1 00:00:00,520 --> 00:00:04,120 Speaker 1: Already and this this is the daily This is the Daily. 2 00:00:04,160 --> 00:00:15,920 Speaker 2: Ohs oh, now it makes sense. Good morning and welcome 3 00:00:15,920 --> 00:00:18,440 Speaker 2: to the Daily OS. It is Wednesday, the eleventh of December. 4 00:00:18,600 --> 00:00:20,000 Speaker 3: I'm Billy, I'm Zara. 5 00:00:20,440 --> 00:00:23,760 Speaker 2: A twenty six year old man named Luigi Manngioni has 6 00:00:23,800 --> 00:00:26,640 Speaker 2: been arrested over the killing of a health insurance CEO 7 00:00:26,920 --> 00:00:29,760 Speaker 2: last week in New York. For now, it has brought 8 00:00:29,800 --> 00:00:32,760 Speaker 2: to an end a nearly week long manhunt that captivated 9 00:00:32,800 --> 00:00:35,560 Speaker 2: the world and has triggered a wave of anger directed 10 00:00:35,600 --> 00:00:39,000 Speaker 2: at the healthcare system in the US. On today's podcast, 11 00:00:39,000 --> 00:00:41,479 Speaker 2: we'll take you through how this story unfolded and what 12 00:00:41,560 --> 00:00:43,920 Speaker 2: we know about the man they are now alleging was 13 00:00:43,960 --> 00:00:45,040 Speaker 2: behind the murder. 14 00:00:48,159 --> 00:00:51,720 Speaker 3: Billy, this is a story that has captivated genuinely the 15 00:00:51,760 --> 00:00:54,640 Speaker 3: whole world, Like every corner of the Internet seems to 16 00:00:54,680 --> 00:00:57,560 Speaker 3: be obsessed with this story. But for people that perhaps 17 00:00:57,600 --> 00:01:00,240 Speaker 3: haven't been watching the play by play, can do you 18 00:01:00,280 --> 00:01:03,160 Speaker 3: just take us through how did this murder play out? 19 00:01:03,160 --> 00:01:05,200 Speaker 3: And why has it captivated so many people? 20 00:01:05,520 --> 00:01:09,080 Speaker 2: Yeah, this story has literally captivated the world, even my 21 00:01:09,160 --> 00:01:11,400 Speaker 2: for you page on TikTok like I'm in a deep 22 00:01:11,640 --> 00:01:14,840 Speaker 2: rabbit hole. So it's massive News yesterday. But we'll go 23 00:01:15,120 --> 00:01:18,480 Speaker 2: right back to the beginning. So this story starts when 24 00:01:18,680 --> 00:01:21,880 Speaker 2: a man arrives in New York on November twenty four. 25 00:01:22,360 --> 00:01:24,720 Speaker 2: Now they didn't know where he came from. We just 26 00:01:24,760 --> 00:01:27,720 Speaker 2: know that he arrived on November twenty four, and that 27 00:01:27,959 --> 00:01:30,520 Speaker 2: is a week and a bit before the actual shooting, 28 00:01:30,600 --> 00:01:33,680 Speaker 2: just to give you some context of the timeline. So 29 00:01:33,760 --> 00:01:36,399 Speaker 2: this man then took a cab when he arrived that 30 00:01:36,600 --> 00:01:40,600 Speaker 2: night to New York Hilton Midtown, which is the scene 31 00:01:40,640 --> 00:01:44,640 Speaker 2: of where the crime actually happened. Okay, Now, police say 32 00:01:44,640 --> 00:01:46,960 Speaker 2: that detail about him going to where the crime actually 33 00:01:46,959 --> 00:01:49,360 Speaker 2: happened is important because it kind of paints this picture 34 00:01:49,360 --> 00:01:53,880 Speaker 2: of how premeditated and calculated the entire thing was. There 35 00:01:53,920 --> 00:01:57,920 Speaker 2: was a plan that was well established before it actually happened. Now, 36 00:01:57,960 --> 00:01:59,960 Speaker 2: after he went to that scene, we don't know it's 37 00:02:00,000 --> 00:02:01,480 Speaker 2: factly what he did there, but he was there for 38 00:02:01,480 --> 00:02:04,320 Speaker 2: about an hour and then he went to a hostel. 39 00:02:05,000 --> 00:02:07,560 Speaker 2: Now at the hostel, we know that he used a 40 00:02:07,600 --> 00:02:11,000 Speaker 2: fake ID, and we also know that he was acting 41 00:02:11,080 --> 00:02:14,600 Speaker 2: quite strangely throughout the week that he was there. Police 42 00:02:14,639 --> 00:02:16,360 Speaker 2: have obviously spoken to a lot of the people that 43 00:02:16,440 --> 00:02:19,400 Speaker 2: were also staying there and little things that we know 44 00:02:19,480 --> 00:02:21,400 Speaker 2: he did. So we know that he used cash the 45 00:02:21,440 --> 00:02:23,679 Speaker 2: whole time, so he used cash to pay for his day. 46 00:02:24,240 --> 00:02:26,880 Speaker 2: We also know that he hid his face with a mask. 47 00:02:27,120 --> 00:02:30,080 Speaker 2: There was that one moment where he took his masks 48 00:02:30,120 --> 00:02:32,880 Speaker 2: down to smile at the receptionist, but other than that, 49 00:02:33,040 --> 00:02:35,680 Speaker 2: his face was covered pretty much the whole time. And 50 00:02:35,720 --> 00:02:38,359 Speaker 2: we also know that he didn't speak to anyone, so 51 00:02:38,400 --> 00:02:41,480 Speaker 2: he very much stayed to himself throughout his entire stay. 52 00:02:42,520 --> 00:02:45,959 Speaker 2: Then a week after he arrived, in the early hours 53 00:02:45,960 --> 00:02:49,440 Speaker 2: of Wednesday morning, he left that hostel. And the next 54 00:02:49,440 --> 00:02:51,840 Speaker 2: thing that we know for sure is that just before 55 00:02:51,880 --> 00:02:55,480 Speaker 2: six forty five am, a man named Brian Thompson, who 56 00:02:55,560 --> 00:02:58,040 Speaker 2: was the CEO of one of the biggest health insurance 57 00:02:58,080 --> 00:03:01,480 Speaker 2: companies in the US called United Healthcare, was on his 58 00:03:01,520 --> 00:03:04,120 Speaker 2: way to a conference when he was shot and killed. 59 00:03:04,680 --> 00:03:07,400 Speaker 3: And so many of us have now seen that vision. 60 00:03:07,760 --> 00:03:11,040 Speaker 3: As you said, it was just so visceral. It was, 61 00:03:11,120 --> 00:03:13,600 Speaker 3: you know, in broad daylight, and he walks up to 62 00:03:13,720 --> 00:03:17,920 Speaker 3: him and just at point blank range, kills this CEO. 63 00:03:18,280 --> 00:03:20,600 Speaker 2: Yeah, I think what stuck with me is just how 64 00:03:20,720 --> 00:03:24,000 Speaker 2: eerily calm he was when he raised that gun and 65 00:03:24,080 --> 00:03:27,720 Speaker 2: he shot Thompson. We also know that he used a silencer, 66 00:03:27,880 --> 00:03:30,320 Speaker 2: which meant that it wasn't as loud of a gunshot 67 00:03:30,360 --> 00:03:32,760 Speaker 2: as it otherwise would have been. Authority said that they 68 00:03:32,760 --> 00:03:37,080 Speaker 2: haven't actually seen silences be used in many crimes, but 69 00:03:37,160 --> 00:03:41,200 Speaker 2: that they have exploded in popularity recently. Now we then 70 00:03:41,320 --> 00:03:44,480 Speaker 2: know that the suspect got on a bike, he cycled 71 00:03:44,480 --> 00:03:45,400 Speaker 2: to Central Park. 72 00:03:45,640 --> 00:03:49,920 Speaker 3: That blows my mind. Why it just like shooting someone 73 00:03:49,960 --> 00:03:52,600 Speaker 3: in daylight, in broad daylight, and then getting on a 74 00:03:52,640 --> 00:03:55,440 Speaker 3: bike just like nothing happened. Yes, you can very easily 75 00:03:55,560 --> 00:03:56,720 Speaker 3: catch someone on a bike. 76 00:03:57,040 --> 00:03:59,560 Speaker 2: Yes, yeah, but I guess because there weren't that many 77 00:03:59,640 --> 00:04:01,240 Speaker 2: witnesses around him. 78 00:04:01,360 --> 00:04:01,560 Speaker 3: Yeah. 79 00:04:01,560 --> 00:04:03,240 Speaker 2: And I think the other big thing is that he 80 00:04:03,560 --> 00:04:07,200 Speaker 2: wasn't necessarily acting super suspiciously like he had just committed 81 00:04:07,200 --> 00:04:09,320 Speaker 2: a crime, because, as we said, he was just so 82 00:04:09,640 --> 00:04:12,600 Speaker 2: calm as this whole thing played out. We then know 83 00:04:12,760 --> 00:04:16,400 Speaker 2: that he disposed of his backpack in Central Park and 84 00:04:16,400 --> 00:04:19,440 Speaker 2: then again he cycled away. He then took a cab 85 00:04:19,680 --> 00:04:22,440 Speaker 2: and then he took a bus inter state. But there 86 00:04:22,480 --> 00:04:25,560 Speaker 2: are about five days between the killing and then this 87 00:04:25,760 --> 00:04:29,880 Speaker 2: latest development of a man now being charged because they 88 00:04:29,920 --> 00:04:32,520 Speaker 2: believe that he is the suspect in this case. 89 00:04:33,480 --> 00:04:36,160 Speaker 3: I want to talk about the man hunt because it 90 00:04:36,440 --> 00:04:40,120 Speaker 3: for me really brought back memories of the Boston bombing 91 00:04:40,160 --> 00:04:43,000 Speaker 3: and the man hunt that occurred after that. That's kind 92 00:04:43,000 --> 00:04:46,080 Speaker 3: of the last time I remember an entire country, or 93 00:04:46,120 --> 00:04:50,599 Speaker 3: indeed the whole world, fixating on where the suspects were, 94 00:04:50,640 --> 00:04:54,120 Speaker 3: on how they had managed to evade any sort of attention. 95 00:04:54,720 --> 00:04:57,440 Speaker 3: The same thing really has happened here. Can you talk 96 00:04:57,520 --> 00:05:00,719 Speaker 3: me through what we understand occurred? 97 00:05:01,200 --> 00:05:04,480 Speaker 2: Yeah, So it was a nationwide manhunt for this suspect. 98 00:05:04,680 --> 00:05:06,560 Speaker 2: When I was writing this, I was thinking, do I 99 00:05:06,600 --> 00:05:11,719 Speaker 2: say nationwide or global manhunt because TikTok manhunt. Well, we 100 00:05:11,760 --> 00:05:13,599 Speaker 2: didn't know if he had got on a plane because 101 00:05:13,800 --> 00:05:15,600 Speaker 2: they didn't even have a name for him. They had 102 00:05:15,600 --> 00:05:19,200 Speaker 2: no idea who he was. But police released a couple 103 00:05:19,240 --> 00:05:22,600 Speaker 2: of photos to the public throughout those five days, which 104 00:05:22,720 --> 00:05:25,400 Speaker 2: ultimately did prove to be the most successful thing they 105 00:05:25,440 --> 00:05:28,760 Speaker 2: did in trying to find their suspect. His photos were 106 00:05:28,760 --> 00:05:31,640 Speaker 2: shared to the public and to the media, who shared 107 00:05:31,680 --> 00:05:33,960 Speaker 2: them far and wide. Like you mentioned, this was kind 108 00:05:33,960 --> 00:05:36,960 Speaker 2: of a TikTok manhunt. Although I would say that most 109 00:05:36,960 --> 00:05:40,159 Speaker 2: of the sentiment on TikTok was actually trying to keep 110 00:05:40,240 --> 00:05:42,280 Speaker 2: him hidden from the police. 111 00:05:42,360 --> 00:05:43,960 Speaker 3: I mean, that's a whole nother kettle of fish. We 112 00:05:43,960 --> 00:05:45,320 Speaker 3: will talk about that in a moment. 113 00:05:45,600 --> 00:05:48,680 Speaker 2: But having his photo everywhere is what proved to be 114 00:05:48,720 --> 00:05:51,800 Speaker 2: the most successful, because it was ultimately an employee at 115 00:05:51,839 --> 00:05:55,920 Speaker 2: a McDonald's that recognized his face from those photos that 116 00:05:56,080 --> 00:05:59,360 Speaker 2: led to the ultimate arrest. But in terms of those 117 00:05:59,440 --> 00:06:02,479 Speaker 2: days where a man hunt was still ongoing on Friday, 118 00:06:02,480 --> 00:06:05,240 Speaker 2: we know that they recovered a backpack in Central Park. 119 00:06:05,440 --> 00:06:08,160 Speaker 2: I mentioned that, we know that he had discarded that 120 00:06:08,240 --> 00:06:10,840 Speaker 2: backpack at some point. Do you know what was in it? 121 00:06:11,200 --> 00:06:12,120 Speaker 3: I don't know what was in it? 122 00:06:12,240 --> 00:06:16,200 Speaker 2: Monopoly money? Whoa, Yeah, it was kind of just like 123 00:06:16,320 --> 00:06:18,480 Speaker 2: this guy is just joking. 124 00:06:18,080 --> 00:06:20,279 Speaker 3: The round taking the place. Yeah. 125 00:06:20,560 --> 00:06:24,159 Speaker 2: Police also announced a ten thousand dollars reward for anyone 126 00:06:24,200 --> 00:06:27,600 Speaker 2: who provided information that led to the arrest of their suspect. 127 00:06:27,880 --> 00:06:30,760 Speaker 2: That ten thousand dollars amount definitely caused a lot of 128 00:06:30,760 --> 00:06:33,359 Speaker 2: conversation on TikTok, a lot of criticism, a lot of 129 00:06:33,360 --> 00:06:36,800 Speaker 2: criticism saying that is not nearly enough to make people, 130 00:06:36,960 --> 00:06:40,000 Speaker 2: they were saying, want to. 131 00:06:39,200 --> 00:06:42,880 Speaker 3: To incentivize them to share that information. It is unusually 132 00:06:42,960 --> 00:06:44,159 Speaker 3: low it's actually not. 133 00:06:44,400 --> 00:06:47,400 Speaker 2: In Australia that is unusually low, but for the US 134 00:06:47,440 --> 00:06:49,600 Speaker 2: it was actually higher than it usually is. Wow. 135 00:06:49,880 --> 00:06:52,520 Speaker 3: Yeah, had no idea. And so this man hunt went 136 00:06:52,560 --> 00:06:55,640 Speaker 3: on for a number of days, as you mentioned, but 137 00:06:55,760 --> 00:07:01,880 Speaker 3: it all culminated yesterday when the suspect was finally cornered, arrested, 138 00:07:02,040 --> 00:07:05,120 Speaker 3: and then later charged. How did they actually find him? 139 00:07:05,160 --> 00:07:06,880 Speaker 3: You said something about a McDonald's. 140 00:07:07,160 --> 00:07:09,440 Speaker 2: Yeah, it was big news. I heard someone say like 141 00:07:09,560 --> 00:07:11,760 Speaker 2: going out with a bang but ending in a whimpa, 142 00:07:12,160 --> 00:07:15,280 Speaker 2: which I think really adequately describes how this played out. 143 00:07:15,720 --> 00:07:18,360 Speaker 2: So yesterday morning, when we woke ups are in a 144 00:07:18,400 --> 00:07:21,920 Speaker 2: press conference, New York authorities explained that the man was 145 00:07:22,000 --> 00:07:25,280 Speaker 2: just eating at a McDonald's in western Pennsylvania in the 146 00:07:25,320 --> 00:07:29,200 Speaker 2: morning just after nine am, when he, like I said before, 147 00:07:29,280 --> 00:07:32,400 Speaker 2: was recognized by an employee who then called police. 148 00:07:32,680 --> 00:07:35,160 Speaker 1: At this time, he is believed to be our person 149 00:07:35,280 --> 00:07:39,560 Speaker 1: of interest in the brazen targeted murder of Brian Thompson, 150 00:07:40,120 --> 00:07:44,520 Speaker 1: CEO of United Healthcare, last Wednesday in midtown Manhattan. 151 00:07:44,960 --> 00:07:48,160 Speaker 2: So, like I said, he was in a suburb in Pennsylvania. 152 00:07:48,200 --> 00:07:50,240 Speaker 2: Just to give you an idea, that is about two 153 00:07:50,320 --> 00:07:53,240 Speaker 2: hundred and eighty miles or four hundred and fifty kilometers 154 00:07:53,680 --> 00:07:57,520 Speaker 2: from where the shooting took place. Now, court documents have 155 00:07:57,600 --> 00:08:00,600 Speaker 2: since been released that tell us that the man was 156 00:08:00,640 --> 00:08:03,560 Speaker 2: wearing a medical mask when he was at the McDonald's 157 00:08:03,880 --> 00:08:06,920 Speaker 2: and he was sitting alone with a laptop when police 158 00:08:07,040 --> 00:08:10,040 Speaker 2: approached him and they asked him if he had been 159 00:08:10,160 --> 00:08:13,560 Speaker 2: to New York recently. Obviously that is where this crime happened, 160 00:08:13,960 --> 00:08:17,000 Speaker 2: and that caused him to go quiet and apparently he 161 00:08:17,080 --> 00:08:21,520 Speaker 2: started to shake. Now police told us that ultimately when 162 00:08:21,560 --> 00:08:24,160 Speaker 2: they started to have a conversation and search his belongings, 163 00:08:24,480 --> 00:08:29,200 Speaker 2: he was carrying multiple fake IDs, including one that matched 164 00:08:29,360 --> 00:08:32,679 Speaker 2: the fake ID given to the hostel where the suspect 165 00:08:32,760 --> 00:08:34,800 Speaker 2: was staying prior to the murder that I was talking 166 00:08:34,840 --> 00:08:38,000 Speaker 2: about earlier. What they did say was that his name 167 00:08:38,160 --> 00:08:42,280 Speaker 2: is Luigi Mangioni and he is twenty six years old. 168 00:08:42,559 --> 00:08:45,600 Speaker 2: We also know I found this interesting that his name 169 00:08:45,840 --> 00:08:49,280 Speaker 2: was not on their raidar whatsoever prior to this call 170 00:08:49,360 --> 00:08:52,080 Speaker 2: from the McDonald's employee. So I think that gives a 171 00:08:52,120 --> 00:08:56,920 Speaker 2: really clear indication of despite this nationwide manhunt, they did 172 00:08:56,960 --> 00:08:59,640 Speaker 2: not have this person who we had a photo, but 173 00:09:00,000 --> 00:09:02,679 Speaker 2: they had a photo and they had his face, but 174 00:09:02,760 --> 00:09:06,720 Speaker 2: they did not have his name, anything about him. 175 00:09:06,840 --> 00:09:09,800 Speaker 3: Because he has no arrest history or no criminal record. 176 00:09:10,400 --> 00:09:13,280 Speaker 2: It's because no one called in and said, this phase 177 00:09:13,360 --> 00:09:14,360 Speaker 2: looks like the name. 178 00:09:14,240 --> 00:09:18,360 Speaker 3: Of this person, which we spoke about as being crazy, crazy, 179 00:09:18,400 --> 00:09:20,720 Speaker 3: given what we now know about him, which is that 180 00:09:21,040 --> 00:09:23,760 Speaker 3: you know, he attended an ivy league college, he had 181 00:09:23,760 --> 00:09:27,880 Speaker 3: a job, and yet somehow his name wasn't brought to 182 00:09:27,880 --> 00:09:28,880 Speaker 3: the attention of authority. 183 00:09:29,000 --> 00:09:31,920 Speaker 2: Yeah, it's fascinating that something like when I think when 184 00:09:32,080 --> 00:09:35,000 Speaker 2: he wasn't known, a lot of people presumed that he 185 00:09:35,280 --> 00:09:39,040 Speaker 2: was this individual who had kind of remained hidden from society, 186 00:09:39,120 --> 00:09:41,720 Speaker 2: and that was why his name wasn't coming to life. 187 00:09:41,840 --> 00:09:42,520 Speaker 3: It's not what happened. 188 00:09:42,520 --> 00:09:44,480 Speaker 2: But now that is not what happened. 189 00:09:45,080 --> 00:09:46,839 Speaker 3: So you mentioned that that he was found with a 190 00:09:46,840 --> 00:09:49,760 Speaker 3: fake ide that matched up with the identification given at 191 00:09:49,840 --> 00:09:52,680 Speaker 3: the hostel, and of course there must have been a 192 00:09:52,760 --> 00:09:55,880 Speaker 3: visual similarity between the man that sat at that McDonald's 193 00:09:56,080 --> 00:09:59,120 Speaker 3: and the suspect whose photo had been, as you said, 194 00:09:59,120 --> 00:10:01,760 Speaker 3: blasted around the world world. Was there anything else that 195 00:10:01,760 --> 00:10:04,200 Speaker 3: suggested that this was the suspect that they were looking for? 196 00:10:04,440 --> 00:10:06,480 Speaker 2: There were so many I think a lot of people 197 00:10:06,520 --> 00:10:09,920 Speaker 2: were shocked at how many different things happened to align 198 00:10:10,040 --> 00:10:13,280 Speaker 2: with the suspect. So he was carrying a gun and 199 00:10:13,320 --> 00:10:15,960 Speaker 2: also a silencer that I mentioned before, and they said 200 00:10:15,960 --> 00:10:18,520 Speaker 2: that both of those things, the gun and the silencer, 201 00:10:18,679 --> 00:10:22,200 Speaker 2: were consistent with what was used in the killing. So 202 00:10:22,240 --> 00:10:25,440 Speaker 2: he just had those true things on him. One thing 203 00:10:25,480 --> 00:10:27,640 Speaker 2: they said that was also fascinating is that they think 204 00:10:27,679 --> 00:10:30,680 Speaker 2: the gun he was carrying was built from parts that 205 00:10:30,720 --> 00:10:32,360 Speaker 2: were made from a three D printer. 206 00:10:32,640 --> 00:10:33,360 Speaker 3: Blows my mind. 207 00:10:33,440 --> 00:10:36,320 Speaker 2: Doesn't that just give you an meditation that can kill someone? 208 00:10:36,720 --> 00:10:38,320 Speaker 3: Is really something? Yeah? 209 00:10:38,360 --> 00:10:40,800 Speaker 4: It shows just like this new era of crime that 210 00:10:40,840 --> 00:10:43,720 Speaker 4: we're in and gun control. Yeah, you know, so much 211 00:10:43,720 --> 00:10:46,040 Speaker 4: of gun control comes down to background checks, so all 212 00:10:46,080 --> 00:10:48,560 Speaker 4: of these things, and you can't do that if someone's 213 00:10:48,600 --> 00:10:49,520 Speaker 4: printing it off at home. 214 00:10:49,720 --> 00:10:53,720 Speaker 2: Yeah. He also had clothing and masks on him that 215 00:10:53,760 --> 00:10:56,720 Speaker 2: matched the ones worn by the suspect in the CCTV 216 00:10:56,760 --> 00:10:59,520 Speaker 2: footage that has come out. Another sign was that he 217 00:10:59,559 --> 00:11:02,560 Speaker 2: actually had I had a handwritten document on him that 218 00:11:02,640 --> 00:11:06,560 Speaker 2: they said spoke to his mindset and motivation. They said 219 00:11:06,559 --> 00:11:11,000 Speaker 2: the document illustrated ill will toward corporate America and that 220 00:11:11,120 --> 00:11:16,480 Speaker 2: it criticized healthcare companies in particular for putting profits above care. 221 00:11:16,920 --> 00:11:19,160 Speaker 2: So I think that gives you a pretty clear indication 222 00:11:19,400 --> 00:11:22,480 Speaker 2: that this man who was sitting alone at the McDonald's 223 00:11:23,160 --> 00:11:26,880 Speaker 2: had very similar belief systems to the person who killed 224 00:11:27,000 --> 00:11:31,199 Speaker 2: this health insurance executive. Now, authorities didn't in this press 225 00:11:31,200 --> 00:11:34,640 Speaker 2: conference go into detail about the document, which they're calling 226 00:11:34,679 --> 00:11:37,560 Speaker 2: a manifesto, but parts of it have been leaked to 227 00:11:37,840 --> 00:11:41,080 Speaker 2: the media, and we know that it said these parasites 228 00:11:41,080 --> 00:11:44,480 Speaker 2: had it coming. And also I do apologize for any 229 00:11:44,520 --> 00:11:47,880 Speaker 2: strife and trauma, but it had to be done. So 230 00:11:47,920 --> 00:11:50,240 Speaker 2: I think some pretty clear signs that they had straight 231 00:11:50,280 --> 00:11:52,800 Speaker 2: away from just again, this man at McDonald was on 232 00:11:52,880 --> 00:11:56,760 Speaker 2: him that he was their suspect. But at this stage 233 00:11:56,800 --> 00:12:00,280 Speaker 2: he's only been charged. He hasn't been convicted of any crime. 234 00:12:00,120 --> 00:12:01,440 Speaker 3: But charged with the murder. 235 00:12:01,840 --> 00:12:03,240 Speaker 2: He has been charged with the murder. 236 00:12:03,280 --> 00:12:05,480 Speaker 3: Now yet Yeah, okay, so I think I got a 237 00:12:05,480 --> 00:12:08,280 Speaker 3: bit ahead of myself before by describing a bit about 238 00:12:08,679 --> 00:12:11,880 Speaker 3: the suspect. Can you just tell us a bit about 239 00:12:12,040 --> 00:12:14,680 Speaker 3: who Luigi Mangioni is, or at least what we know 240 00:12:14,760 --> 00:12:17,520 Speaker 3: about him, because one of the really unique things here 241 00:12:17,720 --> 00:12:20,480 Speaker 3: is that all of his social media handles were still 242 00:12:20,559 --> 00:12:24,760 Speaker 3: live when he was arrested, and like usually even in Australia, 243 00:12:24,840 --> 00:12:28,559 Speaker 3: like the second there is a high profile suspect, all 244 00:12:28,600 --> 00:12:31,560 Speaker 3: of that is taken off the internet. And yet this 245 00:12:31,720 --> 00:12:32,520 Speaker 3: wasn't the case here. 246 00:12:32,840 --> 00:12:34,600 Speaker 2: Yeah, you and I. As soon as his name was 247 00:12:34,600 --> 00:12:37,680 Speaker 2: being released, we were all sharing his social media profiles 248 00:12:37,679 --> 00:12:41,880 Speaker 2: to see what we could garner from his profiles. What 249 00:12:42,000 --> 00:12:44,320 Speaker 2: we know what authority said is that he was born 250 00:12:44,360 --> 00:12:47,000 Speaker 2: in the US state of Maryland and his last known 251 00:12:47,040 --> 00:12:50,560 Speaker 2: address was in Hawaii, and he also had no prior 252 00:12:50,800 --> 00:12:53,920 Speaker 2: arrest history from what they've been able to determine in 253 00:12:54,120 --> 00:12:58,640 Speaker 2: the hours since he was arrested. Obviously though the media 254 00:12:58,679 --> 00:13:01,600 Speaker 2: and also just anyone with a phone who was interested 255 00:13:01,640 --> 00:13:03,760 Speaker 2: in this case like you and Isa, although we are 256 00:13:03,800 --> 00:13:06,480 Speaker 2: also the media, but we were able to pretty quickly 257 00:13:06,520 --> 00:13:10,280 Speaker 2: find out a lot about this man on his LinkedIn profile. 258 00:13:10,320 --> 00:13:12,800 Speaker 2: For example, we were able to determine that he had 259 00:13:12,840 --> 00:13:16,840 Speaker 2: two degrees, a master's and a bachelor's in computer science 260 00:13:17,160 --> 00:13:20,160 Speaker 2: which was completed over at four years and that was 261 00:13:20,200 --> 00:13:23,280 Speaker 2: from the University of Pennsylvania, which, like you said before, 262 00:13:23,360 --> 00:13:26,520 Speaker 2: is an Ivy League college. We also know that he 263 00:13:26,600 --> 00:13:30,440 Speaker 2: graduated school in twenty sixteen, as valedictorian, which just means 264 00:13:30,440 --> 00:13:32,760 Speaker 2: that he was the top of his graduating class. I 265 00:13:32,800 --> 00:13:34,800 Speaker 2: think we more commonly refer to it as a dux 266 00:13:35,000 --> 00:13:39,920 Speaker 2: in Australia, but clearly a very well educated person. 267 00:13:40,440 --> 00:13:43,320 Speaker 3: Yeah. Something I found interesting when I was looking at 268 00:13:43,320 --> 00:13:46,200 Speaker 3: his Twitter is that, And I mean, like his Twitter 269 00:13:46,200 --> 00:13:49,560 Speaker 3: followers went up by like the thousands every minute. 270 00:13:49,640 --> 00:13:52,280 Speaker 2: It was more than one hundred thousand before it was taken. 271 00:13:52,080 --> 00:13:54,360 Speaker 3: Down by X But I mean I looked at it 272 00:13:54,400 --> 00:13:57,200 Speaker 3: before it was taken down, and in the cover photo, 273 00:13:57,320 --> 00:13:59,800 Speaker 3: you know, on X and actually most platforms you have 274 00:13:59,840 --> 00:14:01,520 Speaker 3: a have a photo and on it was an X 275 00:14:01,600 --> 00:14:06,040 Speaker 3: ray of someone's back and a cartoon character. Like there 276 00:14:06,080 --> 00:14:09,800 Speaker 3: was just little kind of bread crumbs almost that were 277 00:14:09,800 --> 00:14:13,160 Speaker 3: being left about what this story could be. And it 278 00:14:13,240 --> 00:14:15,400 Speaker 3: was just, yeah, I mean absolutely fascinating. 279 00:14:15,480 --> 00:14:18,439 Speaker 2: He had a very wide online presence. There was stuff 280 00:14:18,480 --> 00:14:22,320 Speaker 2: about Google reviews that he had left, Yeah, a Goodreads profile, 281 00:14:22,400 --> 00:14:23,360 Speaker 2: there was a lot. 282 00:14:23,640 --> 00:14:26,400 Speaker 3: Yeah, And I guess that's just a characteristic of a 283 00:14:26,440 --> 00:14:29,640 Speaker 3: modern day story like this. I do want to zero 284 00:14:29,720 --> 00:14:32,160 Speaker 3: in and we're kind of spoken around it a little bit, 285 00:14:32,240 --> 00:14:35,280 Speaker 3: but I think it's such an interesting and unique part 286 00:14:35,320 --> 00:14:39,760 Speaker 3: of this story is the online discourse, especially you know, 287 00:14:39,920 --> 00:14:45,600 Speaker 3: on social media, surrounding the killing of this healthcare executive. 288 00:14:45,760 --> 00:14:48,960 Speaker 3: So it really feels like there is a large portion 289 00:14:49,040 --> 00:14:53,280 Speaker 3: of the online community who are almost trying to protect 290 00:14:53,360 --> 00:14:57,800 Speaker 3: this suspect because of what the action stands for, and 291 00:14:58,040 --> 00:15:00,640 Speaker 3: you know, perhaps what it says about the healthcare system 292 00:15:00,680 --> 00:15:04,480 Speaker 3: in the US. We are obviously in Australia and there 293 00:15:04,480 --> 00:15:07,200 Speaker 3: are stark differences. Do you want to talk me through 294 00:15:07,440 --> 00:15:09,160 Speaker 3: some of that, because, as you said, you texted me 295 00:15:09,160 --> 00:15:11,200 Speaker 3: on like Saturday night and you were like deep in 296 00:15:11,320 --> 00:15:14,680 Speaker 3: this online whole. So talk me through. 297 00:15:14,480 --> 00:15:16,880 Speaker 2: This just on the social media. I think usually when 298 00:15:16,920 --> 00:15:20,200 Speaker 2: we see crimes like this, the broad population is often 299 00:15:20,400 --> 00:15:23,280 Speaker 2: unified in trying to help police find a suspect on 300 00:15:23,320 --> 00:15:26,680 Speaker 2: the crime. But this time they really felt unified in 301 00:15:26,720 --> 00:15:27,840 Speaker 2: trying to protect him. 302 00:15:28,200 --> 00:15:31,720 Speaker 3: Yeah. And I mean, like I mentioned the Boston bombings before, 303 00:15:31,840 --> 00:15:35,600 Speaker 3: this is where those stories going completely opposite directions. In 304 00:15:36,120 --> 00:15:40,960 Speaker 3: that instance, the whole country was behind trying to locate those, yes, 305 00:15:41,040 --> 00:15:43,920 Speaker 3: you know, those suspects here. As you said, the whole 306 00:15:43,960 --> 00:15:46,360 Speaker 3: online world was trying to protect him. 307 00:15:46,560 --> 00:15:49,520 Speaker 2: Yeah, and it's largely because it did propel this wave 308 00:15:49,600 --> 00:15:53,360 Speaker 2: of frustration being directed at the healthcare system in the US. 309 00:15:53,840 --> 00:15:56,400 Speaker 2: So for those not familiar with the healthcare system in 310 00:15:56,400 --> 00:15:59,680 Speaker 2: the US, you mentioned that there were stark differences with 311 00:15:59,800 --> 00:16:03,640 Speaker 2: him in Australia. So the US doesn't have Medicare like 312 00:16:03,680 --> 00:16:07,320 Speaker 2: we do here, so they have no universal health care system. 313 00:16:07,960 --> 00:16:10,320 Speaker 2: So that means that to have health care you need 314 00:16:10,360 --> 00:16:13,640 Speaker 2: to go through a private company, which is really expensive. 315 00:16:13,680 --> 00:16:16,600 Speaker 2: And so mostly employees are the ones who pay for 316 00:16:16,720 --> 00:16:20,840 Speaker 2: people's health insurance. But even then the private health insurance companies, 317 00:16:21,040 --> 00:16:24,720 Speaker 2: they mostly don't cover the full amount of medical expenses. 318 00:16:25,120 --> 00:16:27,520 Speaker 2: And then on top of that, about one in five 319 00:16:27,640 --> 00:16:32,000 Speaker 2: claims actually get rejected by health insurance companies. So the 320 00:16:32,040 --> 00:16:36,040 Speaker 2: big topic of conversation has been that healthcare companies reject 321 00:16:36,080 --> 00:16:38,240 Speaker 2: a lot of claims, and the argument is that they 322 00:16:38,280 --> 00:16:42,160 Speaker 2: allegedly do that to maximize their profits. One thing I 323 00:16:42,240 --> 00:16:46,280 Speaker 2: haven't mentioned about the killing is that the words delay, deny, 324 00:16:46,520 --> 00:16:50,400 Speaker 2: depose we're etched on the bullets that killed Brian Thompson. 325 00:16:50,800 --> 00:16:54,240 Speaker 2: Now we don't know exactly how the shooter intended for 326 00:16:54,280 --> 00:16:56,760 Speaker 2: those words to be interpreted, but I think we can 327 00:16:56,800 --> 00:17:01,320 Speaker 2: pretty safely infer that he's claiming those tactics by health 328 00:17:01,320 --> 00:17:03,800 Speaker 2: insurance companies to avoid paying claims. 329 00:17:04,359 --> 00:17:07,159 Speaker 3: Okay, so clearly there is this you know, big conversation 330 00:17:07,359 --> 00:17:10,880 Speaker 3: happening online. You know, not necessarily I guess, pouring into 331 00:17:10,920 --> 00:17:13,439 Speaker 3: the political realm yet if I don't know if it 332 00:17:13,480 --> 00:17:17,920 Speaker 3: will about the state of health insurance in the US. 333 00:17:18,600 --> 00:17:22,760 Speaker 3: There's a suspect who has been arrested and charged, and 334 00:17:22,800 --> 00:17:26,399 Speaker 3: there's a CEO who has been killed. What happens next 335 00:17:26,480 --> 00:17:27,520 Speaker 3: in this story. 336 00:17:27,720 --> 00:17:29,960 Speaker 2: Well, this is just the beginning. We know that he 337 00:17:30,000 --> 00:17:32,639 Speaker 2: has now been charged with the murder, but just like 338 00:17:32,880 --> 00:17:35,600 Speaker 2: any charge, it now needs to go through. 339 00:17:35,400 --> 00:17:36,480 Speaker 3: The court system. 340 00:17:36,880 --> 00:17:39,760 Speaker 2: Before that even happens, though, he needs to be extradited 341 00:17:39,840 --> 00:17:41,359 Speaker 2: to New York. I feel like that's a word that 342 00:17:41,400 --> 00:17:42,320 Speaker 2: we've spoken a lot about. 343 00:17:42,320 --> 00:17:45,119 Speaker 3: I think, yeah, we've used to already this week. 344 00:17:45,200 --> 00:17:48,000 Speaker 2: It's just the formal transfer of one person from one 345 00:17:48,000 --> 00:17:50,800 Speaker 2: location to another when they are in a separate location 346 00:17:50,960 --> 00:17:54,000 Speaker 2: to the one where the crime they allegedly committed. So 347 00:17:54,080 --> 00:17:56,440 Speaker 2: that's mostly just a procedural point, but it could drag 348 00:17:56,480 --> 00:17:59,280 Speaker 2: this process out. But in terms of what's next, it's 349 00:17:59,320 --> 00:18:02,439 Speaker 2: that and then the court system. We don't know if 350 00:18:02,440 --> 00:18:05,200 Speaker 2: he will plead guilty or not, but that is something 351 00:18:05,240 --> 00:18:07,080 Speaker 2: that we will keep our eyes on Billy. 352 00:18:07,119 --> 00:18:09,359 Speaker 3: Thank you very much for taking me into the depths 353 00:18:09,359 --> 00:18:12,479 Speaker 3: of the Internet and for explaining the story that really, 354 00:18:12,560 --> 00:18:15,600 Speaker 3: as we led with, has captured so much of the 355 00:18:15,640 --> 00:18:16,640 Speaker 3: world's attention. 356 00:18:17,400 --> 00:18:19,840 Speaker 2: Thank you so much for listening to this episode of 357 00:18:19,840 --> 00:18:22,240 Speaker 2: The Daily os. We'll be back again this afternoon with 358 00:18:22,320 --> 00:18:27,760 Speaker 2: your evening headlines. Until then, have a great day. My 359 00:18:27,880 --> 00:18:30,760 Speaker 2: name is Lily Madden and I'm a proud Arunda Bungelung 360 00:18:30,880 --> 00:18:35,199 Speaker 2: Kalkuton woman from Gadighl Country. The Daily oz acknowledges that 361 00:18:35,280 --> 00:18:37,680 Speaker 2: this podcast is recorded on the lands of the Gadighl 362 00:18:37,720 --> 00:18:41,080 Speaker 2: people and pays respect to all Aboriginal and Torres Strait 363 00:18:41,119 --> 00:18:44,080 Speaker 2: Island and nations. We pay our respects to the first 364 00:18:44,080 --> 00:18:46,560 Speaker 2: peoples of these countries, both past and present.