#48 Adam Robinson: Winning at the Great Game (Part 2)

Author, educator, and hedge fund advisor, Adam Robinson returns for part 2 of our fascinating discussion. We talk chess, AI, handicapping horse races, and the secret to learning that nobody is teaching. Go Premium: Members get early access, ad-free episodes, hand-edited transcripts, searchable transcripts, member-only episodes, and more. Sign up at: https://fs.blog/membership/ Every Sunday our newsletter shares timeless insights and ideas that you can use at work and home. Add it to your inbox: https://fs.blog/newsletter/ Follow Shane on Twitter at: https://twitter.com/ShaneAParrish Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  So what happens in a world where people don't have to work? And the utopians go, well, that's the best of all possible worlds. Good. People are free to pursue their dreams, whatever. But imagine the person who loses their job. They don't go cartwheeling down the street going, great, now I can write that novel.

• 0:26Shane Parrish?

  Hey guys, this is part two of my amazing conversation with Adam Robinson. We split it up into two episodes because the conversation was about four hours. You're not missing anything by starting here, but I'd highly recommend you go back and listen to part one. I mean, why wouldn't you? Adam is phenomenal and our conversation is fascinating. Anyway, here's part two with Adam Robinson.

• 0:57Shane Parrish?

  Which are the habits that work well in school and life? And which are the habits that work well in school and then don't work well in life?

• 1:05Speaker 00

  Well, if you think about it, that's such a good question. If you think about it, in school, we're graded. We're graded and the expectations are set by someone else.

• 1:16Speaker 00

  By the way, this is, this is a really cool study I did once on school. And then we'll get to the other part of your question. I was giving a talk in Sacramento some years back to 500 teachers. And I said, grading is subjective. And they got really kind of like, grumble, grumble, grumble, right? And I said, but you don't have to take my word for that. My teachers think their grading is objective, right? And I said, oh, no, like, we tell the students exactly what we expect and we're very objective at our grading. And I said, look, you don't have to take my word for it. Let's do an experiment. So I, I took out a box and I, I was in a big gymnasium, right? With 500 teachers. And I put a big box on the table and with great fanfare, I held up a bunch of sample

• 2:01Speaker 00

  tests. And I said, I had students write an answer to the question, is there evidence of global warming? And I've got hundreds of tests here. I'd like to pass it out to you guys and you grade it. And, and as an afterthought, I said, put down an M or an F if you're a male or female teacher. Now unbeknownst to the teachers, they were all grading exactly the same essay. But on some of the, on half the tests, I had a female's name at the top and on some a male name at the top. On half the tests, I had the paragraphs clearly indented and on half not. And on half the tests were printed and half script. And I gave them, and I said, graded on an A to F scale, F being failing, and, uh, and put an M or an F if you're, and I said, I know

• 2:46Speaker 00

  that you're all not environmental scientists, but we're all adults. We know something about global warming. Just kind of, just grade it intuitively, right? And then, um, over their lunch break, I fed all the numbers into a stat program. And I said, um, I said, guys, remember I said grading is subjective? The number one positive factor on, um, on your, on the essay was a female name at the top of the paper. It was worth an extra quarter of a grade. A equals 4.0, B equals 3.0, C equals 3.0. It was worth a quarter of a grade. It was worth a full half a grade, half a grade, mind you, if a male teacher was grading the female. So male teachers graded female students a half a grade easier than they graded male

• 3:30Speaker 00

  teachers. Both teachers, male and female, graded the opposite sex more leniently. Both male and female teachers graded boys more harshly. Mind you, this was on a science test, not like, you know, some other, like this is, this was an actual science paper, right? You had to like provide evidence and stuff. Um, and it was worth three, almost three fourths of a letter grade, uh, when you added in the paragraph indenting. Printing or script was not a factor. So if a male student was graded by a male teacher and forgot to indent his paragraphs, his letter grade dropped three fourths of a, .73 of a, of a grade, almost a full grade.

• 4:12Shane Parrish?

  Same content.

• 4:13Speaker 00

  From exactly the same content. So how do you measure how well students are doing, right? You know, like, and how do you measure how well the teachers are doing, right? Anyway, to go back to your question, sorry, I couldn't resist that. So skills in life are following instructions, doing what's expected. And in life, I don't think there are many assignments like that, you know? Even when your boss says, do X, you don't really mean just do X. Like, you're not a robot. We're not, um, I mean, I, I imagine certain jobs are like that. Like if you're flipping burgers.

• 4:47Shane Parrish?

  Well, you could almost make the argument that more increasingly, jobs are becoming procedural and the procedures are the mechanism by which you assign people tasks. If this situation, you do this. If this, you do this.

• 5:02Speaker 00

  Right. It's, that may be, that's certainly where jobs are going. And it's certainly where AI and robotics are taking things, right? In another, we can argue about whether it's 20 years or 30 or 40 or 50. Sometime in the next few decades, an algorithm or a robot powered by algorithms is going to do whatever you do better, faster, more reliably in every, cheaper. And that that isn't terrifying people.

• 5:31Shane Parrish?

  Does that scare you?

• 5:33Speaker 00

  It scares me for the world. It, it scares me because people define themselves largely in terms of what they're able to contribute economically. And so what happens in a world where people don't have to work? And the, the utopians go, well, that's the best of all possible worlds. Good, people are free to pursue their dreams, whatever. But yeah, but I don't think so.

• 5:56Shane Parrish?

  Psychologically, if you're not contributing to society, there's an impact on, on you as a person.

• 6:02Speaker 00

  It's devastating. Imagine the person who loses their job. They don't go cartwheeling down the, the street going, great, now I can write that novel. They're devastated. Now imagine everyone's out of work. And so, so that's a, that's a future we really have to, to, to prepare for. Silicon Valley has begun to prepare the world for that, floating notions of universal basic income, right? That's largely being floated out of Silicon Valley because they see where it's going. They see where the technology is going. And even in creative fields, AI is such a terrifying threat. Stephen Hawking gave mankind a 1 in 20 shot of surviving AI, a 1 in 20 shot.

• 6:47Speaker 00

  And you can do the math, that means a 19 in 20 shot, we don't survive. AI, that's how serious it is. And Stephen Hawking, no slouch in the IQ department.

• 6:58Shane Parrish?

  What is it about that, the AI, that scares us so much? Or threatens humanity in this case?

• 7:05Speaker 00

  Okay, so the real threat with AI, first, let's talk about how fast AI progresses. So, right now, there is no AI. It's not really AI. It's machine learning, pattern recognition. It's not really AI. What people think of AI is an intelligence that, left on its own, can learn, right? So, let's talk about a domain I know something about, chess, right? So, I'm a rated chess master with a life title. I'm pretty darn good at chess. So, I understand the implications of this with AI. So, the best human chess player in the world is a 27-year-old Norwegian named Magnus Carlsen. He has a chess rating of 2820, so 2,820-ish, give or take, something like that.

• 7:49Speaker 00

  The best computer software that had been trained on the best human games, right? Software trained on the best human games, has a chess rating now of about 3,300, would crush Magnus Carlsen in a match.

• 8:02Shane Parrish?

  And that's software you can get on your iPhone, right?

• 8:05Speaker 00

  On your iPhone?

• 8:06Shane Parrish?

  Yeah.

• 8:07Speaker 00

  Yeah, yeah. Maybe a little more, maybe on your laptop, but yes. Your iPhone software is probably like 2,600. Your laptop, yeah, it'd crush Magnus Carlsen in a 100-game match. Carlsen would be lucky to get five games out of 100. Like, it'd just be a wipeout. And he's the human champion, right? Okay, that was the best software trained on human games. Google's company, DeepMind, said, "What if we don't train it on human games? What if we just have the software play itself?" So, they gave...

• 8:38Shane Parrish?

  They gave it rules and was basically like...

• 8:39Speaker 00

  Just the rules of the game.

• 8:40Shane Parrish?

  Nothing else.

• 8:41Speaker 00

  Nothing else. Just play yourself. And in four hours, that program leapfrogged all existing human knowledge of the game. And has a chess rating of hard to estimate, like 36, 3700 compared with 3300. That program, mind you, it had no human intervention. They just gave it the rules. And this is what was fascinating about it. It recreated all human knowledge of the game on its own. Imagine giving a computer the rules of syntax and it creates the English language and Russian and Japanese and just on its own.

• 9:15Shane Parrish?

  It's like the story of if you had enough monkeys, it would eventually.

• 9:19Speaker 00

  Exactly. But now, so it, but also with enough monkeys, you create a lot of gibberish. But this, it actually created.

• 9:26Shane Parrish?

  Replicated all human knowledge without any existence of that human knowledge.

• 9:30Speaker 00

  Without any knowledge of the game. And because after all, human beings are pretty smart. But then, this is two interesting things about this. Google, which is to say DeepMind, only released 10 of the 100 games. This computer program played a match against the reigning software, 3300. It beat it 72 to 28 in a 100 game match with no losses.

• 9:52Shane Parrish?

  28 draws.

• 9:53Speaker 00

  Exactly. 56 draws.

• 9:56Shane Parrish?

  Okay.

• 9:57Speaker 00

  Right? And so the reason is that even if God were playing the software, it's not gonna, God's not gonna win every game because it's like tic-tac-toe. If you don't make a mistake, it's a draw.

• 10:10Shane Parrish?

  Yeah.

• 10:11Speaker 00

  Right? You can't, so there's a limit actually on how, God's chess rating is probably like 3900. I'm making that up. I'm being goofy now. So, so what was fascinating is they only released 10 of the games. And this is what was interesting and so scary is that the chess program, when you looked at the games, and again, I'm in a position to assess the value of the moves, how good they are. When I looked at the games, I went, wow, this is, this computer is so good. But then the computer would make alien chess moves. Surprising moves. Not just surprising, just like, like you just go, what? Why is it doing that? That doesn't make any sense. Makes no sense. So get this.

• 10:53Speaker 00

  So for example, it is a rule of thumb with human chess players that you should, even if you don't know about the game, you can sort of appreciate this. Your king is the most valuable piece. You should tuck your king away in the corner and keep it well protected. In this one game, the chess computer is called Alpha Zero Go, sorry, Alpha Zero Chess, marched the king smack into the middle of the board. Imagine you're Napoleon, leading your troops, and you yourself go right into the center of the battle, and bullets are whizzing by you, and nothing touches you. And you go, how can the computer get away with this? Like, there's no way, that's gotta lose. Like, and it won the game. Like, five, 10 moves later, it wins the game. You go, how the heck did it do that?

• 11:38Speaker 00

  And so it played alien moves. So not only did it recreate human knowledge of the game, it then created alien chess. Now imagine that computer is unleashed, not in the domain of chess, but in other domains. It'll totally recreate everything we know, and then go beyond it in hours. So the scary thing with AI is this, that it will become exponentially smarter than we are in minutes. So imagine the following scenario. Let's say the current reigning AI has an IQ of, say, 50, right? Let's say, I'm just picking a number out of the air. Eventually, it'll get to like 150. It'll be as smart as a really smart human being, like really super smart. Then the computer will go, oh, wait a second. I can do a better job of programming myself.

• 12:23Speaker 00

  It'll then reprogram itself. Now it has an IQ of 200, and then goes, wait a second, I can do much better than that. And it reprograms itself again. Now it's got an IQ of 300. It goes, oh, I was a dummy two minutes ago. And it will keep reprogramming itself with alien AI. And I say alien because we won't recognize it. We won't be able to even follow what it's doing. And it'll control everything. That's the problem. You know, there's the Terminator scenario, like, you know, these machines are gonna destroy us, and blah, blah, blah. No, they're not. They're just not gonna care about us. And it's a bit like the genie when you let the you get three wishes and the genie will give you three wishes and then it'll say goodbye and it'll control so an alien

• 13:08Speaker 00

  intelligence will control everything. You won't be able to cut it out of the

• 13:14Shane Parrish?

  And we might not even understand it.

• 13:15Speaker 00

  Oh, you won't understand it. Right now, there are mathematical proofs done by computers that human beings can't understand.

• 13:22Shane Parrish?

  Huh.

• 13:23Speaker 00

  The best mathematicians in the world don't understand those proofs and all they can say is, we can't find a mistake in it. It's probably right, but we're not real sure. We can't follow it. And the reasoning will be so convoluted that human, there's no way you could even explain it. So even now, the computer Watson, IBM's Watson, can come up with a medical diagnosis, the challenge of which is to explain the diagnosis to the doctor. Because the doctor can't follow the reasoning of the neural net and all the com-

• 13:54Shane Parrish?

  So an accurate diagnosis, they wouldn't have come to through a convoluted sort of mechanism of, here's how we arrived at that.

• 14:02Speaker 00

  Right. You couldn't, they couldn't explain it because it's in an embedded neural net. And there's with all kinds of feedback loops, you wouldn't be able to describe it so that any human being could understand it.

• 14:13Shane Parrish?

  Isn't that a bonus? I mean, outside of the understanding, if we're creating more accurate diagnoses and more-

• 14:20Speaker 00

  Sure. But now what happens when those machines are controlling not just diagnoses, but they're actually controlling surgeries and controlling weather patterns and controlling tanks.

• 14:32Shane Parrish?

  Because they'll think that they know best and then automatically-

• 14:35Speaker 00

  They will know best.

• 14:36Shane Parrish?

  Yeah.

• 14:37Speaker 00

  The algorithms are just, this is the thing about algorithms and AI. It is optimizing, unforgiving and relentless because it continues to optimize. And whatever values you've put into the into the AI, it will just execute that with with unstoppable efficiency.

• 14:56Shane Parrish?

  So you got into AI in the 1990s.

• 15:00Speaker 00

  In the 90s.

• 15:00Shane Parrish?

  Way before any of this stuff.

• 15:02Speaker 00

  Yeah.

• 15:02Shane Parrish?

  How did you get started? Where did that come?

• 15:04Speaker 00

  Right, so I was interested in, so I saw my interest in the Princeton Review in the late 1880s. Oh, 1980s, early 1990s, and I got into AI. And, um, because I was interested in intelligence and thinking, right? And the problem with AI back then, and even if you had asked a computer scientist, you know, what do you into? He or she would not have said AI because the problem then was the speed of the computers.

• 15:32Shane Parrish?

  The hardware limitations.

• 15:34Speaker 00

  The hardware limitations. So when I wanted to run a neural net, remember Pentium chips?

• 15:39Shane Parrish?

  Yep.

• 15:40Speaker 00

  Right? So I'd literally set up the neural net and hit enter on my computer and walk away from it for a week. And a week later, maybe I'd get an answer. And if the result was good, I'd go, great, good model. And if it wasn't, I'd have to tweak the variables and hit enter again and then walk away from the computer. And, and so now AI is done, you know, you can run a neural net like in minutes or something. And soon they'll have quantum computing, right? That's really scary and.

• 16:08Shane Parrish?

  What is quantum computing, just for people listening?

• 16:11Speaker 00

  So, right, so quantum computing is when you use actually subatomic quantum states to, to do your computations. And I, I myself don't understand the, the physics and the math of it. But evidently you'll be able to do things pretty much instantaneously. So for example, anything that's encrypted with quantum computing, you'll be able to crack that, whatever the encryption is, in, I don't know, seconds or minutes. So quantum computing is scary because there are no secrets now. Now you can't encrypt, you can't hide things. And I know hiding sounds bad, but sometimes you want things hidden. You don't want your social security number hackable and other things or government secrets.

• 16:55Speaker 00

  So, um, so yeah, uh, quantum, quantum computing is, is scary and, and the speed with which it will accelerate AI is also pretty frightening.

• 17:07Shane Parrish?

  How, how will it accelerate just based on the power of the technology?

• 17:11Speaker 00

  Right. And sheer power in the same way that things that used to take me a week on my computer on Pentium chips back in the early 1990s now take seconds. And now I mentioned seconds take milliseconds.

• 17:24Shane Parrish?

  Right.

• 17:24Speaker 00

  And, and

• 17:25Shane Parrish?

  It's a parabolic leap almost.

• 17:27Speaker 00

  Parabolic leap and which fundamentally changes reality. It's not just we're doing things faster. It's you, now you're doing things fundamentally differently. You, like when information can't be protected, imagine anyone can know anything about everything. That's pretty scary.

• 17:44Shane Parrish?

  I want to come back to something you said about the computers, AI and chess. And so the first version of the program you mentioned had learned chess from the human games. There was data available. The second version of the program didn't use data. What's the role in data today in terms of machine learning and AI? And then what do you see that role as in the future? Is, are those data sets going to be proprietary or will some guy in his garage be able to compete with Google on search?

• 18:12Speaker 00

  That's so funny you should say that. So that's a really profound question that goes to who owns the data, right? So, so when you log into Google, when you use Google or you use Facebook, Google and Facebook are gathering data, right? When you buy something on Amazon, when you look at something and don't buy it, Amazon is gathering data and it's able to use that data and monetize the data, right? And so the question is, why, even by the way, when you don't use something, that's a data point, right? If Shane hasn't logged into Google for three days, Google has learned something about Shane, right? Um, so.

• 18:52Shane Parrish?

  It's remarkable how much data they have on you.

• 18:54Speaker 00

  Oh, it's remarkable. And so there was a woman, a female journalist in the United States. Get this, in the United States, you don't own your data. Google does, or Facebook. It's their corporate data. But in Europe, the individual owns his or her data. So a female journalist asked Tinder, the dating app, "Give me all the data you have on me." And they gave her, I forget whether it was seven or eight hundred pages of unique information. So not seven hundred duplicate pages. Seven hundred, they had seven hundred pages worth of information about her. Like, I'm just making this up. They knew her first grade.

• 19:30Shane Parrish?

  Yeah.

• 19:31Speaker 00

  Transcript, you know, they, they knew what she ate for lunch five years ago. Like, they knew so much about her. And she was horrified that they were like, how could you even get this data? Like, some kind of data you kind of can figure out how they would get. But remember, the value of your data is when they cross-reference it with other people.

• 19:50Shane Parrish?

  Yep.

• 19:50Speaker 00

  Right? The value emerges not just because Shane is using Google, but lots of other people are. And they're able to, to, to do, use statistics and machine learning to find patterns so that they uncover things about Shane that even Shane didn't know.

• 20:06Shane Parrish?

  Yeah.

• 20:07Speaker 00

  There was a famous case about five or six years ago of Target. Do you know this? Where Target.

• 20:14Shane Parrish?

  The pregnancy?

• 20:15Speaker 00

  Yes.

• 20:16Shane Parrish?

  Yeah.

• 20:16Speaker 00

  Right. So Target's algorithms knew that a young woman was pregnant because she shifted from unscented products.

• 20:24Shane Parrish?

  Yeah.

• 20:24Speaker 00

  Sorry, so from, from, from scented to unscented.

• 20:27Shane Parrish?

  They knew before she knew.

• 20:28Speaker 00

  Right. She didn't know she was pregnant.

• 20:30Shane Parrish?

  Right.

• 20:30Speaker 00

  So the algorithm, by the way, the algorithm, I'm using air quotes now, didn't know that she was pregnant. They just knew that she would tend to buy baby products six months later. So let's start hitting her up now. Like, the computer doesn't, as it were, know pregnancy.

• 20:44Shane Parrish?

  Yeah.

• 20:44Speaker 00

  It just knows that when a woman of a certain age shifts from scented products to unscented, X months later, she's buying baby products. So let's hit her up right now. And so, so, yes. Google and Facebook and Amazon know things about you that you don't even know, like for sure.

• 21:06Shane Parrish?

  And Is that a cumulative advantage? Like, can that ever be?

• 21:10Speaker 00

  I don't know how it can be you could ever compete with that. You'd need to find some other way of gathering the data.

• 21:17Shane Parrish?

  Should data be a public good?

• 21:19Speaker 00

  Well, you know, that's a political thing. I, you know, it may be. There's Aristotle Onassis, who was once one of the wealthiest men in the world, said, "The secret to business is knowing something that others don't." Well, that's certainly the secret to Google and Facebook and Amazon and Netflix. They know everything about you and and they can leverage that. I'm not making a political statement now, but it's something that needs to be examined. And and

• 21:46Shane Parrish?

  Well, it's it's almost anti-competitive in a way.

• 21:48Speaker 00

  It's usually anti-competitive. Right. There's no way anyone could ever compete with that. They know exactly what you'll buy and won't buy. They know what price points to offer it to you at. How can someone compete with that? And and so the problem is on an anti-competitive level is we're in a global economy.

• 22:09Shane Parrish?

  Hmm.

• 22:10Speaker 00

  And so

• 22:11Shane Parrish?

  As soon as one country defects from these policies.

• 22:14Speaker 00

  Exactly right. A country will offer its own companies a competitive advantage globally.

• 22:19Shane Parrish?

  Right.

• 22:20Speaker 00

  So, good. Use that data for sure. So it's it's tough to argue for anti, these antitrust laws, because you put yourself at a globally

• 22:30Shane Parrish?

  Disadvantaged, say.

• 22:32Speaker 00

  Exactly right. So it's tough. It's gotta be, these are really tough questions we need to work out now. And again, one of the problems with algorithms is they just get embedded into our daily lives and then they execute with relentless, ferocious, unforgiving efficiency, 24/7. And we don't even know why they're doing the things they're doing. Again, human beings can't understand the algorithms. They're too complex. They just execute. So, so we have some hard choices as a, as a, not just as a country, but as a, as a planet. We gotta come together on these things. Yeah.

• 23:10Shane Parrish?

  I want to come back to chess a little bit.

• 23:13Speaker 00

  Sure.

• 23:13Shane Parrish?

  I know when you were a kid, how did you learn chess? You went to school. You played this guy at lunch. You got beat.

• 23:20Speaker 00

  So my father taught me how to When I was a boy, I had to be careful of the questions I asked my father because I remember one day he was playing chess with a friend. I was all of six and a half. And I said, can I watch? And he said, yeah, sure you can. But I had to learn the rules of the game, right? And so, so that's all I knew about chess. I just knew the rules. So I wasn't interested at all. And then in high school, freshman year, first day of high school, a kid in homeroom had a little magnetic chess set and he turned around in homeroom. We had 20 minutes to kill. And he said, you know how to play chess? And I said, yeah, I know how to play very proudly. Like, it's like saying I know how to play baseball when you've swung a bat once, right? And so, so he beat me in, you know, four or

• 24:05Speaker 00

  five moves. And I got kind of pissed. And I thought, okay, I'm gonna beat him the next day. And he beat me every day that week. And I just thought, he was so smug about it. I just, I was a swimmer. And that's really all I cared about was swimming, competitive swimmer, right? Four or five hours a day. And I thought, I just want to beat this kid. I just want to, by the end of the year, it was my little goal. So I went to the bookstore and I got a book of Bobby Fischer's games and called My 60 Memorable Games. And I, I played over those games every day after swim practice when I got home.

• 24:35Shane Parrish?

  And by playing over them, you mean mentally or physically?

• 24:37Speaker 00

  Oh, I set up a chessboard. And his book would play through, you know, he would list the moves of his games. And with annotations, he would explain why he did and did not, you know, that was a good move. Here's why that was a bad move. That's why. So I played over these games over and over. So I knew them by heart. And I thought, wait a second, he's been playing chess at that point, let me see, 69, he'd been playing for, you know, 20 plus years. And I thought, there's more than 60 memorable games. I want to get every game he has.

• 25:06Shane Parrish?

  Bobby Fischer.

• 25:07Speaker 00

  Bobby Fischer, right. This is before he won the world championship. So I went to the library and I got every old chess magazine. I went to downtown Chicago on a train. I was, what, thirteen? And I went to the library. People don't remember what libraries were in this day of the internet. But I, and I spent weeks going there, going through every back issue of every chess magazine globally to find Fisher games. And if there was a Fisher game, that's all I wrote down. Like, I didn't copy down anybody else's games. It was just my little mania. And so, at the end of the year, actually, I did it in a couple of months. I had about 700 of his games in a little playbook, that I had a little notebook.

• 25:49Speaker 00

  And I, by hand, had written down all these games, and I played them over, over and over and over. And he was the most famous chess player in the world, but he hadn't yet won the world championship. He was 27, 26, 26 at this point, 26, 27. And by the end of the year, I had beaten that kid, the kid with the smug smile.

• 26:08Shane Parrish?

  Of course.

• 26:09Speaker 00

  Yeah. And then, and then, a couple of years later, I was one of the best high school players in the country. And my team, this is from Evanston, Illinois, we sent a team to New York. And we finished second place that year. We won the next year. And just by chance, on Easter Sunday, and I was, what, 16? I was walking with my mother, and near Macy's, those of you who know New York, it's on 34th and Broadway, I, across the street, I spot Bobby Fischer, which was, like, he was the most reclusive person in the world. And I said, "Mama, I'll see you later. That's my hero over there." And I ran across this, like, dodging traffic to get to him out of a crowd. He was enormous, 6'3".

• 26:52Shane Parrish?

  Yeah.

• 26:52Speaker 00

  Like, but even still, to spot him in a crowd, like, what are the odds? And I just ran up to him, and I said, "Mr. Fischer, Mr. Fischer, you know, in 1962, when you played Ryshevsky and the Sicilian, why'd you play pawn to king rook 3 on move 6? Like, what was that about?" Like, because I knew all of his games by heart. And it didn't occur to me that he would, like, say, "Get lost, kid," right? And he was a famous recluse, like, just paranoid about everybody. But here's this strange little kid, knows all of his games. And he just became a mentor. He was, you know, and again, this was in the two years leading up to his winning the world championship.

• 27:30Shane Parrish?

  And you spent time with him before the...

• 27:32Speaker 00

  Yeah. I got a chance to spend time with him at the, there used to be a resort called Grossinger's in the Catskills. If you saw the movie Dirty Dancing with Patrick Swayze back in the day, it was where...

• 27:47Speaker 00

  Muhammad Ali had trained. I guess he was, I don't know if it was, yeah, Muhammad Ali had trained for one of his boxing matches there. So they offered Fisher a chance to train for the Spassky match, the world championship. And I got to spend two weeks with him, watching him prepare for the world championship, which was so cool.

• 28:05Shane Parrish?

  What did you learn from watching him prepare?

• 28:08Speaker 00

  Hmm. Well, this is interesting. Fisher, Fisher woke up at 11 or 12 in the morning, and went to sleep at 3 or 4 at night. So you learn that for him, that was the optimal time of day, right? Time of day and night, right? Where he functioned the best. And so you learn to find out like, how you function the best. We all do that, right? Like, I know there's certain times of the day, like, the first 30 minutes when I wake up are where I get the most creative ideas, or after 10 at night, for me. So each of us learned, so I learned the importance of that. I learned the importance of, of, of pretty much a

• 28:49Speaker 00

  single-minded focus. That's all he did, which was one of his tragedies. He said famously once, "All I ever want to do, ever, is play chess." And that's great, but when you win the world championship, now what do you do? And, you know, he, he sadly was, lost his mind to paranoia, over the years. And that was a real shame. Paranoia is tough, because you don't trust anybody. And after a while, he didn't even trust me. He just fell out of touch with, with the world. But on a positive note, I learned the importance of focus, of knowing your opponent. He, he had a game, a red book of his opponent's games. That's

• 29:33Speaker 00

  all he did. He just played over those games, over and over. And, and I could tell-

• 29:38Shane Parrish?

  Which is the same way you learn.

• 29:40Speaker 00

  Right, exactly. I just played over Fisher's games. Now, the thing is, I played people other than Fisher. So, so it's not the optimal way. I should have studied other people. I should have. And so did Fisher, but when he was preparing for the world championship match, that's all he did.

• 29:55Shane Parrish?

  Didn't he do like, a bait and switch? Because he assumed-

• 29:58Speaker 00

  Yes, yes. So, his whole life, so mind you, he was a world-class chess player. Actually, let me talk about Fisher, because Fisher was unique in the world, in the following way. Fisher learned the game of chess at the age of six. And by the time he was 11, sorry, by the time he was 12, he was a good 12 year old chess player, not a great 12 year old chess player. He was a good 12 year old player. That's six years later, right? After six years of playing chess, Bobby Fischer was good. At the age of 13, a year later, he played a game that some people say was the game of the century as a 13 year old. So one year later, he goes from good to playing a game people today still play over

• 30:40Speaker 00

  going, oh, my God, like a 13 year old played that game? At the age of 14, he was the US champion. Mind you, at 12, he was merely a good 12 year old. At 13, he played a game that some people say is one of the best ever. At 14, he was the US champion. At 15, he was one of the top eight players in the world. What happened? Exactly. And he did that on his own. Imagine No coach, no? No coach, no nothing. Now, that's not entirely true. He had a coach, but the coach had a chess rating of like 2000, like not really a coach. It'd be like, a decent player. It'd be like, you pick up a tennis racket and your coach is the best player in your neighborhood. Okay,

• 31:22Speaker 00

  that's not going to get you too far, right? Like it'll get you the rudiments. Fischer did that entirely on his own. And no one in the history of the game has improved like that, not just that game, in any field on his own. And How'd he do it? Well, he was a genius. And he was very simple. And he played the same series of openings. You know, Tim asked me that question, Tim first. He said, what was unique about him? And I said, he had a childlike simplicity. He really did. He looked, when you looked at his games, it was like a child playing them. And, and everyone else had really complicated games. And Fischer's were always very simple. And the thing about Fischer, oh, this is something

• 32:07Speaker 00

  really about Fischer. He always played to win. He didn't mind losing. Actually, he hated losing, but he wanted to win more. And so there were games where anyone else would have accepted a draw, that Fischer would play to win, and in doing so, sometimes lost. And I think there are two ways to live your life. You can play to win. No one wants to lose. You can play to win, or you can play not to lose. And Fischer always played to win. And you knew, even if in a losing position, He was looking for a way to win. He was not giving up, not till you actually totally beat him. Not that that happened too often, but so there was a ferocious will to win.

• 32:50Speaker 00

  That was something also about Fisher. And he did it entirely on his own against the Russians, who were determined to beat him as a group, as a block. Imagine a kid in Russia taking up the game of baseball and becoming the best baseball player in history on his own.

• 33:05Shane Parrish?

  This was during the Cold War.

• 33:07Speaker 00

  Right, during the Cold War era.

• 33:09Shane Parrish?

  Politics things going on.

• 33:10Speaker 00

  So many political things.

• 33:11Shane Parrish?

  And he had the ultimate bait and switch with.

• 33:14Speaker 00

  With Spatsky, yeah. He always played pawn to king four, always played the same openings. Imagine always coming out with a right hook and then in the world championship, switching up and.

• 33:23Shane Parrish?

  Playing something different. And Spatsky had been going over his games, just like he was going over Spatsky's. And then all of a sudden, this doesn't look.

• 33:29Speaker 00

  Fisher did something totally different.

• 33:30Shane Parrish?

  Doesn't look the same.

• 33:31Speaker 00

  Now, Fisher, it was a total bait and switch. And Fisher set up the Russians for, let me just figure this out, 10 to 20, for 16, 17 years, played exactly the same moves. So everyone knew exactly what he was going to do. And in the world championship, only he did something different.

• 33:49Shane Parrish?

  Which must have been unnerving if you're on the other side of the table.

• 33:52Speaker 00

  You wouldn't know what to do. You would have been flabbergasted, like, uh-oh, all the preparation I did for Fisher is useless. I thought I was playing one person, I'm now playing someone else. So, so that was, yeah, an incredible bait and switch that Fisher pulled, yeah.

• 34:07Shane Parrish?

  I want to come back to a little bit, tie this to AI a little bit, but I want to come back to the role of information in decision making.

• 34:15Speaker 00

  Sure.

• 34:16Shane Parrish?

  Computers can handle way more information than we can as humans. You had talked about the Paul Slovac study.

• 34:22Speaker 00

  Yes.

• 34:23Shane Parrish?

  On the phone with me. Can you elaborate a little bit about that?

• 34:26Speaker 00

  Sure. So, human beings have a limited processing ability, right? Our brains are.

• 34:33Speaker 00

  Have very little what's known as working memory, right? We can't maintain a whole lot of information in our head at any one point. And so because of that limited processing ability, we, we have a hard time with too much information. And so, so we like to think that the more information we get, I'm using air quotes now, the better informed we are and we'll make better decisions. But that's not true. And a seminal study was done by, by a psychologist named Paul Slovic back in 1974. So Paul Slovic gets eight horse handicappers into a room. And he says, I'm going to see how good you guys are. Right? And so he says, we're going to spend today handicapping horse races,

• 35:18Speaker 00

  which is to say predicting the winner of a horse race. And these had been races that had been run over the last few decades that Slovic had gotten the stats on. And he deleted the names of all the horses because if you knew the name of the horse, it would give you an edge, right? So all you saw was numbers. Right. It's all you saw. And so he said, we're going to handicap 40 horse races. And we're going to do so in four rounds, 10 races each. And in the first round, I'm going to give each of you horse betters, handicappers, any five pieces of information you want. So like you might want the weight of the jockey, but that guy next to you, the other handicapper, he doesn't really care about the weight of the jockey, right? He wants some other variables. So each of you, whatever five pieces you wanted and that guy wanted, and each of the horse handicappers wanted, they got.

• 36:03Speaker 00

  And at the end of the, the first round with five pieces of information, they were 17% accurate, right? Which is 17 or 19? Hold on. 19% accurate, which is pretty good. It's almost twice as good as chance, right? Apologies, it's been a while since I looked at the study. 17 or 19%. Anyway, almost twice as good as chance, which is pretty darn good with five pieces of information. I say twice as good as chance. There were 10 horses in every race. So we would expect 10% accuracy, just blind guessing. Just pick one in 10. Yeah. You got a 10% chance of getting the horse right. So if you're betting 19%, you've almost doubled your, your results. That's pretty good.

• 36:46Speaker 00

  And he also asked each of the betters to rate how confident

• 36:50Shane Parrish?

  They are in their predictions.

• 36:52Speaker 00

  And they were, oh, I remember what it was. That's why I was confusing the two. They were 17% accurate. They were 19% confident.

• 37:00Shane Parrish?

  Okay.

• 37:00Speaker 00

  That was it. So almost identical confidence and accuracy.

• 37:05Shane Parrish?

  Round one.

• 37:06Speaker 00

  Round one with five pieces of information. Round two, they were given 10 pieces of information, then 20. And in round four, they had 40 pieces of information. And there were 10 races. So this was statistically valid results, right? Their accuracy was still only 17% with 40 pieces of information. But their confidence almost doubled to 31%. It went from 19% to 31%. So they are now almost twice as confident as they ought to be, which is to say they're overconfident. So all the extra information did was just feed their confirmation bias. They had already made a decision based on five pieces of information.

• 37:49Speaker 00

  And all the new information did was make them more confident in a decision they already made, right? Which is why, by the way, in my investment analysis, when I look at global markets, I reduce all global markets down to a handful of variables like copper versus gold or investment grade bonds versus corporate bonds, right? LQDIEF, that ratio I told you about. Now, those are my, two of my really key variables to predict not just the stock market, but interest rates. And so the goal is to reduce complexity to a few pieces of information that you can follow and reason with. The trouble with too much information is you can't reason with it.

• 38:32Shane Parrish?

  And you don't know how things interact. Whereas if you have the few key variables, you can figure out how they interact and how.

• 38:38Speaker 00

  That's exactly right. That's such a good point, Shane. You can figure out how they can interact and you can figure out when you're wrong.

• 38:45Shane Parrish?

  Right.

• 38:45Speaker 00

  Right? So one of my favorite investment questions is, what would I need to see to change my view? And if you're dealing with dozens of variables, there's no way. That you can change your view on, like, there's just too much information to keep in mind, right, the way they all interact. But if you're dealing with three or four or five variables, I can say, I'm bullish on the US stock market until I see this one variable decline by more than 3%, in which case, then I'm bearish.

• 39:14Shane Parrish?

  Because now I know, I've gotten the feedback I need on the variables I understand. Do you, like, I have a hypothesis that distilling things down to the essence or the key variables, not all the variables, but the ones that are probably going to govern the outcome.

• 39:29Speaker 00

  Sure.

• 39:29Shane Parrish?

  Also helps you with information filtering, because now you don't have to pay attention to all of these other things coming at you. You don't have to read every press release. You don't have to...

• 39:39Speaker 00

  Yes, exactly. I, so, you had asked me earlier before we started this, you know, like, how long do I look at markets? And I, I size up global markets in really in, in 15 seconds or 30 seconds, because I know exact, and by the way, when I say global markets, I mean all global markets, including currencies, bonds, and current commodities. It's not to say I look at every single currency, but I look at most of the major stock markets, and commodities, and the major currency pairs, and interest rates, in 15 to 30 seconds, because I know what I'm looking for. And I'm only looking for changes that are unexpected, because I've already formed a view, right? I know how the market should behave, and now I'm just looking for deviations. So I just have to glance and see if there's a deviation.

• 40:24Speaker 00

  It's kind of like looking at a, imagine a, a classroom of kids, and a teacher just scans every day and just looking for, is a kid missing, or is there a new kid present? And then, oh, gotta pay attention. And so I'm able to do that in global markets, because I know what I'm looking for, which gives me a reasoning edge also.

• 40:42Shane Parrish?

  How does that give you a reasoning edge?

• 40:45Speaker 00

  There's a saying in Zen Buddhism. The beginner mind sees many possibilities. The expert sees only a few. Think about driving. Think about when you learned how to drive, Shane. When you first got behind the wheel, it's terrifying. You have no idea where like, what do you look at? There are people walking around. There's stoplights. There are other cars.

• 41:08Shane Parrish?

  There's millions of inputs.

• 41:09Speaker 00

  Millions of inputs. And you have no idea what to look at. And the process of becoming a skilled driver, that all becomes automated, right? You don't have to look for very much at all. You know exactly what's relevant and what's not. And so I think that's true with all experts in all fields is you learn what not to pay attention to so that you can give more attention to what's important. Right? Otherwise, the person is like looking at a million different things. I actually don't understand that about the investing world. I look at three or four or five things to understand global markets. I don't understand people who look at literally dozens to hundreds to thousands of things.

• 41:51Speaker 00

  This statistic, that government report, that annual report. How in the world can you possibly form a view of the world that you can test? Like which variable is having which effect? Like, how would you know?

• 42:06Shane Parrish?

  You can't.

• 42:07Speaker 00

  You can't.

• 42:08Shane Parrish?

  But if you're consistently wrong and you have a few variables and you know those aren't the variables, or at least one of them is.

• 42:13Speaker 00

  One of them is askew or your reasoning is askew. And like modify and find out what works.

• 42:19Shane Parrish?

  And that that allows you the feedback to actually get better over time.

• 42:23Speaker 00

  Right.

• 42:24Shane Parrish?

  And getting better might just keep you in the same relative position because the world's always changing. But hopefully you can actually accelerate that and break out of.

• 42:32Speaker 00

  I think you can. Any individual who approaches his or her life in any domain can get better.

• 42:40Speaker 00

  You know what, I'm gonna tell you something from chess. This is an interesting rule. Fischer played a very limited opening repertoire, which is to say he played very few openings, and got really good at those openings before he did anything else. So the thing is, instead of doing lots of different things, get good at a couple. So for example, if I were a guitar teacher, I'm just making this up, I'm not. If I were, I would have a student gain mastery over a few songs and get really good at those. And then slowly, build on that expertise to introduce new songs. Instead, what we do is we try to teach a student dozens of songs.

• 43:20Shane Parrish?

  Right.

• 43:20Speaker 00

  And you don't really get any good at any.

• 43:23Shane Parrish?

  Right.

• 43:23Speaker 00

  That's the difference between the US education system, by the way, and Oxford and Cambridge.

• 43:28Shane Parrish?

  Oh, tell me more about that.

• 43:29Speaker 00

  Sure. So, the idea of a liberal arts education is this. If you learn a lot, sorry. If you learn a little about a lot of different subjects, you'll be able to sort of piece it all together, "it" being in air quotes, right? If you learn a little bit about a lot of things, you'll be able to generalize and kind of think about anything. Well, no you won't, because you've never learned how to think. At Oxford and Cambridge, the belief is, "learn one thing really well, and then you can learn anything else really well." Until you've gone into depth...

• 44:02Shane Parrish?

  Until you've actually done something, learned it, mastered it, and gone through the process of learning, you probably don't really understand how to learn.

• 44:10Speaker 00

  You don't understand how to learn, right. Because you've only stayed at a really superficial level. In the United States, you don't really begin to specialize and to go into depth until graduate school. I don't know why they do that. Instead, it would be much better if you learned one or two subjects really well, and then branch out from there, right? I think US schools would be much better off if they focused on teaching students simply how to read well, and write well, and rudimentary mathematics. Get that down for the first eight years. Make sure they're really good at that.

• 44:44Shane Parrish?

  Right.

• 44:45Speaker 00

  And then introduce a subject.

• 44:47Shane Parrish?

  Right. One at a time.

• 44:49Speaker 00

  One at a time. Get good at that, right? How much... How much do you remember from high school chemistry? I mean, I barely remember anything, right?

• 44:57Shane Parrish?

  Not much at all.

• 44:58Speaker 00

  Right, not much at all, really a waste of how many hours of my life.

• 45:02Shane Parrish?

  Yeah.

• 45:02Speaker 00

  Right, there are lots of stuff, and college too, like you don't really get a chance to to learn much. And ultimately, it's it's wasted time. Learn one thing well, then you can learn anything well.

• 45:15Shane Parrish?

  What is the process for learning? Is there a process?

• 45:19Speaker 00

  Well, I think, yes, there is.

• 45:21Shane Parrish?

  Like, how do we learn?

• 45:23Speaker 00

  Right, so that's such a good question. I I wrote a book, wow, 25 years ago, called What Smart Students Know. And I I did the following. I I realized that, by the way, I'm not plugging the book, I am not, absolutely not. Uh, cuz I can summarize it now, and I wish I had the time to rewrite the book. But what I did was this. No one ever shows us how to learn, ever. Nowhere in school, for example, imagine Shane in French class, French 101, your first French class. Your teacher said, everyone, you're gonna have to learn a lot of vocabulary in this class. So before I teach you any words, I'm gonna teach you a way to remember vocabulary. They never do that. They just go, we're gonna have a quiz on these 30 words on Monday, good luck.

• 46:08Shane Parrish?

  Right.

• 46:09Speaker 00

  But they don't teach us how to learn, actually, or remember things. Like, for example, they don't tell students, if you wanna remember anything, create a picture, a pattern, a story, or a rhyme out of it. All mnemonics come back to picture, pattern, story, or rhyme. But they don't tell us that. So we struggle, we, you know, we create flashcards, which are totally ineffective. And we keep rereading our notes. So I wrote What Smart Students Know. I I gave students a page from a geology textbook, like a sample page. And I spent the next 200 pages showing how to actually, what it would mean to learn that. Like, I actually.

• 46:46Shane Parrish?

  That's amazing.

• 46:47Speaker 00

  It's really cool, right? I mean, not that you would do that depth, but like, what does it mean to learn that page of information? Like, here's everything that you would actually need to do. By the way, if I told you all the steps it would take you to tie your shoe, it'd be much harder than just

• 47:01Shane Parrish?

  Show it.

• 47:02Speaker 00

  Watch this.

• 47:02Shane Parrish?

  Yeah, yeah.

• 47:03Speaker 00

  Right? So, so the secret to learning anything is this, anything. I'm glad you asked that question, rehearsing. If you want to get good at football, play football. If you want to get good at playing the guitar, play the guitar. If you want to get good at chess, you've got to play chess. Now, you want to break that down to certain skills and rehearse each one of them. So you see people playing pickup basketball or tennis and they haven't broken it down to skills and they're just out there playing, right? You want to break the domain down to sub-skills and then rehearse each one. Now, the reason I use rehearse is you want to do exactly what you would do in the actual game, right?

• 47:47Speaker 00

  So, for example, if you want to get good at taking tests, you have to take tests, which is to say the following, let's deconstruct that. So I'm going to, in the next two minutes, summarize everything there is to know about learning a subject. And it's this, you rehearse whatever you were required to do on the test. So think about a test. On a test, you were asked questions you've never seen before. And you have to search your memory for the relevant information, right? So step one, read the question. Step two, search brain for relevant information. Step three, collate that information into an answer, write answer.

• 48:28Speaker 00

  You have to rehearse each one of those steps to do well in those subjects. Right. So what that means is you need the way to prepare for a test. I hate the word prepare or study. Because here's what most people mean by the word prepare for or study for a test. Reread my notes. If you think back to when you were in high school and college, I looked at most students and what they would do is they would highlight their textbooks and take lots of notes and then reread their highlightings and reread their notes. But that's not rehearsing a skill. Right. No one tests you on how will you highlight. Right. No one tests you on rereading your notes. Because on the test, you're not rereading anything. You're seeing an entirely new situation.

• 49:12Speaker 00

  So the way to get good at any subject and any domain is to rehearse the skills that you're actually required to do. So practice questions. Practice questions that you've never seen before. And you then have to search your memory for the relevant information. By the way, it helps. What I would do in college is I would get textbooks the teacher wasn't using. And I would see what questions were asked there. So I'd really get questions I'd never seen before, even from teachers, teachers, authors, textbook authors, that weren't my professor and weren't the authors of the textbook I was reading. So I'd really get stumped with questions, right? And so, because that's going to happen in the actual game.

• 49:57Speaker 00

  So for example, imagine you're a basketball coach, right? And you want to train your basketball players. At certain points, your key player is going to be out of action, right? Fouled out or injured, right? I would have them play basketball games where, take out one of the players and you're now playing with four, right? Or one of you, like, I would try to find a way to make their arm a little, like, wrap it up or something, so it was a little constrained, like, okay, you've got a muscle sore, now you're playing the game.

• 50:27Shane Parrish?

  Now practice.

• 50:28Speaker 00

  Now practice, now rehearse, right? So rehearse under varying conditions. But a key, the key to learning any skill, really, if there's anything I said today, like, that was super important, the key to learning any skill, rehearse it. Break it down into sub-skills and then rehearse each of those skills. If you're doing something other than that, you're wasting your time. Rereading your notes, waste of time. You want to get good at a job interview? Have someone ask you questions, someone who doesn't know you, ask you questions, right?

• 51:00Shane Parrish?

  And then grade your feedback and listen to it and...

• 51:03Speaker 00

  Exactly right. And then, exactly right with the feedback, Shane. Then, okay, I spoke too fast.

• 51:09Shane Parrish?

  Right.

• 51:10Speaker 00

  I was coaching a young woman. She had a job interview coming up. And whenever I spoke, she did the following. Here, talk to me, talk to me right now, and I'm going to pretend to be her listening. So talk to me right now, Shane, just say anything.

• 51:26Shane Parrish?

  What I want you to do is...

• 51:27Speaker 00

  Uh huh, uh huh.

• 51:28Shane Parrish?

  Go to the...

• 51:31Speaker 00

  She would say, uh huh, so quickly. And I said, are you aware that you are signaling that you're not listening to the other person? And she was dumbfounded. And she'd gone to Columbia University, I mean, you know, a good school, right? Great school. She said, no one's ever told me that before. I said, you say aha so quickly. There's no way you heard what I asked you or said to you. And all you're signaling is you're not listening to me. I already don't like you. I liked her. I mean, I was giving her feedback as a mentor, right? And so, so you need feedback. And she was stunned. She said, no one's ever told me that before. And I said, just talk more slowly. Don't say aha so quickly. Listen to the person.

• 52:12Shane Parrish?

  So let me encapsulate this a little bit. If I'm in school, I'm in university, high school, I'm doing physics. The question's at the end of the chapter, which most people annoy or avoid. And teachers may assign the odd numbers or the even numbers.

• 52:27Speaker 00

  Right.

• 52:27Shane Parrish?

  You should be doing them all and not, not looking at your notes, trying to do them. And then if you're stuck, go back and look in your book.

• 52:34Speaker 00

  Exactly right. If you reread your notes, all you're getting good at is like following, following problems you've already seen before. That's not going to help you when you get a new problem because that's what's going to happen on the test. I'll go one better. You want to get really good? Try the sample questions at the end of the chapter before you read the chapter.

• 52:52Shane Parrish?

  Oh, that's interesting.

• 52:53Speaker 00

  Now, because what that does is it primes you. Now, now all of a sudden, whoa, how would I, there's no way I can answer those questions. Let's now you're primed as you read the chapter of what's relevant and what's not. And you also prime yourself for the following. What happens when I have incomplete information?

• 53:11Shane Parrish?

  Right.

• 53:12Speaker 00

  What happens if I forget the Pythagorean theorem? How do I answer the question then? That's what I did at the Princeton Review, by the way. What happens when you know only two of the five choices? What do you do?

• 53:23Shane Parrish?

  Right.

• 53:23Speaker 00

  Like there's, there's a whole range of things that you can do when you're skilled. Right? So what happens? In a, what happens as a baseball player? If I've, if I've got sweat in my eye and a, and a fly ball is coming at me, what do I do? Right? I mean, you need to rehearse for the unusual as well as

• 53:44Shane Parrish?

  Non-optimal conditions.

• 53:45Speaker 00

  Non-optimal conditions because you can't ever count on optimal, ever. And if you get them, great, you're lucky.

• 53:52Shane Parrish?

  So would you organize what's, what smart students know differently now? Or would you take the same approach, which is like, here's a page of geometry? And how would you update that?

• 54:01Speaker 00

  I would ask them to say, I'd, I'd ask them to break down. I'd have, I'd teach them how to teach themselves. I'd say, okay, in a little Socratic way. Will on their test on this material, will you have seen the questions before? Yes or no? No, like I'd step them through and get them to discover whoa, reading my notes, rereading my notes is just a total waste of time.

• 54:24Shane Parrish?

  Right.

• 54:25Speaker 00

  Like, that's all they do. They take notes in class verbatim. Here's a skill on the test. Do you parrot back exactly your teacher's words or do you express them in your own words? Well, of course you express them in your own words. Well, then you have to rehearse doing that.

• 54:40Shane Parrish?

  Right.

• 54:41Speaker 00

  Right? So when you take notes in school, they're probably verbatim just because you've got to keep up with the teacher. Right? But then translate those notes into your own words because that's what you're going to have to do on the test. Don't reread your notes, translate them.

• 54:54Shane Parrish?

  Right.

• 54:54Speaker 00

  Because you've got to do that on the test. And if you haven't done it before, you're not going to be able to do it on the test.

• 55:00Shane Parrish?

  That's really fascinating. How does that carry over to adults then who might be working in an organization or need to acquire new skills? Or?

• 55:10Speaker 00

  Ah, well, to figure out what it is you're required to do and then and to rehearse that skill. Like, let's say it's presentations, you've got to give presentations to clients. Right? Then you're going to have to rehearse that.

• 55:23Shane Parrish?

  What if the skill is more murky? What if it's like managing people?

• 55:26Speaker 00

  Oh.

• 55:27Shane Parrish?

  How do we go about learning to manage people? How do we get the feedback?

• 55:31Speaker 00

  That's such a good question. I have to think about that. That's a, that's a challenging one because after all, you're going to have to teach yourself unless you're being coached. Right? Here's the way to think about it. If you're playing tennis by yourself, do you think you, Shane, are going to be able to correct your tennis strokes? I don't think so. Right? Because you're not going to be able to see what you did wrong.

• 55:53Shane Parrish?

  Yeah.

• 55:53Speaker 00

  Right? You're not going to have.

• 55:54Shane Parrish?

  You're part of the system.

• 55:55Speaker 00

  You're part of, right, you're embedded within it. It's like a fish, like not knowing that it's surrounded by water because it doesn't know non-water. Right? So. Fisher in chess was able to do that because he saw the results of his game. He could play over the games and go, oh, that was a mistake. I'm never doing that again.

• 56:11Shane Parrish?

  Right.

• 56:11Speaker 00

  Right? But when you're dealing with people, how do you know, like, what results am I getting? And for example, people could smile. You could be getting totally the wrong feedback. They may be smiling because they don't want to upset you. Right? Here's an example. When I want to give a talk and I want to rehearse for that talk, I need to do it in front of people who don't know me. If they're my friends, they're going to be smiling and nodding their heads at like, just because they know me. Right? When I have to make a pitch, it's going to be to someone who doesn't know me.

• 56:42Shane Parrish?

  Right.

• 56:43Speaker 00

  Right? So I need that feedback. Right? Here's something. When I want to find out whether I know something, I explain it to people that I barely know. Like, I could be sitting next to someone at a restaurant going, this is a new book I'm writing and like, would you like to listen? And, you know, if I can engage that person who's a stranger.

• 57:00Shane Parrish?

  And get them.

• 57:01Speaker 00

  And then get them interested, then I know, okay, good. Now I'm getting some feedback now. That's useful information. Right? I mean, I gave you a copy of my book, right? And I've given other friends copies of my book to get feedback. Right? And if they said, oh, Adam, you know, this one chapter is a little long, like, then it's useful. And by the way, I've given it to people who, like, who know me, but they're not friend friends. Like, they don't know me that well. Like, you didn't know me that well, really? And, and so I use that feedback to, to revise. But your question is a good one. In everyday life, how do we get feedback? Boy, I think sometimes you just have to ask. Here's a question I wanted to ask friends. What do people know about Adam that Adam doesn't know about Adam?

• 57:45Shane Parrish?

  Oh, that's a great question. Have you, have you asked that?

• 57:49Speaker 00

  Yeah, I just started to ask, you know? And be brutal, right? Like, what does Adam know about, what does everyone know about Adam that Adam doesn't know? And like, okay, like, and be prepared for the answers and be honest. Really, if you wanted to be scientific about that, you could submit it to 30 friends and give them some like online forum where like Survey Monkey or something where they didn't, you just like, okay. By the way, someone told me it was really good advice regarding writing. He said, Adam, if one person tells you something, that's that person's opinion. But if three people tell you the same thing, you've really got to listen. And, and I, I think that's, that's good advice. That's really good advice. It's hard because sometimes your friends, they don't want to hurt, I'm using air quotes now, hurt your feelings.

• 58:33Shane Parrish?

  But they're hurting you by, by not being honest with you in a way.

• 58:36Speaker 00

  Yeah, you know, yeah, I think that's, boy, that would be a great website. You know, someone could start a website here, someone out there listening to Shane's brilliant blog and podcast, here's an idea, you create a website where people can write feedback for people and it's submitted to the person anonymously.

• 58:56Shane Parrish?

  I like that.

• 58:57Speaker 00

  Like, just thought you ought to know.

• 58:59Shane Parrish?

  Yeah.

• 59:00Speaker 00

  Like, that'd be really cool. That'd be a great service for people and like, oh, wow, I didn't realize, you know, I cut people off.

• 59:07Shane Parrish?

  Right.

• 59:08Speaker 00

  Or I talk too fast.

• 59:09Shane Parrish?

  Because now you can start seeing things about yourself that you're blind to.

• 59:12Speaker 00

  Totally blind to.

• 59:13Shane Parrish?

  People don't want to bring up because of social norms or they're your friends or...

• 59:16Speaker 00

  Yeah, or, or they just don't think someone, I, I know a young man, brilliant, and he's so brilliant, he almost comes across as too slick.

• 59:25Shane Parrish?

  Hmm.

• 59:27Speaker 00

  And I was talking to someone about him who knows the same young man and, and they said, well, Adam, you should tell him. And it didn't occur to me to tell him that and I, and I, I said to him, I said, by the way, you might want to stumble occasionally.

• 59:41Shane Parrish?

  Right.

• 59:41Speaker 00

  Because you're so polished and so slick that you're not approachable.

• 59:46Shane Parrish?

  Right.

• 59:47Speaker 00

  And even there, his response was a slick, oh yeah, the pratfall effect, I know that, okay, I'll do that.

• 59:54Speaker 00

  So, so I mean, he even know where, he knew where I was going with that, right?

• 59:58Shane Parrish?

  Right.

• 59:58Speaker 00

  And so, so yeah, I think providing feedback is a, is a tough one. I'm sure in the comment section, there's going to be all kinds of feedback for, for me now. And okay, bring it on, you know, and, and as long as it's, comes from a position of love, you know, and, and, and I think that's important. I think, yeah, I think that's what people know. If you, if you come up from a place of love and constructive, I don't want to say constructive criticism, but just feedback, because we're all blind, really, to the effect we have on people. And not totally blind, we have some idea, uh, but it'd be good to get feedback.

• 1:00:39Speaker 00

  And and by the way, if I were an employer to your question, and I and you asked about managing people, I'd I'd sit down my entire department and say, I'm I have not I've I have an online form. I want you to tell me ways I'm I could be improved, ways I really suck.

• 1:00:58Shane Parrish?

  Yeah.

• 1:00:58Speaker 00

  And

• 1:00:59Shane Parrish?

  I do think people would tell you that. But then you also get into this, like, I don't want to tell my boss they suck, right? Like, there's a social dynamic to it, or a psychological impediment.

• 1:01:08Speaker 00

  And there's also like, you kind of go, whatever, you know, you just kind of roll your eyes and go, whatever. But but I think if it were earnestly submitted, the petition, like, hey, I need this feedback. I want to do better for you guys. By the way, your bonuses are tied to your performance. So help me make you more money.

• 1:01:30Shane Parrish?

  Yeah.

• 1:01:31Speaker 00

  And help our company make more money. Help us contribute to the world. Please give me some feedback.

• 1:01:36Shane Parrish?

  I found when I was managing people, they would always put their toe through that door, but it wouldn't be a foot, it would be a toe. And how you responded to that first sort of, here's something you could do better, or this criticism, or whatever you want to call it, or in fact, you you don't know about yourself, how you respond to that is indicative of whether that foot would come in the door. And then, you know, the body and then the person.

• 1:01:58Speaker 00

  Probing, yeah.

• 1:01:59Shane Parrish?

  They're probing you. And most people, and I observed this at work, most people have this default response of like, oh, you don't know what you're talking about, or that's not true, or here's a case where it wasn't true. And that's a complete shutdown.

• 1:02:11Speaker 00

  Oh, yeah.

• 1:02:12Shane Parrish?

  For that other person. And they'll never put that foot through the door with you again.

• 1:02:15Speaker 00

  They and when they, by the way, I hear this with investors, where I'm trying to to convey some information, and their their response is to argue against it.

• 1:02:25Shane Parrish?

  Yeah.

• 1:02:25Speaker 00

  Instead of going, okay, well, let me see if that's a valid idea. Let me just explore that. Let me just entertain it. It's so funny, you should talk about this. In in the Middle Ages, there was an institution designed by kings to provide feedback, and it was called the court jester. And the function of the court jester was not to amuse the king. The function of the court jester was far more serious than that. The court jester was the one person who was empowered by the king always to tell the truth. And so the king who might say, I was thinking of invading France. And the court jester would go, ha, good luck with that, buddy. Remember the last time you invaded Germany?

• 1:03:07Shane Parrish?

  Right.

• 1:03:07Speaker 00

  And, and so because he was a jester, the court, um, the king's court could then laugh it off. But the function of the court jester was actually to tell the king the truth.

• 1:03:18Shane Parrish?

  I had no idea.

• 1:03:19Speaker 00

  Yeah. And, and he was empowered to do so because then the king could save face. Everyone would laugh, but the king would go, okay, maybe I shouldn't invade France. Maybe that's not such a good idea. And so, right, it wasn't an entertaining function. It was the real function, tell the truth, feedback. How do we get that? It's so hard.

• 1:03:39Shane Parrish?

  It's incredibly difficult.

• 1:03:41Speaker 00

  Yeah.

• 1:03:42Shane Parrish?

  Switching gears just a little bit, maybe a last question. Um, what are some of the biggest learnings that you've gotten from other people that were unexpected?

• 1:03:52Speaker 00

  Oh gee, that was an unexpected question. Um, I don't know so much that they were, this is important. We're always teaching on multiple levels. So for example, when there's the direct lesson, but the teacher's also saying any number of other things. Right? So for example, one thing this, my students always learned from me is I believe they can improve. Not just there's the lesson like this is the Pythagorean theorem. They also have learned lots of things. Adam believes I can raise my score. Raising scores are possible, right? You're teaching on multiple levels.

• 1:04:33Speaker 00

  And, and so one thing I've learned just from observation, and it's more indirect, is all the multiple ways we influence others. And we're always teaching, whether we're aware of it or not. We're always making a statement. And by the way, not just a statement, multiple statements. I, I was so, um, Not really sad, but a couple of Sundays ago, I was walking with a friend through a park in Soho, New York, and there was a little stand that was being set up for the afternoon by some musicians. And a mother, and I could tell the mother loved her little son very much, the son was, I'm guessing, three and a half, four, something-ish, was walking by, and the son was, wanted

• 1:05:16Speaker 00

  to get involved, and as it were, I'm using air quotes, help the musicians set up their equipment. And the mother, I overheard the mother say to her son, "No, no, you can't play music yet, but you can learn how." And I just thought, how sad. That child has now internalized that he can't play. And the only, in fact, he can't play, I'm using air quotes now, until he learns. So the mother, with all the best intentions,

• 1:05:41Shane Parrish?

  Right.

• 1:05:42Speaker 00

  was giving him a very bad message, right? And if you think back to your life, Shane, I know, certainly know in mine, the number of offhand comments that an individual said that positively or negatively impacted me to this day, I'll bet you, you can think of a handful of statements by this teacher or that adult that, that you still remember in a good way, or you-

• 1:06:06Shane Parrish?

  Or a negative way.

• 1:06:07Speaker 00

  Or a negative way.

• 1:06:08Shane Parrish?

  Yeah.

• 1:06:09Speaker 00

  And it's astonishing that the impact that offhand comments can have on young people. And I know one of the, the really important things that, I'm, I'm really worried about the world, and I'm worried about young people in particular, and who's the under 25 generation, Gen Z, right? They're, they're inheriting a world that's falling apart, and, and their brains and attention have been hijacked by technology. And it's, I'm, I'm deeply worried, not just about the world as a whole, but about young people. And I think all of us can-

• 1:06:44Shane Parrish?

  What should we do differently to, to stem that or abate it in your mind?

• 1:06:48Speaker 00

  Well, for one, see, I'm, I'm not sure that there's an answer to that question, because I think the adults are so embedded, adults, the over 25s. Are so embedded in their, in their worldviews, I'm not sure that, that we're going to change too quickly. And on the positive side, young people, the younger generation, under 25, Gen Z, the youngest generation, is free from many of the, the labels that everyone over the age of 25, like male versus female, or Republican versus Democrat, or American

• 1:07:27Speaker 00

  versus non-American, that bedevil political and social and economic discussions of the adults. And so I, I think the youngest generation, Gen Z, the youngest generation, is more homogeneous in a global way than, than all prior generations. And I think that's a plus. On the minus side, they're inheriting a world where there are few positive voices, few if any. And I think that's what's needed in the world right now. You need beacons of people offering positive visions that others can rally behind. And I say positive vision, not us versus them, positive visions, positive inclusive visions. And, and maybe

• 1:08:10Speaker 00

  young people will provide that. Maybe, maybe it'll flip. Maybe we'll get the leadership from Gen Z, maybe. But we certainly need positive voices in the world.

• 1:08:21Shane Parrish?

  I think that's a great place to wrap up, because now we can invite everybody listening, we can give them an invitation to the great game.

• 1:08:27Speaker 00

  Yay!

• 1:08:28Shane Parrish?

  Thank you so much, Adam.

• 1:08:30Speaker 00

  Shane, it was a delight. Thank you so much.

• 1:08:36Shane Parrish?

  Hey, guys. This is Shane again. Just a few more things before we wrap up. You can find show notes at farnamstreeblog.com/podcast. That's F-A-R-N-A-M-S-T-R-E-E-T-B-L-O-G.com/podcast. You can also find information there on how to get a transcript. And if you'd like to receive a weekly email from me filled with all sorts of brain food, go to farnhamstreetblog.com/newsletter. This is all the good stuff I've found on the web that week that I've read and shared with close friends, books I'm reading, and so much more. Thank you for listening.