1 00:00:10,750 --> 00:00:15,260 Speaker 1: Musk is probably the richest couch surfer ever. He didn't 2 00:00:15,300 --> 00:00:18,680 Speaker 1: have a home in Palo Alto, so he would stay 3 00:00:18,739 --> 00:00:21,820 Speaker 1: with Larry Page and they'd stay up all night. And 4 00:00:21,900 --> 00:00:25,220 Speaker 1: Musk would talk about how we have to be careful 5 00:00:25,260 --> 00:00:29,270 Speaker 1: of AI. It could destroy us. And Page was having 6 00:00:29,350 --> 00:00:32,350 Speaker 1: nothing of it. Page loved the notion of AI. And 7 00:00:32,390 --> 00:00:35,230 Speaker 1: Page would even say, it'd be great if we could 8 00:00:35,270 --> 00:00:37,870 Speaker 1: have robots that would be conscious and that we could 9 00:00:37,950 --> 00:00:40,530 Speaker 1: upload our consciousness into it. It would be the next 10 00:00:40,590 --> 00:00:45,270 Speaker 1: phase of evolution. Why are you so worried about humans 11 00:00:45,310 --> 00:00:49,290 Speaker 1: being left behind by the robots? And once Page even 12 00:00:49,370 --> 00:00:53,740 Speaker 1: called him speciesist, meaning you're biased towards the human species. 13 00:00:54,500 --> 00:00:57,860 Speaker 1: And Ma said, yeah, dude, I am speciesist. I like 14 00:00:57,900 --> 00:01:01,780 Speaker 1: the human species. And believe it or not, these fights 15 00:01:02,220 --> 00:01:05,540 Speaker 1: caused them to quit speaking to each other. I mean, 16 00:01:05,560 --> 00:01:08,520 Speaker 1: they really still don't speak to each other because of 17 00:01:08,580 --> 00:01:16,420 Speaker 1: this philosophical fight. I think Musk looks upon himself as 18 00:01:16,470 --> 00:01:20,910 Speaker 1: an epic figure on a grand quest, just like the 19 00:01:20,950 --> 00:01:24,030 Speaker 1: comic book characters wearing their underpants on the outside and 20 00:01:24,090 --> 00:01:28,569 Speaker 1: kind of knowing they're ridiculous, but also very insecure about it. 21 00:01:29,670 --> 00:01:32,350 Speaker 1: And I think it's true of a whole lot of people. 22 00:01:33,110 --> 00:01:35,720 Speaker 1: I think it's a human trait. But I think like 23 00:01:35,920 --> 00:01:39,700 Speaker 1: every human trait in Elon Musk, it's at least two 24 00:01:39,880 --> 00:01:41,479 Speaker 1: orders of magnitude greater. 25 00:01:47,350 --> 00:01:50,490 Speaker 2: In the weeks since the release of Walter Isaacson's doorstop 26 00:01:50,590 --> 00:01:53,610 Speaker 2: biography of Elon Musk, some stories from the book have 27 00:01:53,650 --> 00:01:57,570 Speaker 2: jumped off the page. Tabloidish fodder, like the secret birth 28 00:01:57,630 --> 00:02:01,310 Speaker 2: of Musk's third child with Grimes, or the secret births 29 00:02:01,360 --> 00:02:05,560 Speaker 2: of his twins with his colleague. Non-procreative stories, like the 30 00:02:05,620 --> 00:02:09,079 Speaker 2: fact-checking drama around the role that Musk's Starlink satellite network 31 00:02:09,180 --> 00:02:13,440 Speaker 2: has and has not occupied in Ukraine. And since Isaacson 32 00:02:13,480 --> 00:02:16,400 Speaker 2: and I spoke, there's of course been the unending drama 33 00:02:16,520 --> 00:02:21,520 Speaker 2: emanating from Musk himself. From amplifying anti-Semitic tweets, to publicly 34 00:02:21,560 --> 00:02:26,000 Speaker 2: telling Disney CEO Bob Iger to go fuck himself. But 35 00:02:26,080 --> 00:02:29,060 Speaker 2: after each tempest dies down, what should we really take 36 00:02:29,100 --> 00:02:32,530 Speaker 2: away from this 600-page epic retelling of the life of Musk? 37 00:02:33,300 --> 00:02:38,040 Speaker 2: and about the world in which he operates. I'm Evan Ratliff. 38 00:02:38,410 --> 00:02:41,730 Speaker 2: This is On Musk with Walter Isaacson. And today we're 39 00:02:41,770 --> 00:02:46,210 Speaker 2: tangling with Isaacson over questions around Musk, the speciesist. I mean, 40 00:02:46,570 --> 00:02:49,970 Speaker 2: whose side is he on anyway? What does his growing 41 00:02:50,050 --> 00:02:53,240 Speaker 2: geopolitical influence tell us about the power that one man 42 00:02:53,340 --> 00:02:56,720 Speaker 2: can hold in the modern world? And finally, What are 43 00:02:56,760 --> 00:03:00,019 Speaker 2: we meant to learn from Isaacson's exhaustive account? How does 44 00:03:00,080 --> 00:03:02,560 Speaker 2: he think the book will age as Musk seems to 45 00:03:02,580 --> 00:03:09,290 Speaker 2: grow more divisive and even self-destructive by the day? Episode four, Legacy. 46 00:03:09,310 --> 00:03:14,290 Speaker 2: I mean, you spent so much time with Jobs in 47 00:03:14,350 --> 00:03:30,419 Speaker 2: the world of Silicon Valley, understanding that world, the whole 48 00:03:30,620 --> 00:03:33,720 Speaker 2: way that world operated at that time, Jobs versus Gates, 49 00:03:34,080 --> 00:03:37,220 Speaker 2: et cetera. And when you came to the end of that, 50 00:03:38,290 --> 00:03:40,130 Speaker 2: there's one way you could go where you would say, 51 00:03:40,150 --> 00:03:41,810 Speaker 2: I think I get it. I think I get what 52 00:03:41,830 --> 00:03:46,170 Speaker 2: Silicon Valley is all about. But then you go after Musk. 53 00:03:46,590 --> 00:03:50,480 Speaker 1: We biographers have a dirty little secret that we sometimes 54 00:03:50,620 --> 00:03:53,560 Speaker 1: distort history by making it seem like one guy or 55 00:03:53,680 --> 00:03:56,260 Speaker 1: one gal goes into a garage in a garage. They 56 00:03:56,280 --> 00:04:00,730 Speaker 1: have a light bulb moment and then history happens. And 57 00:04:01,070 --> 00:04:04,330 Speaker 1: usually it's done by groups of people and teams as 58 00:04:04,390 --> 00:04:10,530 Speaker 1: a collaborative nature to creativity. And so after doing Steve Jobs, 59 00:04:11,130 --> 00:04:14,760 Speaker 1: in which I showed him as a motive force pushing 60 00:04:14,800 --> 00:04:18,560 Speaker 1: the digital revolution, I decided to do a book called 61 00:04:18,600 --> 00:04:25,979 Speaker 1: The Innovators, It was a collective biographical study with dozens 62 00:04:26,380 --> 00:04:29,240 Speaker 1: of people who helped invent the concept of the personal 63 00:04:29,279 --> 00:04:32,820 Speaker 1: computer and the concept of the network and then the 64 00:04:32,880 --> 00:04:38,670 Speaker 1: microchip and how they interwove and collaborated. I think in 65 00:04:38,850 --> 00:04:42,750 Speaker 1: some ways that can be more true to history is 66 00:04:42,810 --> 00:04:47,589 Speaker 1: to show partnerships and teamwork that lead to things. I 67 00:04:47,630 --> 00:04:50,490 Speaker 1: kind of liked it. But it didn't really sell all 68 00:04:50,529 --> 00:04:56,870 Speaker 1: that well. I do think that people like following a 69 00:04:56,910 --> 00:04:58,330 Speaker 1: main character. 70 00:04:59,130 --> 00:05:02,030 Speaker 2: But for Musk, some of the minor characters are pretty 71 00:05:02,070 --> 00:05:07,390 Speaker 2: big personalities, and sometimes controversial ones. As Musk's bluster about 72 00:05:07,430 --> 00:05:10,190 Speaker 2: buying Twitter turns into reality, a crew of his old 73 00:05:10,230 --> 00:05:13,940 Speaker 2: Valley pals start to resurface in Isaacson's tale. Many of 74 00:05:13,980 --> 00:05:17,380 Speaker 2: them are from what Fortune magazine once called the PayPal Mafia. 75 00:05:18,100 --> 00:05:22,200 Speaker 2: Ex-PayPal execs like David Sachs, Ken Howery, Reid Hoffman, and 76 00:05:22,240 --> 00:05:25,460 Speaker 2: Peter Thiel. Many of them seem to be Musk's whisperers, 77 00:05:26,020 --> 00:05:30,270 Speaker 2: simultaneously steering Musk away from jagged financial shoals and toward 78 00:05:30,310 --> 00:05:35,150 Speaker 2: a frothing ocean of an anti-woke free speech maelstrom. There 79 00:05:35,190 --> 00:05:39,289 Speaker 2: is a whole world of how these Silicon Valley moguls, 80 00:05:39,310 --> 00:05:41,850 Speaker 2: you would call many of them, or executives sort of 81 00:05:41,930 --> 00:05:44,750 Speaker 2: like relate to each other. And a lot of it 82 00:05:44,790 --> 00:05:47,750 Speaker 2: goes back to PayPal and and the PayPal mafia and 83 00:05:47,790 --> 00:05:49,770 Speaker 2: people who started PayPal and then becoming these friends and 84 00:05:49,790 --> 00:05:52,630 Speaker 2: Musk being involved in it. I mean, you mentioned Antonio Gracias, 85 00:05:52,650 --> 00:05:54,330 Speaker 2: you already knew him. Is that a world that you 86 00:05:54,350 --> 00:05:58,070 Speaker 2: already had entry into and understood or you learned through 87 00:05:58,150 --> 00:06:02,580 Speaker 2: Musk the relationships between these people and how that actually 88 00:06:02,700 --> 00:06:04,300 Speaker 2: influences what happens in these? 89 00:06:05,060 --> 00:06:08,140 Speaker 1: By writing about Steve Jobs and then doing the innovators, 90 00:06:08,300 --> 00:06:11,780 Speaker 1: I certainly got to know that world very well of 91 00:06:11,839 --> 00:06:18,230 Speaker 1: tech bros and even that world of the quasi-libertarian tech 92 00:06:18,270 --> 00:06:24,060 Speaker 1: bro mentality that's a Peter Thiel at the center. One 93 00:06:24,080 --> 00:06:29,620 Speaker 1: of the things that helps understand Musk today goes back 94 00:06:29,860 --> 00:06:35,420 Speaker 1: to those PayPal years. He had started a company called x.com, 95 00:06:35,960 --> 00:06:38,960 Speaker 1: which he wanted to have be a payments app, but 96 00:06:39,020 --> 00:06:41,320 Speaker 1: also an everything app, an app that would be social 97 00:06:41,360 --> 00:06:47,910 Speaker 1: media and would be a publishing platform, and it merges 98 00:06:47,990 --> 00:06:50,589 Speaker 1: with a company that Peter Thiel has done, and it 99 00:06:50,650 --> 00:06:56,180 Speaker 1: becomes PayPal. Musk wants to keep it named X, X.com. 100 00:06:56,210 --> 00:06:58,640 Speaker 1: He loves the mystery of that letter X. He thinks 101 00:06:58,700 --> 00:07:02,260 Speaker 1: it's hardcore, and they overrule him, and they use the 102 00:07:02,279 --> 00:07:05,700 Speaker 1: name PayPal, which he thinks is a sweet little name 103 00:07:05,760 --> 00:07:07,880 Speaker 1: of pals who want to pay each other, but it's 104 00:07:07,960 --> 00:07:10,360 Speaker 1: not an everything app that's going to change the world. 105 00:07:11,240 --> 00:07:15,180 Speaker 1: and they kick him out. And for 20 years, it's 106 00:07:15,240 --> 00:07:18,560 Speaker 1: eating away at him, which is why, of course, he 107 00:07:18,620 --> 00:07:22,000 Speaker 1: wants to buy Twitter, and it becomes the booster to 108 00:07:22,080 --> 00:07:25,490 Speaker 1: create what he'd always wanted, which is a payments platform 109 00:07:25,550 --> 00:07:31,070 Speaker 1: connected to a publishing platform connected to social media. But 110 00:07:31,110 --> 00:07:34,850 Speaker 1: he does something that I found somewhat surprising until I 111 00:07:34,850 --> 00:07:38,530 Speaker 1: fully understood it, is when he gets connected kicked out 112 00:07:38,810 --> 00:07:43,630 Speaker 1: of PayPal in this coup by Peter Thiel and Reid Hoffman, 113 00:07:44,210 --> 00:07:51,610 Speaker 1: Ken Howery, David Sachs, and Max Levchin. Musk decides instead 114 00:07:51,910 --> 00:07:56,420 Speaker 1: of hating them forever and thinking they're enemies, he makes 115 00:07:56,510 --> 00:07:59,900 Speaker 1: up with them, even though he says, they knifed me 116 00:07:59,960 --> 00:08:03,300 Speaker 1: in the forum, kicked me out of my job. And 117 00:08:03,340 --> 00:08:06,960 Speaker 1: it comes back as good karma. They end up investing 118 00:08:07,200 --> 00:08:09,360 Speaker 1: in SpaceX. Yeah, Thiel gives him $ 20 million. 119 00:08:09,380 --> 00:08:12,240 Speaker 2: Basically, you write as an apology almost. 120 00:08:12,540 --> 00:08:16,760 Speaker 1: As a way after three rocket launches by SpaceX have 121 00:08:16,870 --> 00:08:20,610 Speaker 1: failed and they've run out of money, Thiel says it's 122 00:08:20,630 --> 00:08:23,570 Speaker 1: a good way to try to make it up to him. 123 00:08:24,290 --> 00:08:29,950 Speaker 1: And it saves SpaceX. And this crowd remains relatively friendly. 124 00:08:30,730 --> 00:08:36,760 Speaker 1: And their political views and their technology views influence each other. 125 00:08:37,540 --> 00:08:43,240 Speaker 1: And it all feeds in to understanding why his politics 126 00:08:43,320 --> 00:08:49,890 Speaker 1: have become somewhat of this populist, right, libertarian streak. 127 00:08:50,850 --> 00:08:53,050 Speaker 2: This book is going to, people are going to take 128 00:08:53,150 --> 00:08:56,960 Speaker 2: lessons from it, even if you don't explicitly prescribe what 129 00:08:57,000 --> 00:08:59,939 Speaker 2: those lessons are going to be. And especially in the 130 00:08:59,980 --> 00:09:04,429 Speaker 2: business world, People like to read these books for tips 131 00:09:05,040 --> 00:09:09,120 Speaker 2: and for advice. And let's take people in Silicon Valley, 132 00:09:09,140 --> 00:09:12,160 Speaker 2: for example. What do you think they are going to 133 00:09:12,220 --> 00:09:15,040 Speaker 2: draw from the book? And are you at all concerned 134 00:09:15,320 --> 00:09:16,819 Speaker 2: that they might draw the wrong lesson? 135 00:09:17,380 --> 00:09:21,130 Speaker 1: Now, with Steve Jobs, when that book came out, there 136 00:09:21,150 --> 00:09:23,530 Speaker 1: were a lot of stories of, do you have to 137 00:09:23,570 --> 00:09:26,670 Speaker 1: be like Steve Jobs to be successful? A Wired Magazine 138 00:09:26,730 --> 00:09:29,520 Speaker 1: cover story did it. And I was saying, no, this 139 00:09:29,640 --> 00:09:33,400 Speaker 1: book was not a how-to manual. Sometimes people come up 140 00:09:33,460 --> 00:09:37,479 Speaker 1: to me after I talked about Steve Jobs and they'd say, 141 00:09:37,580 --> 00:09:39,079 Speaker 1: I'm just like Steve Jobs. 142 00:09:39,440 --> 00:09:40,800 Speaker 2: Like I'm not a waz, I'm a jobs. 143 00:09:40,960 --> 00:09:43,880 Speaker 1: Yeah, I'm not waz. I'm not sweet. I'm not cuddly. 144 00:09:44,450 --> 00:09:48,150 Speaker 1: I'm like jobs. If people screw things up, I tell 145 00:09:48,170 --> 00:09:51,130 Speaker 1: them they've screwed up. I fire them. I tell them 146 00:09:51,170 --> 00:09:55,189 Speaker 1: they stink, I'll say on a podcast. And I'll look 147 00:09:55,270 --> 00:09:57,480 Speaker 1: at them and I say, yeah. And have you ever 148 00:09:57,540 --> 00:10:01,140 Speaker 1: invented the iPod? Did you ever make the Mac? the iPhone? 149 00:10:01,660 --> 00:10:04,600 Speaker 1: You don't have the right to do this. Probably Steve 150 00:10:04,640 --> 00:10:07,079 Speaker 1: Jobs didn't have the right to do it, but you're 151 00:10:07,120 --> 00:10:08,860 Speaker 1: not supposed to try to be like this. 152 00:10:09,300 --> 00:10:11,320 Speaker 2: Do you worry at all? You mentioned the person who 153 00:10:11,340 --> 00:10:13,830 Speaker 2: comes up to you and says, I'm like Steve Jobs, 154 00:10:14,230 --> 00:10:18,270 Speaker 2: that there are going to be Musk acolytes, who will 155 00:10:18,309 --> 00:10:20,890 Speaker 2: take those wrong lessons, and that some of those people 156 00:10:21,929 --> 00:10:26,100 Speaker 2: run Silicon Valley. They run very important aspects, if not 157 00:10:26,140 --> 00:10:28,819 Speaker 2: the most important aspects of our society right now. Does 158 00:10:28,860 --> 00:10:32,080 Speaker 2: it concern you that people might take a Muskian approach 159 00:10:32,420 --> 00:10:37,860 Speaker 2: and lack the vision but have the persona, and that 160 00:10:37,920 --> 00:10:41,319 Speaker 2: those people are making consequential decisions about the tools we use? 161 00:10:42,360 --> 00:10:45,980 Speaker 1: Yeah. I mean, one lesson a lot of Silicon Valley 162 00:10:46,040 --> 00:10:50,770 Speaker 1: executives seem to have taken from the book is, oh, 163 00:10:51,330 --> 00:10:53,890 Speaker 1: my workforce is probably too flabby. I could fire 80% 164 00:10:53,890 --> 00:10:58,610 Speaker 1: the way Elon Musk did at Twitter. And no, you 165 00:10:58,650 --> 00:11:03,580 Speaker 1: can't just do that. Also, there's a larger issue, which 166 00:11:03,670 --> 00:11:07,480 Speaker 1: the book wrestles with, which I call the old Twitter, 167 00:11:07,540 --> 00:11:11,439 Speaker 1: new Twitter issue, which is that life is about a 168 00:11:11,500 --> 00:11:16,599 Speaker 1: little bit more than simply having the leanest, meanest machine 169 00:11:16,640 --> 00:11:19,630 Speaker 1: you can create. And some people may want to do that, 170 00:11:20,090 --> 00:11:22,830 Speaker 1: especially people doing startups. They may want to be lean, mean, 171 00:11:22,890 --> 00:11:25,830 Speaker 1: and hackathon all night long. But there are other people 172 00:11:26,370 --> 00:11:30,250 Speaker 1: who will keep in mind the larger mission of having 173 00:11:30,290 --> 00:11:34,670 Speaker 1: an enterprise or a company and that it's there to 174 00:11:34,750 --> 00:11:40,050 Speaker 1: create good for all of society, for consumers, for good products, 175 00:11:40,330 --> 00:11:42,630 Speaker 1: but also the people who work there and the communities 176 00:11:42,670 --> 00:11:45,890 Speaker 1: where they're based. And I think that's a good tension 177 00:11:46,150 --> 00:11:49,330 Speaker 1: to have in our society. You know, I used to 178 00:11:49,370 --> 00:11:53,970 Speaker 1: work at Diamond Incorporated, and boy, it was nice and flabby. 179 00:11:54,770 --> 00:11:57,910 Speaker 1: You know, we had a dozen people working in the 180 00:11:57,950 --> 00:12:03,069 Speaker 1: nation section to produce maybe eight pages every week. 181 00:12:03,510 --> 00:12:03,990 Speaker 2: Sounds lovely. 182 00:12:04,030 --> 00:12:08,160 Speaker 1: We had researchers. We had assistants and schedulers. We even 183 00:12:08,200 --> 00:12:10,260 Speaker 1: had the person who brought the food cart and the 184 00:12:10,300 --> 00:12:16,340 Speaker 1: drink cart around every evening. And then, you know, everybody from... 185 00:12:16,809 --> 00:12:21,480 Speaker 1: activist investors to McKinsey consultants come in and say, you 186 00:12:21,500 --> 00:12:23,420 Speaker 1: can cut this, you can cut that, you can make 187 00:12:23,480 --> 00:12:27,000 Speaker 1: it leaner and meaner. And there are people who are 188 00:12:27,040 --> 00:12:32,560 Speaker 1: comfortable being all in and hardcore. Bill Gates, Jeff Bezos, 189 00:12:34,100 --> 00:12:38,520 Speaker 1: Steve Jobs, Elon Musk, totally hardcore. And there are people 190 00:12:38,600 --> 00:12:43,750 Speaker 1: who are more comfortable finding a nurturing, good environment for people. 191 00:12:43,929 --> 00:12:47,250 Speaker 1: We have to find the right balances and I would 192 00:12:47,330 --> 00:12:51,829 Speaker 1: disdain somebody who is always as tough as an Elon Musk. 193 00:12:52,980 --> 00:12:57,080 Speaker 1: I'd also kind of disdain people who lack a sense 194 00:12:57,120 --> 00:13:00,459 Speaker 1: of passion and mission. But the books aren't a how-to 195 00:13:00,500 --> 00:13:05,140 Speaker 1: manual saying you should do this at your company. These books, 196 00:13:05,660 --> 00:13:08,620 Speaker 1: especially when it comes to Elon Musk, are supposed to 197 00:13:08,660 --> 00:13:11,880 Speaker 1: do two things that people have a hard time keeping 198 00:13:11,940 --> 00:13:16,600 Speaker 1: both in their mind. Be inspirational and be cautionary. But 199 00:13:16,679 --> 00:13:20,490 Speaker 1: above all, it is a story of a real person 200 00:13:21,090 --> 00:13:24,990 Speaker 1: that is one of the most consequential of our day 201 00:13:25,050 --> 00:13:25,770 Speaker 1: and generation. 202 00:13:27,190 --> 00:13:30,310 Speaker 2: And I mean, I think a certain percentage of people 203 00:13:30,390 --> 00:13:35,240 Speaker 2: today have a hard time understanding the approach where you 204 00:13:35,740 --> 00:13:39,120 Speaker 2: could happily sit and listen to a Peter Thiel or 205 00:13:39,360 --> 00:13:44,200 Speaker 2: someone with those politics and not kind of challenge them, 206 00:13:44,280 --> 00:13:47,530 Speaker 2: be angry about and just sort of sit with them 207 00:13:47,920 --> 00:13:49,820 Speaker 2: in a very reporter-like way. 208 00:13:49,840 --> 00:13:54,160 Speaker 1: I go back to the notion of I'm supposed to 209 00:13:54,200 --> 00:13:58,760 Speaker 1: tell you the story. Am I supposed to say I 210 00:13:58,840 --> 00:14:02,520 Speaker 1: totally disagree with Peter Thiel's view on the Ukraine war? No, 211 00:14:02,570 --> 00:14:05,229 Speaker 1: that's bull. I mean, do I disagree? 212 00:14:05,270 --> 00:14:05,490 Speaker 2: Yeah. 213 00:14:06,010 --> 00:14:09,590 Speaker 1: I don't share his beliefs on that or many other things. 214 00:14:09,670 --> 00:14:12,679 Speaker 1: But If you want the hot take on whether or 215 00:14:12,720 --> 00:14:15,400 Speaker 1: not you agree with Peter Thiel's politics, my book's not 216 00:14:15,440 --> 00:14:20,100 Speaker 1: for you. I'm telling you how this story happened. 217 00:14:20,840 --> 00:14:24,280 Speaker 2: When we come back, stacking Musk up against jobs and 218 00:14:24,330 --> 00:14:27,510 Speaker 2: answering Isaacson's critics, including those who keep quoting him. 219 00:14:28,410 --> 00:14:28,790 Speaker 1: Stay with us. 220 00:14:41,830 --> 00:14:43,490 Speaker 2: This is a very small detail, but because you're a 221 00:14:43,510 --> 00:14:46,320 Speaker 2: New Orleanian, I have to ask this. You quote Musk 222 00:14:46,400 --> 00:14:49,980 Speaker 2: talking about how if he couldn't skip meals and just 223 00:14:50,000 --> 00:14:52,900 Speaker 2: get his nutrients from like, you know, soylent or liquid 224 00:14:53,520 --> 00:14:55,720 Speaker 2: beverage or whatever, he would just do that. It's very 225 00:14:55,780 --> 00:14:59,240 Speaker 2: Valley thing. And what did you do for food when 226 00:14:59,280 --> 00:15:00,180 Speaker 2: you were alongside him? 227 00:15:01,120 --> 00:15:04,630 Speaker 1: One of the wonderful things about Boca Chica, Texas, and 228 00:15:04,670 --> 00:15:10,990 Speaker 1: this rough little scrub land, there's a canteen that's stocked. 229 00:15:11,620 --> 00:15:16,940 Speaker 1: with amazingly good barbecue, salads, and you can walk in 230 00:15:16,940 --> 00:15:20,380 Speaker 1: 24 hours a day. I could walk from my Airstream trailer. 231 00:15:20,940 --> 00:15:25,160 Speaker 1: And remarkably, it actually had good coffee too, or at 232 00:15:25,200 --> 00:15:28,780 Speaker 1: least good coffee for Texas. But Musk doesn't care about food. 233 00:15:28,860 --> 00:15:31,840 Speaker 1: He doesn't care about fine wines. He really doesn't drink 234 00:15:31,980 --> 00:15:36,280 Speaker 1: that much. Occasionally, you go out to dinner with him 235 00:15:36,520 --> 00:15:41,120 Speaker 1: and a few people, and there'll be craft cocktails, you know, 236 00:15:41,200 --> 00:15:44,820 Speaker 1: I don't know, cactus juice with tequila, and he'll always 237 00:15:44,860 --> 00:15:48,700 Speaker 1: try one and never quite finish it. He never cares 238 00:15:48,760 --> 00:15:53,880 Speaker 1: that much about the food he's ordering. But I know 239 00:15:53,900 --> 00:15:58,530 Speaker 1: that when I finally came off the trail, having traveled 240 00:15:58,610 --> 00:16:01,510 Speaker 1: with him and having been summoned back even in April 241 00:16:01,550 --> 00:16:05,010 Speaker 1: to watch the Starship launch, or then to Austin for 242 00:16:05,050 --> 00:16:08,920 Speaker 1: him to launch XAI, I finally said, okay, I'm going 243 00:16:08,950 --> 00:16:12,450 Speaker 1: to have to start eating right again. And I remember 244 00:16:12,530 --> 00:16:17,470 Speaker 1: eating very carefully, but also craving really good food. And 245 00:16:17,490 --> 00:16:19,690 Speaker 1: so I'd be down in New Orleans, and my wife 246 00:16:19,730 --> 00:16:22,190 Speaker 1: Kathy and I, we made a habit of once a 247 00:16:22,250 --> 00:16:26,510 Speaker 1: week eating at Galatoire's, once a week eating at Herb Saint, 248 00:16:26,610 --> 00:16:30,370 Speaker 1: and once a week eating at Pesh. And maybe once 249 00:16:30,430 --> 00:16:32,690 Speaker 1: every week or two eating at Mosca's, which is a 250 00:16:32,730 --> 00:16:33,350 Speaker 1: great place. 251 00:16:33,410 --> 00:16:34,190 Speaker 2: I've been to Mosca's. 252 00:16:34,250 --> 00:16:37,980 Speaker 1: Yeah, just so. I can remember the taste of really 253 00:16:38,020 --> 00:16:42,920 Speaker 1: good food, having spent two years watching him grab sandwiches 254 00:16:42,980 --> 00:16:43,740 Speaker 1: and hamburgers. 255 00:16:44,500 --> 00:16:47,160 Speaker 2: On Isaacson's book tour for his Musk biography, he was 256 00:16:47,250 --> 00:16:50,890 Speaker 2: regularly quizzed about how Musk compares with jobs, perhaps the 257 00:16:50,910 --> 00:16:53,110 Speaker 2: most obvious foil among Isaacson's subjects. 258 00:16:53,810 --> 00:16:56,870 Speaker 1: At one of my events, a high school student came 259 00:16:56,930 --> 00:17:00,190 Speaker 1: up to the microphone, and he actually had read the 260 00:17:00,230 --> 00:17:00,790 Speaker 1: whole book. 261 00:17:01,070 --> 00:17:01,490 Speaker 2: Impressive. 262 00:17:02,210 --> 00:17:05,250 Speaker 1: He had a question that he said I hadn't answered. 263 00:17:05,730 --> 00:17:09,690 Speaker 1: I said, what's that? He said, was Elon Musk nice 264 00:17:09,810 --> 00:17:16,870 Speaker 1: to waiters and waitresses? I realized that was an insightful question. 265 00:17:16,890 --> 00:17:21,430 Speaker 1: I thought of Steve Jobs. I remember one day at 266 00:17:21,630 --> 00:17:24,850 Speaker 1: a Whole Foods in Palo Alto, there's an older woman 267 00:17:24,890 --> 00:17:29,189 Speaker 1: who was making the smoothie. Steve Jobs just chewed her 268 00:17:29,330 --> 00:17:31,560 Speaker 1: out because she wasn't doing it fast enough and wasn't 269 00:17:31,580 --> 00:17:35,580 Speaker 1: doing it in the right way. I remember Of all 270 00:17:35,619 --> 00:17:41,010 Speaker 1: the things that made me recoil, it was being mean 271 00:17:41,090 --> 00:17:44,929 Speaker 1: to a person making the smoothie or being a waiter, 272 00:17:45,470 --> 00:17:51,609 Speaker 1: like Jobs could be. Musk was actually incredibly rough on 273 00:17:51,650 --> 00:17:55,770 Speaker 1: people he worked with. But all the times I saw 274 00:17:55,830 --> 00:18:00,189 Speaker 1: him where there were waiters or waitresses or somebody at 275 00:18:00,230 --> 00:18:03,050 Speaker 1: a shop or whatever, he would get into sort of 276 00:18:03,090 --> 00:18:07,900 Speaker 1: a jovial mood. And so I don't think he had 277 00:18:09,140 --> 00:18:12,220 Speaker 1: a meanness that would have been reflected in the way 278 00:18:12,300 --> 00:18:17,929 Speaker 1: he treated waiters. And I thought, shoot, that was a 279 00:18:18,030 --> 00:18:21,050 Speaker 1: really good question that kid asked. And I'll probably get 280 00:18:21,070 --> 00:18:22,730 Speaker 1: in trouble with Steve Jobs, but boy. 281 00:18:23,590 --> 00:18:27,889 Speaker 2: Well, Jobs isn't around anymore, sadly, but Musk could still, 282 00:18:28,359 --> 00:18:30,400 Speaker 2: is there something he could do that would make you 283 00:18:31,080 --> 00:18:33,639 Speaker 2: fundamentally rethink whether you should have written the book about him? 284 00:18:34,170 --> 00:18:40,210 Speaker 1: No, I think the book explains correctly who he is. 285 00:18:41,330 --> 00:18:44,889 Speaker 1: And his reputation will go way up and way down 286 00:18:45,200 --> 00:18:50,020 Speaker 1: as it has for the past 25 years. And he'll 287 00:18:50,080 --> 00:18:53,020 Speaker 1: get Starship into orbit someday and he'll be on the 288 00:18:53,060 --> 00:18:57,080 Speaker 1: front page of the paper. And also he will do things, 289 00:18:57,680 --> 00:19:02,520 Speaker 1: be it with Twitter or with self-driving, that'll cause problems 290 00:19:02,800 --> 00:19:06,410 Speaker 1: and be bad. So there will be a roller coaster 291 00:19:06,730 --> 00:19:09,750 Speaker 1: on his reputation, and that will be the case for 292 00:19:09,770 --> 00:19:10,760 Speaker 1: the next 20 years. 293 00:19:11,380 --> 00:19:14,320 Speaker 2: How does that feel to kind of be connected to 294 00:19:14,359 --> 00:19:18,440 Speaker 2: someone who, as you have amply captured, is extremely volatile 295 00:19:18,480 --> 00:19:21,660 Speaker 2: and is also maybe becoming a little more controversial every day? 296 00:19:21,680 --> 00:19:24,450 Speaker 1: Yeah, I mean, it's not great. I would love it 297 00:19:24,490 --> 00:19:27,350 Speaker 1: if he would lie low for like a year, but 298 00:19:27,369 --> 00:19:29,929 Speaker 1: he ain't gonna do that. And that's what this book explains, 299 00:19:29,970 --> 00:19:34,250 Speaker 1: which is at one point, Antonio Gracias, his friend, takes 300 00:19:34,290 --> 00:19:37,090 Speaker 1: his phone away from him when they're traveling and puts 301 00:19:37,130 --> 00:19:40,250 Speaker 1: it in the hotel room safe so Musk won't get up. 302 00:19:40,270 --> 00:19:42,770 Speaker 1: And in the middle of the night, Musk calls hotel 303 00:19:42,790 --> 00:19:45,410 Speaker 1: security and makes them open the safe so he can 304 00:19:45,830 --> 00:19:48,470 Speaker 1: start tweeting out weird things. That's who Musk is. 305 00:19:48,810 --> 00:19:51,300 Speaker 2: And you have this body of work when it comes 306 00:19:51,340 --> 00:19:55,260 Speaker 2: to biographies. You've got Ben Franklin, you've got Einstein, you've 307 00:19:55,300 --> 00:20:00,320 Speaker 2: got Da Vinci, and then you have the living ones, Doudna, Jobs, 308 00:20:00,720 --> 00:20:04,240 Speaker 2: now Musk. And I think it tends to create an impression, 309 00:20:04,640 --> 00:20:08,330 Speaker 2: even sometimes I think they're packaged together for marketing purposes, 310 00:20:08,350 --> 00:20:11,820 Speaker 2: of that all of these people are of a kind. 311 00:20:12,340 --> 00:20:16,399 Speaker 2: They're almost like a trajectory of human achievement. Do you 312 00:20:16,460 --> 00:20:20,820 Speaker 2: think of Musk as fitting in with Da Vinci, Einstein, 313 00:20:20,960 --> 00:20:25,850 Speaker 2: these world legendary figures? Or do you feel like, well, 314 00:20:25,869 --> 00:20:28,050 Speaker 2: the jury's still out on that, but he's the closest 315 00:20:28,109 --> 00:20:29,350 Speaker 2: I can get in modern times? 316 00:20:30,430 --> 00:20:33,330 Speaker 1: I don't think that all the people I've written about 317 00:20:33,830 --> 00:20:38,210 Speaker 1: are of one kind. But the reason you write biographies 318 00:20:38,560 --> 00:20:44,720 Speaker 1: rather than sort of how-to manuals for innovation is that 319 00:20:44,840 --> 00:20:50,740 Speaker 1: each is different. And there's certain common threads, which is 320 00:20:50,760 --> 00:20:56,980 Speaker 1: a passion to push reality into a certain mission that 321 00:20:57,030 --> 00:21:02,859 Speaker 1: you have. But I don't try to say, I'm writing 322 00:21:02,890 --> 00:21:05,859 Speaker 1: about Elon Musk because he's like Benjamin Franklin. 323 00:21:06,380 --> 00:21:09,480 Speaker 2: Do you think he's spoiled other subjects for you in 324 00:21:09,540 --> 00:21:13,060 Speaker 2: that it's difficult to find a subject who has those 325 00:21:13,119 --> 00:21:16,379 Speaker 2: different personalities, all of that contained in one person? 326 00:21:16,859 --> 00:21:19,159 Speaker 1: Yeah, I mean, it would be hard to find a 327 00:21:19,200 --> 00:21:31,410 Speaker 1: contemporary character who comes even close to being as head-snapping, amazing, gut-wrenching, mercurial... 328 00:21:31,280 --> 00:21:38,929 Speaker 1: of a rollercoaster and emotional and professional subject. I can't 329 00:21:39,010 --> 00:21:46,750 Speaker 1: think of anybody who's this fascinating for good and for bad. 330 00:21:47,810 --> 00:21:50,030 Speaker 2: So I want to talk about some of the criticism 331 00:21:50,070 --> 00:21:52,270 Speaker 2: that comes up around the book and getting you a 332 00:21:52,270 --> 00:21:54,950 Speaker 2: chance to respond to some of that stuff. There's Musk 333 00:21:54,990 --> 00:21:58,770 Speaker 2: being a difficult and demanding person, even an asshole, whether 334 00:21:58,820 --> 00:22:02,679 Speaker 2: that matters for how creative he is, how innovative he is. 335 00:22:03,420 --> 00:22:09,310 Speaker 2: And then there's these sort of larger societal accusations, let's say, 336 00:22:09,430 --> 00:22:14,850 Speaker 2: like allowing misinformation or encouraging misinformation or the self-driving and 337 00:22:14,930 --> 00:22:18,490 Speaker 2: people getting killed or the sort of lawsuit against Tesla 338 00:22:18,540 --> 00:22:20,719 Speaker 2: when it comes to racial discrimination. Those seem to be 339 00:22:21,200 --> 00:22:25,020 Speaker 2: two separate ideas. And I'm wondering, we've talked a lot 340 00:22:25,040 --> 00:22:28,200 Speaker 2: about the first one and how you feel about that 341 00:22:28,340 --> 00:22:31,659 Speaker 2: second basket, that question of whether Aside from whether he 342 00:22:31,720 --> 00:22:35,060 Speaker 2: is or isn't a bad person to his employees, there 343 00:22:35,100 --> 00:22:37,740 Speaker 2: are things that he's doing in the world that have 344 00:22:38,180 --> 00:22:40,040 Speaker 2: negative implications. 345 00:22:41,330 --> 00:22:44,590 Speaker 1: Yeah, I think when you barrel ahead impulsively, you do 346 00:22:44,650 --> 00:22:50,370 Speaker 1: things that have negative implications. You know, bad workplace environments. Well, 347 00:22:50,450 --> 00:22:54,890 Speaker 1: it starts at the top because he's all in hardcore driven. 348 00:22:54,950 --> 00:22:59,619 Speaker 1: He's not into what he thinks are touchy-feely HR guidelines. 349 00:23:00,450 --> 00:23:05,220 Speaker 1: And that's bad. Likewise, he pushes a little fast on 350 00:23:05,280 --> 00:23:09,240 Speaker 1: full self-driving. I mean, he feels that humans will kill 351 00:23:09,240 --> 00:23:12,359 Speaker 1: 10 or 100 times more people than a self-driving car will. 352 00:23:12,660 --> 00:23:15,800 Speaker 1: So he doesn't get the fact that a self-driving just, 353 00:23:15,859 --> 00:23:18,940 Speaker 1: you know, one time as it did this once hit 354 00:23:19,040 --> 00:23:21,840 Speaker 1: a side of a big white truck, you know, and 355 00:23:21,859 --> 00:23:24,500 Speaker 1: that's been in the news after three, four years. It's 356 00:23:24,520 --> 00:23:27,510 Speaker 1: still in the news. He says, you know, people focus 357 00:23:27,609 --> 00:23:30,949 Speaker 1: on that, not the million people got killed by humans. Well, 358 00:23:30,970 --> 00:23:34,409 Speaker 1: it's because he doesn't have a real feel for human 359 00:23:34,710 --> 00:23:37,879 Speaker 1: feelings and emotions. He doesn't realize that a self-driving car 360 00:23:37,950 --> 00:23:41,879 Speaker 1: smashing somebody into a truck is going to really shake 361 00:23:41,900 --> 00:23:45,240 Speaker 1: people up more than the fact that a bad driver, 362 00:23:45,440 --> 00:23:49,160 Speaker 1: you know, here on Claybourne Avenue in New Orleans got 363 00:23:49,200 --> 00:23:53,510 Speaker 1: into an accident. So these are the things that his 364 00:23:53,609 --> 00:23:59,949 Speaker 1: engineering mindset doesn't, And. 365 00:23:58,850 --> 00:24:01,230 Speaker 2: I feel like when people bring those things up, they're 366 00:24:01,290 --> 00:24:04,470 Speaker 2: often saying they want you to engage with those things more. 367 00:24:04,790 --> 00:24:08,229 Speaker 2: And we've talked about, you know, explaining what's going on 368 00:24:08,310 --> 00:24:11,970 Speaker 2: versus moralizing. But how do you feel about how you 369 00:24:12,040 --> 00:24:14,719 Speaker 2: engaged with sort of that aspect of Musk? 370 00:24:15,100 --> 00:24:16,959 Speaker 1: Well, I like the fact that people who say I'm 371 00:24:16,980 --> 00:24:19,439 Speaker 1: not as tough on Musk as I should be are 372 00:24:19,500 --> 00:24:22,340 Speaker 1: always using anecdotes from my book to show why we 373 00:24:22,359 --> 00:24:24,840 Speaker 1: should be tough on Musk. And a couple people have 374 00:24:24,920 --> 00:24:28,460 Speaker 1: pointed that out. I mean, certainly if you're looking at 375 00:24:28,520 --> 00:24:32,889 Speaker 1: the bad workplace environments that he may engender either at 376 00:24:32,930 --> 00:24:36,750 Speaker 1: Tesla or at Twitter, that's in the book, you know, 377 00:24:36,910 --> 00:24:42,690 Speaker 1: in no uncertain terms. Likewise, the accidents on the self-driving 378 00:24:42,750 --> 00:24:47,490 Speaker 1: cars are definitely in the book, starting with Autonomy Day 379 00:24:47,650 --> 00:24:50,240 Speaker 1: in 2019 all the way to the present. There's a 380 00:24:50,320 --> 00:24:53,679 Speaker 1: lot of evidence that his obsession with this might be 381 00:24:53,760 --> 00:24:58,060 Speaker 1: moving things too fast. So I'm perfectly happy when people 382 00:24:58,080 --> 00:25:01,109 Speaker 1: say I should have been tougher on Musk, but also say, man, 383 00:25:01,450 --> 00:25:04,609 Speaker 1: read the book. If you want ammunition, both of how 384 00:25:05,230 --> 00:25:07,570 Speaker 1: amazing he can be at times in getting things done, 385 00:25:07,630 --> 00:25:09,889 Speaker 1: but also the rubble he leaves in his wake. 386 00:25:10,590 --> 00:25:14,470 Speaker 2: When it came to the Ukraine Starlink situation, you've talked 387 00:25:14,510 --> 00:25:17,959 Speaker 2: about that, the thing that got corrected in the post 388 00:25:18,100 --> 00:25:21,000 Speaker 2: and Musk tweeting. But maybe you've talked about this, but 389 00:25:21,020 --> 00:25:23,660 Speaker 2: I haven't heard it yet. But I'm interested in what 390 00:25:23,700 --> 00:25:25,830 Speaker 2: it felt like for you. You strike me as someone 391 00:25:25,850 --> 00:25:30,490 Speaker 2: who's relatively unbothered by some of the noise that's around 392 00:25:30,510 --> 00:25:30,750 Speaker 2: these things. 393 00:25:30,770 --> 00:25:32,690 Speaker 1: I think you have to be unbothered by the noise, 394 00:25:32,730 --> 00:25:35,670 Speaker 1: and you have to keep the essence of the story 395 00:25:36,490 --> 00:25:39,600 Speaker 1: in mind. The essence of that story was fine. It 396 00:25:39,619 --> 00:25:43,060 Speaker 1: was correct, which was that night he was deciding whether 397 00:25:43,080 --> 00:25:46,020 Speaker 1: or not to allow Starlink to be enabled or not 398 00:25:46,060 --> 00:25:49,480 Speaker 1: be enabled to allow a sneak attack on Crimea. And 399 00:25:49,500 --> 00:25:51,100 Speaker 1: there was a fix that had to be made because 400 00:25:51,140 --> 00:25:54,820 Speaker 1: it had already been geofenced. So his decision was not 401 00:25:54,920 --> 00:25:58,740 Speaker 1: to permit the movement of the geofencing. I hadn't gone 402 00:25:58,810 --> 00:26:00,590 Speaker 1: into it enough. I just said he turned it off. 403 00:26:00,730 --> 00:26:03,709 Speaker 1: So that was oversimplifying. But I didn't want to get 404 00:26:03,770 --> 00:26:06,929 Speaker 1: distracted from the main thing, which is this private citizen 405 00:26:07,990 --> 00:26:12,030 Speaker 1: is suddenly deciding that night whether or not Ukraine gets 406 00:26:12,050 --> 00:26:15,350 Speaker 1: to do a sneak attack on the Russian fleet in Crimea. 407 00:26:15,790 --> 00:26:20,790 Speaker 1: The essence is a private citizen has that power to decide. 408 00:26:21,090 --> 00:26:24,270 Speaker 1: And neither he nor anybody else corrected that. And then 409 00:26:24,290 --> 00:26:27,650 Speaker 1: I talked to him. I said, well, have you talked 410 00:26:27,690 --> 00:26:31,409 Speaker 1: to the U.S. government? And he turns over power to 411 00:26:31,450 --> 00:26:33,500 Speaker 1: these satellites to the U.S. government. 412 00:26:33,580 --> 00:26:34,180 Speaker 2: At a later point. 413 00:26:34,200 --> 00:26:37,500 Speaker 1: Yeah, at a later point. After that night where we 414 00:26:37,580 --> 00:26:41,900 Speaker 1: talk about it. So you see all of these things happen. 415 00:26:41,980 --> 00:26:44,800 Speaker 1: And I try to have it shown in real time. 416 00:26:45,600 --> 00:26:48,960 Speaker 1: And the essence of the story being How does somebody 417 00:26:49,040 --> 00:26:53,160 Speaker 1: acquire this much power? Why is it that the rest 418 00:26:53,280 --> 00:26:58,500 Speaker 1: of government and other contractors have become so paralyzed and 419 00:26:58,520 --> 00:27:02,000 Speaker 1: sclerotic that they can't do some of these things? And 420 00:27:02,040 --> 00:27:06,160 Speaker 1: then how does he, with his megalomania, finally back down 421 00:27:06,220 --> 00:27:08,520 Speaker 1: and say, maybe I should give up some of this power? 422 00:27:09,220 --> 00:27:12,580 Speaker 2: There's something chilling about Musk's power and influence growing beyond 423 00:27:12,619 --> 00:27:16,010 Speaker 2: his companies, beyond the rocket launch pad and the Tesla 424 00:27:16,030 --> 00:27:19,100 Speaker 2: factory floor. And in the case of Starlink satellites use 425 00:27:19,160 --> 00:27:22,580 Speaker 2: in Ukraine, even Musk himself finds this a little unsettling. 426 00:27:23,020 --> 00:27:26,100 Speaker 2: From failing to understand how people might respond to self-driving 427 00:27:26,160 --> 00:27:30,040 Speaker 2: car deaths, to his outwardly blase approach to controlling global 428 00:27:30,080 --> 00:27:33,550 Speaker 2: geopolitics with a thumbs up or thumbs down, like a 429 00:27:33,590 --> 00:27:38,369 Speaker 2: Roman emperor in the Colosseum. People are not Elon Musk's forte, 430 00:27:38,650 --> 00:27:42,050 Speaker 2: by his own admission, but we are increasingly in his hands. 431 00:27:43,050 --> 00:27:45,270 Speaker 2: And depending on where you stand on Musk, some of 432 00:27:45,330 --> 00:27:50,200 Speaker 2: his ideas can seem either sinister logical, or simply baffling. Take, 433 00:27:50,220 --> 00:27:54,699 Speaker 2: for example, his stated concern about underpopulation and declaration that 434 00:27:54,760 --> 00:27:58,000 Speaker 2: people need to be having more children. Well, more specifically, 435 00:27:58,320 --> 00:28:00,780 Speaker 2: smart people need to be having more children. It's a 436 00:28:00,800 --> 00:28:03,550 Speaker 2: creed he's lived with all 10 of his surviving children 437 00:28:03,590 --> 00:28:06,810 Speaker 2: born by IVF. He's put his money behind it too, 438 00:28:06,990 --> 00:28:09,810 Speaker 2: funding a University of Texas at Austin research group called 439 00:28:09,830 --> 00:28:13,610 Speaker 2: the Population Wellbeing Initiative to the tune of $ 10 million. 440 00:28:14,490 --> 00:28:17,000 Speaker 2: What I wanted to know from Isaacson was... given his 441 00:28:17,080 --> 00:28:20,840 Speaker 2: front row seat to Musk's unusual family dramas. What are 442 00:28:20,859 --> 00:28:24,080 Speaker 2: we supposed to make of this particular Musk obsession? He 443 00:28:24,260 --> 00:28:26,980 Speaker 2: tweets and talks about low birth rates, and he seems 444 00:28:27,020 --> 00:28:29,609 Speaker 2: very obsessed, maybe it's too much, but I think I 445 00:28:29,970 --> 00:28:32,310 Speaker 2: wanted to know, what does this add up to? What 446 00:28:32,369 --> 00:28:34,690 Speaker 2: is this about? I was sort of left, I don't 447 00:28:34,730 --> 00:28:37,230 Speaker 2: understand what this tells me about Elon Musk, which is 448 00:28:37,270 --> 00:28:38,930 Speaker 2: maybe my problem, but... Like a. 449 00:28:38,970 --> 00:28:41,940 Speaker 1: Lot of things with Elon Musk, it goes back to 450 00:28:41,960 --> 00:28:45,380 Speaker 1: the father a bit. It also goes to Musk's theory 451 00:28:45,400 --> 00:28:49,180 Speaker 1: of consciousness issue. The human species is a fragile thing. 452 00:28:49,800 --> 00:28:54,090 Speaker 1: And one of the threats is a low birth rate. Now, 453 00:28:54,170 --> 00:28:56,470 Speaker 1: most of us probably don't think that way. We think 454 00:28:56,490 --> 00:29:00,530 Speaker 1: we're overpopulated. But there is a decline in birth rate 455 00:29:00,770 --> 00:29:07,560 Speaker 1: in many, many countries. And Musk deeply feels that's a problem. And, 456 00:29:07,580 --> 00:29:11,260 Speaker 1: you know, people can totally disagree with that and say, hey, 457 00:29:11,420 --> 00:29:14,850 Speaker 1: overpopulation is a big problem. They can also think he's 458 00:29:14,910 --> 00:29:20,150 Speaker 1: weird to fund IVF for other people or fund clinics. 459 00:29:20,490 --> 00:29:22,190 Speaker 2: It's the kind of thing where people can look at 460 00:29:22,250 --> 00:29:25,709 Speaker 2: it and they can say, he has this vision for 461 00:29:25,750 --> 00:29:29,990 Speaker 2: humanity and it involves people having more children. And then 462 00:29:30,020 --> 00:29:31,640 Speaker 2: there are people who see it through a lens of, 463 00:29:32,060 --> 00:29:34,660 Speaker 2: is this some kind of eugenics situation? I feel like 464 00:29:35,060 --> 00:29:39,520 Speaker 2: people bring these lenses to it. And I'm wondering if 465 00:29:40,250 --> 00:29:42,410 Speaker 2: that has happened in your past work or if this 466 00:29:42,450 --> 00:29:43,410 Speaker 2: is a unique situation. 467 00:29:44,260 --> 00:29:50,219 Speaker 1: I think it's somewhat unique that people have such extraordinarily 468 00:29:50,900 --> 00:29:56,320 Speaker 1: strong feelings for and against Musk. When I started working 469 00:29:56,340 --> 00:29:58,390 Speaker 1: on this book, He was one of the most popular 470 00:29:58,550 --> 00:30:01,250 Speaker 1: people on earth. There's some people who didn't like him, 471 00:30:01,850 --> 00:30:07,090 Speaker 1: but his politics was generally a supporter of Obama. He 472 00:30:07,130 --> 00:30:10,209 Speaker 1: had done really bad, dumb tweets in the past, like 473 00:30:10,270 --> 00:30:12,430 Speaker 1: saying he was going to take Tesla private or calling 474 00:30:12,890 --> 00:30:18,560 Speaker 1: some cave diver a pedophile. But generally, he wasn't that controversial. 475 00:30:19,260 --> 00:30:24,180 Speaker 1: And then his politics shift, and it's reflected in his tweets, 476 00:30:24,580 --> 00:30:27,460 Speaker 1: and he buys Twitter. And so I end up with 477 00:30:27,530 --> 00:30:31,530 Speaker 1: a book in which people either think he's an absolute 478 00:30:31,590 --> 00:30:35,670 Speaker 1: hero or an absolute villain. And if you come at 479 00:30:35,690 --> 00:30:40,050 Speaker 1: it from a frame of Musk is inherently an evil person, 480 00:30:41,070 --> 00:30:45,190 Speaker 1: even having a lot of kids seems like something evil. 481 00:30:46,010 --> 00:30:53,950 Speaker 1: And pushing for self-driving cars or robots seems evil. Likewise, 482 00:30:54,520 --> 00:30:59,150 Speaker 1: If you're one of these starry-eyed fans, even the weird, 483 00:30:59,310 --> 00:31:03,709 Speaker 1: dark things he does on Twitter, people will be slamming 484 00:31:03,770 --> 00:31:08,090 Speaker 1: me for telling the stories of his behavior, both at 485 00:31:08,130 --> 00:31:13,160 Speaker 1: Twitter and at factories. So, yeah, it's a difficulty that 486 00:31:13,260 --> 00:31:19,160 Speaker 1: people frame his every action often based on their own 487 00:31:19,900 --> 00:31:21,330 Speaker 1: love or hatred for him. 488 00:31:23,290 --> 00:31:27,070 Speaker 2: Up next... I ask Isaacson, does Musk really believe his 489 00:31:27,110 --> 00:31:40,670 Speaker 2: own hype? Stay with us. There's a tension, it feels like, 490 00:31:40,730 --> 00:31:45,710 Speaker 2: between the way that Musk talks about that epic idea, 491 00:31:46,010 --> 00:31:49,400 Speaker 2: getting to Mars, helping save humanity with interplanetary species, etc., 492 00:31:50,560 --> 00:31:53,360 Speaker 2: And the way he treats individual people. Like, he doesn't 493 00:31:53,420 --> 00:31:58,000 Speaker 2: like people sometimes. He can be very cruel. And I'm wondering, 494 00:31:58,300 --> 00:31:59,980 Speaker 2: does he really care? Or is he just trying to 495 00:32:00,020 --> 00:32:02,900 Speaker 2: make himself an epic figure? Or is he actually trying 496 00:32:02,980 --> 00:32:05,830 Speaker 2: to solve the energy problem, send us to Mars for 497 00:32:05,920 --> 00:32:06,770 Speaker 2: humanity reasons? 498 00:32:07,190 --> 00:32:11,330 Speaker 1: When Musk first started talking about his three great missions, 499 00:32:12,310 --> 00:32:18,140 Speaker 1: you know, space travel, artificial intelligence, and sustainable energy, I 500 00:32:18,160 --> 00:32:21,120 Speaker 1: thought it was a type of pontifications that you'd do 501 00:32:21,160 --> 00:32:24,310 Speaker 1: for a biographer or do for a podcaster, do for 502 00:32:24,330 --> 00:32:28,190 Speaker 1: a pep talk. And then I'd see him over and 503 00:32:28,290 --> 00:32:34,350 Speaker 1: over again just chant it to himself, like walking around 504 00:32:34,650 --> 00:32:39,070 Speaker 1: the factory for building Starship and things are getting delayed. 505 00:32:39,690 --> 00:32:42,300 Speaker 1: And he would keep saying to himself and others around him, 506 00:32:42,970 --> 00:32:46,400 Speaker 1: we have to have an urgency of getting humanity to Mars. 507 00:32:47,280 --> 00:32:51,640 Speaker 1: And I came to believe that, I don't know if 508 00:32:51,700 --> 00:32:55,739 Speaker 1: he always fully believed it, but I know he believed 509 00:32:55,780 --> 00:33:00,160 Speaker 1: he believed it. I know that may sound strange, but sometimes, 510 00:33:00,260 --> 00:33:03,440 Speaker 1: as Shakespeare teaches us, we become the mask we wear. 511 00:33:04,320 --> 00:33:09,760 Speaker 1: And he had internalized and externalized this so much that 512 00:33:09,880 --> 00:33:14,520 Speaker 1: he was driven by by a fierce urgency that we've 513 00:33:14,780 --> 00:33:17,360 Speaker 1: got to get rockets that can get us to Mars 514 00:33:17,420 --> 00:33:20,219 Speaker 1: within the next few decades, or that we have to 515 00:33:20,280 --> 00:33:25,730 Speaker 1: sustain solar and battery and electric vehicle energy on this planet. 516 00:33:26,130 --> 00:33:32,170 Speaker 1: And I am totally convinced that he is driven by 517 00:33:32,230 --> 00:33:37,990 Speaker 1: his belief in those missions. And then he backfills and 518 00:33:38,050 --> 00:33:40,690 Speaker 1: figures out, well, how can I make money on the 519 00:33:40,730 --> 00:33:46,870 Speaker 1: way But if you're driven mainly by financial or selfish reasons, 520 00:33:48,030 --> 00:33:50,150 Speaker 1: you're not going to start a rocket company. That's not 521 00:33:50,170 --> 00:33:52,570 Speaker 1: a good idea for making money. You're not going to 522 00:33:52,610 --> 00:33:55,450 Speaker 1: start an EV company when every other car company is 523 00:33:55,470 --> 00:33:58,450 Speaker 1: getting out of the business. You're not going to worry 524 00:33:58,520 --> 00:34:02,140 Speaker 1: about robots and you're not going to buy Twitter. So 525 00:34:02,360 --> 00:34:05,600 Speaker 1: I don't think he was motivated by money. He was 526 00:34:05,680 --> 00:34:10,759 Speaker 1: motivated by this almost man-child epic sense of him as 527 00:34:10,980 --> 00:34:14,990 Speaker 1: a hero in a comic book or a video game. 528 00:34:15,989 --> 00:34:19,089 Speaker 2: Well, the Twitter one is interesting because I felt like 529 00:34:19,130 --> 00:34:22,190 Speaker 2: the way you wrote that almost reversed the polls there 530 00:34:22,710 --> 00:34:26,150 Speaker 2: in which he decides to buy Twitter. He impulsively decides, 531 00:34:26,489 --> 00:34:28,870 Speaker 2: gets stuck with it. And then he almost seems to 532 00:34:28,910 --> 00:34:31,910 Speaker 2: be backfilling the mission where he says, I. 533 00:34:32,969 --> 00:34:36,190 Speaker 1: Ask him at one point, how does this fit into 534 00:34:36,210 --> 00:34:39,310 Speaker 1: your mission? Makes no sense. I mean, I'm thinking it's 535 00:34:39,410 --> 00:34:42,130 Speaker 1: idiotic to buy Twitter because he doesn't have a fingertip 536 00:34:42,190 --> 00:34:47,510 Speaker 1: feel for social emotional networks. And he admits, he said, yes, 537 00:34:47,610 --> 00:34:50,190 Speaker 1: maybe it's a lark. Maybe it doesn't really fit in. 538 00:34:50,760 --> 00:34:53,279 Speaker 1: And then later he says, well, maybe it will help 539 00:34:53,340 --> 00:34:58,980 Speaker 1: democracy so that civilization will survive long enough that we'll 540 00:34:59,040 --> 00:35:01,980 Speaker 1: be able to become multi-planetary. And that's why I just 541 00:35:02,020 --> 00:35:04,130 Speaker 1: didn't believe him. And I'm not even sure he believed himself. 542 00:35:04,170 --> 00:35:09,230 Speaker 1: That's just a bullcrap explanation. but he had to try 543 00:35:09,270 --> 00:35:12,710 Speaker 1: to justify it to himself. But my own opinion is 544 00:35:12,750 --> 00:35:16,850 Speaker 1: he kind of stumbled into that impulsively and had mixed 545 00:35:16,890 --> 00:35:18,840 Speaker 1: feelings about it. And if he had to do it 546 00:35:18,910 --> 00:35:20,520 Speaker 1: all over again, I'm not sure he would. 547 00:35:22,080 --> 00:35:25,220 Speaker 2: You've talked about how you think Twitter will just be 548 00:35:25,239 --> 00:35:29,040 Speaker 2: a blip of his legacy, but he certainly can and 549 00:35:29,219 --> 00:35:33,049 Speaker 2: is getting mired in it. And there's this quote in 550 00:35:33,070 --> 00:35:36,040 Speaker 2: the book. It's him saying, I probably spend too much 551 00:35:36,100 --> 00:35:38,040 Speaker 2: time on Twitter. It's a good place to dig your 552 00:35:38,080 --> 00:35:40,620 Speaker 2: own grave. You get your shoulder into it and you 553 00:35:40,660 --> 00:35:45,700 Speaker 2: keep on digging. Do you feel that he could be 554 00:35:46,440 --> 00:35:51,280 Speaker 2: undoing some of that magic, that vision that you captured 555 00:35:51,300 --> 00:35:52,960 Speaker 2: when it comes to space or electric cars? 556 00:35:53,510 --> 00:35:57,430 Speaker 1: Yeah, I personally feel that the time he spends on 557 00:35:57,630 --> 00:36:01,160 Speaker 1: Twitter and the mindshare he devotes to it is not 558 00:36:01,219 --> 00:36:03,520 Speaker 1: as important. It's not as high value as him doing 559 00:36:03,580 --> 00:36:06,480 Speaker 1: something else. And I don't think he's particularly good at 560 00:36:06,520 --> 00:36:11,580 Speaker 1: the social interactions and human emotions that come in Twitter. 561 00:36:12,320 --> 00:36:16,140 Speaker 1: And he admits he's just addicted to it. I don't 562 00:36:16,180 --> 00:36:18,740 Speaker 1: think it's going to be an important part of his legacy. 563 00:36:18,780 --> 00:36:20,980 Speaker 1: It's not going to be a great part of his legacy. 564 00:36:21,040 --> 00:36:24,020 Speaker 1: I think it makes the book more interesting for this 565 00:36:24,080 --> 00:36:27,100 Speaker 1: guy to go down this rabbit hole, but also near 566 00:36:27,140 --> 00:36:29,879 Speaker 1: the end of the book to say, you know, this 567 00:36:29,989 --> 00:36:33,960 Speaker 1: isn't the best use of my time even talking about Twitter. 568 00:36:34,160 --> 00:36:37,620 Speaker 1: He said, we probably could be talking about more important things. 569 00:36:38,200 --> 00:36:41,120 Speaker 2: It's also, it's made him disliked in a way that 570 00:36:41,239 --> 00:36:44,180 Speaker 2: I feel like he wasn't disliked before. I mean, if 571 00:36:44,219 --> 00:36:47,380 Speaker 2: you look at the category of things that people dislike 572 00:36:47,420 --> 00:36:50,700 Speaker 2: him for, Twitter and things he's said on Twitter and 573 00:36:50,780 --> 00:36:54,940 Speaker 2: done with Twitter occupy a large percentage of those things. 574 00:36:55,710 --> 00:36:58,950 Speaker 1: Absolutely. When you look at the controversies caused and for 575 00:36:58,989 --> 00:37:04,850 Speaker 1: that matter, the enmity and hatred that he's engendered, about 95% 576 00:37:04,850 --> 00:37:08,090 Speaker 1: of that comes either from what he says on Twitter 577 00:37:08,210 --> 00:37:10,069 Speaker 1: or what he does on Twitter or what he does 578 00:37:10,190 --> 00:37:10,850 Speaker 1: to Twitter. 579 00:37:12,800 --> 00:37:16,180 Speaker 2: Musk is polarizing, arguably one of the two most polarizing 580 00:37:16,239 --> 00:37:18,680 Speaker 2: figures of our time. I'll let you guess the other. 581 00:37:19,340 --> 00:37:22,460 Speaker 2: His fans can be slavishly adoring. His critics can be 582 00:37:22,540 --> 00:37:25,890 Speaker 2: blind with rage. But if there was one common thread 583 00:37:26,150 --> 00:37:29,089 Speaker 2: among the more critical takes on Isaacson's biography, it was 584 00:37:29,130 --> 00:37:32,950 Speaker 2: a demand for more judgment, or at least analysis, from Isaacson. 585 00:37:33,489 --> 00:37:36,030 Speaker 2: What was the ultimate meaning in all these stories he'd gathered, 586 00:37:36,310 --> 00:37:39,730 Speaker 2: these hours at Musk's side? Were we supposed to believe 587 00:37:39,770 --> 00:37:42,310 Speaker 2: that he was some kind of tortured genius? Or that 588 00:37:42,350 --> 00:37:44,750 Speaker 2: he was a cruel tyrant who'd muscled his way to 589 00:37:44,790 --> 00:37:47,870 Speaker 2: valley success and was now inflicting a dangerous outlook on 590 00:37:47,890 --> 00:37:50,410 Speaker 2: the world outside it? What did it all add up to? 591 00:37:51,410 --> 00:37:53,870 Speaker 2: For two days, I played out different versions of this 592 00:37:53,910 --> 00:37:54,910 Speaker 2: question with Isaacson. 593 00:37:55,469 --> 00:37:59,509 Speaker 1: I'm here to be as straightforward as I can with 594 00:37:59,570 --> 00:38:03,100 Speaker 1: a reader in mind to tell you stories that I 595 00:38:03,140 --> 00:38:10,500 Speaker 1: think are very revealing, somewhat exciting, somewhat appalling, but always informative. 596 00:38:11,080 --> 00:38:14,069 Speaker 1: And in face of the criticism that, well, maybe I 597 00:38:14,090 --> 00:38:17,509 Speaker 1: didn't render too much judgment, I tried pretty hard to 598 00:38:17,610 --> 00:38:20,969 Speaker 1: pull back a bit to say, You can kind of 599 00:38:20,989 --> 00:38:23,370 Speaker 1: tell what I think by the way I'm telling this story, 600 00:38:23,489 --> 00:38:26,629 Speaker 1: but I'm not going to hammer that into you. You 601 00:38:26,730 --> 00:38:30,670 Speaker 1: should wrestle with each of these things and figure out 602 00:38:30,830 --> 00:38:33,850 Speaker 1: how it fits with your own vision of life. 603 00:38:34,310 --> 00:38:36,870 Speaker 2: You never say to yourself, maybe I should put 10% 604 00:38:36,870 --> 00:38:37,670 Speaker 2: more judgment in there. 605 00:38:37,710 --> 00:38:41,420 Speaker 1: No, no. That's something I cop a plea to totally. 606 00:38:41,739 --> 00:38:47,160 Speaker 1: I certainly don't feel in any way bad that I 607 00:38:47,200 --> 00:38:49,830 Speaker 1: didn't impose more of my judgments in it. 608 00:38:50,620 --> 00:38:52,200 Speaker 2: There's a lot of writing in the book about the 609 00:38:52,239 --> 00:38:57,140 Speaker 2: chaos that surrounds Musk. But then I wondered, you have 610 00:38:57,180 --> 00:39:00,430 Speaker 2: had many war reporters working for you that you're responsible 611 00:39:00,450 --> 00:39:03,850 Speaker 2: for in some sense. And so do you feel like 612 00:39:04,250 --> 00:39:07,569 Speaker 2: the reporting and editing that you did prepared you for 613 00:39:07,590 --> 00:39:10,090 Speaker 2: the chaos of Musk or to say like, this is 614 00:39:10,130 --> 00:39:13,290 Speaker 2: not real chaos compared to other types of reporting? 615 00:39:13,850 --> 00:39:16,420 Speaker 1: Every now and then when Musk is doing something incredibly 616 00:39:16,480 --> 00:39:20,259 Speaker 1: chaotic or has himself worked up into a lather, I 617 00:39:20,360 --> 00:39:24,680 Speaker 1: do remember times where things were much worse. And I 618 00:39:25,239 --> 00:39:28,210 Speaker 1: remember being in Belfast in Northern Ireland when I worked 619 00:39:28,230 --> 00:39:31,340 Speaker 1: for the Sunday Times and all the explosions. And I 620 00:39:31,380 --> 00:39:34,900 Speaker 1: certainly remember the Gulf War when I was at CNN 621 00:39:35,620 --> 00:39:39,839 Speaker 1: and went out to one of America's aircraft carriers, which 622 00:39:39,910 --> 00:39:45,290 Speaker 1: is where CNN had some of its reporters embedded. And 623 00:39:45,330 --> 00:39:48,440 Speaker 1: I think, okay, When we think things are going bad, 624 00:39:48,580 --> 00:39:52,270 Speaker 1: let's remember there's some really bad things happening in this world. 625 00:39:53,010 --> 00:39:56,850 Speaker 1: And I wish if I could do many things for Musk, 626 00:39:56,989 --> 00:39:59,870 Speaker 1: it would sometimes be calm down a bit. Don't be 627 00:39:59,930 --> 00:40:04,569 Speaker 1: so apocalyptic about things. Because he has an apocalyptic mindset. 628 00:40:13,739 --> 00:40:16,759 Speaker 2: You told a story about... going to Northern Ireland when 629 00:40:16,780 --> 00:40:19,560 Speaker 2: you're a reporter and you were with another reporter and 630 00:40:19,580 --> 00:40:22,080 Speaker 2: you left the hotel and the hotel got bombed. And 631 00:40:22,120 --> 00:40:26,000 Speaker 2: then he actually later died reporting in El Salvador. 632 00:40:26,260 --> 00:40:26,440 Speaker 1: Yeah. 633 00:40:27,219 --> 00:40:31,980 Speaker 2: And the question I had was, what's the lesson from that? 634 00:40:32,360 --> 00:40:36,540 Speaker 2: Like leaving the hotel saved you in a way, but 635 00:40:36,580 --> 00:40:42,070 Speaker 2: he then was killed taking risks. Where do you triangulate 636 00:40:42,110 --> 00:40:42,810 Speaker 2: the lesson in that? 637 00:40:42,830 --> 00:40:46,620 Speaker 1: One of the things you learned is that sometimes there 638 00:40:46,700 --> 00:40:51,680 Speaker 1: are no lessons. That sometimes things happen and they're random. 639 00:40:52,370 --> 00:40:57,930 Speaker 1: Sometimes a sniper bullet kills somebody. Sometimes risk-taking can get 640 00:40:57,950 --> 00:41:04,520 Speaker 1: you killed. Sometimes not taking enough risks makes you paralyzed. 641 00:41:05,360 --> 00:41:12,540 Speaker 1: So there's not always easy lessons. And those stories happen 642 00:41:12,580 --> 00:41:16,570 Speaker 1: to be valuable, because they tell you that there's a 643 00:41:16,660 --> 00:41:22,469 Speaker 1: mosaic in life. Sometimes complex patterns are there, and sometimes 644 00:41:22,969 --> 00:41:25,210 Speaker 1: you can't see the pattern just with one or two 645 00:41:25,290 --> 00:41:30,609 Speaker 1: data points. Maybe you should restrain yourself. Maybe, maybe there's 646 00:41:30,650 --> 00:41:33,180 Speaker 1: not a hot take to be had. Maybe there's not 647 00:41:33,219 --> 00:41:39,100 Speaker 1: even a lesson. It's just a part of this beautiful 648 00:41:39,200 --> 00:41:45,790 Speaker 1: complexity of humans and human life that And you appreciate 649 00:41:45,850 --> 00:41:51,350 Speaker 1: those patterns, and eventually they lead to intuitions as opposed 650 00:41:51,450 --> 00:41:52,430 Speaker 1: to quick lessons. 651 00:41:53,750 --> 00:41:55,950 Speaker 2: That's a great ending for this whole show, perhaps. I 652 00:41:55,969 --> 00:41:57,299 Speaker 2: just want to point that out, so I'll have that 653 00:41:57,360 --> 00:41:57,719 Speaker 2: on tape. 654 00:41:57,940 --> 00:41:59,520 Speaker 1: Don't ask it again. I'll never be. 655 00:41:59,540 --> 00:42:00,580 Speaker 2: Able to repeat that. 656 00:42:00,640 --> 00:42:02,919 Speaker 1: We've got it. But it has the virtue of being true. 657 00:42:02,980 --> 00:42:03,759 Speaker 1: I feel that way. 658 00:42:07,480 --> 00:42:10,279 Speaker 2: On Musk with Walter Isaacson is a production of Kaleidoscope 659 00:42:10,540 --> 00:42:13,310 Speaker 2: and iHeart. This show is based on the writing and 660 00:42:13,370 --> 00:42:17,050 Speaker 2: reporting of Walter Isaacson. It's hosted by me, Evan Ratliff. 661 00:42:17,390 --> 00:42:21,660 Speaker 2: Produced by Lizzie Jacobs. Assistant production from Serena Chow. Mixing 662 00:42:21,719 --> 00:42:25,160 Speaker 2: and sound design by Rick Kwan. Thomas Walsh did the engineering. 663 00:42:25,640 --> 00:42:29,360 Speaker 2: From iHeart Podcast, the executive producers are Katrina Norvell and 664 00:42:29,480 --> 00:42:33,839 Speaker 2: Allie Perry. For Kaleidoscope, it was executive produced by Mangesh Hatikador, 665 00:42:34,180 --> 00:42:38,280 Speaker 2: with an assist from Oz Wolishan, Kostas Linos, and Kate Osborne. 666 00:42:39,239 --> 00:42:43,930 Speaker 2: Special thanks to Bob Pittman, Conal Byrne, Will Pearson, Nikki Etor, 667 00:42:44,370 --> 00:42:48,330 Speaker 2: Carrie Lieberman, Nathan Otoski, Allie Gavin, and the folks at 668 00:42:48,550 --> 00:42:51,170 Speaker 2: WWNO who let us use their beautiful studio in New Orleans. 669 00:42:51,890 --> 00:42:54,230 Speaker 2: If you like stories about writers and their process, check 670 00:42:54,250 --> 00:42:56,950 Speaker 2: out my other show, The Long Form Podcast. If you 671 00:42:56,969 --> 00:42:59,330 Speaker 2: want a story about a different South African programmer who 672 00:42:59,350 --> 00:43:01,609 Speaker 2: became one of the world's biggest criminals, you can check 673 00:43:01,630 --> 00:43:04,950 Speaker 2: out my book, The Mastermind. And for more shows from Kaleidoscope, 674 00:43:05,130 --> 00:43:09,090 Speaker 2: be sure to visit kaleidoscope.nyc. Thanks so much for listening. 675 00:43:12,320 --> 00:43:12,700 Speaker 2: Thank you.