1 00:00:00,360 --> 00:00:03,720 Speaker 1: I distinctly remember it being a Saturday night in November 2 00:00:03,960 --> 00:00:07,680 Speaker 1: of twenty twenty two, and I was around some friends 3 00:00:07,680 --> 00:00:09,680 Speaker 1: and we were having some wine and stuff, and I 4 00:00:09,720 --> 00:00:14,079 Speaker 1: look at Twitter. Elon tweets something like that out and 5 00:00:14,200 --> 00:00:16,640 Speaker 1: I knew right away what was actually happening. 6 00:00:17,320 --> 00:00:20,759 Speaker 2: This is Katie Harbeth. For a decade, she worked at Facebook. 7 00:00:21,239 --> 00:00:24,160 Speaker 2: Her job there was public Policy director for Global Elections, 8 00:00:24,880 --> 00:00:28,840 Speaker 2: which means she understands the dilemma that Twitter, YouTube, every 9 00:00:28,840 --> 00:00:32,520 Speaker 2: other social media site faced on January sixth. It also 10 00:00:32,560 --> 00:00:34,680 Speaker 2: means she was at Facebook when they banned Donald Trump. 11 00:00:35,720 --> 00:00:38,680 Speaker 2: Facebook had removed Trump's post before, like when he claimed 12 00:00:38,720 --> 00:00:41,879 Speaker 2: that COVID was quote less lethal than the flu, but 13 00:00:41,960 --> 00:00:45,680 Speaker 2: January sixth was different. That's because after losing the election, 14 00:00:46,040 --> 00:00:48,400 Speaker 2: he kept saying it had been stolen, that he was 15 00:00:48,440 --> 00:00:52,960 Speaker 2: the rifle winner, and then he encouraged his followers in 16 00:00:53,040 --> 00:00:55,320 Speaker 2: vague terms, to get in the way of certifying the 17 00:00:55,360 --> 00:01:00,160 Speaker 2: election by showing up at the capitol. Katie remembers it 18 00:01:00,200 --> 00:01:04,160 Speaker 2: was a tough decision. Suddenly they were having these precedented 19 00:01:04,160 --> 00:01:09,240 Speaker 2: conversations about truth, democracy and text role in all of that. 20 00:01:09,959 --> 00:01:12,760 Speaker 2: Elon Musk had a different approach. He tweeted a poll 21 00:01:13,120 --> 00:01:17,759 Speaker 2: quote reinstate former President Trump and a Latin phrase Vox 22 00:01:17,800 --> 00:01:20,679 Speaker 2: Popular Vox day, the voice of the people is the 23 00:01:20,720 --> 00:01:24,720 Speaker 2: voice of the gods. Yes, fifteen million people voted yes 24 00:01:24,840 --> 00:01:26,320 Speaker 2: is one, and then. 25 00:01:26,600 --> 00:01:29,760 Speaker 1: The Trump account was back by the next Sunday afternoon. 26 00:01:31,880 --> 00:01:35,000 Speaker 2: Facebook, on the other hand, was so anxious about what 27 00:01:35,040 --> 00:01:37,480 Speaker 2: to do with Trump they took their decision to an 28 00:01:37,520 --> 00:01:41,280 Speaker 2: oversight board. Elon, he just tweeted it. 29 00:01:41,959 --> 00:01:42,200 Speaker 3: For me. 30 00:01:42,280 --> 00:01:47,200 Speaker 1: It was just like it was another indication of just, frankly, 31 00:01:47,240 --> 00:01:51,160 Speaker 1: how reckless he is around this and the naivete that 32 00:01:51,280 --> 00:01:54,600 Speaker 1: I felt like he had around trust and safety and 33 00:01:54,600 --> 00:01:57,440 Speaker 1: content moderation and what it means to actually have a 34 00:01:57,480 --> 00:01:58,440 Speaker 1: healthy town square. 35 00:01:58,880 --> 00:02:02,240 Speaker 2: Elon kept going. He didn't just bring back Trump's Twitter. 36 00:02:02,800 --> 00:02:05,600 Speaker 2: He brought back a live streamer who goes by Baked Alaska, 37 00:02:05,640 --> 00:02:10,280 Speaker 2: who'd been banned for anti semitism, Kanye West also anti semitism, 38 00:02:10,520 --> 00:02:13,720 Speaker 2: Nick Fuentes, who, among a litany of other things, was 39 00:02:13,760 --> 00:02:14,720 Speaker 2: being anti Semitic. 40 00:02:15,200 --> 00:02:18,080 Speaker 1: I think Elon has this ethos like I can just 41 00:02:18,160 --> 00:02:21,640 Speaker 1: do better, Like this isn't that hard, Like you know, 42 00:02:21,800 --> 00:02:23,640 Speaker 1: I can figure this out. 43 00:02:23,840 --> 00:02:26,240 Speaker 2: When he bought Twitter, when he announced he was going 44 00:02:26,280 --> 00:02:28,480 Speaker 2: to take Twitter and make it a free speech platform. 45 00:02:28,880 --> 00:02:30,520 Speaker 2: What did you think when you when you. 46 00:02:30,480 --> 00:02:30,880 Speaker 4: Heard that. 47 00:02:32,520 --> 00:02:34,560 Speaker 1: That he doesn't know what the heck he's getting into 48 00:02:35,120 --> 00:02:36,320 Speaker 1: and what that actually means. 49 00:02:40,600 --> 00:02:47,079 Speaker 2: I'm Max Chafkin. This is Citizen Elon. On episode one, 50 00:02:47,160 --> 00:02:49,720 Speaker 2: we looked at what radicalized Elon Musk and led him 51 00:02:49,720 --> 00:02:53,760 Speaker 2: to buy Twitter today, why that matters, and how it's 52 00:02:53,760 --> 00:02:57,560 Speaker 2: affecting the election. The early days of Twitter, which Elon 53 00:02:57,680 --> 00:03:01,639 Speaker 2: later renamed x, were crazy. He tried to back out 54 00:03:01,680 --> 00:03:04,200 Speaker 2: of the purchase, then a judge forced her to buy it. 55 00:03:04,680 --> 00:03:08,160 Speaker 2: Then he took over. He immediately fired a huge chunk 56 00:03:08,160 --> 00:03:11,200 Speaker 2: of the staff, which led to chaos and lawsuits. He 57 00:03:11,320 --> 00:03:14,480 Speaker 2: was leaking documents about his own company. He named his 58 00:03:14,520 --> 00:03:15,920 Speaker 2: own leak the Twitter Files. 59 00:03:16,840 --> 00:03:20,799 Speaker 3: How and what he did to purchase Twitter is pretty 60 00:03:20,800 --> 00:03:21,720 Speaker 3: astounding here. 61 00:03:22,040 --> 00:03:25,480 Speaker 2: Joan Donovan is a journalism professor at BU. We talked 62 00:03:25,520 --> 00:03:26,560 Speaker 2: to her last episode. 63 00:03:26,960 --> 00:03:31,240 Speaker 3: He was able to bring about billions of dollars in 64 00:03:31,360 --> 00:03:36,120 Speaker 3: loans that are now troubling major banks in order to 65 00:03:36,280 --> 00:03:40,440 Speaker 3: overpay for something that he would never be able to 66 00:03:40,480 --> 00:03:45,760 Speaker 3: recoup his losses on That's not smart for us. Twitter 67 00:03:45,840 --> 00:03:53,120 Speaker 3: really represented the beating heart of centrist media. And the 68 00:03:53,160 --> 00:03:54,760 Speaker 3: mainstream media in general. 69 00:03:55,360 --> 00:03:58,480 Speaker 2: In other words, this was not business as usual, and 70 00:03:58,520 --> 00:04:02,360 Speaker 2: he kept making decisions that's the company's value plummeting. He 71 00:04:02,440 --> 00:04:05,280 Speaker 2: started charging for the blue check which used to mean 72 00:04:05,280 --> 00:04:08,000 Speaker 2: you were verified like you are who you say you are. 73 00:04:08,760 --> 00:04:12,720 Speaker 2: The only people who had them were journalists, politicians and celebrities. 74 00:04:13,560 --> 00:04:17,680 Speaker 2: Now you can just buy one, which whatever, right it 75 00:04:17,720 --> 00:04:19,919 Speaker 2: seemed to lead us in the first place. But the 76 00:04:19,920 --> 00:04:23,240 Speaker 2: difference between say, Joe Biden and someone who says he's 77 00:04:23,360 --> 00:04:25,760 Speaker 2: Joe Biden, it really does matter. 78 00:04:26,120 --> 00:04:30,600 Speaker 3: And so you saw this massive exodus of high value 79 00:04:30,800 --> 00:04:36,360 Speaker 3: users along with also the advertisers. Right at the beginning 80 00:04:36,880 --> 00:04:41,680 Speaker 3: of his purchase, his attitude was, you know, goodbye. And 81 00:04:41,720 --> 00:04:44,560 Speaker 3: then of course he brought back in all of the 82 00:04:45,279 --> 00:04:48,880 Speaker 3: folks that had been removed previously. 83 00:04:49,000 --> 00:04:54,200 Speaker 2: Many of whom paid to be verified, paid for check marks. Suddenly, 84 00:04:54,240 --> 00:04:58,560 Speaker 2: trending accounts had names like end Wokeness, hat Turn, and 85 00:04:58,640 --> 00:05:02,520 Speaker 2: also accounts belong to far right influencers like Mike Cernovich 86 00:05:02,920 --> 00:05:08,680 Speaker 2: and Glenn Greenwald and Elon. He was right there with them, liking, retweeting, 87 00:05:08,839 --> 00:05:13,400 Speaker 2: commenting on those same accounts, and anyway, the most important 88 00:05:13,440 --> 00:05:17,120 Speaker 2: influencer on the right, Donald Trump he wanted nothing to 89 00:05:17,160 --> 00:05:20,200 Speaker 2: do with Elon Musk, maybe because he'd built his own 90 00:05:20,279 --> 00:05:23,000 Speaker 2: free speech platform and wanted his followers to use that 91 00:05:23,040 --> 00:05:24,159 Speaker 2: one instead. 92 00:05:24,680 --> 00:05:26,839 Speaker 5: And go out by the way while I'm here and 93 00:05:26,960 --> 00:05:30,279 Speaker 5: sign up now for truth Social It's hot is a pistol, 94 00:05:30,360 --> 00:05:34,359 Speaker 5: and you stop left wing censorship and restore free speech 95 00:05:34,640 --> 00:05:35,280 Speaker 5: in America. 96 00:05:37,000 --> 00:05:40,080 Speaker 2: This is from a rally in twenty twenty two, basically 97 00:05:40,240 --> 00:05:43,080 Speaker 2: Trump saying he gets to wear the free speech crown. 98 00:05:43,320 --> 00:05:46,200 Speaker 2: He's the guy bringing a public square back to the web. 99 00:05:47,120 --> 00:05:52,720 Speaker 5: I tell you what, Elon, Elon is not going to 100 00:05:52,760 --> 00:05:53,360 Speaker 5: buy Twitter. 101 00:05:54,520 --> 00:05:54,760 Speaker 6: Nah. 102 00:05:54,760 --> 00:05:55,960 Speaker 5: He's a bullshit artist. 103 00:05:56,240 --> 00:05:58,359 Speaker 7: He's got himself a mess, but he's not gonna be 104 00:05:58,400 --> 00:05:58,760 Speaker 7: buying it. 105 00:06:00,000 --> 00:06:00,960 Speaker 6: He'm not going to be buying it. 106 00:06:01,760 --> 00:06:04,640 Speaker 5: Sign up for truth. We love the Truth. 107 00:06:07,920 --> 00:06:10,440 Speaker 2: For almost a year after Elon lennonim back on Twitter, 108 00:06:10,720 --> 00:06:14,960 Speaker 2: Trump's account was silent, but then August twenty fifth, twenty 109 00:06:15,000 --> 00:06:18,760 Speaker 2: twenty three, Trump makes his comeback. It's a photo of 110 00:06:18,800 --> 00:06:23,640 Speaker 2: his mugshot. Elon knows Trump tweeting again is very good 111 00:06:23,640 --> 00:06:27,359 Speaker 2: for business. He retweets it. Quote next level. 112 00:06:27,880 --> 00:06:31,080 Speaker 4: You recently met with Donald Trump in Florida. What did 113 00:06:31,160 --> 00:06:31,960 Speaker 4: you guys talk about? 114 00:06:33,200 --> 00:06:35,080 Speaker 2: I was at a I was not done. 115 00:06:35,120 --> 00:06:37,240 Speaker 8: I was at a breakfast at a friend's place and 116 00:06:37,360 --> 00:06:38,279 Speaker 8: Donald Trump came by. 117 00:06:38,480 --> 00:06:38,880 Speaker 4: That's it. 118 00:06:39,240 --> 00:06:42,360 Speaker 2: Eight months later, Elon interviewed by Don Lemon. 119 00:06:42,640 --> 00:06:44,560 Speaker 9: So you didn't go there to meet him? 120 00:06:45,200 --> 00:06:49,160 Speaker 8: No, I went to a friend of mine's house and said, 121 00:06:49,400 --> 00:06:50,760 Speaker 8: Donald Trump's coming by for breakfast? 122 00:06:50,880 --> 00:06:51,120 Speaker 6: Is that. 123 00:06:52,800 --> 00:06:53,200 Speaker 5: Just so you know? 124 00:06:53,320 --> 00:06:53,400 Speaker 4: Like? 125 00:06:53,480 --> 00:06:57,440 Speaker 2: Okay? Fine? By the way, at this point, Trump was 126 00:06:57,480 --> 00:07:00,480 Speaker 2: way behind Biden in the money race. She Elon had 127 00:07:00,480 --> 00:07:05,240 Speaker 2: plenty of Now Trump needed Elon too. Here's the thing. 128 00:07:05,880 --> 00:07:09,640 Speaker 2: Elon may be rich, but he's also cheap. And nobody 129 00:07:09,640 --> 00:07:14,400 Speaker 2: in Washington was expecting him to give money to anyone really. 130 00:07:14,720 --> 00:07:17,320 Speaker 4: And that's what really matters to Republicans in Washington. 131 00:07:17,680 --> 00:07:21,720 Speaker 2: Josh Green, my colleague at Bloomberg BusinessWeek, he covers politics. 132 00:07:22,080 --> 00:07:24,559 Speaker 4: If you're a big capitalist, are you willing to stroke 133 00:07:24,600 --> 00:07:28,600 Speaker 4: a big check to Republicans? And Elon never was. Elon 134 00:07:28,720 --> 00:07:31,240 Speaker 4: Musk talks a big game, but he's never going to 135 00:07:31,280 --> 00:07:39,960 Speaker 4: stroke a check, and therefore nobody really cared about him. 136 00:07:40,160 --> 00:07:40,920 Speaker 10: Good afternoon. 137 00:07:41,520 --> 00:07:43,280 Speaker 2: Then everything changed. 138 00:07:43,680 --> 00:07:47,240 Speaker 10: Last night I spoke with Donald Trump. I'm so surely 139 00:07:47,320 --> 00:07:52,040 Speaker 10: grateful that he's doing well and recovering an assassination attempt 140 00:07:52,280 --> 00:07:55,400 Speaker 10: is contrary to everything we stand for as a nation. Everything. 141 00:07:55,760 --> 00:07:59,120 Speaker 2: Elon experienced the attempt on Donald Trump's life pretty much 142 00:07:59,160 --> 00:08:02,520 Speaker 2: like the rest of us. Online, he saw the photos 143 00:08:02,560 --> 00:08:06,080 Speaker 2: on social media Trump at the rally, Trump bleeding, or 144 00:08:06,120 --> 00:08:11,160 Speaker 2: Trump's fist in the air shouting fight, fight fight. Thirty 145 00:08:11,200 --> 00:08:15,680 Speaker 2: minutes later, Elon tweets quote, I fully endorse President Trump 146 00:08:15,680 --> 00:08:19,920 Speaker 2: and hope for his rapid recovery. Soon after, Elon announces 147 00:08:19,960 --> 00:08:24,120 Speaker 2: he's creating his own super pack for Trump, meaning a great, 148 00:08:24,400 --> 00:08:29,440 Speaker 2: big check just like that. Elon's a player in Washington, DC. 149 00:08:33,120 --> 00:08:33,960 Speaker 9: And you know Elon. 150 00:08:34,120 --> 00:08:36,079 Speaker 7: I love Elon MUNKK do we love him? 151 00:08:36,120 --> 00:08:37,880 Speaker 5: I love Elon. 152 00:08:39,000 --> 00:08:40,520 Speaker 7: Endorsed me at the end of the day, and I 153 00:08:40,600 --> 00:08:42,559 Speaker 7: read I didn't even know this, he didn't even tell 154 00:08:42,600 --> 00:08:47,600 Speaker 7: me about it. But he gives me forty five million 155 00:08:47,679 --> 00:08:48,559 Speaker 7: dollars a month. 156 00:08:49,800 --> 00:08:54,360 Speaker 5: A month, not forty five million. Gives me forty five 157 00:08:54,480 --> 00:08:55,320 Speaker 5: million a month. 158 00:08:55,800 --> 00:08:58,120 Speaker 7: And I talked to him just a little while ago 159 00:08:58,240 --> 00:09:00,920 Speaker 7: to say I was coming here, how you doing? And 160 00:09:01,200 --> 00:09:04,120 Speaker 7: he didn't even mention it. He didn't mention. I mean, 161 00:09:04,160 --> 00:09:06,000 Speaker 7: other guys, they give you two dollars and you got 162 00:09:06,000 --> 00:09:08,120 Speaker 7: to take them to lunch. You gotta wind up Diamond. 163 00:09:08,760 --> 00:09:11,000 Speaker 2: That's from a Trump rally in July. And if you 164 00:09:11,000 --> 00:09:14,600 Speaker 2: think this feels like a departure from Nah, he's artist 165 00:09:15,000 --> 00:09:23,520 Speaker 2: will buckle up to start Elon's tweets. They've gone from 166 00:09:23,800 --> 00:09:26,600 Speaker 2: I fully endorse Trump to saying that there won't be 167 00:09:26,679 --> 00:09:30,200 Speaker 2: in America if Trump loses, to saying that humanity will 168 00:09:30,200 --> 00:09:33,720 Speaker 2: never reach the stars without having a president Donald Trump 169 00:09:33,720 --> 00:09:37,520 Speaker 2: a second time. Then there was Elon's two hour live 170 00:09:37,679 --> 00:09:38,839 Speaker 2: interview of Trump on. 171 00:09:39,000 --> 00:09:42,440 Speaker 7: X you have definitely got a fertile mind. 172 00:09:42,920 --> 00:09:43,840 Speaker 9: We can talk about. 173 00:09:43,600 --> 00:09:45,520 Speaker 7: Tuddles and rockets, so many things. 174 00:09:45,880 --> 00:09:48,559 Speaker 2: Then the ads paid for by Elon's pack. 175 00:09:48,840 --> 00:09:52,040 Speaker 4: Trump is the American badass, will stop this nonsense. 176 00:09:52,679 --> 00:09:56,120 Speaker 2: When Trump returned to Butler, Pennsylvania, where the summer's assassination 177 00:09:56,160 --> 00:09:59,680 Speaker 2: attempt happened, Elon went there too. He jumped up and 178 00:09:59,720 --> 00:10:02,400 Speaker 2: down like a kid in a bouncy castle and then 179 00:10:02,440 --> 00:10:06,920 Speaker 2: delivered this kind of halting speech with sentences like bye bye. 180 00:10:06,840 --> 00:10:09,160 Speaker 5: Bute and blood coming down the place. 181 00:10:10,040 --> 00:10:13,960 Speaker 2: Two days later, he offered actual payouts to anyone willing 182 00:10:14,000 --> 00:10:17,480 Speaker 2: to refer potential voters in swing states. At first, he 183 00:10:17,520 --> 00:10:20,040 Speaker 2: said he'd pay forty seven dollars because Trump would be 184 00:10:20,040 --> 00:10:22,520 Speaker 2: the forty seven president. Then he up to two one 185 00:10:22,600 --> 00:10:25,800 Speaker 2: hundred dollars. There was no good reason for that. It's 186 00:10:25,840 --> 00:10:28,400 Speaker 2: just a bigger number. And then. 187 00:10:29,640 --> 00:10:34,680 Speaker 8: I have a surprise for you, which is that we 188 00:10:34,720 --> 00:10:41,200 Speaker 8: are going to be awarding a million dollars to randomly 189 00:10:41,320 --> 00:10:43,839 Speaker 8: to people who have signed signed the petition. 190 00:10:44,960 --> 00:10:45,920 Speaker 4: Every day. 191 00:10:47,240 --> 00:10:49,040 Speaker 8: From now until the election. 192 00:10:49,960 --> 00:10:54,360 Speaker 2: What Elon's doing here, it's probably illegal. The government bans 193 00:10:54,440 --> 00:10:57,880 Speaker 2: vote buying, including by way of lottery, But for Elon, 194 00:10:58,320 --> 00:10:59,199 Speaker 2: that's sort of the point. 195 00:10:59,280 --> 00:11:01,440 Speaker 8: You know. One of the challenges we're having is like, well, 196 00:11:01,480 --> 00:11:03,760 Speaker 8: how do we get people to know about this petition? 197 00:11:04,280 --> 00:11:07,480 Speaker 8: Because the legacy media is one to report on it, 198 00:11:08,240 --> 00:11:12,640 Speaker 8: you know, not everyone's on X So So I figure, 199 00:11:13,320 --> 00:11:14,959 Speaker 8: how do we get people to know about it? Well, 200 00:11:15,200 --> 00:11:17,360 Speaker 8: this news, I think is going to really fly. 201 00:11:18,400 --> 00:11:20,600 Speaker 2: It's easy to see this as a gimmick or a 202 00:11:20,640 --> 00:11:23,760 Speaker 2: marketing stunt, but by now the money that Elon is 203 00:11:23,800 --> 00:11:27,320 Speaker 2: throwing around is starting to add up. Actually in every way, 204 00:11:27,640 --> 00:11:31,079 Speaker 2: these two guys kind of hated each other before are 205 00:11:31,120 --> 00:11:32,240 Speaker 2: now on the same team. 206 00:11:32,600 --> 00:11:36,120 Speaker 4: I mean, to me, the reason that I always thought 207 00:11:36,160 --> 00:11:38,160 Speaker 4: that Elon and Trump would never get together, and to 208 00:11:38,240 --> 00:11:41,400 Speaker 4: be clear, I was very wrong about this was that 209 00:11:41,440 --> 00:11:46,000 Speaker 4: they're both these kind of alpha male narcissists who always 210 00:11:46,040 --> 00:11:48,400 Speaker 4: want all the attention to be about them. 211 00:11:48,800 --> 00:11:51,520 Speaker 2: Josh Green again, it just didn't seem like it could happen, 212 00:11:51,600 --> 00:11:52,320 Speaker 2: and yet it has. 213 00:11:53,120 --> 00:11:55,080 Speaker 4: I think the two of them kind of vibe off 214 00:11:55,080 --> 00:11:58,520 Speaker 4: each other in the sense that they both feel persecuted 215 00:11:58,559 --> 00:12:01,920 Speaker 4: by mainstream media and the popular culture. They're mad, They're 216 00:12:01,920 --> 00:12:04,040 Speaker 4: not going to take it anymore. They're going to gleefully 217 00:12:04,080 --> 00:12:05,120 Speaker 4: attack their enemies. 218 00:12:05,880 --> 00:12:09,520 Speaker 2: Suddenly, Elon, who just to remind you, world's riches man 219 00:12:09,720 --> 00:12:12,680 Speaker 2: two hundred million Twitter followers, becomes one of the most 220 00:12:12,679 --> 00:12:16,680 Speaker 2: important political actors, a guy who actually might swing an election. 221 00:12:17,120 --> 00:12:18,920 Speaker 9: You have donors that just want to give money, they 222 00:12:18,960 --> 00:12:20,960 Speaker 9: care about a cause. They will cut the check. 223 00:12:21,280 --> 00:12:24,079 Speaker 2: Matt Askowski is a political marketer. He worked on the 224 00:12:24,160 --> 00:12:25,280 Speaker 2: last two Trump campaigns. 225 00:12:25,559 --> 00:12:27,280 Speaker 9: They will give it to a group or a cause 226 00:12:27,360 --> 00:12:29,760 Speaker 9: they support, and what happens to the money kind of 227 00:12:29,800 --> 00:12:33,079 Speaker 9: becomes irrelevant to them because they supported the cause. I 228 00:12:33,120 --> 00:12:35,400 Speaker 9: would say Elon looks to be on the opposite side 229 00:12:35,400 --> 00:12:38,439 Speaker 9: of the spectrum where he's giving means, but he's also 230 00:12:38,520 --> 00:12:41,079 Speaker 9: activist where he's actually involved with how the money is 231 00:12:41,080 --> 00:12:42,480 Speaker 9: spent and it's being deployed. 232 00:12:42,920 --> 00:12:46,360 Speaker 2: What Matt's good at is using data, especially to reach 233 00:12:46,400 --> 00:12:50,240 Speaker 2: people on the Internet. Elon is, of course on Matt's radar. 234 00:12:50,960 --> 00:12:55,320 Speaker 2: His world runs on campaign contributions, specifically the big checks. 235 00:12:56,360 --> 00:12:58,959 Speaker 2: As of the middle of October, Elon's given one hundred 236 00:12:58,960 --> 00:13:01,320 Speaker 2: and thirty two million dollar, most of it to his 237 00:13:01,360 --> 00:13:05,200 Speaker 2: America Pack. He's undeniably one of the biggest donors. 238 00:13:05,600 --> 00:13:08,280 Speaker 9: It seems like America Pack is largely focused on the 239 00:13:08,320 --> 00:13:13,160 Speaker 9: political operation canvassing, door knocking, phone calls, phone baking, those 240 00:13:13,200 --> 00:13:16,079 Speaker 9: types of things, GOOTV and turnout GOOTV. 241 00:13:16,400 --> 00:13:17,600 Speaker 2: That's get out the vote. 242 00:13:17,720 --> 00:13:21,240 Speaker 9: Usually the pack model is use soft dollars to raise 243 00:13:21,240 --> 00:13:23,199 Speaker 9: a bunch of big checks to be able to buy media. 244 00:13:23,440 --> 00:13:25,760 Speaker 9: It's we're gonna buy TV, We're gonna buy digitalized and 245 00:13:25,800 --> 00:13:27,000 Speaker 9: buy mail and things like that. 246 00:13:27,400 --> 00:13:27,959 Speaker 8: But this is. 247 00:13:27,920 --> 00:13:29,680 Speaker 9: Almost like a quasi campaign. 248 00:13:29,679 --> 00:13:34,000 Speaker 2: Outside of the campaign, Elon micromanages. He's proud of it. 249 00:13:34,200 --> 00:13:36,840 Speaker 2: So that's how he's running his pack. At the start, 250 00:13:36,880 --> 00:13:39,959 Speaker 2: he hired a few hundred canvassers, folks who go door 251 00:13:40,000 --> 00:13:42,520 Speaker 2: to door trying to convince regular people to vote for 252 00:13:42,559 --> 00:13:46,360 Speaker 2: their candidate. Then something happened that annoyed Elon, so he 253 00:13:46,400 --> 00:13:48,679 Speaker 2: fired a bunch of them. Then he brought on an 254 00:13:48,840 --> 00:13:51,400 Speaker 2: entirely new team and fired a bunch of them too. 255 00:13:52,760 --> 00:13:56,960 Speaker 2: Still it seems to be working. Matt says. Most canvassing 256 00:13:57,000 --> 00:14:00,839 Speaker 2: operations take years to assemble, built one in just a 257 00:14:00,880 --> 00:14:05,160 Speaker 2: few months. His specific target younger men in swing states. 258 00:14:05,840 --> 00:14:08,480 Speaker 2: Now he's got an office set up in Pennsylvania, the 259 00:14:08,559 --> 00:14:11,440 Speaker 2: swing state he said he's specifically focusing his attention on. 260 00:14:12,160 --> 00:14:15,280 Speaker 2: He's even sort of stumping, traveling from town to town 261 00:14:15,360 --> 00:14:19,960 Speaker 2: giving talks to voters. By the way, whatever his politics 262 00:14:19,960 --> 00:14:25,160 Speaker 2: were before, Elon's politics right now largely mirror Trumps across 263 00:14:25,200 --> 00:14:31,560 Speaker 2: the board, immigration, gender, voter rights, the environment. In those 264 00:14:31,600 --> 00:14:36,440 Speaker 2: ways and so many others, he's fallen in line. Let's 265 00:14:36,480 --> 00:14:38,840 Speaker 2: step back for a second and answer the question at 266 00:14:38,840 --> 00:14:42,800 Speaker 2: the heart of this Why Why is Elon, who has 267 00:14:42,840 --> 00:14:45,960 Speaker 2: six companies and at least twelve kids, spending all of 268 00:14:46,000 --> 00:14:49,360 Speaker 2: this time and money on Trump? What does he stand? Again? 269 00:14:53,240 --> 00:14:57,760 Speaker 2: Elon's a defense contractor SpaceX his rocket company. They already 270 00:14:57,800 --> 00:15:02,760 Speaker 2: have huge contracts with the US government. Elon wants more. Specifically, 271 00:15:02,960 --> 00:15:05,280 Speaker 2: he's gunning for NASA to spend tens of billions of 272 00:15:05,320 --> 00:15:06,800 Speaker 2: dollars on his Mars colony. 273 00:15:07,120 --> 00:15:10,320 Speaker 7: Elon get those rocket ships going because we want to 274 00:15:10,400 --> 00:15:13,280 Speaker 7: reach Mars before the end of my term. We want 275 00:15:13,280 --> 00:15:16,680 Speaker 7: to do it, and we want to have also great 276 00:15:16,960 --> 00:15:20,000 Speaker 7: military protection in space because that's where it's going to 277 00:15:20,040 --> 00:15:20,440 Speaker 7: be at. 278 00:15:21,040 --> 00:15:23,880 Speaker 2: Right now, the government's likely to spread the workout across 279 00:15:23,920 --> 00:15:29,440 Speaker 2: a bunch of different defense contractors Boeing, Lockheed Martin, Northrop Grumman. 280 00:15:30,360 --> 00:15:32,240 Speaker 2: But Trump could decide to throw a bunch of business 281 00:15:32,240 --> 00:15:37,160 Speaker 2: to SpaceX instead. Also, SpaceX has this side business it's 282 00:15:37,160 --> 00:15:41,120 Speaker 2: called Starlink. Elon's long wanted the government to pay Starlink 283 00:15:41,280 --> 00:15:44,640 Speaker 2: to provide internet to rural areas, to get subsidies that 284 00:15:44,640 --> 00:15:47,600 Speaker 2: the government already has, but to direct them to him. 285 00:15:47,760 --> 00:15:51,800 Speaker 2: Starlink has struck out so far, but under another Trump presidency, 286 00:15:52,280 --> 00:15:56,200 Speaker 2: maybe we'ld have more of a chance. Second, Tesla's trying 287 00:15:56,200 --> 00:16:00,960 Speaker 2: to develop these autonomous cars driverless robotaxis. Trump could help 288 00:16:01,000 --> 00:16:05,800 Speaker 2: get those approved and potentially block Tesla's Chinese competitors from 289 00:16:05,880 --> 00:16:07,880 Speaker 2: offering their robotaxis in the US. 290 00:16:08,280 --> 00:16:14,120 Speaker 6: I will stop Chinese and other countries produced audible, bial 291 00:16:14,280 --> 00:16:18,480 Speaker 6: and autonomous vehicles. Do you like autonomous? Does anybody like 292 00:16:18,480 --> 00:16:19,760 Speaker 6: an autonomous vehicle. 293 00:16:20,840 --> 00:16:23,840 Speaker 2: Third, Trump could give Elon a job, and not just 294 00:16:23,920 --> 00:16:24,480 Speaker 2: any job. 295 00:16:24,920 --> 00:16:26,400 Speaker 8: I mean, I think it would be great to just 296 00:16:26,440 --> 00:16:29,760 Speaker 8: have a government efficiency commission that ensures that the taxpayer money, 297 00:16:30,480 --> 00:16:33,840 Speaker 8: the taxpayers are harder money, is spent in a good way. 298 00:16:35,200 --> 00:16:38,120 Speaker 8: And I'd be happy to help out on such a commission. 299 00:16:38,160 --> 00:16:38,800 Speaker 4: I'd love it. 300 00:16:39,440 --> 00:16:42,040 Speaker 9: Well, you you're the greatest cutter. I mean, I look 301 00:16:42,080 --> 00:16:42,640 Speaker 9: at what you do. 302 00:16:42,720 --> 00:16:46,520 Speaker 2: You walk in during the Twitter spaces interview, and I'm 303 00:16:46,520 --> 00:16:49,640 Speaker 2: the stump. Trump said Elon will be in charge of 304 00:16:49,680 --> 00:16:53,960 Speaker 2: streamlining the government, which, among other things, means he'll be 305 00:16:53,960 --> 00:16:57,120 Speaker 2: the one to decide which government programs get cut in 306 00:16:57,200 --> 00:17:01,440 Speaker 2: which stay. I don't think Elon wants another job, but 307 00:17:01,520 --> 00:17:04,520 Speaker 2: there are lots of federal agencies that are investigating him 308 00:17:04,640 --> 00:17:07,359 Speaker 2: right now, and the simplest way to resist some of 309 00:17:07,400 --> 00:17:10,960 Speaker 2: these investigations would probably just be to defund those agencies. 310 00:17:12,560 --> 00:17:14,720 Speaker 2: In short, it'd be the most powerful guy in the 311 00:17:14,760 --> 00:17:17,560 Speaker 2: world in the pocket of the richest guy in the world. 312 00:17:18,280 --> 00:17:20,959 Speaker 2: I can't express enough what a big deal that would be. 313 00:17:22,000 --> 00:17:24,240 Speaker 1: Fuck, dude, if you lose. 314 00:17:26,000 --> 00:17:30,200 Speaker 5: It does seem that way. You can't just be like like, yeah, 315 00:17:30,320 --> 00:17:32,639 Speaker 5: I'm like, how long do you think my prison sentence 316 00:17:32,680 --> 00:17:35,600 Speaker 5: is going to be well, I see my children. 317 00:17:35,680 --> 00:17:38,160 Speaker 8: I don't know, because it's not like you can say, well, yeah, 318 00:17:38,160 --> 00:17:39,080 Speaker 8: I maxed out to him. 319 00:17:39,119 --> 00:17:43,720 Speaker 2: But you know, I get This is from an interview 320 00:17:43,760 --> 00:17:47,119 Speaker 2: Elon did with Tucker Carlson in October. It made me 321 00:17:47,160 --> 00:17:50,719 Speaker 2: think maybe Elon's got no choice now that he's back Trump. 322 00:17:51,920 --> 00:17:55,760 Speaker 2: Maybe he's afraid that if Kamala Harris wins, she would 323 00:17:55,760 --> 00:18:02,240 Speaker 2: have him punished. At the same time, skeptical for starters, 324 00:18:02,520 --> 00:18:07,000 Speaker 2: nobody's talking about retribution or about Elon's rifle place in jail. 325 00:18:07,760 --> 00:18:10,879 Speaker 2: I think maybe he's trying to distract folks from what 326 00:18:10,920 --> 00:18:15,680 Speaker 2: Trump's actually saying and raise himself up as a Maga martyr. 327 00:18:16,119 --> 00:18:20,520 Speaker 2: But no matter what, if Trump loses the election, so 328 00:18:20,640 --> 00:18:28,560 Speaker 2: does Elon. We've been talking a lot about traditional politics, money, speeches, 329 00:18:28,760 --> 00:18:32,639 Speaker 2: canvassing ads, But there's another way Elon's helped Trump that 330 00:18:32,680 --> 00:18:36,240 Speaker 2: I'd argue is a lot more important. I keep thinking 331 00:18:36,280 --> 00:18:39,959 Speaker 2: about something Joan said about the aftermath of Elon buying Twitter, 332 00:18:40,480 --> 00:18:44,399 Speaker 2: a bunch of users leaving the platform, advertisers cutting ties. 333 00:18:45,000 --> 00:18:48,639 Speaker 3: His attitude was, you know, goodbye, and then of course 334 00:18:48,680 --> 00:18:52,360 Speaker 3: he brought back in all of the folks that had 335 00:18:52,400 --> 00:18:54,480 Speaker 3: been removed previously. 336 00:18:55,480 --> 00:18:58,520 Speaker 2: The thing is, just because Elon's era of Twitter is 337 00:18:58,600 --> 00:19:02,000 Speaker 2: less successful in business to doesn't mean it's not still 338 00:19:02,040 --> 00:19:03,560 Speaker 2: powerful or dangerous. 339 00:19:04,080 --> 00:19:05,840 Speaker 3: You know, we're not going to code it as a 340 00:19:05,880 --> 00:19:11,560 Speaker 3: campaign contribution to Trump, but it certainly was. He understood, 341 00:19:12,400 --> 00:19:20,160 Speaker 3: perhaps more than most, that communication tools are weapons of war, 342 00:19:21,000 --> 00:19:27,359 Speaker 3: and he has now the largest psychological weapon that the 343 00:19:27,400 --> 00:19:31,120 Speaker 3: world may have ever known. You can really change how 344 00:19:31,160 --> 00:19:34,560 Speaker 3: an entire society sees itself. 345 00:19:35,280 --> 00:19:37,840 Speaker 2: Time and again, Twitter has proven to be a massively 346 00:19:37,840 --> 00:19:42,600 Speaker 2: effective tool of communication and organization. Just because advertisers don't 347 00:19:42,600 --> 00:19:44,480 Speaker 2: want any part of it, or because there are fewer 348 00:19:44,480 --> 00:19:47,960 Speaker 2: people tweeting, doesn't mean it's not still happening. It doesn't 349 00:19:48,000 --> 00:19:48,840 Speaker 2: mean it doesn't matter. 350 00:19:49,400 --> 00:19:52,000 Speaker 3: In my world. I have to do what I call 351 00:19:52,160 --> 00:19:57,080 Speaker 3: doom scaping. I have to think about every possible outcome 352 00:19:57,520 --> 00:20:02,800 Speaker 3: there is, including Musk pulling a Trump. This is the 353 00:20:02,920 --> 00:20:06,000 Speaker 3: type of guy who if he starts to feel as 354 00:20:06,040 --> 00:20:09,960 Speaker 3: if something has gone wrong. Imagine if he believes the 355 00:20:10,000 --> 00:20:14,920 Speaker 3: twenty twenty four election is rigged, he could start a 356 00:20:14,960 --> 00:20:19,879 Speaker 3: civil war. And you know, we're loading up the flame throwers. 357 00:20:19,960 --> 00:20:22,360 Speaker 3: We're going mad Max style to the Capitol. 358 00:20:22,960 --> 00:20:26,159 Speaker 2: Since leaving Facebook, Katie Harbeth told me she's been a 359 00:20:26,200 --> 00:20:30,640 Speaker 2: consultant basically advising tech companies on how to avoid accidentally 360 00:20:30,640 --> 00:20:33,120 Speaker 2: promoting disinformation or political violence. 361 00:20:33,640 --> 00:20:36,720 Speaker 1: One of the scenarios that we've been thinking through is like, 362 00:20:37,400 --> 00:20:40,359 Speaker 1: you know what if somebody has this video part AI 363 00:20:40,480 --> 00:20:43,720 Speaker 1: generated of something nefarious is happening at a polling place, 364 00:20:43,760 --> 00:20:46,080 Speaker 1: whether it's around the counting of votes or something like that. 365 00:20:47,560 --> 00:20:51,240 Speaker 2: One example, at the last presidential debate, Trump made a 366 00:20:51,280 --> 00:20:55,639 Speaker 2: debunked claim about Haitians eating people's pets, and just before 367 00:20:55,680 --> 00:20:58,359 Speaker 2: the debate, Elon had tweeted out the same thing to 368 00:20:58,480 --> 00:21:00,000 Speaker 2: his two hundred million followers. 369 00:21:00,400 --> 00:21:03,439 Speaker 1: We saw the Haitian immigrants eating dogs in Ohio. It 370 00:21:03,480 --> 00:21:06,800 Speaker 1: doesn't take very long for that to get amplified by others. 371 00:21:07,119 --> 00:21:09,000 Speaker 1: The thing I am most worried about, and I think 372 00:21:09,040 --> 00:21:12,920 Speaker 1: is most important, is us protecting trust in the actual 373 00:21:12,960 --> 00:21:17,120 Speaker 1: process of conducting elections and people trusting that their vote 374 00:21:17,119 --> 00:21:19,879 Speaker 1: counted and that those votes were counted fairly, even if 375 00:21:19,920 --> 00:21:21,800 Speaker 1: they disagree with the outcome. 376 00:21:22,359 --> 00:21:26,080 Speaker 2: This isn't some theoretical issue. It's a thing that's already happened, 377 00:21:26,320 --> 00:21:28,760 Speaker 2: that is happening now in some of the most closely 378 00:21:28,800 --> 00:21:33,960 Speaker 2: contested precincts in America. Neil mckijah chairs the Board of 379 00:21:33,960 --> 00:21:38,160 Speaker 2: Elections in Montgomery County in Pennsylvania. It's not far from Philadelphia, 380 00:21:39,000 --> 00:21:41,560 Speaker 2: Neil says, the most important message he wants out there 381 00:21:42,280 --> 00:21:45,080 Speaker 2: the thing he wishes more people understood and believed. 382 00:21:45,600 --> 00:21:51,560 Speaker 11: People don't realize how safe, how secure our elections actually are, but. 383 00:21:51,560 --> 00:21:54,560 Speaker 2: The amount of miss and disinformation it's hard to keep 384 00:21:54,640 --> 00:21:57,679 Speaker 2: up with. Back in twenty twenty one, right after the 385 00:21:57,680 --> 00:22:01,200 Speaker 2: attacks on the capital, the local Democratic Party committee received 386 00:22:01,200 --> 00:22:03,919 Speaker 2: a letter from somebody complaining the election had been stolen. 387 00:22:04,600 --> 00:22:07,119 Speaker 2: The letter made it clear something bad was going to happen. 388 00:22:08,200 --> 00:22:11,240 Speaker 2: Then two weeks later, three shots were fired through a 389 00:22:11,280 --> 00:22:14,239 Speaker 2: window at the party's office just across the street from 390 00:22:14,280 --> 00:22:16,040 Speaker 2: where Neil works today. 391 00:22:17,000 --> 00:22:19,919 Speaker 11: Thankfully no one was in the office when the shots 392 00:22:19,920 --> 00:22:26,360 Speaker 11: were fired into it, but it showed us that disinformation 393 00:22:26,480 --> 00:22:30,000 Speaker 11: can lead to violence. You may have clear moments like that, 394 00:22:30,560 --> 00:22:33,560 Speaker 11: you know, essentially a redocs of January sixth, where people 395 00:22:33,640 --> 00:22:35,959 Speaker 11: tried to disrupt the process, and that could be at 396 00:22:35,960 --> 00:22:38,720 Speaker 11: the polling places, it could be at the transition of power. 397 00:22:42,359 --> 00:22:43,080 Speaker 11: I think. 398 00:22:46,880 --> 00:22:50,280 Speaker 2: Neil seemed nervous throughout our call. That popping sound in 399 00:22:50,320 --> 00:22:53,640 Speaker 2: the background it was him clicking his pen over and over, 400 00:22:53,880 --> 00:22:54,679 Speaker 2: faster and faster. 401 00:22:55,840 --> 00:23:01,680 Speaker 11: I think people who perpetuated the lies certainly bear responsibility 402 00:23:01,720 --> 00:23:04,720 Speaker 11: if they should have known better, and I think certainly 403 00:23:04,720 --> 00:23:06,160 Speaker 11: Elon Musk should know better. 404 00:23:08,680 --> 00:23:11,119 Speaker 2: As you try to do your job, what are you 405 00:23:11,119 --> 00:23:12,440 Speaker 2: most worried about? 406 00:23:16,240 --> 00:23:19,800 Speaker 11: You're so yeah, you're asking these great question. So I'm 407 00:23:19,800 --> 00:23:20,360 Speaker 11: just kidding. 408 00:23:21,960 --> 00:23:23,880 Speaker 2: Tell me why I made you Why you laughed there. 409 00:23:25,240 --> 00:23:27,800 Speaker 11: Because I'm like, you're just like, if I thought about 410 00:23:27,840 --> 00:23:29,520 Speaker 11: what I'm worried about all day, I would not be able. 411 00:23:29,400 --> 00:23:30,080 Speaker 9: To do this job. 412 00:23:30,960 --> 00:23:33,040 Speaker 2: Neil's one of the most polished people I spoke with 413 00:23:33,080 --> 00:23:36,199 Speaker 2: for this show, which makes sense. His job is to 414 00:23:36,240 --> 00:23:40,200 Speaker 2: instill calm, to remind folks that voting is safe. What 415 00:23:40,240 --> 00:23:42,960 Speaker 2: that also means is he's got the most to lose. 416 00:23:49,000 --> 00:23:51,600 Speaker 2: It's easy in the heat of a campaign to miss 417 00:23:51,640 --> 00:23:55,199 Speaker 2: the forest for the trees. But of course, none of 418 00:23:55,200 --> 00:23:59,200 Speaker 2: this ends on November fifth. If anything, November fifth is 419 00:23:59,240 --> 00:24:02,920 Speaker 2: when it begins. Elon and Trump are ready to either 420 00:24:03,040 --> 00:24:06,480 Speaker 2: overhaul the US government or to say the election was stolen, 421 00:24:06,800 --> 00:24:10,359 Speaker 2: that America as we know it is dead, and Elon 422 00:24:10,480 --> 00:24:15,240 Speaker 2: pulling back further and further on content moderation. It's his 423 00:24:15,359 --> 00:24:20,240 Speaker 2: call to arms. He's gathering the troops for what we 424 00:24:20,280 --> 00:24:27,960 Speaker 2: won't know until November fifth. That's next time. Citizen Elon 425 00:24:28,080 --> 00:24:31,679 Speaker 2: is produced by Lina Mesitzi's Rayhan Harmanci is our senior editor, 426 00:24:32,040 --> 00:24:36,719 Speaker 2: Blake Maples handles engineering and William Elstrom fact checking. Brendan 427 00:24:36,720 --> 00:24:39,960 Speaker 2: Francis Newnham is our executive producer. Sage Bauman is the 428 00:24:39,960 --> 00:24:43,280 Speaker 2: head of Bloomberg Podcasts. Big thanks to the Elon and Crewe, 429 00:24:43,720 --> 00:24:49,120 Speaker 2: David Papadopolis, Naomi Shaven, Mangus Hendrickson, Stacy Wong listen every 430 00:24:49,160 --> 00:24:53,480 Speaker 2: Tuesday for breaking Elon news, and thanks to our Bloomberg 431 00:24:53,480 --> 00:24:58,160 Speaker 2: colleagues David Fox, Julia Press, Dana Hull, Sarah Fryar, Kurt Wagner, 432 00:24:58,400 --> 00:25:03,560 Speaker 2: Mark Millian, Becca Greenfe, Margaret Sutherland, Alison Mobley, Jackie Kessler, 433 00:25:03,720 --> 00:25:08,320 Speaker 2: Ariel Brown, Chris Nescenzo, and Albert Hicks. An extra big 434 00:25:08,320 --> 00:25:11,640 Speaker 2: thanks to Bradstone, editor of BusinessWeek, and Katie Boyce, executive 435 00:25:11,720 --> 00:25:15,560 Speaker 2: editor of Bloomberg Digital, for their unflagging support. We'll see 436 00:25:15,560 --> 00:25:18,080 Speaker 2: you after the election for Part three of Citizen Elon. 437 00:25:18,960 --> 00:25:21,199 Speaker 2: I'm Max Chafkin. If you have a minute, rate and 438 00:25:21,240 --> 00:25:25,600 Speaker 2: review our show, it'll help other listeners find us. Thanks again,