scott-young-ultralearner.mp3

Scott Young: [00:00:00] It doesn't matter that you're not ready, you know, like take the job at the programing office and what's the worst that can happen? They'll fire you because you're not good at it. Right. And then you'll go back and you'll learn something. And so I think that we need to take the attitude of doing things way before we're ready, because that's how you learn things and also because failure isn't really that bad. And if you just kind of go into it with the attitude of, no, I'm not ready, but I'm going to do it anyways and I'm going to be really bad at it, you often find that you're a lot better than you thought you were.

Harpreet Sahota: [00:00:40] What's up, everyone? Welcome to another episode of the @TheArtistsOfDataScience be sure to follow the show on Instagram at @TheArtistsOfDataScience and on Twitter at @ArtistsOfData. I'll be sharing awesome tips and wisdom on Data science, as well as clips from the show join the Free Open Mastermind selection by going to bitly.com/artistsofdatascience @TheArtistsOfDataScience. We'll keep you updated on biweekly open office hours that I'll be hosting for the community. I'm your host Harpreet Sahota. Let's ride this beat out into another awesome episode. And don't forget to subscribe, rate, and review the show.

Harpreet Sahota: [00:01:27] Our guest today is a writer, programmer, traveler and avid reader of interesting things for the last decade, he's been experimenting with how to find out how to learn and think better. In that time, he's written over 1000 articles, a few e-books and guides and has been exploring what it means to get more from life with themes ranging from productivity to learning the meaning of life itself. More recently, his focus has narrowed onto one question: What's the best way to learn? This question has formed the basis of much of his later writing as he began to cultivate the belief that learning is the key to living well. This pursuit has led him to take on two year-long experiments in learning, including the MIT challenge, where he attempted to learn MIT's four-year computer science curriculum without taking classes and the year without English, where he went with a friend to learn four languages in one year. So please help me in welcoming our guest today, author of The Wall Street Journal best selling book, Ultra Learning, Scott H. Young. Scott, thank you so much for taking time out of your schedule to be here today. I really, really appreciate you being here.

Scott Young: [00:02:39] Oh, thank you so much for having me. It's great to chat.

Harpreet Sahota: [00:02:42] So talk to us a bit about your journey. How did you get to where you are today?

Scott Young: [00:02:47] Oh, wow. It's a long story, but I've always really been interested in learning and how can you learn things better? And I started writing my blog. This is now almost 14 years ago. And when I started, I was interested in self-improvement topics like things like productivity, goal setting, how you can be a better version of yourself. And learning seemed to vibe with that. It seemed to be the kind of the mechanism by how we get better at things. And that sort of led me down the road of trying some of these projects out and then eventually to writing this book. And I wanted to try to share some of not only my own experiences, but some of the people that I've been able to meet have just released fascinating stories that can give these kind of examples of things that are possible to do if you're committed to it.

Harpreet Sahota: [00:03:30] So on this path to becoming an ultralearner, what were some of the struggles you faced along the way and how did you overcome them?

Scott Young: [00:03:38] Yeah, so I think the story that probably epitomizes it best was when I was trying to learn French. And I think learning a language is like the kind of classic example, because all of us have these experiences of maybe like high school or something where we took a class and went, oh, I can't I can't speak to anyone. You know, I took a high school Spanish class and I can't speak Spanish at all. And so my story was a little different than most because I actually had the opportunity to go on exchange. So I mean, more so than even just a class. I had the ability to live in France and actually interact with French speaking people, and I still found it really difficult. I find it really difficult to learn French. Most people that I was friends with spoke to me in English, including the French ones, and I found it challenging, even though I felt like I was putting in a lot of effort to try to learn French. So I would go home and I would study and listen to a podcasts and do all the things that you're supposed to do for learning a language. But it was it was hard.

Scott Young: [00:04:33] I felt like I wasn't making as much progress as I wanted to. And around this time someone - I was kind of complaining about this to a friend from home. And he's like well, do you know Benny Lewis? And I said, well, who's  Benny Lewis? And he pointed me to his website. And this guy's website was very modestly called Fluent in three months. And it was about how he did these challenges, where he went around the world on these three month tourist visas. That's like the typical length of a tourist visa, especially in Europe. And he would just go to a new country and try to learn as much as he could of this language in a short period of time. And then post little videos of his progress. And at the end he's having, like, actual conversations with people. And I thought this was just kind of incredible, given that I was struggling so much and I felt like I was a smart enough guy and I was having so much difficulty with it. And I had all the, you know, same advantages. That I was also living in France. I was also trying to study really hard. And so he was kind of one of these first people that I call ultralearners. These people who just really aggressively pursue kind of self chosen learning projects.

Scott Young: [00:05:32] And when I met him, I realized that he just had a completely different attitude and strategy towards learning things. So for me, my major problem was that I was very hesitant to speak with other people and most of my social environment was speaking in English, whereas he would go to a country where he speaks almost none of the language and construct a social environment that was almost entirely speaking the language that he wanted to learn. And so this kind of became not only an example to me of - if you really rethink the way in which you approach learning you can often get a different result. But also this sort of style of like kind of exploring these projects and talking about online. So I thought it was really interesting. And so when I was, you know, I was also blogging at the time. And so that sort of also was part of my inspiration for trying to do some of these projects myself of where you really think about what's the right way to learn this, and maybe is their way of doing it better.

Harpreet Sahota: [00:06:22] And I'm excited, actually, to get into some topics that you talk about in your blog. And then we'll get into some some concepts from Ultralearning. But starting off with your blog here, you write on such a wide variety of topics that that I find to be extremely interesting. One thing that I liked was how you talk about motivation. So what's wrong with motivation and why is that not enough to carry us through to the completion of our goals?

Scott Young: [00:06:47] Yeah, so I think there is an idea a lot of people have, which is that if you just get motivated enough to do something, it'll naturally kind of carry you to the finish line. And I think there are examples of where people were super motivated to do something. And so they wanted to work on it every day. But I think the problem is just that the motivation is an emotion, not just like a reason to do something, but as an emotion is kind of necessarily pretty transient. And so it's not enough to have motivation because you're going to feel really motivated to do something and then you'll work on it for like an hour or two, and then you'll be like, that's enough. And then you'll stop. And an hour or two is rarely enough to get done anything really serious, especially if we're talking about like a personal project, like learning a language or, you know, learning programming or learning something intensive. It's maybe going to take months or even years to really be successful with it. And so what you need is not just motivation, but you need some kind of system. You need some way to channel that initial burst of enthusiasm into creating structures for your life so that you will kind of consistently re-engage with it and consistently do what you need to do to learn things better.

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Harpreet Sahota: [00:08:25] Then you also talk about this concept of like the narrow path to success. I found that to be really interesting. So would you mind walking us down that path? And what are some of the sights that we should stop and see along the way?

Scott Young: [00:08:39] Sure. So this was an article I wrote recently, and it was sort of inspired by reading Jason Brennan's book Good Work If You Can Get It. Which is about basically a very kind of honest look at academic success. And a lot of people go into pursuing a graduate degree or they want to become a professor and they don't really educate themselves on what is the likelihood of getting a job and what are the difficulties and, you know, what things they need to do in order to be successful at it. They just kind of go into it and then only realize after several years later, oh, I've been doing the wrong thing, it doesn't work. And I thought there was a lot of interesting parallels with that and with some other examples, including I had a podcast interview with Cal Newport, and he was talking about sort of very similarly that like most people, when they're writing a book, just kind of get into it like, oh, I'm just going to write a thousand words per day and then I'm going to have a book at the end of it. Whereas if you want to actually get a book deal with a traditional publisher, that's not really the way you go about it. And and that's sort of a mistake a lot of people make. And there are some other examples from different fields sort of related. And so the idea that I wanted to put a forth in that article was that a lot of people don't really consider that you need to have a very specific effort to achieve most goals.

Scott Young: [00:09:53] And that's a little bit abstract. But the basic idea is that a lot of people don't really investigate what kind of efforts count, and they just think that applying effort generally in that direction is good enough. And I don't want to say this is true for every single goal. Like certainly if you want to get in shape, you can do lots of different types of exercise and they're all going to be helpful for you if you can stick with them. But for a lot of other goals - and I think this is particularly true for learning goals - it's only very certain types of efforts that actually build the skill that you want or that actually build the kinds of assets that you need to get a job or to get a book deal or to build a company or the kinds of goals that you might want to have. And so I think that there's a real advantage in being able to research. What is that path? What is the things that matter before you get started or if you're already in the middle of doing it to be critical about the time that you spend learning things or the time that you spend investing in these goals, that you make sure that they're going towards the right direction.

Harpreet Sahota: [00:10:47] And what are some questions that we could ask ourselves before we set out on this path to make sure that we are applying efforts in a more intelligent manner and not just haphazardly applying it, you know, wherever?

Scott Young: [00:11:02] So one of the big principles I talk about in my book is this idea of directness and directness comes from this huge literature that we have transfer of learning. And transfer of learning is basically when you learn something in one situation and say like classroom or for a book, and then you want to apply in a different situation in real life or in your job. And there is a ton of evidence that shows that we're not very good at this. That we kind of naively assume that if we spend time doing something related to what we care about, that we'll get good at something else. So if we just spend a lot of time, you know, reading in a language that will necessarily be able to speak it. Or if we spend a lot of time just taking a course in economics that we'll be better critical thinkers about economics problems when they come up in the news. And there's evidence to show that that's not true. And so the conclusion that I kind of took away from this research is sort of related the theory of transfer appropriate processing is basically that if you want to get good at a skill, you have to take as your starting point the idea that skills are quite narrow, that they are not going to transfer by default. This doesn't mean that transfer can never happen or that you should never learn things if they're not like immediately practical, but just that if you have a practical goal, you should get really serious about what is the actual skill that I need to learn and then how can I learn in a way that facilitates that.

Scott Young: [00:12:17] So if I want to build my own app programing, then let's learn the language that's going to actually a part of that. Let's learn about app development. Let's actually work in that environment and build those kind of protocols. Whereas the way that a lot of people approach things and which is particularly prevalent in schools, is to teach things in kind of a general unspecified way with the assumption that you'll be able to transfer it later like that. That's just sort of a trivial thing that you have to do at the end. And because it's not just a trivial thing that you have to do at the end and because it matters, I think there's often an advantage to be gained by someone who takes it seriously. Who takes the difficulties of transfer seriously, and so designs a project that will laser in on what makes it hard for you to learn that thing and what makes it difficult for you to accomplish that. And so if you can focus on doing the real thing as opposed to fake substitutes, you can make a lot more progress.

Harpreet Sahota: [00:13:05] Thank you so much for that. And I'm also a huge fan of Cal Newport myself. Like his books are so good they can't ignore. He was very, very pivotal in my understanding of what passion really is and what it isn't. Thank you for sharing that.

Harpreet Sahota: [00:13:18] So you've also got this awesome blog post on mental models. Can you talk to us about the importance of mental models, and how can we use those to improve our thinking?

Scott Young: [00:13:29] Mental models have become a little bit of a kind of a sort of trendy topic, I guess you could say. And I really like the idea of mental models, but I think I'm also careful in how I talk about them. Because I think there's an idea that like all that's necessary to do to use mental models well, is to just sort of read a list of them. A big list of them and oh, now I can use them. And that really contradicts the point I just made, which is that transfer is hard. And so if you want to be able to apply mental model the situation, you have to kind of practice applying it to that situation. And and the way that mental models become useful is when you really spent a lot of time thinking about them, not when you just heard their name and kind of written them down and understood a few sentences. However, I do think that there's something to this idea of mental models if you are willing to really study them. And so the original kind of concept of mental models comes from Charlie Munger, who is Warren Buffett sort of investing partner. His idea was that there's basically a few set of fairly generic concepts that describe a lot of the world. And if you can really wrap your head around those mental models, then you can apply them to many, many domains because you'll recognize that this pattern in action and it can give you tools for solving problems, even if you maybe never seen anything like that before.

Scott Young: [00:14:40] And so a lot of my favorite mental models come from subjects that are somewhat academic. So things like economics, mathematics, biology, computer science, systems thinking. But if you can really sort of deeply internalize them and see them coming up in many, many places, they give you kind of a sanity check for understanding other ideas.

Scott Young: [00:15:00] So just as an example, like if you really understand natural selection. Just as the idea that if you have some system where some kind of element is getting copied over and over again and that it will change slightly, like it has these changes that get preserved when you're copying it. And if some of those changes make it more likely to be copied, then what you end up having is this drift to the versions that are more likely to get copied. Now, that's really, really abstractly stated and it obviously explains a lot of evolution that we see in the biological world. But you can also use that to explain a lot of things like, let's say in idea spaces. So if we're communicating ideas and we're talking about things and someone manages to convey the idea in a slightly different form, which makes it more likely to be conveyed to other people, then that's the form it's going to end up taking. And that sort of explains how sometimes ideas can get, in some cases oversimplified because they become easier to propagate. In some cases, it can explain why certain formulations of an idea tend to stick, and that's just ideas. And so this is sort of transplanting this model that was originally used to understand biological systems, but you can use it to understand ideas, technologies, cultures, other things like that. And so I think that there is definitely a benefit to if you see a particularly robust idea like this deserves a name of a mental model to really, really deeply understand it and to practice applying it to lots of things, because it does give you this kind of window where you can spot these patterns and makes sense of situations that otherwise you would just be baffled by.

Scott Young: [00:16:30] You have no way of knowing what the answer would be.

Harpreet Sahota: [00:16:32] It's kind of like it's like one thing to know the name of something and another to actually understand it and be able to see it from that perspective, if that kind of makes sense.

Scott Young: [00:16:41] That's that's a huge point. I think you just hit the nail on the head here, is that a lot of people think learning is learning the names of things. It's not like I talked to a lot of students who think that the goal of learning something is to be able to like  - what is the definition of this? And then to give the correct sentence is the answer. And that is the most sort of useless kind of learning. And that's not to say that you never need to know the names of things, but knowing the names of things is the most superficial layer of understanding. And so to know what I mean by what is natural selection to give like an adequate definition is not to really understand that idea. To really understand the idea is to understand that it's a mechanism. It's like a little machine. And you understand how the parts work. And you understand, OK, well, this is a situation that has similar parts, you know, will you get a similar kind of outcome? And so often it really depends on understanding those parts. So an example is that you can very often misapply mental model. So I remember someone was talking about evolution of corporations and they were saying something like, well, corporations evolved because people copy different business practices of other people and then they, you know, that's how we have different forms of, you know, corporations that are getting like, you know, better and better at making phones or handbags or something like this.

Scott Young: [00:17:49] And someone was making the point that, well, the problem is that corporations are really complicated and they don't actually copy each other like that perfectly. So you're not going to see the same pattern of things that you would if you see in real life. And so sometimes seeing the disanalogy between things is a big part of understanding them. Is that you not only understand, oh, this is an example of this, but you understand when it's not an example or when the machine parts don't quite align. And so I think that it's another example of kind of shallow thinking to start of not really understand how the idea works. And so I spent a lot of time focusing on that in my advice for students is to really try to understand the kind of machinery behind an idea.

Scott Young: [00:18:25] And not just the label that's attached to it.

Harpreet Sahota: [00:18:27] I think it was David Epstein in his book Range kind of talks about the essence of innovation is really to be able to apply something from a different domain where it doesn't normally belong, if that makes sense. Right. So you understand the deep structure, whatever problem that you're working with, and then find a strategy to match it. And sometimes that strategy could be, like you mentioned, a mental model applying, you know, the theory of evolution to businesses or something like that. And that's really interesting. I really enjoyed that blog post.

Harpreet Sahota: [00:18:54] And I'm just curious, what would you say is the one mental model that really impacted your life the most and in what way?

Scott Young: [00:19:04] I don't know. I think there's lots. But I think if I were to pick one that I turn to again and again because I find it like it's not obvious, but it's you know, because there's there's the mental models that are just common sense. And so then it's not really a mental model. And then there's the ones that really only apply to very specific situations. And so you don't find you're using them that much in your personal life. But for me, the idea of marginal benefits and costs is one that I learned from economics. And I find I use it all the time. And so the basic idea is that a lot of people reason with averages. So if they think about, well, should I do more of X?

Scott Young: [00:19:41] And it can be anything. It could be playing a video game. It could be reading a book, it could be going to college, it could be whatever. And then they go back and they think back in their history and maybe they do this implicitly. They go back to their history and they think, well, how good was it for me the last time I did it? Right. And they use that reasoning and sort of extrapolate and sort of say, oh, OK, well, if it was this good the last time I did it, then it means that I should do it again. And that's actually not true. And it's not true, because if you think in terms of marginal thinking, then it's the idea that, well, the amount of benefit you get from something is often changing over time. So something may be really, really good. The first time you do it and a little bit less good the second time will get less good the third time and then you can do it the tenth time and maybe even negative. So if you're thinking about eating pieces of pie in that first piece of pie is really, really sweet. The tenth piece of pie makes you sick. And so I think this idea of marginal thinking applies to a lot of decision making because we're often kind of implicitly thinking back to how something was in the past and not thinking about how it's going to be for the next one. And I mean, you don't always know what the next one's going to be, but you can kind of reason in that way and make wise decisions. And so there's a lot of thinking where where people are kind of making that mistake of just sort of reasoning from the average instead of the margin.

Harpreet Sahota: [00:20:55] Pretty interesting. I saw that on I think it was either Instagram or on your LinkedIn recently where you had a sketch or a doodle about the marginal.

Scott Young: [00:21:03] Oh yeah, I've got lots of doodles now. Yeah.

Harpreet Sahota: [00:21:05] Yeah, that's that's been interesting. I've seen that pop up recently. Do you mind talking to us about that. What's the inspiration behind doing that.

Scott Young: [00:21:13] The doodles, Oh yeah. This is like the most random thing that ended up becoming a major staple of my blog. I just, I just do the doodles I started about a year or two ago, so I've been writing for 14 years. So I most of my time writing, I didn't do that many images. And then I just did them sort of randomly as a four like one or two articles. I was just thinking, I'll just try it out. And then they kind of became a popular part of the writing. So now I do them for for all of the articles. So for like the mental models post you're talking about, I have a little doodle for each one of the ideas that I'm trying to write about.

Scott Young: [00:21:45] And I don't know. I think it sometimes helps people make sense of it, because sometimes if you just use words, it's you only have one access point to the idea. And if you have a picture, it gives sort of it kind of makes it a little bit more stable. You can kind of figure out what the ideas about.

Harpreet Sahota: [00:21:59] Does that help you kind of learn the concept better yourself when you kind of have to take this complex idea and then a represent it in  you know, and a nice, clean, simple doodle?

Scott Young: [00:22:08] I think it does. I think it helps me. I do think that for me, I naturally think in terms of pictures. So I feel like I kind of always already like there's a lot of articles where I'm talking about ideas where I was all always sort of visualizing them as like a graph or something like that. And so doing the doodles is just kind of made the mental picture that was already in my head explicit. It's not always the case. There's some times where I have I really struggle to find a way to to represent something visually. But I often find like I have some sort of abstract picture in my head. And that's sort of how I'm thinking about the idea fundamentally. And the text is sort of me trying to use words to describe the picture. So I think the doodles have kind of helped me go back to that of like just being explicit. This is the picture I have in my head when I was thinking about writing the article.

Harpreet Sahota: [00:22:55] I'm really enjoying them. They're pretty awesome.

Scott Young: [00:22:57] Oh, thank you.

Harpreet Sahota: [00:23:03] What's up, artists? Be sure to join the Free Open Mastermind Slack Community by going to bitly.com/artistsofdatascience. It's a great environment for us to talk all things Data science, to learn together, to grow together. And I'll also keep you updated on the open biweekly office hours that I'll be hosting for a community. Check out the show on Instagram at @TheArtistsOfDataScience. Follow us on Twitter @ArtistsOfData, look forward to seeing you all there.

Harpreet Sahota: [00:23:33] So Marcus Aurelius has this quote from Meditation's "Discard your thirst for books... Throw away your books". I think Seneca talks about in the Discursiveness in Reading. He's got this whole letter to Lucilius about that. And then you've got a blog post titled "Is Reading Making You Stupid?"

Harpreet Sahota: [00:23:47] So now I'm wondering.

Harpreet Sahota: [00:23:49] Am I reading too much? Is is is it making me is making me stupider? 

Scott Young: [00:23:54] Yeah. Well, I love reading. So let me just preface that first that I'm definitely not anti-reading. Most people don't read any books. So I think if we're talking about the problem of someone reading too many books, we're really talking about a pretty niche problem here. Like the average person maybe reads one book a year, maybe. So I think I think for the average person, the problem is definitely not Are you reading too many books? But are you spending time on Instagram or are you spending too much time not reading? However, I do think that there is a certain type of person who likes to read books and really uses books and reading and listening to things and taking courses as a substitute for taking action or doing practice or doing hard things. And so there is a certain type of person, I guess you could say that like they do need to stop reading, they need to actually start just taking action on things and implementing things. And so I think this sort of, again, takes another economic concept that I'm a fan of, which is the idea of substitutes versus complements. But the idea from economics is you can have substitute products from each other. So going to see one movie is a substitute for seeing another movie at the same showing time - you can only go see one. However, there's also complements. So eating popcorn is a complement to going to the movie because when you go to the movie, you're more likely to buy popcorn than if you weren't going to go. And so in this case, there's a question of whether reading a book is a substitute or a compliment for improving your life.

Scott Young: [00:25:18] And in some cases, they're obviously a complement. If you're if you wanted to take a big learning project and then you can read my book and you have understood some principles, maybe you'd save some time and improve your ability to learn those things. And so in which case, reading the book is very helpful. But in other cases, you're reading the book to kind of satisfy your overall urge to do something about this problem in your life. And then you read it and you feel a little bit better about that. You're you're you're taking some action. You're doing something that's helpful, but you're not actually doing anything to fix the problem. You're just reading and it's functioning as a substitute. So that hour or two hours you were spending reading, you could have been spending doing something to actually materially improve the situation or problem you were trying to solve. And so I think it's it is a difficult question, but it's something that you should investigate in yourself of like how much of the activities you engage in. Do they act as complements for the things that really matter versus substitutes and in some cases that you act as substitutes. And I think it can be important to wean yourself off of them, even if sort of like I said, book reading is generally good. It can sometimes be the case that it's crowding out taking action or crowding out solving the problem that you were actually reading the book for.

Harpreet Sahota: [00:26:23] And I think you mentioned in that same blog post that spending a lot of time learning theories without practical experience, without applying it. That's not really a good idea, right?

Scott Young: [00:26:34] Yes. And I think it depends on what we're talking about. Like if we're talking about computer science, that we're talking about machine learning or we're talking about some kind of practical skill, then it can definitely be the case of just reading lots of stuff without actually, you know, writing some programing code or making something can be detrimental. I think it can be detrimental for this exact reason that it starts to act as a substitute. And I find it this often happens in situations where reading is a lot more comfortable than the thing that you're trying to do. So it can often be the case that, you know, it's a lot easier to read, you know, sort of motivational articles about getting in shape than it is to maybe go jogging. And so if you find yourself, you're reading a lot about it, but you're not taking action, then it's sometimes beneficial to kind of wean yourself off of reading and to sort of take a break until you take some action, because you're using the book as a way to sort of satisfy this drive to to do something. It's a little bit like empty calories, like you're using it to satisfy that drive without doing anything. But that isn't the case all the time. I do think that books and reading and listening to podcasts like this one can be complements to the things that matter. But it's important to recognize when it isn't.

Harpreet Sahota: [00:27:37] It definitely agree with you. And I think that's important for a lot of the Data scientists out there who are to be listening to this, because in the world of Data science, there are a ton of courses, a lot of noise, and there are a lot of different courses that do teach the same thing. And I noticed that a lot of my mentees, they just start taking course after course and passively absorbing the information without putting it into like a project. So here you kind of expound on this concept. I believe it's going to help our students kind of get out of that, consuming the knowledge and to the applying loop.

Scott Young: [00:28:06] Well, I think that's a really big problem with something like machine learning, because there's a certain ease to following along homework exercises and lectures and have to say that it's as easy as doing nothing. But in some ways starting your own project where you, you know, you have to find your own Data and you have to construct the problem and you're not sure which model to use and maybe you're going to screw it up and like that. Strictly harder problem than just following some homework exercise that has been carefully selected for you to be able to solve it, and so because that's harder and more frustrating, a lot of people avoid it. Right. And so they get in this cycle where they just they just keep doing this strictly easier thing.

Scott Young: [00:28:43] Now, I don't want to say that this is bad. Again, like, it can be a good complement to taking action, but you have to sort of recognize what role it's filling. If you're just continually taking courses and you don't feel ready, then there's probably some kind of negative aversion that's like keeping you from doing the real work. And it may not be entirely rational. It may not be like, well, I'm taking this course because if I don't take this course, I'm not going to be a real Data scientist. But it's more like, well, taking this course is something that's doable and I can just plod away at it and I can get a satisfactory result. Whereas if I take on this project, it may be, you know, impossible or I may not be able to do it at all, or I may get stuck and frustrated and, you know, it may be totally imposed. And that's kind of scary for me. And so I'd rather just sort of slink away and do another course.

Harpreet Sahota: [00:29:27] So what can we do when we're stunned into inaction by, like, the difficulty of what it is that's in front of us? Like, how can we get out of that?

Scott Young: [00:29:35] So good way of doing it just to make it so that that's the only way forward? Right. I wrote in an article called Do the Real Thing, where I sort of argued somewhat a little bit more provocatively that maybe I should have that doing nothing is often better than doing something. And this is particularly in these cases of where it's a substitute that. And so you have to just be honest with yourself about what it is. Right. And this isn't to say that this is universally applicable advice, but that there are certain people that really need to hear it. And the idea is just that you can satisfy a drive with some sort of related activity. So if you're hungry, you could you know, you could eat a burger, but you could also, you know, eat some fruit or something like that. And if your real goal was to get a lot of vitamins and then you're just eating some hamburger, maybe it's not the best way to satisfy that urge. And then you're going to feel full, but you're maybe not going to have had the nutrition that you want. And so similarly, you can get into a situation where you just you have this aversion to doing it. And so you're just like, well, something is better than nothing, right. That's the mentality. And so you spend a lot of time kind of proverbially eating the hamburgers and that prevents you from making progress.

Scott Young: [00:30:37] And so what I think is often beneficial is to sort of set up a concrete project like, OK, well, I'm going to now actually start working on my first set of machine learning project, which is not through a course. And it's going to be building something that I care about. And I have to make a certain amount of progress before I go back and take another course. And so sometimes when I'm designing learning projects, I kind of do them explicitly in this way that explicitly I have to do it a sort of harder way than is most natural to me, because if I do it that harder way, I won't sort of slink off and do some serious substitute activity. So, you know, with the language learning, the no English rule is such a benefit for that, just because if you don't let yourself speak in English, you allow yourself to actually get some of that early conversation practice, which is so valuable for getting to a point where you can actually chat with people as opposed to just endlessly engaging in kind of this. You know, they're they're related to learning. I want to say they're useless, but they're they're definitely not the most direct attack on the problem. And they're definitely going to take you much, much longer to get to a point where you can have something rewarding come out of it.

Harpreet Sahota: [00:31:39] And I think that kind of like that, the cliche that all the growth really happens and that discomfort to that uncomfortable zone, I think it's easy for people to recognize that when it comes to your actual body for lifting weights, you know, that that when you're lifting to that discomfort, you'll see your muscles get bigger, but you don't really see your brain getting smarter or stronger.

Scott Young: [00:31:59] Well, there's two things here that I think are important. One of them is related to kind of just the intrinsic mental challenge. And I think we do have a little bit of an avoidance of mental challenges, the same way we have with lifting. And so there can sometimes be an aversion to just like doing something that's a little bit harder. And so, you know, obviously, if you're actually making your own program, that's harder than just watching YouTube videos about machine learning. Right. Or YouTube videos that are so vaguely topic related or scrolling Twitter like it's a lot harder to do programing than is to do that. And so therefore, if you spend more time actually doing the programing, you're probably going to make more progress and it is related to that mental exertion. But there's also, I think, a sense that sometimes we have other reasons for not wanting to do something. So like I already mentioned, one, that if you are doing a course, it's kind of carefully structured in a way. So you can't really fail at it. Or if you do fail at it, it's sort of you can definitely resolve the problem.

Scott Young: [00:32:49] Whereas if you work on your own project for programing it's very easy to kind of inadvertently design something that's insolvable based on what you already know. Right. It's very easy to get into a situation where you just hit this impasse and you're not able to make progress. And so it can be a different kind of frustration. Or you can also be a situation where, you know, maybe you're being judged by other people and that's a way you can get feedback and make progress. But now you have this sort of social anxiety about, oh, what if this person judges me from doing or something like that. And so I find that a lot of times there's this sort of negative affect, not just because something more difficult, but because we're a little bit afraid of doing it, that we avoid doing the thing that could really cause growth. And so the more you can just push yourself to do what really matters, the more you can make progress in a lot of domains in a lot of domains.

Harpreet Sahota: [00:33:36] Thanks so much for expanding on that. I really appreciate that. And our audience is going to enjoy hearing that, too. I think it's pretty interesting that there are certain types of the luck that have very common cliches that everybody knows about. And then there's a certain type of luck that comes out of the way. You act that there's no real cliche. All right. So we've got, like, dumb luck or blind luck, and then we've got fortune favors the bold, and then we've got chance favors the prepared mind, some of these common cliches. But there's a type of luck that doesn't have a common cliche, and that's the one that kind of matches the unique character of the action. And I think that this kind of luck starts becoming deterministic, right. It moves from luck to destiny. So you talk about this kind of luck in a blog post. Would you mind expan...?

Scott Young: [00:34:17] Yeah, well, people talk about luck. And the problem is that I think there's lots of different ways that you can view it. And I think especially since we're talking about kind of Data science, is that there is always a sense that, like luck is just the part of the signal you can't explain. So there's the your model and what it fits, and then there's all the noise that's on top of it. And that's kind of just like that's luck. Luck in the sense that it's not something you have control over. It's not something you're able to predict. But in the article that I was writing, I was kind of saying that I think it makes more sense to more carefully subdivide these sort of topics because otherwise we can be talking about things but be talking past each other. So one of the three types I was talking about in there were kind of luck that happens before sort of your point right now in time. And this is a very important kind of luck in the sense that you don't have control over it. And it makes a huge difference in terms of outcomes.

Scott Young: [00:35:07] So, you know, just the fact that I was born in Canada and I was born to a loving family and this kind of like economic opportunity and privilege is just huge. It makes such a huge difference in kind of experiences I have. But at the same time, if you were to say something like, well, what's the chance that you're going to be able to be successful at X and Y, and you don't take into account the knowledge of who you already are when you kind of come into that problem, it can be disastrous. So I think I forget who the author is, but he calls it the kind of the "go pro fallacy". Which is if you look at like professional baseball players and I think something like one out of every forty thousand people who I don't know the actual statistic, but who goes into little league can become a professional baseball player. And so if you were to go into Data like those are astronomically low odds. And so the go pro fallacy is to assume, well, that my chance of becoming a professional baseball player is one in forty thousand. But that's actually not true because you already know kind of how talented you are at baseball. And so the way it is is that basically for most people who aren't that talented in baseball, your probability of becoming a successful baseball player is actually zero. Like you just you're not going to be able to do it at all versus there's people who are reasonably talented in baseball that have a shot at it, that if they really worked it, maybe their probability is actually quite a bit higher, maybe like one in 10 or one in three or something if they got the right approach. And so this is an example of there's a lot of luck here. This one in forty thousand. You have to be extraordinarily lucky in order to become a professional baseball player. But knowing who you are in the world already tells you something that changes those odds.

Scott Young: [00:36:36] And so that's sort of like in Bayesian reasoning that your prior shouldn't just be one in forty thousand because, you know, all this information about yourself that gives you a sense of who you are relative to the other people who are trying. So one of the ways that I think this can impact you is that if you're looking at something like what's the rate of success for some sort of like online course. And maybe most people who take the course don't finish it. And so you might say, well, it's must be must be really lucky to take the course. But the thing that you know about yourself is how much drive and motivation you have. If you don't have very much, then maybe your chance of passing it is actually zero. But if you have a lot of motivation, then maybe it's actually quite high. And so that's that's an example of luck that I think is important to think about, which is the the luck that it certainly luck to be the kind of person that you are.

Scott Young: [00:37:22] But once you know what kind of person you are or what position you are actually in, a lot of it goes away. And the other two types of luck that I distinguish are things that happen after. So things that you are kind of future oriented and those include luck. That is purely random, kind of what you were talking about with blind luck versus things that are based on having a certain amount of skill or because the method for doing it is quite difficult. And so those, I think, are also important to distinguish. I feel like for me in starting a blog, you have to be quite lucky to be successful. Most people who start a blog are not able to get to a point where they're able to do it full time, even if they want to do. However, I don't think it's the case that the person who becomes a successful blogger is because they're lucky. I don't think even if you have the right amount of talent, I think there's a certain type of content and stuff that you have to do, which is not always obvious. But if you do all those things and you're very consistent with it over time, you will, you know, probably more than likely be successful at it, as opposed to, you know, just having one of your articles go viral.

Scott Young: [00:38:21] And it was just like super random, which when you could get picked. Now, I would contrast that maybe with, let's say, a professional actor and I don't know as much about acting. My imagination is it a lot of it depends on getting your big break, right? Just having some person take a chance on you and then that kick start your career and then you're in all sorts of movies and stuff. And so in my case, I think that it's sort of similarly difficult to be a top tier level writer as it is to be reasonably tier level actor or it's comparably difficult. But the writer is a much more. If you know how to do it and you do the correct things, you will be successful, whereas an actor might depend on things that are just fundamentally outside of your control. It's just sort of rolling the dice. And so I think these three types of luck, they're all things that can be considered lot when we think about how lucky you are and how privileged you are in this kind of thing. But they kind of have fundamentally different meanings in terms of how you should live your life and make decisions based on the awesome.

Harpreet Sahota: [00:39:14] Thank you for clarifying that. So I'd love to finally get into your book, Ultralearning, which is a book that I absolutely love. So what exactly is ultralearning?

Scott Young: [00:39:24] So ultralearning is the process of aggressively teaching yourself skills. And so the idea I wanted to contrast it with was two things. I wanted to contrast it with the normal way we think about learning, which is you go to a school and there's a teacher and they tell you what to do and you just follow along with their instructions. So ultra learning is self directed, meaning that you are the one designing the project. You're trying to get what you want to get out of it, not what the teacher tells you to get out. And second is that it's aggressive. And I wanted to contrast that with the way a lot of people approach hobbies, where it's just about dabbling, it's just about having fun. And not to say that having fun is bad, but I wanted to focus on if you really cared about getting good at it, if you really cared about doing it right, how would you do it? And so the entire book is a collection of not only principles, but stories and examples of people who were really serious about learning and really approached it with a mind for what is the right way to do this. And so that often leads to doing things that are harder or more difficult, but ultimately more efficacy than and simply just doing what would be most spontaneously occur to you.

Harpreet Sahota: [00:40:27] And how can we use ultra learning to accelerate, transition, or rescue our careers?

Scott Young: [00:40:34] So the idea that I have is that if you are trying to improve your career, you mentioned Cal Newport's book So Good They Can't Ignore You. And the basic thesis there is that if you want to have a great career, you need to have rare and valuable skills. And this is basic economics. This is chest. If you you get money and you get a great career because people are willing to give it to you. It's not the case. It just the idea that, oh, well, if I just find the thing that I'm really passionate about, that's all that matters. It's a fundamentally an economic transaction that if you have something that people really value and is really rare, you get to have negotiating leverage when deciding how many vacation days you have or how much they pay you or what kind of environment you want to work. And if you don't have that leverage, then very often, even if the job is something that you're really passionate about the industry, you don't have that leverage, you often get trampled on in the workplace. And so the way ultralearning fits into that is that very often we find ourselves in a situation where maybe we're not that remarkable and we don't have rare or valuable skills. Maybe we don't even like the career that we're in right now. And so being able to acquire hard skills automatically pulls you outside of the pack and positions you in a different place than other people. And it gives you this power to search out things that you can have to give you an advantage.

Harpreet Sahota: [00:41:46] And in your book, you outline nine principles that underlie ultralearning. I want to dig into two in particular, and that is focus and intuition. I think is first, probably a good place to start is trying to understand why is it that we procrastinate.

Scott Young: [00:42:02] Yeah. So well, we've already been talking about it a little bit. I think the reason we procrastinate is invariably because we either have an aversion to doing what we want to do. It can be because it's hard. It could be because it's difficult. So we have problems kind of initiating our action or we have problems with getting distracted. So we're in the middle of doing something. And I don't just mean like your phone ringing, but even just the internal impulse to being like, maybe I should watch TV or maybe I should take a break right now. And I think both of those can be problems. I think that the way that we can get better at focusing is often by sort of deliberately training ourselves to focus. And so I do think focus in many ways is something that you can generate for yourself by controlling your environment, controlling your habit, controlling the little rules that you use to decide when to take breaks or what kinds of breaks to take. And I think those can make a really big difference.

Harpreet Sahota: [00:42:55] And how can we recognize that tendency to procrastinate and then create a mental habit that will kind of get us back on track?

Scott Young: [00:43:03] So self awareness is a really big part of it. And I think we're typically quite bad at self-awareness. We're not that self-aware. And so often it's just the process of just asking yourself these kinds of questions that I think themselves can unlock solution. So the problem is very often that you don't frame it in terms of I'm procrastinating, you just frame it in terms of "I'm taking a well needed break". Or "Oh, it's hard. I should probably work on this first". Instead of actually getting started, it's kind of rare that we actually genuinely admit to ourselves that we're procrastinating. It's usually more likely that we're saying to ourselves something like, well, I'm not ready yet, or yeah, I know I should do that. But you know what? I'm just going to do this first because it's easier or, you know, I'm going to take a little break and I'll get started with that, too. And so I think part of the way that we can make progress against these kinds of problems is simply by not giving ourselves sort of only a certain list of valid excuses to make for things. And so I think if you recognize, for instance, that you have a tendency to, you know, spend too long prepping before you're ready, then, well, what if you took a stab at doing it, even though it's going to be bad? And very often you take a stab at doing it and it turns out not so bad and you realize that it's the sort of fear of getting started that was holding you back.

Scott Young: [00:44:17] Or if you have if you're the kind of person that you continually do research and you don't actually do it, you know, you even set yourself some sort of time limit. So it's sort of like, OK, I'm only allowed to research for an hour and then I actually have to spend half an hour doing something. And so you can create these kind of little mental rules for yourself and doesn't mean you're going to always follow them.

Scott Young: [00:44:35] But I think they help us kind of cue in our self awareness. So even in things like I'm not allowed to like distracting fun things when I'm taking a break is a little rule that you can have for yourself that makes a huge difference in terms of your ability to resume studying or working or doing difficult intellectual work. And if you say to yourself, OK, if I need a break, I'm allowed to like, meditate or have a glass of water or an apple or like sit quietly, but I'm not allowed to let go on Twitter or watch YouTube. And even just saying that to yourself makes a big difference, because often that I want to take a break signal is not coming from "I'm exhausted I need to take a break from doing this". But rather, "it's been a while since I've been on YouTube" and you have that pull to do so. And so I think creating these little rules for yourself can often be quite valuable. And it is a process to hear what the rules should be. But I think even now you could probably recognize what are some of your tendencies. If you're listening to this and make some adjustments,

Harpreet Sahota: [00:45:26] You're saying there's that self talk. You tell yourself like, oh, I'm not ready. I get that so much from a lot of my mentees. It's always like, oh, I want to go apply for a job, but I'm not ready. And oftentimes it's like you actually already, but you just tell yourself that you're not ready.

Harpreet Sahota: [00:45:40] So do you have any tips for the listeners out there who are kind of stuck in that? I'm not ready to do this yet, but they actually might be ready.

Scott Young: [00:45:47] Well, but that's the thing, though. I think I do lots of stuff that I'm not ready for. And I think the idea is that you have to be willing to do things that you're not ready for. I know that sounds kind of funny. It just sounds like I'm just twisting words around. How can you do it if you're not ready? But I think there's just sort of an expectation that we hold ourselves to that we need to be successful at the things that we do that like I can't fail and not... Like I'll give an example. So I was talking to one person and they were learning a language and they got offered a job opportunity in that language and they turned down the opportunity because they didn't feel like they were good enough in the language. Now, I don't know that their exact level of ability, this person, but I got the sense from the conversation that they've been studying it for a while. It wasn't like they were clearly not even close to ready. Like if someone said you've been studying for two days, I'm going to give you a job opportunity. It was just that they didn't feel like they were as fluent as they'd like to be. And I think I mentioned that, you know, well, obviously, the way to get really good at this language was to work the job right, to actually just say yes to it and then yes, if you're not very good, but you're going to get good by just being forced to use it in the job. And I mentioned this story in an article.

Scott Young: [00:46:52] Some woman replied back to me and said something like, well, what if they are genuinely not ready? And then shouldn't I trust their opinion on it? And I think the problem is just that we have this assumption. And she was like, well, what if what if this guy got fired? Or what if this person got fired from their job because they weren't good enough? The language. And I said, and then they get fired. Like, we have this assumption that, like, you're not allowed to fail at anything in life, like you're not allowed to try anything that's too hard. You're not to like. And so I really think there's a benefit to being ambitious. There's a real return in life, having ambition and to doing things that you're not entitled to do. And I think there's a real culture of discouraging people from doing things that that they're not qualified for or that they're not up to yet. And I kind of feel like you should - unless people's lives are at stake unless there's, like, extreme circumstances - you should go out and do things that you're not ready for. I remember when I was in China learning Chinese in this year, an English project, and I was about a month and a half and someone at a local bookstore I was sort of visiting found out that I had written a book, that it was published in China and they wanted me to give a talk. And I was doing this whole no English thing. So I said, well, I only do it if I can do the talk in Chinese.

Scott Young: [00:47:59] And I remember I did the talk in Chinese. And I think there's actually I have a recording of it somewhere that I never published and me doing this talk. And it was brutal because I'm a month and a half into learning Chinese. I'm clearly not ready to do a speech in Chinese. I like memorizing it. And there was, I don't know, maybe like fifty to one hundred people in the room. And I remember talking to someone after and they're like, well can you understand, is it just like part of what he was saying. But like other parts, you didn't understand my speech that I had memorized stuff. And so the thing is. Is that yes, clearly I wasn't ready to give a speech a month and a half into learning Chinese. This isn't just because I'm arrogant and I think that I was ready. But that it doesn't matter that you're not ready. You don't take the job at the programing office. And what's the worst that can happen? They'll fire you because you're not good at it. Right. And then you'll go back and you'll learn something. And so I think that we need to take the attitude of doing things we before we're ready, because that's how you learn things and also because failure isn't really that bad. And if you just kind of go into it with the attitude of, no, I'm not ready, but I'm going to do it anyways and I'm going to be really bad at it, you often find that you're a lot better than you thought you were.

Harpreet Sahota: [00:49:01] Yeah, I mean, because readiness is almost like a spectrum. Right. And it's like just by starting to do something, you get on that spectrum of readiness, just like mastery is a journey. Nobody comes out the womb like I got machine learning down pat. It's a journey and it's a spectrum of readiness. So the way you put it was really beautiful. Thank you for that. So there are a few sources of distractions that we can just get away from, right. We could change, get away from them. But there's one source of distraction that is with us wherever we go, and that's our mind.

Harpreet Sahota: [00:49:32] So how can we mitigate the distraction of our mind?

Scott Young: [00:49:36] Well, I think that there is a policy some people have where they're like overly severe with themselves if they kind of daydream or their minds wandering or this kind of thing. And the way I like to think about it is that mind wandering and daydreaming in these kinds of things are often signs of low engagement. There are signs that you're not actually synching up with what you're trying to learn right now. And so sometimes the way to take this sort of signal of like you, you're feeling an urge to procrastinate or this kind of thing is to take it as a positive sign. I think a lot of times we kind of get an overly negative feeling about it. But I think if you take it as a positive sign, you can say to yourself, OK, I'm not engaged right now with what I'm doing. What can I do to make it more engaging? And even just asking that question, you often uncover strategies for doing it. So like, if you're watching a lecture and you're finding you're not very engaged, maybe increase the speed or maybe take more notes or maybe you're not engaged because you're not understanding what they're talking about, then you need to pause and figure out what they're talking about.

Scott Young: [00:50:35] Or maybe you're not engaged because you don't understand why this applies or why it's relevant. And then even asking that question focuses your mind on the relevant information. And so the kinds of distractions that we often experience are often diagnostic of what we need to do to actually learn better. And we just take that feedback signal as a punishment. So the mind wandering is I'm so lazy and undisciplined and this kind of thing, and I hate doing this and I got to do something else. Rather, it's kind of a sign because it's a little signal that says, OK, I'm not doing something right with how I'm learning this. If I'm getting distracted constantly, maybe I need to change how I'm approaching this because I'm I'm approaching it in a way that's not really using my cognitive resources properly.

Harpreet Sahota: [00:51:18] And do you have any tips for our listeners for what they could start doing today to improve the quality of their focus?

Scott Young: [00:51:28] I think the thing that I would start doing is make a little journal. And I think there's a very important feedback cycle you can engage in, which is, one, write down your intentions of what you want to do each day for work. Don't make them unrealistic. I think this is another problem.

Scott Young: [00:51:44] People just like they'll set super unrealistic goals and then not achieve them. And they can't synchronize in on anything because there's this huge gap between what they actually do and what they like to do. So what I would like to say instead is make your intentions something that you one hundred percent believe at the time that you're going to do. It's not a stretch. It's something you think that you're actually going to do, then do it. And if you don't actually do it right now, why do you think you didn't do it or what happened or what got in your way. And I think the problem is that, as I mentioned before, is that we don't have this automatic self awareness. So we get into these patterns where, OK, I say I'm going to do this and then I don't do it. I say I'm going to do this and I don't do it. I say I'm going to do this and I don't do it. And it's the same story again and again and again. And you don't realize that you're stuck in this loop. And so I think the way you break out of that loop is by first realizing what it is. What is the thing that's getting you distracted? Right. What is the problem? And very often it's something really simple. It's not usually something crazy complicated. And it may not be always the easiest thing to fix, but it's usually not something mysterious.

Scott Young: [00:52:41] It'll be something like, oh, well, actually, I had my email open and so there were new email pings and I just checked my email and then I started answering emails without thinking about it. And then half an hour later, I totally forgot about this project I was working on. OK, well then you've got an easy fix. You can keep your email close while you're working on it. And there's things like this that you can do. But I think it only works if you cultivate that self-awareness and you only get that self awareness if you first write down what your intentions actually were and then contrast that with the reality and try to figure out what was the reason for getting derailed. And that only works if you have realistic intentions. But I think writing it down makes a big difference because it gives you visibility of that feedback loop. So you can actually see how does your idea about what you should be focusing on differ from reality

Harpreet Sahota: [00:53:28] Thank you so much. That's an excellent tip. So kind of switching in to the other principle you talk about in your book, and that's intuition. So what is intuition within the context of ultralearning?

Scott Young: [00:53:42] So the idea behind intuition is that we want to have a really deep understanding of things. And I know we were talking about this earlier and the like, just knowing the names of stuff versus kind of understanding the nuts and bolts of how it actually works. And the idea about heightened intuition is simply that for a lot of people, they kind of view understanding in this sort of overly magical light, like either you get something you don't. And I think the Eureka moment,you know, the that Archimedes is sitting in his bathtub and having it over flow and then just immediately understanding water displacement, running out in the streets of Athens naked. Like this is an example of how we think about understanding that it just happens in this snap moment. And a lot of the research on understandings and how they develop itself comes in play for these kinds of slow build up of what are known as chunks. So chunks are this idea that we can only hold a few concepts or ideas in our mind simultaneously, but that as we get exposure to information, we're able to make more, bigger and elaborate chunks. So the kind of classic experiments of these will be to like give someone a list of letters and then try to get them to memorize it. But then if you reorganize the very same letters into recognizable acronyms, it's way easier to remember them, even though it's functionally the same information.

Scott Young: [00:55:01] And so this is this idea of chunking is that when you recognize a pattern, it becomes another object in your sort of mental repertoire that you can use. And the people that are really smart, the people that are able to manipulate things very well and have this really good intuition are very often the people that just have these huge libraries of patterns and those libraries of patterns come from building this huge amount of experience. Now, I know just saying having a lot of experience makes you smarter is not the most immediately practical tip. But I think it's very helpful for thinking about the problem of understanding, particularly in a subject like machine learning or Data science, where you have a lot of abstract concepts and you maybe just don't feel like you're smart enough to really get, let's say, like linear algebra. And but if you go through and you play with it enough and you use it enough and you you keep seeing it again and again and again, then all of a sudden sort of concepts that were really, really, you know, difficult when you first started learning them are at your fingertips now. And so I think this process of building intuition is a long term process, but it's also one that we often try to run roughshod over when we try to memorize things without really trying to understand them or assemble them into patterns that we actually make sense of it.

Harpreet Sahota: [00:56:10] In your book, you give a really beautiful example with Richard Feynman how he used kind of this understanding of his intuition and recognition of patterns within mathematics to quickly do some crazy calculations. So how do these intuitive experts think differently about problems than a novice does?

Scott Young: [00:56:29] This is like a famous study, and I'm not sure that's the Michelin shoe study. So I'm maybe mixing it up with another one.

Scott Young: [00:56:35] But I think it's from Michelin, too. And that study is about kind of they were doing case reports, I think it was physics experts and physics novices, and they were looking at solving physics problems. And I think it was a sort of a read aloud protocol, if I'm remembering correctly where they just sort of asked him, what are you thinking when you're trying to solve like what would be the first step would be the second step. And what they found was that it's not the case that the experts use the same process as the novices. They just do it faster and more automatically. Rather, the experts are looking at qualitatively different features of the problem that allows them to solve it. And it's often much more abstract ideas, much more basic principles that are not just a superficial detail. So an example would be like you have some problem that has like an incline plane and a pulley on it. And so the novice looks at the problem and they're like, oh, right, OK, well, how do I solve problems with incline planes and pulleys? Right? Whereas the expert will look at it and say, oh, this is a conservation of energy problem or this is a conservation of momentum problem. So they're not even really looking at the pulley. They're not really looking at that. They're just looking at, oh, this is a situation where I have to use the fact that there is going to be some conservation of some quantity.

Scott Young: [00:57:48] That's going to be how you solve the problem. And so the problem is that if you're dealing with a new topic, you might say, well, great, well, I'll just reason from first principles then. Well, you probably can't do that because these first principles are inherently more abstract. They're the kinds of chunks that I'm talking about, the need to be assembled first. So it's OK to approach problems in the beginning in a somewhat superficial way. But I think it is helpful to have this kind of in the back of your mind that what you're trying to do is to sort of uncover what the principles are and to reason about them. And so this is sort of related to this mental models idea that we're talking about before, because in some ways, mental models are like the principles the experts used. And no, it's not enough. You just know the name of the mental model to be able to use it, just like just knowing what conservation of energy means, you know, it doesn't help you solve physics problems automatically. You can just recognize the problem that, oh, yes, this problem is going to be a conservation of energy problem versus some other kind of problem. But I think if you kind of get in your head, there are these sort of abstract principles that there are these sort of higher level problem types and principles.

Scott Young: [00:58:53] You kind of develop a sensitivity for them and you start looking for them and you start looking for, you know, like a good example is you're dealing with some difficult, nonlinear problem in physics and you're like, OK, let's do a Taylor expansion. Like, that's just sort of one of the techniques. You just sort of learn to just kind of deal with these sorts of problems or, OK, I can't solve in here, maybe I'll do the Fourier transfer or maybe I'll I'll do something else with the Data before I process it. And these again are not the things that just knowing the word Fourier transform is going to necessarily be helpful to you. But being on the lookout for these kinds of ideas, these kinds of abstractions helps it so that when you're taking a class where they talk about Fourier transforming, they're making a really big deal out of it. You're probably like they're making a big deal out of this because it has this sort of usefulness. And so I think the more you kind of keep your eyes peeled for these sorts of situations, the easier it is to kind of latch on to them when they actually arrive.

Harpreet Sahota: [00:59:47] So how do we build this intuition? Is it just kind of being able to try to understand this thing and then try to see it in the real world as much as possible? Or is it more like a conformal way that we could build our intuition?

Scott Young: [01:00:00] Well, there's different ways. I think having a lot of experience is probably the number one. I think that actually playing and manipulating with the environment is super important. Play was one of the things that Richard Feynman was kind of famous for. And so I really highlighted in that story because I felt like he was just an example of someone who just liked doing the physics problems and thinking about things and trying to get answers for stuff. So there's some example where he's in a cafeteria and he's like thinking about when someone's spinning a plate and how it wobbles and like trying to come up with the formula for that. And I really like that example because do you know Nobel Prize winning physicists? Like, is this the kind of work that's going to make you famous, figuring out plate wobbles? No, of course not. Right. But it's just the kind of example of like using physical concepts and applying them to a situation that maybe is not going to be worthy of any kind of interesting papers. But it's a little puzzle that he can kind of play around with the ideas and develop some flexibility with it. So I think play is very important. And I think also being explicit about recognizing your lack of understanding, recognizing, you know, OK, if I'm going to try to understand this mental model, let's try to apply to different things to see where it applies, to see where it doesn't apply.

Scott Young: [01:01:12] And so I do think there's a certain amount of deliberateness that you can have. I think this is sort of on a spectrum. If it were a spectrum where there is the rote memorization, just learning the names of things, approach to learning, and then there's the kind of trying to take it apart, see what the machinery is. What happens if you press this button like there's this kind of tinkering, playing with things, attitude that you can apply this on the other spectrum and end of the spectrum. And I think that's just the attitude that I want to try to encourage people to have. And I think the most successful learners have this attitude. And I think that it's very often the case that what we sort of mistake for just being raw intelligence is more that this person actually just likes playing with it and tinkering with it. And because they engage in this sort of cognitive process that builds up these chunks there, they're a lot more expert at it, even if maybe their intelligence is just normal. Let's say.

Harpreet Sahota: [01:02:04] Thank you for that, Scott. So less formal question before you jump into Quick Lightning Round. And that's what's the one thing you want people to learn from your story?

Scott Young: [01:02:14] Well, I think if there was one thing I would want people to learn is that the possibilities of learning are a lot more vast than you've maybe previously considered. I feel like the main reason I wanted to write this book was not to really instruct on any particular principle of learning or science, or it wasn't to write a book about the science of transfer, retrieval or feedback or focus. I wrote the book because I wanted people to have the same eye opening experience that I had when I met Penny Lewis. I want them to have this experience where not that they're necessarily going to go off for a year, not speaking English, learning languages, or try to stimulate a formal degree using online resources, but rather that they know that these kinds of things are the kind of things that you might be able to do and that there are lots more things that no one's ever attempted that you might be able to do.

Scott Young: [01:03:00] And I want them to feel that this space of possible learning is much, much, much broader than they've been given the impression of from going to school, that they've maybe gotten the impression from things they've tried to learn in the past. And so if you have this sense of vastness and spaciousness that I feel is obvious to me now, but it wasn't always obvious to me, I think that that itself is more important than any other method that you might both jump into.

Harpreet Sahota: [01:03:25] A quick lightning round started. The first question, if you could put up a billboard anywhere in the world, what would it say?

Scott Young: [01:03:33] You can learn anything you want to.

Harpreet Sahota: [01:03:34] What do you think is the biggest lie that people tell themselves?

Scott Young: [01:03:39] I don't think that there is a specific line, but I think that we in general tell ourselves a story to make sense of our lives in a way that is not always true. So I think the way I would put it is that the the the things that we tell ourselves about why we do certain things or our motivations, these things, they're kind of all lies.

Scott Young: [01:03:59] So I think it's not so much that it's one big lie, but that they're all kind of lies. They're not they're just sort of useful fictions that we use to make sense of why we do certain things. And they may only sometimes bear a resemblance with the real thing of the real reasons that we're doing things.

Scott Young: [01:04:13] And I think that the main sort of lesson to impart from that is just to be somewhat careful with the story you tell yourself, because I think a lot of people take the story of what happened to them and what led to their life and why they are the way they are. They often sort of take for granted that that's just the facts because they were there to experience it. But I think I've come to learn that we're actually the reasons we do certain things are often opaque. We don't actually understand them. And so it's often a very helpful story. But I think you want to always take it a little bit lightly, because sometimes this where you tell yourself can limit you in ways that maybe are somewhat unhelpful later on. And if you take it to be the truth of the final truth of who you are, I think that itself can be problematic.

Harpreet Sahota: [01:04:55] What's an academic topic or area of research outside of Data science that you think every Data scientist should spend some time researching and studying economics?

Scott Young: [01:05:04] Economics is by far the most useful academic subject that I've learned. Maybe it's just my way of thinking about things, but it has a it's it's sort of halfway between math and psychology. So psychology is interesting, but it tends to be a little bit more on the kind of grab bag of various facts and different models and things like this. And so economics, it is too abstract to be realistic for most situations, but for that very sense of abstraction, it's often very useful because you can often get a rough outline of why people do things. The biggest mistake is I think economics is about money and it's not it's much more just a general social science idea. And so I think for people who are doing anything with Data science, understanding economics I think would be quite helpful just because it provides a sort of a background to thinking about things, especially if you're doing systems that involve other people.

Harpreet Sahota: [01:05:58] What's the number one book, fiction or nonfiction that you would recommend our audience read? And what was your most impactful takeaway from it?

Scott Young: [01:06:06] I'm going to recommend a book that many people have not read, and I like recommending it because it's not a book that gets recommended very much, but I really liked it.

Scott Young: [01:06:13] And it's called The Enigma of Reason by Hugo Mersea and Dance for Me. And it is basically the argument of the book is what the Enigma is, is has two parts, basically, if reason is super powerful, which we kind of all think that our ability to be rational animals is is one of the things that really sets us apart. If it is so powerful, then why are we the only kind of animal that seems to have it? Why don't dogs work out syllogisms and and reasoning about things? Why is it that seem to be just human beings that seem to be able to do this? And then second, why do we have so many cognitive biases? So if you've heard of cognitive biases before, you know that we make lots of reasoning errors and that they're fairly systematic reasoning errors. And that's been a popular topic. And so if, you know, if we have this great faculty of reason, why isn't it better? Why don't we actually reason logically? Why are we so biased and wrong? And the answer is, is really, really interesting is that they kind of reframe the idea of what reason actually functions for entirely and that they argue that it's not mostly how we make our decisions, nor should it be and and is really, really interesting. I won't spoil what the resolution of the Enigma is, but you really ought to listen to the whole book. If you're interested in thinking better. 

Harpreet Sahota: [01:07:25] Definitely check that out. Actually, I'm reading a book currently by another Scott, Scott Adams, creator of Gilbert. He wrote a book called LoserThink, and it seems like it's very much in line with the book that you just recommended. So I'll definitely check that one out as well. So if we can get a magic telephone that allows you to contact twenty year old Scott, what would you tell him?

Scott Young: [01:07:44] You know, it's funny. A lot of people like the kind of ask me the what would you tell the younger version of yourself problems. And I have a completely different kind of take on that kind of question than most people do. And my take is just simply that very often the learning, the figuring out what you need to do in life is the thing that you're doing in life. Right. So there's a certain sense that you want to rewind the tape and tell yourself to do something differently. But the thing that we're mostly doing is trying to figure it out. And that is most of what life is, is figuring it out that, yes, if you knew everything, then you could just go back in and do it in a different way. But in some ways, you would not be the person that you were back then. You'd be the person you are now. So just as putting aside the whole time travel.

Scott Young: [01:08:26] Paradox is, I think that what I would suggest to anyone who's thinking about where they are and what are the things that I'm going to wish that I did differently or what are the things that I wish that I did more is to just be more willing to explore and be more forgiving of your mistakes. We were talking about that before, about not being ready for things. I think there's also this idea that we kind of chastise ourselves too much for making mistakes because we didn't know more when in our past. And I think that, you know, that's the whole point of life, is to learn how it works and to make mistakes. And so I don't know whether I would tell my 20 year old self anything.

Harpreet Sahota: [01:08:58] What song do you have on repeat right now?

Scott Young: [01:09:00] Oh, these days I've been listening to a lot of bossa nova. So I have Agua de Beber. That's one of my kind of common ones. But I also like Brazil and a few other ones that are playing in the background.

Harpreet Sahota: [01:09:13] So what's next on the horizon for you? Any new projects, any new books?

Scott Young: [01:09:18] Well, no new books yet. I still have to think a bit more before I figure out what I'm going to write next. But I do have a new course that I'm actually co constructing with Cal Newport is going to be coming out in the summer. More information about that will be forthcoming, but it's going to be called Life of Focus. And it's going to be about a topic we already talked about in this podcast episode, which is about how to focus and really how to improve that, because that seems to be a big problem that a lot of people have these days is with being unable to focus on what matters most to them. And so this is going to be a course that we're hopefully going to be launching at the end of August around that time. And so definitely if you sign up to my newsletter or you come to my blog, we will announce that as soon as it's available.

Harpreet Sahota: [01:10:00] You and Cal Newport are teaching a class together, man. I'm already signed up about Armont that. I'm looking forward to that. So where can people find ultra learning. 

Scott Young: [01:10:07] So you can find it wherever books are sold and get an Amazon audible Barnes Noble. If you're not tired of listening to me now, I also narrate the audible version. So I know a lot of people who like podcasts also like to listen to audiobooks. And so I highly recommend that there. And I go into much more detail in all these kinds of learning advice in a in a neatly edited format, less less ranty than I am right now.

Harpreet Sahota: [01:10:31] So how could people connect with you? Where could they find you online?

Scott Young: [01:10:35] Perfect. You can go to ScottHYoung.com. That's my website. It has everything. I have over fourteen hundred articles on learning productivity, all the things that we've been talking about here, links to descriptions and numerous details of all the projects have undertaken. And that also has links to all of my social media accounts and anywhere else that you might want to connect with me.

Harpreet Sahota: [01:10:56] Scott, thank you so, so much for taking time out of your schedule to come on to the show today. I really, really appreciate it. Thank you. Thank you so much for having me.