Ep. 145 - Mick Ebeling: I'll Teach You How to Do Impossible Things

Transcript

This isn't your average business podcast, and he's not your average host. This is the James Altucher Show on the choose yourself network. Are you hiring? Do you know where to post your job find the best candidates? With ziprecruiter.com, you can post your job to 100 plus job sites all with a single click. Just post once and watch your qualified candidates roll in to ZipRecruiter's easy to use interface. So right now, my listeners can post jobs on ZipRecruiter for free by going to ziprecruiter.com/james. That's ziprecruiter.com/james. One more time because I really want you to try it for free just to see how easy it is. Go to ziprecruiter.com/james. If you like audio books, then you need to check out today's sponsor, Audible. Audible has audio books from the leading audio book publishers, broadcasters, entertainers, magazine and newspaper publishers, business information providers, and one guy named James Altucher. You can catch up on all the hot new books you've been meaning to read while on your daily commute with Audible. So just for listeners of this podcast, Audible is offering a free 30 day trial membership. Go to audible.com/james to start your free trial. Go to audible.com/james to start now. Today on the James Altucher Show. What am I most concerned about? I'm really, really concerned about the rise of superintelligence. And I join in this instance, I join a very impressive crowd of Elon Musk, Bill Gates, Stephen Hawking, Bill Joy, a number of people that I think there's evidence to say are the great technological thinkers of our era. What's the switch that will flip that makes you actually worried? When we get to artificial intelligence at the superintelligence level, the degree of intelligence that we're describing here is impossible for us to really get our arms around. It's a big, big issue. So what's the flip of the switch? I think what we're talking about is when a machine gets so extraordinarily smart that it has a certain amount of self awareness or sentience, and then it's concerned about survival. Someone said to me the other day, oh, well, but when will a machine have an original thought? And the answer is they already have had many original thoughts. Oh my gosh. I'm a little bit nervous. I've got Mega Spy, R. P. Eddy on the podcast. Just wrote this. When's this book coming out? May 23rd. May 23rd. Warnings. Basically, I'll describe it for for a second. It's all of these things where we had massive warnings, big high stakes of world events like 9 11, Madoff, Fukushima, the financial crisis, pandemics, climate change, all these things where we've had major world catastrophes, and somebody knew everything. So there was a warning. There was a legit warning that was communicated up the ranks. Nobody listened or a few people listened. Why did nobody listen? What catastrophes are gonna happen in the future? How we could've how we can start listening to the real, as you call them, Cassandras. But you're the expert on this because you and Richard Clark, your coauthor, because you're you've been on the ground. You've been in the trenches for all of these events and in 2 things. This is really important. One is you're a mega spy, and I'll get to that in a second. The other is totally by coincidence, you and I were on a plane, a year ago. I didn't know you. I didn't know you I didn't know you were gonna write a book, And you started, we started talking. You know, we're on a flight from California almost a year ago to the day, actually. It was, like, late May, 2016. And you were telling me this crazy s**t about being a spy and all of these things. And I was I think I don't didn't let you sleep. Like, I was asking you questions for, like, 3 straight hours. And, by the way, I just wanna say, you've lost a lot of weight since then. That's the best news. You you were eating I was wondering to myself. You were eating garbage, like, the entire like, every time the woman came by, would you like another of this, sir? You were just like and then finally, they had to, like, come in with the garbage bag and, like, pick up all the wrappers and bottles. But you were telling me all this stuff, so I wanna get to the book. But first, I wanna, maybe describe a little bit oh oh, one other thing I wanna mention about your background. Right now, you run what I would almost call, and you could correct me, almost like a mercenary spy agency. So, like, governments hire you to spy on other governments except, of course, the US. Because I remember asking you, like, why was oil crashing? At the time, oil was crashing. And you were like, well, this government hired us. I can't say who. And we have people in this government's prime minister's office that's secretly on our payroll, and this is what happened between Saudi Arabia and Venezuela and Nigeria and the US. And you kinda broke it down, and you're right. And the other thing you were right on is that and, again, this is a year ago. You called Trump. So Good. You you were you gave this amazing definition of income inequality and basically said that's why we have a Donald Trump right now and a Bernie Sanders. You said that's why these fringes are getting so pop these populist movements are happening. So so maybe before I wanna ask you more questions about the conversation we had on the plane because you blew me away there. But then I wanna ask you about this. But maybe just describe really briefly, your your background. Well, first You've had so many jobs. I didn't James, thanks for thanks for having me. First, just a couple things. You thought we sat next to each other by mistake, but maybe it wasn't such a mistake. Right? If I found such a megaspi as you think, then perhaps it was an intentional bump. Well, it could be because our we then it turns out we have a mutual connection who's been on this podcast many times, Ryan Holiday. And Ryan's like, have you should have R. P. Eddy on the podcast. And I'm like, oh my god. That's the guy I sat next to on the plate a year ago. So maybe some things aren't coincidence. Maybe I'm just a pawn in your international spy thriller. If only. And you know that it's funny because there's something called the passenger effect, where you sit next to someone on an airplane, and you just tell all these secrets you wouldn't otherwise tell. So, hopefully, I wasn't, too too indiscreet when we sat down. Well, after this podcast, if you're not arrested, then then you're okay. Okay. So let's correct a couple of things that we're mentioning here. I am not a super spy. I'd say Ergo might be one of the greatest intelligence firms in the world, my firm. I founded about 12 years ago with some great partners and we founded it to work for the US government and I'll get to that in a second. So my background is pretty simple. I was a really, really lucky guy. I got to study neuroscience and then I got to work at the US government for about 10 years with some extraordinary bosses. I got to carry the bags with some great men including Richard Clark. So my co author and I, he hired me at the National Security Council. The office was in charge of all kind of terrorism, chemical and biological weapons, disease. It was this mega issue office with about 5 people in it. This is back when the NSC was small, not And you were in charge of also making sure kind of filtering and seeing what information would get to the White House. That's what the NSC does. Right? So the NSC, at least by its the best definition is, I would say, probably about 60 to a 100 professional staff members. Each one has one issue area. And your job is to work within the interagency state, DOD, CIA, FBI, everybody, and make sure the right information gets up to the president and the right decisions come down from the president. So so as an example, if and this is what kind of happened with you, you know, you or Richard Clark, or both of you, you get this feeling in early 2001 that, Osama Bin Laden is planning something big. You try to communicate that upwards, and then Yeah. Well, that's a great point. So when the system doesn't work and no one's listening to you, it's like any other system that doesn't work. So at that point, Dick was and that, you know, look, Dick is a little, he doesn't want to talk about himself being a Cassandra in this book. And if you look through it, mentions it. We only mention it briefly in the introduction. But Dick is sort of the reason why we're writing this book because in my mind, he and John O'Neil who died at 9:11 and some other people were the great Cassandras of 9:11. So let's just quickly define a Cassandra before we go too far here. Right? So Cassandra from Greek mythology, refused to sleep with 1 of the gods. Apollo. Apollo. So he said, look, you know, no no good. I'm gonna make sure you pay for that. So he first gave her the blessing of being able to see the future. She could foretell any future disaster. She could see it in vivid color. But he also said, oh, and guess what? By the way, no one's going to believe you. Now, she happened to live in Troy. Remember a big horse showed up one day. She kept saying, look, the whole place is going to burn to the ground. This is a big deal. No one believed her. She She could foresee everything with great details. She was fact based, evidence based, and she burned to death in Troy like everybody else. So that's Cassandra. Well, just like this is a stupid question. But if you had a choice, gift of prophecy, but no one would believe you or, you're a total idiot and everyone's always gonna believe you, which would you choose? Well, I think in Cassandra's case, and you see in some of our Cassandras in our book, it's a real cross to bear. It's an unbelievable burden to know with terrific detail and vividness, you know, if you don't put the Fukushima nuclear reactor 20 feet higher or build a higher seawall or put better seals on the doors of the generator, we're gonna have a massive nuclear disaster. And this poor guy, who's one of the Cassandras we profiled in the beginning of the book, spends years years years trying to get the nuclear regulatory authority in Japan to listen to him because he can see exactly what will happen, and no one listens to him. So so so I I wanna I wanna follow-up on that more. But the book itself is called warnings because you're you're what you're suggesting is that there are things that are gonna happen in the future. There are Cassandras right now that nobody potentially is listening to, and you're trying to establish these are the things we should pay attention to. Right. So this is the big idea. And it look. I think this is But I'm sorry to interrupt. I'm totally I'm gonna interrupt. I'm totally sorry to interrupt. But you gave me some advice that I thought was so fascinating. I've quoted you a thousand times. That's why it's such a great coincidence. We're we're sitting across from each other. How do you when you're talking to somebody, what are 3 or 4 things you use to determine if someone's lying? Whether it's an interrogation or just in a relationship or just in a business negotiation. You you had some techniques to determine if someone you were interrogating was lying, but these these I found these techniques to work in many situations. Well, we've been lucky to get to work with some of the great heads of deception detection and the polygraph center and others at CIA who are, you know, really studied to the PhD level on what we call deception detection. And, you know, a couple simple look, the number one rule, bar none, is make sure you know a question you wanna get answered before you start the conversation. What's an example? Let's imagine I wanna go I I'm a stock analyst. I'm Meredith Whitney. I'm trying to figure out Citibank in 2007. She's the first chapter in our book, one of the first chapters in our book. And she sits down with the CFO and there's another analyst there. The other analyst from another large bank says, I'm not I have given up trying to understand your financial Citibank because you're just so great, so big. It's just too complicated. So Meredith says in the book, and it's a fantastic story, that her jaw dropped. She's like, how can you stop trying to figure out the largest company in the world? You are a 3rd party analyst for a research firm giving buy or sell recommendations. What's wrong with you? So she knew what she wanted to understand. Right? She knew from the get go, are they solvent? Can they pay their dividend? Where are they going as a company? She had a very clear set of questions. So when she had her interviews and did her modeling, she knew what she needed answered. Right? When you started this interview today, you may have had a couple questions you really cared about. This isn't as high stakes as some other things. But when you know what it is you wanna have answered, why am I spending my time talking to this person, then you better make sure that you have a strategy to get that question asked very clearly. That's number 1. Number 2, make sure that question is answered. Right? So as humans, we're herd animals. Right? We don't really like to disturb the herd. We don't really like to cause problems with other people next us. It's a very human emotion to not want to get thrown out of the boat. It's very deep in all of us. So if I'm coming down and I know I want to go long on James' company here but I want to really understand the inner workings and I need to know how much you paid for that microphone. And I know when I go in, here's the 3rd question I'm going to ask. I'm going to ask it very directly and I want to get the right answer. If you're going to defer that answer and not answer that question, I've made a huge mistake. So one, no immediate You made a huge mistake. If I'm not forcing you to answer the question I care about, then I'm not properly doing my interrogation, doing my investigation. Or you're lying. Or you're lying. So certainly then we now you're starting to get into the questions of how can I what indications do I have that you are deceiving me? And there's a whole variety, but one of them is you're you're obfuscating your answers. You're not telling me the answer. If I say, this is a classic one, right? If I say, James, my information is you paid $1,000 for the microphone. That's way too much. And if you come back and say defer, deny, deflect, defer. If you say, you know, look, I I why do you care about the price of my microphone? Or, you know, your microphone looks expensive too. Or I don't know. Let's go find let's go find someone else who may understand the microphone pricing issue. I'm not aware of it. All those things are indications of deception. They do not mean you're lying for sure. The whole thing has to be a mosaic. So so I I wanna put it in a relationship context. Let me ask you if you agree or not. If if if someone asks in a relationship, oh, where were you last night? And let's say the other person says, oh, I was hanging out with friends. They didn't quite answer your question. Yeah. Precisely. Or, you know, why do you wanna know? Or don't you trust me? Or any other situation like that. You know? And you notice this throughout your conversations, notice notices walk watching different people on the media. You know, if you're if you're asked a direct question, you probably are gonna give a direct answer if you're telling the truth. And so so That's a good one. In a job context too, like and you say you say to your boss, am I gonna get fired, in all these layoffs? And if the guy says, well, the company's doing a lot of planning right now, that's also could be either Yeah. Deception, deflection, or And you're gonna feel that when you ask that question. Another I'll I'll give you one other idea, one other kind of tip I think is a good one, and it's called sort of, truth setting. So as soon as you start that conversation, job interview, something like that where I'm ultimately trying to get to the answer, a conversation on earnings for a company, ask a series of questions in the beginning that put the person relatively at ease and also that are just fact based questions. Right? Who's your boss right now? What's your address? Where do you live? How long have you been here? Where do you live? What's your favorite you probably wouldn't ask what's your favorite color. But a series of questions that set you sort of a non alerting basis as you're as you're being asked. But that's more of a that's more of a a parlor game for us. No. No. But take but take that to a second level. So then you ask more and more complicated questions, and then you see how they react or what what happens. Because because more complicated questions, they might actually have a harder time answering. Absolutely. And one great lesson that that, you know, we learn from some of the terrific trainers who who who teach this stuff stuff is just because someone seems really, really nervous in a conversation, just because they're looking around the room, looking left, looking right, picking their hair, picking linen off their jacket, obviously getting answers does not mean they're lying, right? You need to establish a baseline what this person's like. And you also have to understand based on the way you're confronting them, the situation that they're in, a lot of people are going to be very nervous, right? Because remember, we are herd animals. We don't want to get thrown out of the boat. I don't want to ask you a really offensive question and get you upset. And you don't want to be asked an offensive question to get really upset. That's very much part of the human, I don't want to say dialectic, part of the human dialogue. And that's why just moving afield for a second, there's, you know, you've heard the idea of Crocker's rules, you know, other concepts of how to have conversations. So one of our Cassanders is a guy named Eli Yudkowsky. And Eli is a real seer on artificial intelligence. So he's in the second half of the book where we're describing folks who claim and really believe that bad news is coming but aren't being totally listened to now. Right? So Eli is one of those individuals. And and Eli, like many of our proven Cassandras who said, you know, bad things are gonna happen. Please, please, please pay attention. Here's data. Listen to listen to me, and they were ignored and disaster happened. Second half are these folks who are predicting disaster. One commonality amongst almost all of them is that they have what we call off putting personalities. Now Eli Like Harry Markopolos, the paid off guy. Yes. And I like Harry. Very, very too. He's I don't think I don't think Meredith's abrasive. I I think so. Abrasive, but I think she was, the media wasn't used to her type of personality. I would put it that way. I think Meredith's a fascinating example. Because, you know, she's actually an extraordinarily, you know, presentable, kind, gracious, well mannered person, great conversationalist. And the vitriol that came on onto her for predicting City, Lehman, and Bear. Right? I mean, she got it right three times in a row Yeah. Is stunning. And I and I I if that was a man who made those predictions, you would have a very different response that it hap that Well, Nouriel Roubini was kind of in that camp, and he's Doctor Doom now. Like, he was put on a pedestal. Absolutely. And and another example is Nouriel Roubini has been I mean, I don't know the exact number, but how many, what is the what's the joke? Nouriel is called 8 of the last two downturns. Right. You know, he's a very, very smart guy. And I'm not talking about him individually. But there are a lot of folks who get it wrong who don't get the kind of opprobrium that Whitney, Meredith Whitney got after her calls. So but I want to Crocker's rules quickly. Crocker's rules is this idea that I'm gonna communicate with you as clearly and directly as I can, and I'm not worried about your feelings or mine. And so Eli follows Crocker's rules. Right? He's in a rush to get things done. I think Harry probably I don't think he says Harry Markopolos who called Madoff. I don't think he says I follow Crocker's rules, but he certainly does when you meet him. And so does Meredith. She's a very direct speaker, particularly when she's doing her her job. But so different aspects of different people make them people that we you know, it's a little harder for us to listen to them. Not Meredith, what the other one said, these off putting personalities. So so I I wanna, and I I have so many questions about each of the Cassandras and also about what's what's happening in in the future. But you had one example where you were interrogating someone. I won't say who, but you you you established that baseline. You were also in a chair that didn't have rollers, and they were in a chair with rollers. And you noticed, at once you So this is just an old trick. Right? So one great one great trick. And and and a lot of times, professional interrogators of which I was not, am not one, but one who are, you know, people who are really, really good at interrogation. One great trick is to put you in a a boardroom chair on a slick surface with wheels on your chair. And it doesn't matter if I have wheels or not, but I know what I'm doing and you don't know what I'm doing. And the more opportunities I give you to physically remove yourself from me, push yourself back slowly, slowly, slowly, swivel your chair, more indications I can have of sort of the tension inside of you. And so we don't want to get into details but there are, you know, there are stories of of people interrogating folks and literally they start at the middle of the boardroom table. It's a picture, it's an oval. By the end of the interrogation, they're all the way at the corner, the far end of the table because just throughout the hour and a half or whatever it is, the guy just inches back a little bit, a little bit, a little bit. And so you feel that it's gone beyond the line where, obviously, there's some, not necessarily deception, but something's going wrong in the conversation. Again, you don't really you can't you can't say any one of these things means someone's lying. But the the terrific interrogators, which I am not one, the ones who are really, really good but I am short of not sure. Those are the ones who are very, very good at this, you know, we'll put this all together in the supercomputer above their shoulders and their brain, and they'll figure out, you know, what I'll tell you what. There's there's a story you and I were talking about. I was in a one of the great interrogators that I've ever met, his name is Barry. We'll leave it at that. So Barry I was in a large group meeting, and Barry asked a question of all of us where we had to answer sort of the only appropriate answer was an anodyne yes. Right? Otherwise, everyone would have sort of revealed something else. And I just we all said yes, yes, yes. And just by the virtue of me just answering yes to that question, he somehow knew that I was being deceptive. Right? Why were you being deceptive there? It wouldn't have been appropriate for me to say no in that group. Because you had some knowledge that you weren't allowed to. It just would have been revealing something I shouldn't have revealed. So I guess what I'm trying to say is, you know, people who are good at this are really, really good at it, and there's not many of them. You told me that story, and you told me that story in the context of microexpressions. Yeah. I'm not sure if he used microexpressions or not. He probably did. But, you know, let's What are microexpressions? Microexpressions is more theoretical than proven. But it's the concept that within your face, as you're having a conversation, watching media, doing whatever you're doing, you're betraying a huge amount of your emotionality and thinking by virtue of musculature on your face. Because these things move faster than your thoughts can control control them. Yeah. And and and they also probably move faster than my eyes can really perceive. Right? So, you know, some folks have more placid faces. Some people have more animated faces. But throughout a conversation, you know, you're going to move your eyes in different directions, your eyelids, your eye eyebrows in different directions, the corners of your mouth. All those things people theorize can be deciphered to understand at least someone's truthfulness. I am not a pro at it, but some folks are and really built their careers around micro expressions. But worth noting, and it's quite interesting, they're experts on on voice tenor, timber, and what your voice sounds like to determine if you're lying or not. They literally could listen to this podcast probably and say who's telling the truth or not. There's experts on the word choice you use in written documents that are really, really talented and they work for insurance companies. And when you file your car crash claim and they ask you, please write 2 paragraphs about what happened, experts can look at those paragraphs, not the handwriting but the words you use and say, this seems more deceptive. This is more likely deceptive than the other 99 we got this week. That's so fascinating. And, again, we're gonna get into all this. But, you know, it's such an important issue for people to determine if the people around them, whether it's loved ones or employee fellow employees or bosses or business dealings. It's so important to determine what the real agendas are, in the people around you, whether they're lying or not. What's, like, some tips people can do to say? I would just say the punch sign of all this is, other than sociopaths, and they are amongst us. It's a whole other conversation. But other than sociopaths, most humans don't want to rock the boat. They don't want to get kicked out of the herd. And when they lie, they feel uncomfortable about lying. That's why the guy in the chair moves around the table. That's why people don't answer the question exactly with hard words when they're lying. That's why people's faces start contorting when they're telling lies. That's why people start fidgeting. Now remember, don't don't put this podcast down and then go talk to somebody and notice they're fidgeting and saying they're lying. It's much more complicated than that. And the people who try to tell you, oh, if you look up to the left, they're lying and up to the right and it's true, baloney. It's it's much more in-depth than that. But remember, we as humans want to stay in the boat. We don't want to upset people. And thereby when we lie, it it it's a certain degree uncomfortable for us. And and those that uncomfortableness can come out in different ways. So that's what you're looking for is the manifestations of someone being uncomfortable. Sociopaths, don't betray as much or any uncomfortableness with the lying. Because they're kind of, they're not in touch necessarily with the side whether they they are lying or not, like, for them? No. They they well know they're lying, but they have no they do not care about the feelings of others, right? So they, by definition, a sociopath has no concern about how you feel, the pain you're in, your situation, etcetera. And because of that, they have no problem lying to you. They have no problem charming you. But that's a whole different conversation. So so there's one other thing I wanna talk about our conversation from the plane, and then we'll we'll we'll and it all segues into warnings because because this was really your warning. You were you were telling me what you were worried about in society, and it's almost like you were being a Cassandra on the plane. But you'd started to explain to me why income inequality exists in America and, how it's not gonna get solved so easily. You were talking about this kind of, intergenerational widening that was happening across classes in America. There's a, I think we had a there's a very large, link analysis that Ergo put together that describes sort of a number of forces. Ergo being your company. Ergo is the name of our firm. Yeah. A number of forces that have led us to Trump being the first of many Trumps and Sanders being the first of many Sanders. Right? So we're now at a point where we have real divisions inside this country based on largely based on what you would call class or income. And of course, the facts that, you know, a 100% of the economic gain of the last 10 or 20 years went only to the top 10% and not to the rest of the country is sort of the manifestation of this reality. And and you can imagine what that the impacts are of that reality. And we don't have to imagine. We just saw it in the election for Trump. And we see it now in the popularity of Elizabeth Warren and we saw it in the population of Sanders and others. Right? So populism on the far left, the far right is going to get more and more more popular. So there's a whole series of dynamics that are leading to it, and some of them have to do with with feelings of of being oppressed, feelings of fear and anxiety, and also a number of factors inside our society, others who are who are firing up those feelings of anxiety and trying to make people feel more fear and trying to make people feel more concerned about the future. So the more nervous one is, the more you feel like you're under attack, the more you're concerned about your safety, the more you will automatically begin to huddle around, spend time with, and listen to people that are more like you. This is a known sociological fact. Right? So Fox News and MSNBC and other side do a great job getting their bases really riled up with fear. If you go look at Fox News, I had a dear friend who used to work there. She worked for O'Reilly. And they literally had a rule that it was something like breasts, bears and, you know, hurricanes. Right? Like, they wanted to lead with stories where they could show breasts. They wanted to lead with stories about bear attacks and etcetera, etcetera. And they love talking about other tragedies. Stephen Colbert did a nice job making fun of all this. If you watch his, his the way he used to make fun of O'Reilly in the show that he used to do. But it's it's not funny. Right? It's actually people realizing the more I can engender fear, the more I can engender animosity, then the more people are going to listen to me and huddle in close. Right? So Because fear also is much more motivating than, let's say, greed or or optimism. Yeah. Fear It's like 10 10 fear thoughts match one optimistic thought. I think so. I mean, I think it's our most motivating our most motivating emotion. Right? So there's a whole number of factors. And if you think about them, one that's really worth understanding, I think, is the rise or the use of artificial intelligence. Right? So we, in the book, talk about what's called artificial general intelligence or superintelligence. This is the stuff of the Terminator movies where the computers are sentient and wired. They're aware of who they are. They're extremely smart. And they don't want to be in a computer anymore. Right? So that's a different story. But that's superintelligence. On the way to superintelligence, you get ATM machines and Siri, and self driving cars, and all these things that are already part of our world. You know, so if you don't think that you're already a part cybernetic organism, if you don't think you're already connected to technology and dependent on it, try to live a few days without your phone. Right? I mean Well, you you have a great example in the book where, from the from the TV show Madam Secretary, where, at at, you know, at one point, Russia does some sort of cyber attack on the US, and she says, okay. To turn off Moscow's power for a day. And, this technology is already here. Like, these types of things can happen. In fact, this is the big discussion about the recent election. And it's not so much AI that's the scary thing. It's the fact that how dependent we are on the world becoming increasingly connected. Like, you give the also the example in the book of, you know, if Nest fails because of a software download, suddenly everyone in the winter is gonna be freezing to death. Yes. And we can't change it. There's there's, a a chapter in here about about the internet of things, meaning 5,000,000,000. There's 5,000,000,000 things now connected to the internet, right? And that number is going up exponentially. So you know, your phones, you're saying your thermostat, your car, your watches, your pacemakers. All these things in different degrees are now connected to the internet or hackable. Which are a good thing in general. There is a reason why they're connected. That's right. It makes life better and more efficient and so on. And but one of our Cassandras is saying, look, this is actually not a good thing. And if you, all these 5,000,000,000 things that are out there, they don't have built in firewalls. They are not upgradeable for security. And so they will become part of hacking tools for malevolent actors. And it turns out, you know, we couldn't write this book fast enough. Right? So as soon as we wrote that chapter, one of the last great denial service or hacks that we saw in this country was based off of baby monitors and Wi Fi routers and others. So people What happened? I don't know the story. By by using, I forgot which hacking collective it was, but they were able to not just use computer to computer to computer as their sort of off-site anonymous beacons to send out viruses. They were able to actually get into baby monitors and people's WiFi routers and others and use those to replicate and pass along different viruses, right? So now that was the last big hack that affected the United States or the world. And this is a real concern. And how did it affect things? What was the bad thing that happened? I think we had Gmail go down. Google went down as I Google went down. I think we had a lot of cell phone challenges. It was the I don't have the the details. It is my fingertips, I'd like to have them. But we had sort of the greatest last attack upon our cyber infrastructure globally was the one I just described. It was empowered in many ways by these Internet of Things Computers, not by computers. Right? So previous large scale hacks were here's a virus I'm sending out in the wild. And if you happen to download this or that or go to this website, or a lot of bots on computers on computers would send out a bunch of these infected emails, etcetera. This hack came not from computers that were kidnapped, but came from, as I said, baby monitors and Wi Fi routers and other things that weren't protected. So you now have stuff totally out of our control, but that we rely on. Exact well, out of our control because we never designed them or built them with the security infrastructure that they probably need. Security technology. Not downloading the virus. Like, a lot of times, you know, you previously, you get a Gmail. Oh, check your Citibank account, and you click on something, and it downloads the virus. It was it was That has nothing to do with us. It took the human failure out of the loop a little bit. That's right. So so we do talk about that. We talk about how our reliance on technology, particularly the Internet of Things, is a risk. And that's one of our chapters in the second half of the book where we say, hey, someone's beating their feet. They're making a big noise about this. Are they right or wrong? I think history, since we started writing this book, has proven that they're already right. But artificial intelligence, just back to this class division issue, narrow intelligence is already removing a lot of jobs. Right? So the if you look at the percentage of jobs in this country where driving is a critical aspect of what you do, I don't mean just bus drivers, truck drivers, and taxi drivers. I mean plumbers who need to drive to go from site to site or lawn care people or tree technicians or whatever it is. Those folks, there's a there's a huge number of job skills, job categories, where driving is a key component of what you do. All that driving, without exception, is gonna be replaced by computers in, let's say, 20 to 30 years. There's just no doubt about it. Right? So that doesn't mean that the lawn man is no longer gonna have a job, but it means a lot of the the labor he's putting in is no longer gonna get paid for. Right? And it certainly means that the bus drivers and the truck drivers and the taxi drivers are out of jobs. Now, the same thing happened to to cashiers at banks when the ATM machine came out. There's a bank near our house where there's 1 cashier, and there's about 15 ATM machines and these new modern ATM machines where I can do even more complicated stuff. Well, let me play devil's advocate. So when ATM machines came out, everybody was worried, oh, that's the end of bank tellers. But what happened was it actually made it more efficient for banks to build new branches because the cost per branch branch was lower. So they actually created more branches, and there's actually more bank tellers than ever because of increased efficiencies that people you know, people this technology doesn't exist just to exist, just for fun, like, as an academic project. It exists because people demanded it, and it increases efficiency. And with that increased efficiency, businesses are able to grow and hire potentially more people, maybe just in different ways. You're exactly right. In sum and so one of the overused and incorrect tropes of this conversation is about the buggy whip manufacturer. Right? We've heard this one many times. When we moved from horse drawn buggies to cars, what became the buggy whip manufacturer? Well, one of the companies that make buggy whips became Studebaker. They make cars and steering wheels. Right? So you can transfer the labor force and other things. I didn't know that. You can transfer your your your point about bank tellers is a good one. Nonetheless, while there are sometimes good stories like that, and while some of my friends at Silicon Valley say, don't worry. So long as you can give me a good labor force that I can pay less than other things, I'll hire them. At some point, we're not going to need to hire them anymore. And we're already seeing a huge amount of labor being lost because of narrow artificial intelligence or machine learning or some sort of whatever you want to call it, but the use of technology. And it is a fact, right? So so combine that though with what you were saying to me on the plane, which is that we also have this situation where, you know, college educated people marry college educated people. Yeah. Non college educated people marry non college educated people. And so across generations, of course, all of these people are going to be widening. Social widening. Right? So we have there was a there's a there's a a survey that was done up and it's still done, but it was done, in the eighties, if you asked folks, certainly from the twenties, thirties, 40, 50, in the eighties, if you asked people, where do you rank on the income hierarchy, the class hierarchy in the United States? Where do you rank in the class hierarchy in the United States? 80% of people said they were sort of in the middle. Right? So 80% of people said I'm either middle class, lower middle class, or upper middle class, upper middle cla*s. Meaning a huge number of people deceive themselves about where they were. The rich, not the super rich, but sort of the very rich didn't quite realize they were very rich. And the poor, not the super poor, didn't realize they were super poor. So 80% of America kind of felt like they were in the boat together as far as where they fit in cla*s. Right? 10% of the top knew I'm really rich. 10% of the bottom knew I'm really poor. But 80% in the middle identified just like the other folks around them, which is, you know, technically inaccurate, obviously. If you ask people that same question now, how do you rank in decile in the United States as far as your wealth? People are extremely accurate about where they live. They're extremely accurate about how poor or rich they are. Why is that a problem? Because one of the other great human responses is the mimetic response. I want what you have. You can't break yourself from it. Right? I want what you have. And now that I'm able to see the way the Kardashians live, it all goes back to Robin Leach and the Lifestyle is Rich and Famous. Do you remember when that show first came out? It was just this most fascinating conversation about these really, really rich people out there. And most people had no idea, you know. You know, welcome to the house. How about some golf? There's 9 holes out the back door. You know, no one really understood that's the way very rich people lived. And I don't think that caused a class revolution. But I think what we're starting to see now through the internet, now through Instagram, now I can watch these people with their hyper idealized lives that they present to me. I realize I'm not doing as well as they are. And I might be able to realize in gradients how poorly I'm doing. So that's one major issue that's causing a widening, and that is a a big problem. The other one is the reality of what's actually separating, back to the point you were referring to from the airplane. When so back to the day in the up until the eighties, it wasn't shocking for the CEO of a major corporation to marry his secretary or to marry someone who was, you know, nominally of a lower economic standing than him. It would it happened. Right? Nowadays, and this is obviously massive generalization, but like the CEO of a venture capital unicorn, venture capital backed unicorn in Silicon Valley, is not going to marry a girl he met driving the Uber. He's going to marry the law firm partner from Sullivan and Cromwell who's taken care of him, you know, professionally, who went to Yale Law, etcetera, etcetera. So the super elite are able to find the super elite in a broader way than they were before and marry and push forward. Obviously, they're you know, you're not gonna be a managing partner in Sullivan and Cromwell and you're a major law firm nor the head of a unicorn if you're not super high IQ. So they're perpetuating that super high IQ strain going forward, high IQ strain. Where on the other end, you know, let's go way, way down to the other end to some poor, either part of the Rust Belt or some poor part of anywhere in the United States where education go to JD Vance's world in Hillbilly Elegy. Right? You're now in a part of the world where people are extraordinarily poor. They're extraordinarily undereducated. They have really, really bad nutrition in some instances and bad health care and medical care. And you then you are perpetuating the future of those poor classes because they're not breaking out and they're continuing to marry where they are. I'm not talking about intermarriage and that whole kind of genetic issue. I'm talking about, you know, people aren't escaping from where they are. And some of it's actually genetic, right? Some of it also has to do with, now here's where we get into the future, right? Okay, great. Now what about the future of genetic engineering and this thing called CRISPR, CRISPR Cas9, which Which we talk about in the book. Which we talk about in the book. Which is one of the future potential dangers. It's already here, right? So Jennifer Doudna, or Doudna, who's a professor and now in California, previously from Hawaii, discovered a way to manipulate genetic code very, very easily. Now we knew in the eighties that if we could start moving parts of the strands of your DNA around, we could certainly change the outcomes. We could make bigger cows or bigger fish or we could maybe someday get rid of genetically borne diseases if we could change those parts of the DNA strand. Jennifer Doudna, this unbelievable woman who will almost certainly win the Nobel Prize sometime soon, figured out a really simple and accurate way to do that. Previously, it was all but impossible. It is so simple now that high school students can literally manipulate the gene line of animals. Right? So high school students can create glow in the dark goldfish by understanding that this set of, this set of snips of DNA creates phospholuminescence. If I can put it into this fish, I can actually get a glow in the dark fish. You can even not just change the expression in one animal, you can change what's called a human. You can change what's called the germ line, right? So we could change the way your genes are so that the children you would have in the future would maintain that genetic change. Now, what this really means is in some ways, we are taking on some of the God functions and deciding in real detail what our children will look like or won't look like, sound like, smell like, how tall are they, how small, how smart they are, etcetera. And in fact, this is already happening. So it sounds great. It sounds great. Tell me the bad. There's a lot of bad. So as far from a social perspective, the bad is, that's gonna be really expensive. And the ability to the expensive function in this equation, the the expensive part of this equation is actually knowing what genes to cut out and which genes to replace. That data is very expensive. But it will get cheaper. Sure it will. But right now people are manipulating genes like this to pick their children. And China is doing a whole lot more of it than they admit. And they're picking for height. They're picking for intelligence. They're picking for eye color, all sorts of things. You could easily do that in the United States now except it's not considered ethical. Now, you can pick, look, my husband and I both are carriers for Huntington's or Parkinson's or Alzheimer's or something like that. There is a very expensive procedure where I can select out the embryos that have those proclivities and end up with healthier children. And I don't think people are complaining about that. But what we do need to start worrying about is when people are selecting to create effectively super children like in the movie Gattaca. Remember? Yeah. This is a real risk. And the problem is from the social division side, the people with the money who can afford it are gonna do it. And thereby, they are gonna branch out even further and further from the poor people from poor people because they're going to be literally have smarter computers in their skulls. They will be smarter. Let's stop to take a quick break. We'll be right back. Audible, thanks for being a sponsor of this podcast. Let me just ask. I'm gonna ask the listeners. Do you love books but find that you never have time to read them? Because sometimes I don't have time to read them. I'm always doing this podcast. With Audible, you can now get audiobooks and listen to those books you've been meaning to read on the go. Their app is totally free. 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Please just try it even if you're just hiring, like, one person. Go to ziprecruiter.com/james. You get it for free. One more time, try it for free. Go to ziprecruiter.com/james. Let's go head first into the book. First off, because I want because you're being a Cassandra on this issue, and I wanna I wanna confront that. But let's just talk about the qualities of, like, a a Meredith wet Whitney, a, Harry Markopolos, or Marco Polis. I don't know how you say his last name. And some of these other ones, you know, so many people complain about bad things, like, you know, the whole population bomb issue, which never really occurred. Example. And how do we know who to listen to and who not to? After in hindsight, which is the first the first half of your book is in hindsight where we see who who was not who was correct, but they were not listened to. And they were not listened to for a reason, and you point out those reasons very well. How can we learn to listen to the right people? So you mentioned Paul Ehrlich who suggested in this book called The Population Bomb, I think in 1968 that, geez, there's just gonna be way, way too many humans given the amount of food we can produce. We're gonna have a massive, massive problem. It was like a Malthusian prediction about the future of humanity. And it was taken very seriously. And there was very smart people talking about putting sterilizers into water. There was very smart people talking about implementing one child policies in the United States like they have in China. Well, and by the way, all of this is related to what you were saying earlier, this kind of eugenics idea that we can sort of pick and choose what qualities we want, and that's who we'll live. Sure. And and what Ehrlich was saying, we don't even need to pick and choose. We just need less humans. Let's just do it across the board because if we don't have less humans, we're going to have a real catastrophe on our hands. So Ehrlich went out and made a lot of noise about this best selling book, listened to congressional testimonies and hearings, like a big deal. Turns out he was totally wrong, right? He didn't realize that agricultural technological revolutions or innovations were gonna allow us to feed everybody. Or was he right and the agricultural revolutions is the response? He can't well, that's that's also that's a really good point. Sometimes, someone who warns of a disaster is proven to be correct because the response happens, but you never actually know they did it. No. I don't think in this instance he was correct and and caused the positive response. Others have in different instances, but I don't think he did. Nathan Borlaug was the guy who invented dwarf wheat, is probably the person who, you know, I think he also did win a Nobel Peace Prize. He discovered how to grow wheat with a much, much higher efficiency, much less waste. And that was a big part of why we were able to feed people. And his innovations were underway well before Ehrlich wrote his book. So you can actually fact base say that's not what happened. So anyway, so you have that's an example of a person I would call chicken little, right? The sky's going to fall. The sky's going to fall. It never did. He was wrong. Okay? Our Cassandras in the first half of the book were right, as you mentioned. And what makes them different from a Paul Ehrlich? So it turns out, look, the primary issue is that they're data driven, right? Paul Ehrlich was not an expert on population. He wasn't. He did not have the proper training to have we would not have considered him serious using what we call the Cassandra coefficient. So the middle of our book is a really, really fascinating, in my mind, a really fascinating chapter that talks a lot really talks about our human biases. It talks about how are we getting it wrong not to listen to these people? Why are we ignoring folks who come to us with really clear explanations of what's happening? And it turns out there's a series of characteristics around the Cassandra, which we'll describe. But it's not just the Cassandra, it's the context in which they come to you that also needs to be understood. So there's 4 major components that impact that we think are worth looking at. One is the Cassandra and the characteristics therein. There's characteristics of the warning itself. What are they complaining about? What are they worried about? There's characteristics of the decision makers, the folks who are supposed to solve these things. And there's characteristics of the critics, the folks who are saying, no, no, the Cassandra's wrong. And we have described 24 characteristics across all those 4 components. So it's 4 components, 24 total. And when you look at each one of those things, we believe we're beginning to understand the outlines of how to identify a Cassandra from a chicken little. So let's talk about the characteristics of a Cassandra. I mentioned data driven. Everybody in our book that was right was a proven technical expert on the topic they were speaking about. This isn't And almost by definition, they're gonna be more of an expert than the people they're talking to. That's why they have the knowledge, and the people they're talking to, the potential critics, don't have the knowledge. That is a great point. So you start ending up having trouble where you're talking to Harry Markopolos is a great example. So Harry Markopolos very, very clearly said Harry said Madoff is a scandal. Madoff is a Ponzi scheme. Harry Markopolos tells me he knew within 45 seconds of understanding the quote unquote hedge fund that Madoff was running that it was a Ponzi scheme. He smelled it right away. He knew the whole thing exactly what was wrong. Right? So so let me ask you a question about that. Like, again, you mentioned he has had a somewhat abrasive personality. Let me just mention this. I wanna get back to your good point. Right? So so Harry is a he does have a semi abrasive personality. But more critically, he's a real numbers wonk. Right? He's a certified fraud examiner. He's a CPA. He's a financial analyst. He understands numbers. He's comfortable and happy with numbers. So he goes to the SEC, who's they're the decision maker. It's their job to oversee Madoff. And he says in excruciating and clear and inarguable detail, Madoff is a fraud, period. Madoff is a Ponzi scheme, period. And he's ignored because they don't speak the language he speaks. But it was so inarguable. I'll tell you the like, like, I don't necessarily know everything either. But there was one argument that he made that was so inarguable as to seem ludicrous that nobody listened to it, which is that to trade Yes. $60,000,000,000 worth of options, there wasn't even that many options traded in the market. You got it. Who could argue with that? You get the the SEC lawyers who found Harry to be off putting, they found him to be obnoxious. They thought that he was a competitor of Madoff, so they began to doubt his veracity and his motivations. And these were kind of liberal arts law student, law lawyers. Right? And Harry came in with complex mathematical equations. You're exactly right, James. That was, to me, the one that was like, there's no way Madoff is telling the truth because there's not enough options sold in the entire world every day to support a split strike conversion process inside his hedge fund. Like, it cannot be true. Look at the facts. But it may have had, like, a $10,000,000 fund or a $100,000,000 fund. Maybe it would have been harder to say make that right now. Even a couple billion, but not 65,000,000,000. Right. So there was no possible way that he could be doing what he's doing. And the SCC, we call so we call that complexity mismatch. So when you have and look. And we're entering a world of increasing complexity. The acceleration of complexity is a whole different issue, but it's a massive problem. So when you're the bureaucrat at the SCC, I don't care how well intentioned you are, but someone shows up who has an off putting personality, you have a complexity mismatch because you don't understand the math, you don't understand what it means to be a fraud examiner or a CPA, and they're giving you mathematical theory you don't get, or you have what we call ideological response rejection. Like, you're just not going to believe it because it doesn't fit in your ideology. You're gonna push this guy away. So a whole series of biases built built into who we are makes them ignore this perfectly accurate Cassandra. So the Cassandra coefficient, the things about them, proven proven technical expert, as I mentioned, often have an off putting personality, not all of them. Data driven. They think differently. They're orthogonal thinkers. They're questioners by personality. They're asking the hard questions. They're the ones who doubt. They have a sense of personal responsibility, meaning when they walk into a restaurant, they're they and and the fire alarm goes off, they're the guy who's gonna say to everybody, let's get out of here. Let's go. Don't sit there and finish your dessert. They have a sense of personal responsibility. You know, there's all these different theories. But some people think of themselves as sheepdogs and some people think of themselves as sheep, but I don't realize they're sheep. And then we all know there's wolves out there. Right? So wolves, sheep, and sheepdogs, these guys think of themselves as sheepdogs. They, to some extent, think it's their job to protect all of us. That's another characteristic. And finally, they have what we call high anxiety. Right? So not only let's go back to our restaurant and the fire alarm. When they walk in, these are the guys who look for the fire exits. Where are the fire exits? And these are the guys, when they smell smoke, pull the fire alarm. And if you think about personalities, a lot of people don't do that. Right? So this is a little bit of a different cast of folks. These Cassanders are a little different. So there's aspects about them that we think are really different and definable. And Than the Paul Ehrlichs. Exactly. Paul Ehrlich was not a proven technical expert. He was not data driven. I don't know about the rest of it, but, you know, we would have, right off the bat, said no. He doesn't deserve to get this much attention in response because he doesn't have the data. He doesn't every one of our Cassandras, including every one of our potential future Cassandras, is an expert in their field for years years years. And I'll tell you though, it's so hard on the other side. You know, I think you have to I think everybody should be made aware of the Cassandra coefficients, what makes a good Cassandra. Because I'll tell you, I intersected with a few stories in here. I visited Bernie Madoff when he was at the peak of his hedge fund. I you don't mention John Paulson, but, obviously, John Paulson's fund Yep. Was a big Cassandra of the financial crisis of 2008. I rejected investing in his fund despite all the data being thrown in front of me. So I was kind of the idiot on the other side of many of these situations. So this book helps me with not not only understanding what my behavior was, but how my behavior could change in the future. But let's, people should read your case studies and your stories. You have 911, which you were intimately involved with. You have all the financial stuff. You have, the swine flu stuff, all these different things. But what are you now personally worried about for the future? The book's called warnings. What are your warnings? Who are the Cassandras? Why do you believe them? You know, I'm worried about a lot of things, I hate to say. But the one so writing this book, the the final seven chapters talk about, again, as I mentioned, people who are stomping their feet, beating the table, and saying, listen to me. Listen to me. Bad news is coming. Dragons be there. And they're right now. That's how they make money is by expressing fear. You see it on every ad in in the Internet, like the end of the world's coming. Buy this report. Why? Yeah. You know, that's true. And there are a lot of people out there that are are are and we talked about this in the beginning that are trying to make hay out of warnings, out of of trying to panic us. I think that the 7 people we profile on the end of the book that are trying to get our attention, I don't think a single one of them is profiting off their warnings. And and just very briefly, we talk about the rise of artificial intelligence in the in the robots. Right? So this is the stuff from the Terminator movies. We talk about how the rise of pandemic disease is never more of a risk than it is today. How the flu of 1919, which, killed a massive amount in the world with only 2% lethality, you know, could look like a walk in the park compared to what Laurie Garrett tells us is coming from the CDC. Avoid that? Because I think people are aware that a pandemic can happen, which is why the the WHO always issues pandemic warning as like, 3 people die, and then there's a pandemic warning warning. Well, that's what people think. But, you know, how do we avoid that is, Laurie Garrett, who is truly one of, you know, I don't think she ever will. But if anyone out there is listening who can who work on this, Lori Garrett should win a Nobel Prize for a Nobel Peace Prize. Lori Garrett's won the Pulitzer, the Polk, and the Peabody, only person ever to win all 3. She's the head of global health at the Council of Foreign Relations. She may be a 2 time Cassandra, one of the few. She foresaw the rise of HIV AIDS when she was a radio reporter in San Francisco and would walk out into the gay district. Was it called Tenderloin? I don't remember. And she would see these men dying of a disease they called gay related immune deficiency, GRID, or gay cancer. They didn't know what it was. And the gay men didn't think that they had a transmissible disease. They thought they were sharing a cancer somehow. But just by looking at them and watching the Kaposi sarcoma on their face and seeing them, Lori Garrett knew this was a contagious illness and started getting the media to pay attention to it. And remember, this is during the era of Ryan White. Ryan White, you may recall, was a young, poor high school student dying of HIV from a blood transfusion. And his local high school wouldn't let him come to school. People shot bullets at his house. And noted politicians called for gay people being put in camps. People were so afraid of this disease. Anyway, she talks about what we need to do to get ready for a pandemic. And it's just simple systematic expenditures for health care infrastructure and surveillance networks. That's what she talks about. But let me I I kind of didn't answer your question. I'm sorry. What am I most concerned about? Certainly that. I think the rise of pandemic disease is an unbelievable issue. I'm really, really concerned about the rise of superintelligence. And, I join, in this instance, I join a very, very impressive crowd of Elon Musk, Bill Gates, Stephen Hawking, Bill Joy, a number of people that we believe, and I think there's evidence to say, are the great technological thinkers of our era, are all very concerned about the rise of superintelligence. What's the switch that will flip that I mean, it's not like artificial intelligence can be conflated to evil human intelligence, which I think is kind of the the Terminator worry. What what's the switch that will flip that makes you actually worried? It's a really, really long and hard complicated conversation made more complicated by the reality that when we try to think about a machine, an entity that's twice as smart, 10 times as smart, or a 1000 times smart, as smart as the smartest human, by definition, our brains can't do that. Right? But there will be they're not it's not like human intelligence times 10. It's a different type of intelligence. You can you can get yourself worked in all sorts of knots trying to figure out what does smart mean? What does intelligence mean? But let's just suffice it to say we're talking about a thing that's able to solve the hardest mathematical and physical challenges of mankind. Questions that, you know, there's a whole litany of questions that physicists and mathematicians have been trying to solve for, in some instances, centuries, right? And and geneticists and biologists and others and energy experts. There's a whole series of questions they've been working on. When we get to artificial intelligence at the superintelligence level, this is very different than the ATM machine and Siri in a self driving car. This is a machine that is as smart as a human or more. And again, now we you know, what does smart mean? But let's skip that for a second. You now have a machine that's gonna be able to answer all those major known questions. Plus, it'll be able to ask questions we don't even know. Right? So the degree of intelligence that we're describing here is impossible for us to really get our arms around. It's a big, big issue. So what's the flip of the switch? I don't know. I mean, I think what we're talking about is when a machine gets so extraordinarily smart that it has a certain amount of self awareness or sentience, and then it's concerned about survival. Right? And you might say, and this was someone said to me the other day, oh, well, but when will a machine have an original thought? And the answer is they already have had many original thoughts. Right. That's why that's why I don't I mean, Google every day has original thoughts. So that's why I don't like conflating Google, which knows many more facts than me and does many things relating to AI. It's not my kind of intelligence. Like, it's a different kind of intelligence. Exactly. So right now, I think just about anything a human can do, including throw a ball or catch a ball or certainly play go chess or backgammon or run a race or drive a car, anything a human can do, a computer can do better. Now, not one computer can do all those things better, but individual computers can do all those things better. Right. And it's improving fast. I mean, you could see the examples of facial recognition. 10 years ago, you couldn't do it. Now, I could be, I don't know, wearing a hat in in a crowd in Times Square, and a satellite could say, hey, there's James Altucher. Absolutely. It's it you know, the the acceleration of complexity, the acceleration of technology is unlike anything we've ever seen before. And certainly, that's manifest in artificial intelligence. So So your question is, why should we be afraid? What's the big issue here? Here's just one way I can sort of describe it. First of all, humans are not the fastest nor strongest organisms on the earth, but we clearly dominate the earth to the point where we're destroying the earth. When another organism is much fat again, we rule because we're smart, right? When another thing comes up that's smarter than us, we should be concerned about what it could do, just that simply. I mean, and you might say you know, that's just paranoid thinking. I don't I don't think it is. Now here's here's one way to think about it. The last time you dug a hole, built a house, built a pool, you know, drove your car on the sand, whatever it was, you may well have killed some ants or some worms or this or that. I don't imagine you went to bed that night crying about it. I don't think you're out there hunting them. I don't think you're the kid with the magnifying glass burning ants. But I think in doing what you needed to do, if you ran over some of these things, that just was what it was, a necessary cost that you didn't think twice about. When it is not impossible to think, and this is a big thing to get and you're not going to believe this, but you might, but a lot of people aren't going to. It is not impossible to think that a self recursive, a self programming computer will be so much smarter than us that it'll be the same as as smart as we are versus an ant. Right? So the difference between us and an ant or us and a dog is easily how much smarter a superintelligent computer could be versus us. So we don't really necessarily know. We don't know. It's not gonna hunt us, I don't think. We don't know. But what we also don't know is that we're not preparing for that. And we do definitely know that superintelligence is coming. Computers obviously get double the speed, double the fast, smart every year. And that's been that's been one of the first you know, there's, Eli Yudkowsky, who's the Cassandra we talked about in this chapter, who's really a fascinating guy and also has an off putting personality. And he's a guy who is behind the you know, he's the guy who taught me about the Crocker rules for conversation, which I didn't finish on when we did. He's a guy who who describes there's a series of stops and a train where people get off if they to not believe you. Right? When he says, look, we need to really worry about the rise of superintelligence and ultimately robots and sort of Terminator type outcomes, he says there's a series of exits where people get off the train. And one of them is, well, it just won't ever happen. Technology won't get there. Well, that stop is you know, the doors don't open anymore. Right? You're knocking up. It's definitely happening. We will definitely have superintelligence, definitely, by the end of this century. Almost I mean, that that's a given. Now will it be in 20 years or 30 years? That's a question. Will Will it be in a 100 years? Absolutely. Right? So it's gonna happen. Then the question is, can we begin at some point programming it, building it in such a way that we can be comfortable about it? Can we be safe with it? Look. The other way to think about it is we're building the greatest weapon in the history of mankind. Right? Now it's also the greatest tool for good. It will solve the molecular sorting issue. It will end all energy challenges. It will end all food, hunger, and starvation challenges. It will end all disease issues. It could end death. Now we're talking about Paul Ehrlich and the population bomb again, right? You know, if we have no death. But this machine will be able to answer all those questions. So that's an extraordinarily good thing. It will it will be so it will confer so much power on the person that or the organization that can control it that we're never gonna stop trying to build it. So potentially, too, that organization is the problem. Like, we we you can be a Cassandra saying, that organization is we're not gonna have a decentralized command. We're gonna have a very centralized command, which is that organization that controls all the superintelligence. No. Look. We we are if if humans or an organization are end up being able to control this thing, you're exactly right. We're gonna have that problem. And if not, if it controls itself, then we don't have to worry about it. We're gonna have a much bigger problem. So so what what other things do you worry about? So that's one I really think about is is, the rise of the machines. And it scared me so much that I I told my little kids about it. Got them scared. They went to school and told their buddies about it. We had parents calling home. It's a joyful parent. I know. But it was You're the life of the party. It's a PTA. The first x y graph my 7 year old ever drew was about the rise of hyper intelligent beings. So I still have it on a napkin. I think that's a real issue. I think pandemic disease is, a real problem. Particularly combined with, what you were describing with the CRISPR. If we can edit if we can, genetically edit a flu, a swine flu Sure. We can edit it so it so things like Tamiflu won't cure. Absolutely. And Tamiflu already doesn't work. But we so nature already creates all sorts of defense mechanisms against antibiotics, antivirals. We know that, right, for antibiotic resistant, antiviral resistant viruses and bacteria. We know that already happens in nature. What you're talking about is a real issue, and that's about, using CRISPR, this really fantastic genetic manipulation tool, to create highly lethal biological weapons. Which is nuclear weapons. It's not like nuclear weapons where, like, Iran needs a particular type of plutonium that's been processed before nuclear weapons. Precisely. This anybody, like you said, a high school student can get this and start getting to work. You got it. Right? So we're we're now talking about a situation where, for very few dollars and certainly on a state level effort, as you're describing, it requires a state level effort to, to create nuclear weapons. For very few dollars, someone could create a highly lethal biological weapon. And and that's a real concern. And look, that's I can guarantee you sometime in the next 15 years, some bad dudes are going to try to use CRISPR to create a highly lethal, highly contagious bug. There's no doubt in my mind. Why? Because bad dudes have been trying to do that already. Right? You read in the book about, the Japanese That's a Japanese cult. The Japanese cult called, from shirikko. Aum Shinrikyo. Thanks. And how they worked really, really hard to try to find smallpox and how to create sarin and other chemical and biological weapons. That's a real problem. I'm really concerned about that as a risk. And, I think I'd say those are the ones. Now, here's one that's really current and really interesting. We could talk about North Korea and talk about what's going on there. But suffice it to say that we are now, Donald Trump or not, we're now in a situation where things between North Korea and the United States are are at a a jam. And there's there's no president ever who could allow North Korea to have a nuclear weapon and a delivery device, a missile, capable of getting to the United States. We cannot allow that to happen. No president could allow it to happen. Bernie Sanders couldn't allow it to happen. So we but but North Korea is now getting there. So as that's happening, the possibility of them using nuclear weapons on us or certainly on South Korea or Japan becomes much more possible. And then our responsibility to respond becomes much more possible. Now what I'm talking about is the possible of an possibility of an exchange of nuclear weapons in the Korean peninsula or towards California. Like, this is now in the realm of the possible. It's in the realm of the quite possible. And again, I'm not saying anything about Trump. I'm saying this is where we find ourselves in the national security kind of arc of time. Right? There's a a madman regime, possibly with a weapon, and we possibly have to respond. In the book, we talk about, the nuclear ice age. Do you recall growing up in the eighties this idea that if there was an exchange between Russia and the United States that the whole world A nuclear winter. Go into a nuclear winter. Exactly. And that fear of a nuclear winter actually led to a lot of the arms control work, that was so successful in the 70s, 80s, 90s between the Soviets and United States. Because nuclear winter was real. Everyone understood it. If there was a nuclear exchange for the United States and the Russians, the entire world would go into, not a freeze, but a deep hard winter for decades. And you mentioned in this book, how the data actually might be worse than it was originally understood. Exactly. That just basically a small exchange of nuclear weapons could put soot throughout the air and create this nuclear winter. Right. So so the the the guy we profile in that chapter talks about India Pakistan. He does the studies on what if India Pakistan throws some nukes back and forth at each other. And he says the world could be in a nuclear winter for 2 to 3 years or a decade, like big catastrophic change. I'm not saying you get to ski for a year all year round for 10 years. I'm saying billions of people die because crops don't grow. The sun doesn't shine. Water doesn't flow. This is a cat a catastrophe of the highest order. Turns out, obviously, if it's an if India Pakistan nuclear exchange could cause this, so could an exchange around the North Korean peninsula. So here's a warning. Right? Not only might we be in real, real trouble with North Korea right now and might there be what did what did Donald Trump say the other day? There's a major, major chance of us going to war with them? Well, not only is there a major, major chance of us going to war with him, there is a real chance of be there being a nuclear exchange. And if there is a nuclear exchange, the science says, pretty incontrovertibly, we could end up in a nuclear winner. And, you know, there's so much fascinating in that chapter you're right. Worldwide. Because you talk also about how tactical nuclear weapons, which seem like almost a friendlier way to exchange nuclear weapons, are in fact worse because they make it psychologically capable of us to say, oh, we could rationalize. It's only a tactical nuclear weapon, not like a big Yeah. It's you know, h bomb or whatever. Right. So tactical you're exactly right. So the part of the good news about us getting rid of tactical nuclear weapons and you know, we used to have a weapon called the Davy Crockett. And it was a hand it was a shoulder fired bazooka with a nuclear warhead on it. Can you imagine that? One soldier with a bazooka could launch a nuclear weapon and destroy downtown Manhattan. Right? That's crazy. So we don't have those weapons anymore. Thank goodness. And the Soviets don't either because of our arms control treaties. And now right now, those weapons might actually make some sense. But, yes, there's a psychological reason not to have them because it would make a president like Trump or others say, hey, this isn't so bad. Let's use it. Now what we do have is the b 61 warhead. B 61 the the b 61 missile effectively is is our our number one part of our new nuclear arsenal. We have basically 2 warheads, the w 88 and the b 61. The b 61 is a is a variable yield weapon. It has a dial on it, and you can dial it down to weaker than Hiroshima or you can dial it up to, I think, 300 megatons, which is, you know, a 100 times more than Hiroshima or much more than that. So you could use the b61, put it on low yield, and drop a bunch of them around the DMZ to prevent South Korea from using their 15,000 artillery pieces and destroying or I don't know if they could destroy Seoul, but some say the North Korean 15,000 strong artillery barrage would turn Seoul into, quote unquote, a sea of fire. 10,000,000 people plus 10,000,000 people in Seoul, 10,000,000 in the city, 10,000,000 in the suburbs. That's a bad thing. So you could use a B61 variable healed weapon or a series of them to denude or the the North Korean capacity to shoot on Seoul. You've now got a nuclear exchange. You've now got the capacity for a nuclear winter. These are bad, bad things. I promise you this conversation has not been had in the White House. So so, you know, it's so scary because so, okay, I just wanna repeat. The book's called Warnings, Finding Cassandras to Stop Catastrophes. It's by Richard a Clark and R. P. Eddy. I've read it. On the one hand, it was very gratifying because it helps to understand, what the Cassandras were for prior disasters, and it's really interesting to see read also about 911 and some of the other issues we didn't talk about. But it's also interesting to see the things you're scared about now. I mean, here's my my final question about this. Given that there are a lot of very realistic things to be scared about, the odds of one of them happening, and these are all worldwide catastrophes, the odds of at least and they're all kind of mutually exclusive to each other. The odds of at least one happening is pretty high. Like, how do you how do you live with the knowledge? Well, we have catastrophes And by the way, people should read about this just to be aware of what's what's happening. Yeah. And and also just noting quickly, it's actually a it's a good news book. Right? Because it talks about how we can identify these catastrophes so we can get ahead of these catastrophes. So look, we have catastrophes, mega mega catastrophes hit us about every 3, 5 years. Fukushima, 911, 9 all the things that well, that that's coming in the future. And of course, asteroids have happened before. This isn't this isn't a never happened before scenario. So, yes, I think, unfortunately, some of these things will come to pa*s. But the more we're aware of how to find the people out there who predict them, the more likely we'll be able to prepare for them or even prevent them entirely. Every major catastrophe from your lifetime or mine had a person waving their hands saying, this will happen. Right? And they had data and we ignored them. We have to not ignore them anymore. But I want do I have one more one more minute? I forgot to mention something to you beforehand, and I wanna mention it to you now. So look, this is a book. It'll get read by a few people. Great. Maybe some of the ideas will get out there. Great. Maybe a couple of managers or a president or a cabinet member might say, geez, I shouldn't kick that guy out of my office so quickly. I remember reading an article about off putting personalities or complexity overload or why I should listen to a Cassandra. If that happens, Dick and I couldn't be happier. But it's just one book. Right? As many people are gonna listen to your podcast, I know a lot do. What we need to do is get the word out a lot further, James. So what we're doing, Dick and I joined by general Hayden, former head of NSA and CIA, joined by ambassador Frank Wisner, the highest ranking diplomat in American history, joined by Dave Cohen, the former head of ops for CIA, joined by Mark Gerson, who I think you know, one of the great entrepreneurs of America in the last decade and great philanthropists, and a number of others are creating something called the Cassandra Award. So we're creating a website for an open submissions globally. We want people to go into that website and submit to us the ideas of people out there who are being ignored, data driven experts. And look at the book about what we think an expert means. People out there who are warning of something and aren't getting the attention that you think they deserve to get. So go to our website and we can maybe put it on your podcast. We can put the link down and submit the name of that Cassandra. And then the people I mentioned and some others are going to be a group of distinguished board to judge these different submissions. And every year, we're going to announce an award on a person who we think deserves more attention because we think that the catastrophe that they're predicting is a possibility. We think they're data driven. We think they're experts. And we want the world to pay more attention. And and And we're gonna give them a cash award as well. Do you think that cash award will be listened to by a Trump or I what what I wanna do first of all, it has to be absolutely nonpartisan, but I wanna create as much news and media as possible around it so that, yes, hopefully, it is listened to Why don't you why don't you do, like, an XPRIZE type thing where you raise 10,000,000 for, you know, these types of awards? I would love to raise a substantial amount of money, to get that out there. But I think, you know, even if we can give the Cassandra $10 or $20,000 I think that's a really good step in the right direction. What we really wanna bring them is, is public publicity. We want people to pay attention and say, oh, you know, I never realized that we're losing Bumblebee's to the extent we say we are. That story's already been kind of been told. But things like that look, we have 7 future Cassandras already published in this book. We have 7 that were ignored. Unfortunately, there's 1 right now, if not 10, that are right. And we've got to find them. We've got to listen to them. So the annual Cassandra award. And James, if you'd like to be, I'd love for you to be one of the judges for the award with us. You have great experience and lot of exposure. You've scared the hell out of me, so I wanna I wanna help. And I'm a natural optimist, so it's good for me to to consider the other side of of all of these great technologies and so on. But RP from from our conversation on on JetBlue a year ago to your book, warnings, finding Cassandra to stop catastrophes that you that you wrote with Dick Clark, just fascinating stuff. I always learn. I hope people read this. The the stories are great. It's not just data driven stories. Like, you tell the real stories of these people and and and of the warnings coming up and and how you hope to deal with them. I really encourage people to read this book. It's it's it's kind of important. It's not just your average book. So And I think it's a good fun read. Buy it for your dad for the beach. He might be Yeah. Crying by the end of the day, but he'll learn something. And thanks for having us, James. I I love your I love the work you do, and I think you're one of the great one of the great commentators and thinkers. So it's a privilege for me to be here. Thank you. Thanks, RP. Go to warningsbook.net and check the annual class Cassandra. Oh, sorry. Check the annual Cassandra award, and that's how you can find out more about how to win the cash prizes and express your own Cassandras and read about others. So thanks very much, RP. Thanks. RP, thanks so much. Hey. This is fine. I know we, spoke a lot about the Jeff Flue conversation, but I think it segued nicely into your own expertise. For more from James, check out the James Altice show on the choose yourself network atjamesalticere.com, and get yourself on the free insider's list today. Listen. I have a favor to ask you, and it'll only take 30 seconds or less. And please, it would mean a lot to me. If you like this podcast, you can easily let me know by going to either iTunes or Stitcher or wherever you download podcasts and subscribe. It'll probably be the biggest favor you could do for me right now, and it's really simple. For instance, go to Itunes, search for the James Altucher show, and click subscribe. Like I said, it will take 30 seconds or less. And if you subscribe now, it will help me a huge amount. Thanks.