1
00:00:03,080 --> 00:00:07,440
Speaker 1: Bloomberg Audio Studios, podcasts, radio news.

2
00:00:09,560 --> 00:00:16,040
Speaker 2: Ladies and gentlemen, please welcome President elect Donald J. Trump,

3
00:00:16,600 --> 00:00:20,800
Speaker 2: First Lady Melaia Trump, and the Trump family.

4
00:00:21,320 --> 00:00:24,000
Speaker 3: It's around two thirty am, the night of the election,

5
00:00:24,480 --> 00:00:25,680
Speaker 3: West Palm Beach, Florida.

6
00:00:26,640 --> 00:00:27,360
Speaker 4: Well, I want to.

7
00:00:27,360 --> 00:00:28,600
Speaker 5: Thank you all very much.

8
00:00:28,640 --> 00:00:29,360
Speaker 4: This is great.

9
00:00:29,400 --> 00:00:30,320
Speaker 5: These are our friends.

10
00:00:30,400 --> 00:00:32,280
Speaker 4: We have thousands of friends in this.

11
00:00:33,760 --> 00:00:35,239
Speaker 5: Incredible movement.

12
00:00:36,120 --> 00:00:39,440
Speaker 3: Pretty much everyone was expecting a close race, the polls,

13
00:00:39,880 --> 00:00:43,880
Speaker 3: the pundits, even the candidates. But by midnight on the

14
00:00:43,920 --> 00:00:47,199
Speaker 3: East Coast, we more or less new Trump had done it,

15
00:00:47,680 --> 00:00:48,920
Speaker 3: and not just Trump.

16
00:00:50,120 --> 00:00:52,720
Speaker 4: Let me tell you, we have a new star. The

17
00:00:52,880 --> 00:01:00,760
Speaker 4: star is born Nylan noh he is now He's an

18
00:01:00,800 --> 00:01:01,480
Speaker 4: amazing guy.

19
00:01:01,560 --> 00:01:07,120
Speaker 3: By the next morning, it was official. Trump won Wisconsin, Pennsylvania, Michigan,

20
00:01:07,360 --> 00:01:11,520
Speaker 3: North Carolina, Georgia, every swing state but Nevada and Arizona.

21
00:01:12,560 --> 00:01:16,319
Speaker 3: Later that week he'd win those two. Kamala Harris called

22
00:01:16,319 --> 00:01:19,800
Speaker 3: Trump the next morning to congratulate him. Biden called two

23
00:01:20,280 --> 00:01:22,880
Speaker 3: at four pm. Harris gave her concession speech.

24
00:01:31,000 --> 00:01:35,959
Speaker 6: I was relieved and grateful that we had a decision

25
00:01:36,080 --> 00:01:36,800
Speaker 6: so fast.

26
00:01:37,319 --> 00:01:42,399
Speaker 3: Joan Donovan, again journalism professor, disinformation expert, spent a lot

27
00:01:42,440 --> 00:01:46,080
Speaker 3: of time thinking and writing about January sixth of twenty twenty.

28
00:01:46,680 --> 00:01:49,760
Speaker 3: She's been watching Elon Musk plus his army of followers

29
00:01:49,760 --> 00:01:53,680
Speaker 3: and fanboys. In the months before the election, they posted

30
00:01:53,720 --> 00:01:56,760
Speaker 3: so many conspiracy theories Democrats were going to steal the

31
00:01:56,840 --> 00:02:00,960
Speaker 3: vote again. You can't trust the media and trust the polls.

32
00:02:01,200 --> 00:02:04,840
Speaker 3: That anything other than a landslide victory for Trump is fraud.

33
00:02:05,480 --> 00:02:08,240
Speaker 3: And so she figured if Harris wins, or even if

34
00:02:08,240 --> 00:02:12,359
Speaker 3: it's close, Elon could call it fraud. That means violence

35
00:02:12,600 --> 00:02:16,600
Speaker 3: against a poll worker or a poll site or something worse.

36
00:02:17,400 --> 00:02:19,960
Speaker 6: And so it's very difficult to know what they're going

37
00:02:20,040 --> 00:02:25,920
Speaker 6: to do. People are planning different kinds of violence and

38
00:02:25,960 --> 00:02:30,320
Speaker 6: destruction if Trump hadn't won again.

39
00:02:30,720 --> 00:02:35,359
Speaker 3: This wasn't theoretical fear. Post election things are mostly calm.

40
00:02:35,760 --> 00:02:39,360
Speaker 3: Three weeks ago, not so much. Ballot boxes set on

41
00:02:39,400 --> 00:02:44,200
Speaker 3: fire in Washington and Oregon and Arizona, bomb threats called

42
00:02:44,200 --> 00:02:48,480
Speaker 3: into polling places in Georgia and Pennsylvania. Elon tweeting like

43
00:02:48,520 --> 00:02:52,160
Speaker 3: a maniac. Felt like we were in a tinderbox and

44
00:02:52,200 --> 00:02:53,280
Speaker 3: he was holding the match.

45
00:02:53,960 --> 00:02:57,280
Speaker 6: And so at least we know what the outcome is,

46
00:02:57,400 --> 00:03:01,799
Speaker 6: we can accept that outcome and can move forward with

47
00:03:01,840 --> 00:03:06,840
Speaker 6: some social assurances that the election had not been rigged.

48
00:03:07,639 --> 00:03:11,040
Speaker 3: There were so many warnings from both sides, from experts

49
00:03:11,040 --> 00:03:16,600
Speaker 3: like Joan about the future of democracy. But then it worked.

50
00:03:17,200 --> 00:03:20,720
Speaker 3: The person with the most votes won. Like Elon said

51
00:03:20,720 --> 00:03:23,360
Speaker 3: when he brought Trump back on Twitter, the voice of

52
00:03:23,360 --> 00:03:26,240
Speaker 3: the people is the voice of the gods.

53
00:03:27,040 --> 00:03:29,359
Speaker 5: I'm Max Chafkin. This is citizen Elon.

54
00:03:32,000 --> 00:03:37,920
Speaker 3: So we made it post election. Trump definitely won. Something

55
00:03:38,000 --> 00:03:39,120
Speaker 3: else that's indisputable.

56
00:03:39,680 --> 00:03:42,880
Speaker 5: Elon won. How did he get there? How did he

57
00:03:42,960 --> 00:03:44,400
Speaker 5: do it? James?

58
00:03:44,640 --> 00:03:50,640
Speaker 3: Are you there not hearing James from Flat Rocket? On

59
00:03:50,680 --> 00:03:54,000
Speaker 3: November fourth, the night before the election, Elon scheduled one

60
00:03:54,040 --> 00:03:56,480
Speaker 3: of his town halls. It was supposed to be virtual

61
00:03:56,720 --> 00:04:00,320
Speaker 3: and it be live streamed on Twitter as usual. The

62
00:04:00,320 --> 00:04:04,280
Speaker 3: event started late, a few things went wrong. Elon got frustrated.

63
00:04:04,560 --> 00:04:08,920
Speaker 7: You know, I think, let's uh, let's cancel this. Give

64
00:04:09,000 --> 00:04:12,040
Speaker 7: him this in some technical challenges, and.

65
00:04:12,000 --> 00:04:15,080
Speaker 3: He announced instead of this town hall Q and A,

66
00:04:15,520 --> 00:04:17,960
Speaker 3: folks should listen to the interview he'd done that day

67
00:04:18,120 --> 00:04:25,159
Speaker 3: on Joe Rogan's show at two and a half hour podcast.

68
00:04:23,400 --> 00:04:25,200
Speaker 5: Good Joe Wrogan Experience.

69
00:04:25,360 --> 00:04:28,800
Speaker 8: First of all, thank you so much for buying Twitter.

70
00:04:29,000 --> 00:04:31,640
Speaker 8: You're looking so much. I think you changed the course

71
00:04:31,680 --> 00:04:33,080
Speaker 8: of history. I really do.

72
00:04:33,200 --> 00:04:36,239
Speaker 3: If you've ever listened to Rogan, you know the conversations wander.

73
00:04:36,760 --> 00:04:38,240
Speaker 3: They started with video games.

74
00:04:38,240 --> 00:04:41,760
Speaker 8: Surgeons who regularly play video games make less errors.

75
00:04:41,520 --> 00:04:44,800
Speaker 3: How awesome eating meat is, how creatine is good for you.

76
00:04:44,960 --> 00:04:47,880
Speaker 8: Yeah, creatine is actually a neotropic, believe it or not, but.

77
00:04:47,920 --> 00:04:51,440
Speaker 3: Factory farming isn't. And about the exact right dosage of

78
00:04:51,480 --> 00:04:53,040
Speaker 3: amphetamines in higher doses.

79
00:04:53,080 --> 00:04:56,800
Speaker 7: Man, I've seen people turn into just raging monsters. They're

80
00:04:56,839 --> 00:04:59,360
Speaker 7: just angry, like extremely angry all the time.

81
00:04:59,520 --> 00:05:00,920
Speaker 5: Yeah, they're messed up.

82
00:05:01,000 --> 00:05:03,720
Speaker 3: They went through a long list of Elon's grievances, which

83
00:05:03,760 --> 00:05:07,480
Speaker 3: basically boiled down to anything stopping him from making money

84
00:05:08,080 --> 00:05:09,640
Speaker 3: is bad, if not evil.

85
00:05:09,720 --> 00:05:14,120
Speaker 7: They decided SpaceX was a target like Stalin's, like chief Torturer.

86
00:05:14,400 --> 00:05:16,280
Speaker 7: One of his famous quotes was show me the man,

87
00:05:16,320 --> 00:05:17,279
Speaker 7: and I'll show you the crime.

88
00:05:18,120 --> 00:05:21,320
Speaker 3: Right, And eventually they got to the White House Correspondent's

89
00:05:21,360 --> 00:05:26,400
Speaker 3: Dinner twenty eleven. Rogan remembers Obama basically saying Donald Trump,

90
00:05:26,600 --> 00:05:27,560
Speaker 3: you know what, You'll never.

91
00:05:27,440 --> 00:05:28,919
Speaker 5: Be president of the United States.

92
00:05:28,920 --> 00:05:30,440
Speaker 8: You see Trump and the ions going okay, I'm on

93
00:05:30,520 --> 00:05:30,880
Speaker 8: the floor.

94
00:05:31,440 --> 00:05:33,760
Speaker 7: The degree to which they attacked Trump at that whitest

95
00:05:33,760 --> 00:05:36,000
Speaker 7: Correspon Center was really so over the top. It was

96
00:05:36,080 --> 00:05:40,240
Speaker 7: like making everyone uncomfortable. They twisted the knife big on Trump,

97
00:05:40,520 --> 00:05:43,120
Speaker 7: and I was like, man, this is not good karma,

98
00:05:43,240 --> 00:05:43,480
Speaker 7: you know.

99
00:05:44,279 --> 00:05:47,680
Speaker 3: And there it is a shared sense of grievance, humiliation,

100
00:05:48,520 --> 00:05:49,440
Speaker 3: a revenge story.

101
00:05:49,960 --> 00:05:50,880
Speaker 5: Elon and Trump.

102
00:05:51,080 --> 00:05:53,760
Speaker 3: They really are the same person, and Elon seems to

103
00:05:53,760 --> 00:05:57,279
Speaker 3: know it. But then Rogan brought up the impetus Obama

104
00:05:57,360 --> 00:05:59,839
Speaker 3: wasn't roasting Trump for the hell of it. He was

105
00:06:00,000 --> 00:06:04,679
Speaker 3: responding to the literal conspiracy theory Trump successfully spread about

106
00:06:04,680 --> 00:06:07,839
Speaker 3: the president not being born in America. And what's funny

107
00:06:07,960 --> 00:06:11,159
Speaker 3: is Elon went ahead and rewrote history.

108
00:06:11,440 --> 00:06:13,960
Speaker 5: He asked Rogan, was Trump actually saying that.

109
00:06:14,640 --> 00:06:15,680
Speaker 9: No, he definitely was.

110
00:06:15,960 --> 00:06:17,960
Speaker 5: He was definitely saying he's from Kenya.

111
00:06:18,400 --> 00:06:21,080
Speaker 3: Trump, Rogan said, he was actually a victim of a

112
00:06:21,120 --> 00:06:26,440
Speaker 3: busted up information ecosystem, people wanting to manipulate him. Elon,

113
00:06:26,480 --> 00:06:30,520
Speaker 3: though he stayed on message, he turned somberly, looked straight

114
00:06:30,520 --> 00:06:32,960
Speaker 3: into the camera and said, men.

115
00:06:32,800 --> 00:06:36,760
Speaker 7: Need to vote. That is the biggest issue. So I'm

116
00:06:36,800 --> 00:06:38,960
Speaker 7: just like saying, there's a message to the men out there.

117
00:06:39,440 --> 00:06:41,240
Speaker 7: Vote like your life depends on it, because I think

118
00:06:41,240 --> 00:06:44,520
Speaker 7: it does. Vote quote tomorrow like your life depends on it.

119
00:06:44,560 --> 00:06:47,719
Speaker 5: Nothing is more important. Oh.

120
00:06:48,240 --> 00:06:50,960
Speaker 3: For a few hours on election day, it seemed Elon

121
00:06:51,080 --> 00:06:54,680
Speaker 3: worried he'd backed the wrong horse. He was quiet he'd

122
00:06:54,720 --> 00:06:58,880
Speaker 3: gambled so much on Trump. The money, yes, but also

123
00:06:58,920 --> 00:07:04,360
Speaker 3: his reputation. Tesla's customers they're fans of the old Elon Musk,

124
00:07:04,800 --> 00:07:07,640
Speaker 3: not the guy who tweets about immigrants replacing white people.

125
00:07:08,600 --> 00:07:13,920
Speaker 3: Mostly they're Kamala voters. In the late afternoon, Musk voted

126
00:07:13,920 --> 00:07:17,400
Speaker 3: in Brownsville, right on the Mexico border. He posed for

127
00:07:17,440 --> 00:07:20,600
Speaker 3: a photo op, then he got on his plane headed

128
00:07:20,600 --> 00:07:24,280
Speaker 3: to mar A Lago, where Trump was. By eight thirty

129
00:07:24,320 --> 00:07:28,320
Speaker 3: that night, things started leaning in Trump's favor. Elon started

130
00:07:28,320 --> 00:07:32,960
Speaker 3: cracking jokes again on Twitter. Later, a picture began circulating

131
00:07:32,960 --> 00:07:36,920
Speaker 3: from Trump's private watch party in mar A Lago. Three

132
00:07:36,960 --> 00:07:41,160
Speaker 3: men huddled in conversation, Donald Trump, his transition co chair,

133
00:07:41,600 --> 00:07:45,960
Speaker 3: and of course Elon Musk. In the background was a

134
00:07:46,000 --> 00:07:49,280
Speaker 3: CNN screen with the electoral count Trump was winning.

135
00:07:50,120 --> 00:07:52,440
Speaker 10: It's kind of rare for people to change their strikes.

136
00:07:52,960 --> 00:07:55,800
Speaker 3: That's Josh Green again. He works with me at BusinessWeek.

137
00:07:56,680 --> 00:08:01,080
Speaker 3: Josh was skeptical of Elon's commitment to politics, that is,

138
00:08:01,280 --> 00:08:03,720
Speaker 3: before Elon started putting his money where his mouth.

139
00:08:03,640 --> 00:08:06,520
Speaker 10: Was, and the fact that he's kind of rocketed onto

140
00:08:06,560 --> 00:08:10,360
Speaker 10: the scene no pun intended. What's exciting about Trump, at

141
00:08:10,440 --> 00:08:13,200
Speaker 10: least from a journalistic standpoint, is there are always these

142
00:08:13,320 --> 00:08:17,960
Speaker 10: new characters and storylines, and like, you know, Elon is

143
00:08:18,120 --> 00:08:22,640
Speaker 10: like the star of Season two, Episode one of the

144
00:08:22,640 --> 00:08:23,520
Speaker 10: Trump White House.

145
00:08:24,120 --> 00:08:28,440
Speaker 3: Elon's everywhere in mar al Lago on election night, Uncle

146
00:08:28,480 --> 00:08:32,439
Speaker 3: Elon on Instagram and Trump's family photos, at meetings with

147
00:08:32,520 --> 00:08:37,200
Speaker 3: lawmakers and DC on the phone with Vladimir Zelenski. Trump

148
00:08:37,280 --> 00:08:41,400
Speaker 3: turns it into a running joke. Wherever he goes, Elon

149
00:08:41,440 --> 00:08:41,920
Speaker 3: goes too.

150
00:08:42,600 --> 00:08:43,640
Speaker 4: You know, he likes his place.

151
00:08:43,720 --> 00:08:44,800
Speaker 5: I can't get him out of here.

152
00:08:44,840 --> 00:08:45,880
Speaker 6: He just likes this place.

153
00:08:47,600 --> 00:08:51,439
Speaker 4: He's done a fantastic job. Really an incredible miss.

154
00:08:51,280 --> 00:08:54,959
Speaker 3: Insult wrapped in compliments. We've seen it before. Trump has

155
00:08:55,000 --> 00:08:57,720
Speaker 3: a long history of firing people. It was true on

156
00:08:57,760 --> 00:09:01,480
Speaker 3: The Apprentice, it was true in the White House almost always.

157
00:09:01,800 --> 00:09:04,199
Speaker 5: You can see it coming, you know, when Trump starts

158
00:09:04,280 --> 00:09:05,440
Speaker 5: to get annoyed with people.

159
00:09:06,080 --> 00:09:08,720
Speaker 10: You can kind of feel it in the Richter's scale

160
00:09:08,760 --> 00:09:11,480
Speaker 10: in Washington, like, there will be little asides in Politico

161
00:09:11,600 --> 00:09:14,319
Speaker 10: or Washington Post stories, and you know they'll be leaked

162
00:09:14,320 --> 00:09:18,240
Speaker 10: anonymously by Trump aids, and then Trump himself will say

163
00:09:18,280 --> 00:09:23,800
Speaker 10: something or tweet something belittling, like publicly humiliating him to

164
00:09:23,880 --> 00:09:27,120
Speaker 10: sort of, you know, assert his dominance and express his annoyance,

165
00:09:27,840 --> 00:09:29,440
Speaker 10: you know, and then all of a sudden, one day

166
00:09:29,600 --> 00:09:31,679
Speaker 10: it will just be announced that, like, you know, he's

167
00:09:31,720 --> 00:09:33,040
Speaker 10: no longer in the end circle.

168
00:09:33,240 --> 00:09:36,440
Speaker 5: Or that's one possibility. There's others too.

169
00:09:37,200 --> 00:09:40,240
Speaker 3: A week after the election, Trump officially named Elon the

170
00:09:40,280 --> 00:09:44,520
Speaker 3: co head of the still unrealized Department of Government Efficiency.

171
00:09:45,360 --> 00:09:49,520
Speaker 3: By the way, the Department of Government Efficiency doge. Elon

172
00:09:49,640 --> 00:09:52,880
Speaker 3: named it for a cryptocurrency he likes. Trump says it

173
00:09:52,880 --> 00:09:56,839
Speaker 3: will become quote potentially the Manhattan Project of our time.

174
00:09:57,240 --> 00:09:59,440
Speaker 10: So really, at the end of the day, it's what

175
00:09:59,559 --> 00:10:01,920
Speaker 10: used to be in Washington, a blue ribbon commission. It's

176
00:10:01,920 --> 00:10:04,400
Speaker 10: basically this kind of phony concoction that you whip into

177
00:10:04,480 --> 00:10:08,760
Speaker 10: being to give important people something to do and something

178
00:10:08,760 --> 00:10:11,280
Speaker 10: to talk about, hopefully draw some media attention. But that

179
00:10:11,320 --> 00:10:13,719
Speaker 10: doesn't have any real power. And as far as I

180
00:10:13,760 --> 00:10:18,360
Speaker 10: can see, Elon's DOGE office doesn't have any real power.

181
00:10:19,120 --> 00:10:21,839
Speaker 3: The thing is, and maybe it's because I've spent nearly

182
00:10:21,880 --> 00:10:25,200
Speaker 3: two decades watching Elon star grow. Part of me thinks

183
00:10:25,240 --> 00:10:28,080
Speaker 3: that Josh could be wrong, that Doge could have power.

184
00:10:29,320 --> 00:10:33,080
Speaker 3: Either way, Elon's already won. In the days following the election,

185
00:10:33,440 --> 00:10:35,640
Speaker 3: He's gotten richer, a lot richer.

186
00:10:36,480 --> 00:10:37,880
Speaker 5: By Friday of that week, his.

187
00:10:37,880 --> 00:10:41,120
Speaker 3: Net worth had gone up by fifty billion dollars. And

188
00:10:41,120 --> 00:10:43,480
Speaker 3: that doesn't even account for money that could be coming

189
00:10:43,520 --> 00:10:47,160
Speaker 3: in in the form of defense contracts or killed investigations

190
00:10:47,200 --> 00:10:51,360
Speaker 3: into his business dealings, or new subsidies or regulations that

191
00:10:51,360 --> 00:10:56,200
Speaker 3: could be tweaked to turn his money into more money. Already,

192
00:10:56,440 --> 00:10:59,400
Speaker 3: Trump's picked Brendan Carr, a massive fan of Elon's, to

193
00:10:59,440 --> 00:11:04,199
Speaker 3: run the fc SEE, which means Elon's satellite internet company, Starlink,

194
00:11:04,600 --> 00:11:06,640
Speaker 3: is much more likely to get money from the government.

195
00:11:07,240 --> 00:11:11,880
Speaker 3: And that's just one example. Normally this is where accountability

196
00:11:11,920 --> 00:11:16,360
Speaker 3: measures come in. But who or what could hold somebody

197
00:11:16,400 --> 00:11:20,360
Speaker 3: like Elon Musk to account. He's got a major media platform,

198
00:11:20,880 --> 00:11:23,719
Speaker 3: he's richer than anyone in all of history, and he's

199
00:11:23,720 --> 00:11:24,840
Speaker 3: got Trump in his pocket.

200
00:11:25,520 --> 00:11:26,760
Speaker 5: I asked Josh about this.

201
00:11:27,440 --> 00:11:30,680
Speaker 10: I don't know what the bright line is between just

202
00:11:30,760 --> 00:11:34,120
Speaker 10: being like a kind of a human hurricane in Washington

203
00:11:34,160 --> 00:11:37,400
Speaker 10: and like destroying these ethical and political norms and being

204
00:11:37,440 --> 00:11:40,680
Speaker 10: an out and out authoritarian. But but it looks, you know,

205
00:11:40,720 --> 00:11:42,400
Speaker 10: it looks more and more like we're gonna we're gonna

206
00:11:42,400 --> 00:11:43,600
Speaker 10: test those bounds every day.

207
00:11:44,480 --> 00:11:46,760
Speaker 3: I don't know where we go from here. There's a

208
00:11:46,800 --> 00:11:49,280
Speaker 3: case to be made that right now, Elon is the

209
00:11:49,320 --> 00:11:53,400
Speaker 3: most powerful person on this planet, maybe in history too.

210
00:11:54,360 --> 00:11:58,080
Speaker 9: Elon Musk, he's a unicorn. He's suey generous.

211
00:11:58,600 --> 00:12:02,480
Speaker 3: David NASA professor meritith of history at CuNi and biographer,

212
00:12:03,000 --> 00:12:03,559
Speaker 3: and I've.

213
00:12:03,360 --> 00:12:07,719
Speaker 9: Written a bunch of books, including biographies of Andrew Carnegy,

214
00:12:08,280 --> 00:12:10,600
Speaker 9: William Randolph Hurst, Joseph Kennedy.

215
00:12:11,559 --> 00:12:15,280
Speaker 3: David's beat is really powerful men, and here he sees

216
00:12:15,320 --> 00:12:16,480
Speaker 3: a lot of parallels with Elon.

217
00:12:16,960 --> 00:12:20,560
Speaker 9: Let me take but one example. He is not the

218
00:12:20,600 --> 00:12:26,480
Speaker 9: first rich man to fund a candidate in the hopes

219
00:12:26,520 --> 00:12:30,599
Speaker 9: of getting a quid or a quo for his quids,

220
00:12:31,120 --> 00:12:35,000
Speaker 9: or however you say it, getting some sort of payback.

221
00:12:37,600 --> 00:12:42,440
Speaker 9: What's different is that this is not dark money. His

222
00:12:42,640 --> 00:12:48,520
Speaker 9: is anything but dark. I mean, it glows, it sparkles.

223
00:12:49,400 --> 00:12:53,160
Speaker 9: He is out front saying this is what I'm doing,

224
00:12:54,280 --> 00:12:56,560
Speaker 9: you know, and this is why I'm doing it, and

225
00:12:56,720 --> 00:13:05,400
Speaker 9: that is unprecedented. In the past, huge donors to campaigns

226
00:13:06,559 --> 00:13:11,040
Speaker 9: who saw it influenced thereafter kept it quiet.

227
00:13:11,360 --> 00:13:14,760
Speaker 3: Like Carnegie, the guy who built America steel industry. He

228
00:13:14,840 --> 00:13:18,959
Speaker 3: was rich, like Elon or Hurst, who the movie Citizen

229
00:13:19,000 --> 00:13:22,840
Speaker 3: Kane is literally based on, had mega cultural influence like

230
00:13:22,880 --> 00:13:28,080
Speaker 3: Elon or Kennedy the original Kennedy had immense political influence

231
00:13:28,559 --> 00:13:33,400
Speaker 3: like Elon, But David says those guys were mostly behind

232
00:13:33,440 --> 00:13:36,360
Speaker 3: the scenes. They didn't act the way that Elon does.

233
00:13:37,120 --> 00:13:41,000
Speaker 9: The other thing that's new is that this guy has

234
00:13:41,360 --> 00:13:48,360
Speaker 9: more He's more presumptuous than any business leader I've seen.

235
00:13:48,960 --> 00:13:53,040
Speaker 3: For instance, Elon's live Twitter interview with Trump back in August,

236
00:13:53,480 --> 00:13:56,600
Speaker 3: when the idea of a government efficiency commission was first floated.

237
00:13:57,440 --> 00:13:59,960
Speaker 3: David points out that was Elon's idea.

238
00:14:00,679 --> 00:14:05,079
Speaker 9: Nobody talked about him entering the government until he did.

239
00:14:05,480 --> 00:14:09,200
Speaker 9: You know, if you look at if you listen to

240
00:14:09,240 --> 00:14:15,120
Speaker 9: that interview, about fifty minutes in, Trump mentioned something about inflation,

241
00:14:16,200 --> 00:14:21,560
Speaker 9: and Musk says, yeah, you're right, and I think we

242
00:14:21,600 --> 00:14:23,760
Speaker 9: need a Department of government efficiency.

243
00:14:23,880 --> 00:14:27,480
Speaker 7: I think we need like a government efficiency commission to say, like, hey,

244
00:14:27,600 --> 00:14:29,120
Speaker 7: where are we spending money that's sensible?

245
00:14:29,160 --> 00:14:30,400
Speaker 9: Where is it not sensible?

246
00:14:31,040 --> 00:14:34,400
Speaker 7: And would you agree that we need to take a

247
00:14:34,400 --> 00:14:39,440
Speaker 7: look at governspending and have perhaps a government efficiency commission

248
00:14:40,160 --> 00:14:43,120
Speaker 7: that just I mean, I think it'd be great to

249
00:14:43,120 --> 00:14:45,440
Speaker 7: just have a government efficiency commission that takes a look

250
00:14:46,080 --> 00:14:48,960
Speaker 7: at these things. And I'd be happy to help out

251
00:14:48,960 --> 00:14:49,800
Speaker 7: on such a commission.

252
00:14:50,200 --> 00:14:52,160
Speaker 9: And Trump doesn't know what to do about it, and

253
00:14:52,200 --> 00:14:52,560
Speaker 9: then he.

254
00:14:52,520 --> 00:14:54,880
Speaker 5: Says, yeah, you know, it's funny.

255
00:14:55,040 --> 00:14:57,120
Speaker 3: The thing that was surprising to me in that interview

256
00:14:57,840 --> 00:15:01,560
Speaker 3: was how subservient he allowed himself to beat a Trump.

257
00:15:02,360 --> 00:15:07,240
Speaker 9: He was subservient, He rolled over on any number of questions.

258
00:15:07,640 --> 00:15:13,320
Speaker 9: But then he saw his opportunity when inflation was mentioned,

259
00:15:14,000 --> 00:15:15,960
Speaker 9: and he must have known this was what he was

260
00:15:16,000 --> 00:15:21,840
Speaker 9: going to do, but he waited almost an hour to

261
00:15:21,960 --> 00:15:23,480
Speaker 9: put in in his plug.

262
00:15:24,440 --> 00:15:27,480
Speaker 3: David says he wants not the first guy to try

263
00:15:27,520 --> 00:15:31,240
Speaker 3: buying himself political influence. All three of his moguls, he

264
00:15:31,320 --> 00:15:33,840
Speaker 3: calls it my moguls. By the way, that's what they

265
00:15:33,880 --> 00:15:37,000
Speaker 3: tried to do too. But the presidents they helped put

266
00:15:37,000 --> 00:15:41,040
Speaker 3: in office mostly ignored them focused on making their voters happy,

267
00:15:41,960 --> 00:15:47,800
Speaker 3: which you know, that's democracy working this time. We don't

268
00:15:47,840 --> 00:15:51,600
Speaker 3: know those moguls of the past. They didn't have Elon

269
00:15:51,760 --> 00:15:56,280
Speaker 3: social media, following a newspaper, even a chain of newspapers.

270
00:15:56,760 --> 00:15:58,720
Speaker 3: It's not the same as owning a social network.

271
00:15:59,400 --> 00:16:02,240
Speaker 1: I just see a lot of triumphalism.

272
00:16:02,600 --> 00:16:05,880
Speaker 3: Ellie Reeve again an expert on right wing extremism. We

273
00:16:05,960 --> 00:16:09,120
Speaker 3: spoke with her in episode one. She says that Twitter

274
00:16:09,200 --> 00:16:12,240
Speaker 3: has been different since Elon bought it, and especially since

275
00:16:12,240 --> 00:16:14,920
Speaker 3: he came out in favor of Trump. It's not just

276
00:16:14,960 --> 00:16:17,520
Speaker 3: that there's a lot of hate, it's that the people

277
00:16:17,560 --> 00:16:19,800
Speaker 3: promoting hate have gotten less restrained.

278
00:16:20,400 --> 00:16:24,080
Speaker 1: Like I was just watching this video hosted by Benny Johnson,

279
00:16:24,400 --> 00:16:27,680
Speaker 1: who used to work for BuzzFeed in other places, talking

280
00:16:27,720 --> 00:16:32,160
Speaker 1: to him Trump official, who was saying joking but not joking,

281
00:16:32,160 --> 00:16:35,120
Speaker 1: We're going to rain down hell fire when we take office.

282
00:16:35,280 --> 00:16:37,880
Speaker 1: We're going to deport all these people and their kids

283
00:16:37,920 --> 00:16:40,000
Speaker 1: and their grandparents, and it's going to be awesome.

284
00:16:40,160 --> 00:16:44,480
Speaker 11: Ten million people in growing anchor babies, their parents, their grandparents.

285
00:16:44,760 --> 00:16:47,359
Speaker 11: We're gonna put kids in cages. It's gonna be glorious.

286
00:16:47,720 --> 00:16:51,000
Speaker 11: We're gonna deport a lot of people. I will reign

287
00:16:51,120 --> 00:16:54,240
Speaker 11: hell on Washington, DC. We've talked about this.

288
00:16:54,280 --> 00:16:55,200
Speaker 5: Like that's the kind of stuff.

289
00:16:55,200 --> 00:16:58,440
Speaker 1: I see real names, real faces saying the stuff you

290
00:16:58,440 --> 00:17:00,640
Speaker 1: could only say anonymously ten years ago.

291
00:17:01,680 --> 00:17:04,639
Speaker 3: Elon says he bought Twitter to save free speech, to

292
00:17:04,680 --> 00:17:08,960
Speaker 3: bring back the town Square. But I don't know. I'm

293
00:17:09,000 --> 00:17:12,639
Speaker 3: not convinced what he's built. It feels less like a

294
00:17:12,640 --> 00:17:16,159
Speaker 3: public forum and more like a soapbox for him and

295
00:17:16,200 --> 00:17:17,080
Speaker 3: his side to stand on.

296
00:17:18,960 --> 00:17:20,080
Speaker 5: I have affection for my.

297
00:17:20,200 --> 00:17:26,680
Speaker 9: Three guys, my three moguls, Carnegie, Hurst and Joe Kennedy.

298
00:17:27,560 --> 00:17:32,159
Speaker 9: I don't have the same affection for Elon Musk. I

299
00:17:32,200 --> 00:17:37,760
Speaker 9: think in the long term, Elon Musk is more dangerous,

300
00:17:39,000 --> 00:17:47,800
Speaker 9: is smarter, and has amassed a kind of political and

301
00:17:47,840 --> 00:17:51,840
Speaker 9: cultural power that no one should have that kind of power.

302
00:17:52,640 --> 00:17:55,080
Speaker 3: Maybe it's that you have been able to figure out,

303
00:17:56,640 --> 00:17:58,480
Speaker 3: like what matters to him beyond himself.

304
00:17:58,840 --> 00:17:59,760
Speaker 5: That's absolutely right.

305
00:18:00,640 --> 00:18:04,800
Speaker 9: What I can't figure out about Musk is what drives him.

306
00:18:05,560 --> 00:18:07,359
Speaker 9: He says what drives him is he wants to go

307
00:18:07,400 --> 00:18:10,440
Speaker 9: to Mars. At various times, he says what drives him

308
00:18:10,480 --> 00:18:14,359
Speaker 9: is that he wants more smart children to be born.

309
00:18:14,880 --> 00:18:17,520
Speaker 9: You know where the country is going to fall apart.

310
00:18:19,280 --> 00:18:24,280
Speaker 9: At various times he wants to save the planet, and

311
00:18:24,320 --> 00:18:27,800
Speaker 9: I don't know what's most important in the end. Somehow

312
00:18:27,880 --> 00:18:34,960
Speaker 9: I think that he he has succeeded in so many

313
00:18:35,080 --> 00:18:39,639
Speaker 9: different areas that he thinks he's godlike.

314
00:18:41,080 --> 00:18:44,680
Speaker 3: Something occurred to me Musk's favorite saying, the voice of

315
00:18:44,720 --> 00:18:47,800
Speaker 3: the people is the voice of the gods. Maybe what

316
00:18:47,880 --> 00:18:50,720
Speaker 3: he actually means is the voice of the people is

317
00:18:50,720 --> 00:18:51,679
Speaker 3: whatever I say it is.

318
00:18:52,560 --> 00:18:57,040
Speaker 9: He can't be president, he can't be king, but he

319
00:18:57,040 --> 00:19:02,040
Speaker 9: can be God. And I think the more he achieves,

320
00:19:03,640 --> 00:19:08,359
Speaker 9: the more power he amasses, the more he thinks he

321
00:19:08,520 --> 00:19:12,840
Speaker 9: is Zeus, you know, And it's you know, it's up

322
00:19:12,840 --> 00:19:15,639
Speaker 9: to us to say, no, we don't want a Zeus.

323
00:19:16,280 --> 00:19:20,320
Speaker 9: We want to live in a democracy.

324
00:19:21,000 --> 00:19:23,720
Speaker 5: What David's saying, I've been thinking about it.

325
00:19:24,520 --> 00:19:28,560
Speaker 3: Of course, it's dramatic, but it also captures the dramatic

326
00:19:28,640 --> 00:19:32,879
Speaker 3: scale of Elon's ambitions and what we've made of them

327
00:19:32,920 --> 00:19:36,400
Speaker 3: looking back. Something I got wrong about Elon from the start,

328
00:19:37,080 --> 00:19:39,200
Speaker 3: when his whole thing was just rockets.

329
00:19:38,800 --> 00:19:41,120
Speaker 5: And climate change. He seemed like some.

330
00:19:41,040 --> 00:19:44,440
Speaker 3: Sort of superhero, like larger than life, more than just

331
00:19:44,520 --> 00:19:47,120
Speaker 3: some guy Elon.

332
00:19:46,920 --> 00:19:48,040
Speaker 5: Musk is not zeus.

333
00:19:49,080 --> 00:19:52,280
Speaker 3: What he is, though, is a celebrity, and we've got

334
00:19:52,320 --> 00:19:56,000
Speaker 3: a lot of say in that. After all, Fox popular

335
00:19:56,840 --> 00:19:59,920
Speaker 3: the people we do make up hathy EQ.

336
00:20:10,400 --> 00:20:10,800
Speaker 5: Citizen.

337
00:20:10,880 --> 00:20:14,520
Speaker 3: Elon is produced by Lena Mesitzis, Rayon Harmonci is our

338
00:20:14,560 --> 00:20:18,280
Speaker 3: senior editor, Blake Maples handles engineering and Emma.

339
00:20:18,040 --> 00:20:19,200
Speaker 5: Sanchez fact checking.

340
00:20:19,600 --> 00:20:22,800
Speaker 3: Brendan Francis Newham is our executive producer, and Sage Bauman

341
00:20:22,880 --> 00:20:25,800
Speaker 3: is the head of Bloomberg Podcasts. Big thanks to the

342
00:20:25,800 --> 00:20:30,600
Speaker 3: Elon Ink crew, David Popadopoulos, Naomi Shaven, Magnus Hendrickson, Stacy

343
00:20:30,640 --> 00:20:34,639
Speaker 3: Wong listen every Tuesday for breaking Elon news. Thanks as

344
00:20:34,640 --> 00:20:38,560
Speaker 3: well to our Bloomberg colleagues David Fox, Julia Press, Dana Hall,

345
00:20:38,920 --> 00:20:43,960
Speaker 3: Sarah Fryar, Kurt Wagner, Josh Green, Mark Million, Margaret Sutherland,

346
00:20:44,240 --> 00:20:49,520
Speaker 3: Alison Mobley, Jackie Kessler, Ariel Brown, Chris Nocenzo, and Albert Hicks.

347
00:20:50,720 --> 00:20:53,480
Speaker 3: An extra big thanks to Brad Stone, editor of BusinessWeek,

348
00:20:53,640 --> 00:20:56,720
Speaker 3: and Katie Boyce, executive editor of Bloomberg Digital, for their

349
00:20:56,800 --> 00:20:57,760
Speaker 3: unflagging support.

350
00:20:59,240 --> 00:21:00,000
Speaker 5: I'm Max Schaft.

351
00:21:00,400 --> 00:21:02,200
Speaker 3: If you have a minute, rate and review our show,

352
00:21:02,280 --> 00:21:03,880
Speaker 3: it'll help other listeners find us