket knife or kitchen knife or something. They're 472 00:24:38,960 --> 00:24:43,359 Speaker 1: walking around swords and machetes. Where are they getting these from? 473 00:24:43,720 --> 00:24:44,520 Speaker 1: Whatever happen to that guy? 474 00:24:44,560 --> 00:24:47,000 Speaker 2: Remember that the guy that attacked the home in Pasadena 475 00:24:47,000 --> 00:24:49,040 Speaker 2: with the michelle was a woman. Actually, yeah, she walked 476 00:24:49,119 --> 00:24:51,080 Speaker 2: up to the front door and she started smashing everything 477 00:24:52,119 --> 00:24:52,480 Speaker 2: where do. 478 00:24:52,440 --> 00:24:53,399 Speaker 1: They sell machetes? 479 00:24:53,600 --> 00:24:55,840 Speaker 2: And there was some guy at a homeless encampment who 480 00:24:55,880 --> 00:24:58,080 Speaker 2: was walking down the street with machetes. Wasn't he remembering 481 00:24:58,119 --> 00:25:01,720 Speaker 2: that story? Yeah, there was an Lincoln Heights. I think, uh, 482 00:25:02,119 --> 00:25:03,640 Speaker 2: where do they get them? I think you can find 483 00:25:03,680 --> 00:25:05,399 Speaker 2: them where the. 484 00:25:05,400 --> 00:25:09,440 Speaker 1: Homeless get them? Where they just it seems a disproportionate 485 00:25:09,520 --> 00:25:11,320 Speaker 1: number of these vagrants are. 486 00:25:11,480 --> 00:25:14,040 Speaker 2: They comes into my category John, nothing to do it, 487 00:25:14,080 --> 00:25:15,720 Speaker 2: all day to do it, So they just wander around. 488 00:25:15,720 --> 00:25:18,600 Speaker 2: Maybe they find one in the trash somewhere, or sword, 489 00:25:19,080 --> 00:25:22,040 Speaker 2: or they go to a flea market or somebody. 490 00:25:22,160 --> 00:25:27,040 Speaker 1: I don't understand yard sale. It's a machete there. I 491 00:25:27,080 --> 00:25:29,080 Speaker 1: don't know. I have no idea. How many how many 492 00:25:29,119 --> 00:25:31,400 Speaker 1: decades of your life did you live before you heard 493 00:25:31,440 --> 00:25:36,280 Speaker 1: about a guy wielding his sword in public, chopping off, 494 00:25:36,560 --> 00:25:38,480 Speaker 1: chopping off, chopping off somebody's hand. 495 00:25:38,720 --> 00:25:40,200 Speaker 2: I guess you know you can make the case gonna 496 00:25:40,200 --> 00:25:42,040 Speaker 2: stab them to the heart. He only chopped off his 497 00:25:42,080 --> 00:25:44,560 Speaker 2: hand and kill them, right, Yeah, Now, this is what 498 00:25:44,600 --> 00:25:47,280 Speaker 2: they do to the thieves. The guys should have went 499 00:25:47,280 --> 00:25:48,800 Speaker 2: back and picked up his hand. I guess they couldn't 500 00:25:48,800 --> 00:25:49,359 Speaker 2: reattach it. 501 00:25:49,440 --> 00:25:52,560 Speaker 1: I wish he'd run into those two robbers who beat 502 00:25:52,560 --> 00:25:55,000 Speaker 1: the guy in downtown in l A. Oh, that's true. 503 00:25:55,040 --> 00:25:57,439 Speaker 1: Shot those guys hands off. Now we got it in 504 00:25:58,320 --> 00:25:58,879 Speaker 1: good fate. 505 00:25:59,240 --> 00:26:01,240 Speaker 2: All right, we got are coming up John and Ken 506 00:26:01,320 --> 00:26:02,880 Speaker 2: KFI AM six forty. 507 00:26:02,880 --> 00:26:05,040 Speaker 1: We're live everywhere the iHeartRadio app. 508 00:26:05,760 --> 00:26:09,120 Speaker 5: You're listening to John and Ken on demand from KFI 509 00:26:09,359 --> 00:26:10,320 Speaker 5: AM six forty. 510 00:26:13,440 --> 00:26:16,160 Speaker 1: What do you think DUCA sports Lakers and six again. Yes, 511 00:26:16,240 --> 00:26:17,280 Speaker 1: that's the theme this year. 512 00:26:17,640 --> 00:26:19,760 Speaker 2: That is the theme in the first two playoff series. 513 00:26:19,760 --> 00:26:21,719 Speaker 2: They can take out the Nuggets and six. That's what 514 00:26:21,720 --> 00:26:22,120 Speaker 2: we got. 515 00:26:22,280 --> 00:26:25,960 Speaker 1: Yes, they're underdogs tonight and they're underdogs for the whole series. 516 00:26:26,720 --> 00:26:29,280 Speaker 1: Do you think every game they'll be underdogs? Well, according 517 00:26:29,320 --> 00:26:32,200 Speaker 1: to Vegas the odds to win the series. Uh oh, 518 00:26:32,240 --> 00:26:34,760 Speaker 1: the night favorite Denver. Well, the Nuggets every one seed. Yeah, yes, 519 00:26:35,040 --> 00:26:36,320 Speaker 1: they had a great regular season. 520 00:26:37,240 --> 00:26:40,840 Speaker 2: John by the way, just looking quickly, what was his name, 521 00:26:40,880 --> 00:26:45,000 Speaker 2: Bailey Opero and O two and oh one era. It's 522 00:26:45,000 --> 00:26:48,399 Speaker 2: two more pitching, two more games than I won this year. Well, 523 00:26:48,480 --> 00:26:50,760 Speaker 2: now we're on the Dianne Feinstein watch here on the 524 00:26:50,840 --> 00:26:54,160 Speaker 2: John and Ken Show. And this is concerning writing in Slate, 525 00:26:54,240 --> 00:26:56,919 Speaker 2: a reporter by the name of Jim Newell related in 526 00:26:57,000 --> 00:27:00,960 Speaker 2: exchange she had with the Senator yesterday afternoon. He called 527 00:27:00,960 --> 00:27:07,160 Speaker 2: it a brief concerning conversation with Dianne Feinstein. Here's how 528 00:27:07,160 --> 00:27:10,960 Speaker 2: it went. I asked her how she was feeling. She responded, Oh, 529 00:27:11,000 --> 00:27:13,200 Speaker 2: I'm feeling fine. I have a problem with the leg. 530 00:27:14,119 --> 00:27:16,880 Speaker 2: A fellow reporter sticking out the elevator asked, what's wrong 531 00:27:16,920 --> 00:27:20,320 Speaker 2: with your leg? Nothing that anyone's concerned but mine. 532 00:27:20,400 --> 00:27:21,880 Speaker 1: She said, okay, so far. 533 00:27:22,480 --> 00:27:24,760 Speaker 2: When the fellow reporter asked her what the response from 534 00:27:24,760 --> 00:27:28,240 Speaker 2: her colleagues had been like since her return, the conversation 535 00:27:28,320 --> 00:27:31,320 Speaker 2: took an odd turn. Well, no, I haven't been gone, 536 00:27:31,359 --> 00:27:35,720 Speaker 2: she said, you should follow me. I haven't been gone. 537 00:27:35,720 --> 00:27:38,320 Speaker 2: I'd been working. When I asked whether she meant that 538 00:27:38,680 --> 00:27:42,240 Speaker 2: working from home, she turned feisty. No, no, I haven't 539 00:27:42,280 --> 00:27:44,720 Speaker 2: been I've been voting. Please you either know where you 540 00:27:44,760 --> 00:27:45,200 Speaker 2: don't know? 541 00:27:45,760 --> 00:27:49,240 Speaker 1: This is all in quotes. She forgot that she wasn't there. 542 00:27:50,280 --> 00:27:54,040 Speaker 2: After deflecting a final question about those like a Representative 543 00:27:54,119 --> 00:27:56,000 Speaker 2: Rocanna who called on her to resign. 544 00:27:55,800 --> 00:27:59,600 Speaker 1: She was wheeled away. I think it's I think it's 545 00:27:59,640 --> 00:28:03,080 Speaker 1: beinished ablished that her mind is is, you know, half 546 00:28:03,119 --> 00:28:05,760 Speaker 1: gone at least, if not more so, she does know 547 00:28:05,840 --> 00:28:08,360 Speaker 1: she was home for three months, she doesn't remember well 548 00:28:08,880 --> 00:28:13,200 Speaker 1: what I've seen, that's right. So if it's as if 549 00:28:13,240 --> 00:28:16,760 Speaker 1: it never happened because the memory wasn't stored. Your memory 550 00:28:16,800 --> 00:28:19,199 Speaker 1: has to be stored, you know, through that magic way 551 00:28:19,400 --> 00:28:22,720 Speaker 1: that brain cells store memories. And if the if the 552 00:28:23,080 --> 00:28:27,320 Speaker 1: cells are dead or the transmission link is cut, then 553 00:28:27,359 --> 00:28:29,480 Speaker 1: it never gets stored as a memory. Think of all 554 00:28:29,480 --> 00:28:32,680 Speaker 1: the things you do that you don't remember, right, Oh, 555 00:28:32,720 --> 00:28:36,119 Speaker 1: of course, I'm sure. In fact, I've read once about 556 00:28:36,160 --> 00:28:40,280 Speaker 1: somebody you heard a photographic memory. This was somebody who 557 00:28:40,400 --> 00:28:45,040 Speaker 1: actually remembered everything everything. Well, there are people that remember 558 00:28:45,080 --> 00:28:46,960 Speaker 1: the details of every day of their life. I'm like, 559 00:28:47,040 --> 00:28:50,720 Speaker 1: that can't be And and this person says it's insanity 560 00:28:51,840 --> 00:28:54,800 Speaker 1: because you know, you crazy, and you don't want to 561 00:28:54,800 --> 00:28:58,640 Speaker 1: remember everything. You you want to you want to forget stuff. 562 00:28:58,680 --> 00:29:00,760 Speaker 1: You want to like glide through the day. You don't 563 00:29:00,800 --> 00:29:02,440 Speaker 1: want to be burdened by because you know, there's a 564 00:29:02,480 --> 00:29:05,520 Speaker 1: lot of bad memories there, right, There's a lot of 565 00:29:05,600 --> 00:29:08,840 Speaker 1: upsetting things or stressful, tense things, and you know eventually 566 00:29:08,880 --> 00:29:11,160 Speaker 1: you want to flush them and after a while pretend 567 00:29:11,200 --> 00:29:13,840 Speaker 1: they never happened. That's what I do. I just pretend 568 00:29:13,880 --> 00:29:16,160 Speaker 1: a lot of stuff never happened. I don't remember it anymore, 569 00:29:16,600 --> 00:29:18,720 Speaker 1: and I'm thinking, my god, that would be a curse, 570 00:29:19,480 --> 00:29:25,760 Speaker 1: not to forget anything at all. It's just fascinating. 571 00:29:25,760 --> 00:29:28,320 Speaker 2: So but my curiosity is if if your short term 572 00:29:28,320 --> 00:29:30,560 Speaker 2: memory has really botched out, so these will never become 573 00:29:30,600 --> 00:29:33,000 Speaker 2: long term memories. So basically you're heading down a road 574 00:29:33,040 --> 00:29:34,960 Speaker 2: of no memories, although you may have your long long 575 00:29:35,040 --> 00:29:37,200 Speaker 2: term memories from she's childhood or your. 576 00:29:37,320 --> 00:29:43,640 Speaker 1: She's living like a goldfish. Yeah, remember what was Dory? Yes? Dory? Yeah? 577 00:29:43,640 --> 00:29:49,680 Speaker 1: From finding Nemo? Yeah, Ellen degenerous right every ten seconds? Wow, 578 00:29:49,800 --> 00:29:51,000 Speaker 1: that was the length that I had heard. 579 00:29:51,000 --> 00:29:52,920 Speaker 2: They were going to monitor her closely because they did 580 00:29:53,000 --> 00:29:56,440 Speaker 2: not want her getting involved in hallway conversations with reporters. 581 00:29:56,480 --> 00:29:59,600 Speaker 1: That's the problem is they wheel her around the capitol. Yeah. 582 00:29:59,680 --> 00:30:02,000 Speaker 2: Well the reporters like, oh, there she is, let's see 583 00:30:02,160 --> 00:30:02,960 Speaker 2: what's going on here. 584 00:30:03,160 --> 00:30:05,880 Speaker 1: Yeah, they have a way getting loose. My wife and I, 585 00:30:05,920 --> 00:30:07,560 Speaker 1: when we first got together, we used to live next 586 00:30:07,560 --> 00:30:10,680 Speaker 1: door across the street from a nursing home. I'm a 587 00:30:10,680 --> 00:30:12,440 Speaker 1: real nursing home. I remember I went in there once 588 00:30:12,600 --> 00:30:15,400 Speaker 1: and these people were so old. All their first names 589 00:30:15,440 --> 00:30:17,760 Speaker 1: were Mildred. There were like a dozen people named Mildred 590 00:30:18,080 --> 00:30:21,280 Speaker 1: because that was like the name of the early nineteen 591 00:30:21,360 --> 00:30:24,760 Speaker 1: hundred and sometimes the Mildred's, that's what I called them. 592 00:30:24,880 --> 00:30:27,600 Speaker 1: The Mildred's got loose, and they'd be walking in the 593 00:30:27,640 --> 00:30:30,080 Speaker 1: middle of the street in front of our house, wandering 594 00:30:30,120 --> 00:30:32,120 Speaker 1: around and some you know, the attendants would have to 595 00:30:32,200 --> 00:30:34,320 Speaker 1: run out and get them because they just would find 596 00:30:34,360 --> 00:30:37,520 Speaker 1: a way to get away. Another loose Mildred wants to 597 00:30:37,560 --> 00:30:38,320 Speaker 1: be locked away. 598 00:30:38,400 --> 00:30:41,240 Speaker 2: People like to get some fresh air. Yeah, new experiences, 599 00:30:41,280 --> 00:30:42,320 Speaker 2: even if you don't remember them. 600 00:30:42,720 --> 00:30:44,760 Speaker 1: Conways here, you know what you should have done is 601 00:30:44,800 --> 00:30:47,560 Speaker 1: just open up the drapes, put on the Benny Hill 602 00:30:47,600 --> 00:30:53,440 Speaker 1: theme song and watch them. Yes, y, yeah, that's what's 603 00:30:54,000 --> 00:30:56,920 Speaker 1: that's right, And you know to nowadays instead of the 604 00:30:56,960 --> 00:30:59,040 Speaker 1: guy coming out and just grabbing him and going home, 605 00:30:59,440 --> 00:31:02,080 Speaker 1: some idiot were filmed them and videotape them. They've been 606 00:31:02,120 --> 00:31:05,480 Speaker 1: all over the internet. I know. Yeah, we regular sightings. 607 00:31:06,400 --> 00:31:08,440 Speaker 1: What would we do with that? You last Night Magoo 608 00:31:08,480 --> 00:31:09,440 Speaker 1: Tonight bands? Right? 609 00:31:09,560 --> 00:31:11,880 Speaker 8: But you remember, can you imagine how much crap we 610 00:31:11,880 --> 00:31:14,280 Speaker 8: miss because none of us had video phones when we 611 00:31:14,280 --> 00:31:14,840 Speaker 8: were younger. 612 00:31:15,040 --> 00:31:16,200 Speaker 1: Yeah, how many? 613 00:31:16,400 --> 00:31:20,040 Speaker 8: How many things you saw that you're like, Wow, Man. 614 00:31:20,560 --> 00:31:25,040 Speaker 1: Isn't that a good thing? Our twenties weren't recorded? That's right, yeah, 615 00:31:25,280 --> 00:31:29,800 Speaker 1: jail time, right exactly. Forty two million Americans are expected 616 00:31:29,840 --> 00:31:32,080 Speaker 1: to travel around Memorial Day weekend. So we're gonna go 617 00:31:32,160 --> 00:31:34,800 Speaker 1: live to the airport and see the latest traveling. Oh, 618 00:31:34,880 --> 00:31:37,680 Speaker 1: it's fantastic. I'll go to the gas stations for you. 619 00:31:37,800 --> 00:31:39,760 Speaker 1: It's good radio. You know. 620 00:31:39,800 --> 00:31:43,440 Speaker 8: It's the guy going to the post office on April fifteenth. Hey, 621 00:31:43,480 --> 00:31:45,600 Speaker 8: we're here at the post office about eleven thirty. So 622 00:31:45,640 --> 00:31:47,600 Speaker 8: why are you so late with your taxes? I just 623 00:31:47,640 --> 00:31:48,240 Speaker 8: blow it off? 624 00:31:50,120 --> 00:31:54,960 Speaker 1: Yeah, where are you traveling to this weekend? Plus Vegas? 625 00:31:55,120 --> 00:31:56,640 Speaker 1: Everyone's going to Vegas? All right? 626 00:31:56,640 --> 00:32:00,520 Speaker 8: And papera LA King's mascot Bailey nominated for the twenty 627 00:32:00,600 --> 00:32:02,360 Speaker 8: twenty three Mascot Hall of Fame. 628 00:32:02,880 --> 00:32:05,560 Speaker 1: That's a lion, right, that's right. You know why he's 629 00:32:05,600 --> 00:32:06,120 Speaker 1: named Bailey. 630 00:32:07,440 --> 00:32:11,720 Speaker 8: The Kings used to have a scout named Bailey, and 631 00:32:11,760 --> 00:32:14,280 Speaker 8: he would scout around the planet for the great greatest 632 00:32:14,320 --> 00:32:17,920 Speaker 8: hockey players. And he was coming from Boston. He left Boston, 633 00:32:18,000 --> 00:32:20,960 Speaker 8: he was flying back to la His flight was hijacked 634 00:32:21,000 --> 00:32:23,360 Speaker 8: and went into the World Trade Center, and he was 635 00:32:23,440 --> 00:32:26,400 Speaker 8: on that flight. So they named the mascot Bailey after 636 00:32:26,440 --> 00:32:26,800 Speaker 8: that match. 637 00:32:26,960 --> 00:32:29,520 Speaker 1: I didn't know that. Yeah, it's a good story. It's 638 00:32:29,520 --> 00:32:30,000 Speaker 1: a good. 639 00:32:29,800 --> 00:32:34,080 Speaker 2: Story and a true story and a sad story story, 640 00:32:34,400 --> 00:32:36,560 Speaker 2: but also good because they named something new. 641 00:32:36,680 --> 00:32:37,440 Speaker 1: Oh and that's right. 642 00:32:37,480 --> 00:32:40,040 Speaker 8: And every time I see Bailey, I think of you know, 643 00:32:40,120 --> 00:32:43,160 Speaker 8: his his kids or whoever you know his family members 644 00:32:43,160 --> 00:32:44,840 Speaker 8: are that they get to you know. 645 00:32:45,320 --> 00:32:48,440 Speaker 1: Mark Thompson, and Mark Thompson is in the he doesn't comin, 646 00:32:48,480 --> 00:32:51,200 Speaker 1: doesn't remember unless I walk in. He doesn't know that tuesdays, 647 00:32:51,240 --> 00:32:51,680 Speaker 1: I come in. 648 00:32:51,840 --> 00:32:54,840 Speaker 8: Okay, if we want to go one on one, come on, 649 00:32:55,320 --> 00:32:59,719 Speaker 8: if you're doing a weekly show a radio show, once 650 00:32:59,840 --> 00:33:01,480 Speaker 8: we don't you think you'd show up on time? 651 00:33:02,520 --> 00:33:08,040 Speaker 1: I thought this was on time. Well you're right, there's 652 00:33:07,320 --> 00:33:11,360 Speaker 1: he he he wins again. I'll give you it's a 653 00:33:11,360 --> 00:33:12,840 Speaker 1: bit of a gray area. 654 00:33:13,080 --> 00:33:15,560 Speaker 5: This is where you got to know when you got 655 00:33:15,560 --> 00:33:17,320 Speaker 5: to know when to tap out, Like if I try 656 00:33:17,320 --> 00:33:20,680 Speaker 5: to come over the top now I'm a real right, 657 00:33:21,120 --> 00:33:22,360 Speaker 5: you got to know when. 658 00:33:22,280 --> 00:33:23,960 Speaker 1: To tap out. Does he stay to the end though? 659 00:33:24,000 --> 00:33:24,640 Speaker 1: Does he do all? 660 00:33:24,800 --> 00:33:25,160 Speaker 7: You know? 661 00:33:25,320 --> 00:33:30,400 Speaker 1: He's great? Come on once he gets here, he's great. 662 00:33:31,520 --> 00:33:39,360 Speaker 1: Want to stumbling come next week Classic Conway, Tom all right, 663 00:33:40,040 --> 00:33:44,120 Speaker 1: different show on My Crozier. He's busy. He's in conversation 664 00:33:44,200 --> 00:33:46,320 Speaker 1: with Belly. Okay, we'll just sit here and wait to 665 00:33:46,400 --> 00:33:48,800 Speaker 1: leave everybody so everybody's a little stuff behind it. He 666 00:33:48,880 --> 00:33:50,720 Speaker 1: has no idea that it's time for him to do 667 00:33:50,800 --> 00:33:52,960 Speaker 1: the news. No, he's having a really good time with Belly. 668 00:33:53,040 --> 00:33:56,400 Speaker 1: In the look they put his headphone on there he is, 669 00:33:56,720 --> 00:34:01,959 Speaker 1: he's are you ready? I'm always ready. I don't have 670 00:34:02,000 --> 00:34:03,240 Speaker 1: my headphones to do my job. 671 00:34:03,320 --> 00:34:08,839 Speaker 3: And like some people, Wow, they're cranked up to ten 672 00:34:08,960 --> 00:34:13,080 Speaker 3: everybody and by would we stay all three hours? 673 00:34:13,360 --> 00:34:13,560 Speaker 7: Eric? 674 00:34:13,680 --> 00:34:19,600 Speaker 1: Screw you too? Who No one's safe today? The Crozer's 675 00:34:19,640 --> 00:34:22,240 Speaker 1: got the news live to play for our Camfie newsroom.