Scott Young on Mastering How to Get Better at Anything

Living a life in full is a conversation you always wanted to have with that person who gave an amazing TED Talk or the author of one of your favorite books, or that inspirational Olympian you always wanted to know more about. It's graduate level conversations with those making a difference in the world and in the lives of others. This show brings you new ideas and approaches so that you can live a life in full. I'm your host, Dr. Chris Stout and I hope you enjoy this episode. This episode is brought to you by the nonprofit I founded, the center for Global Initiatives. The center is an all volunteer organization so there are no salaries and thus all tax deductible donations can go to the work. While our key country partner is in Tanzania, our work is global and generally focused in the areas of education and healthcare. We also help others to get their nonprofits started or augment others project based initiatives. It's our goal to open source humanitarian intervention and to help make it easier for others to do more good in the world. We are proud to have been ranked a great nonprofit every year since 2011 and to have achieved a Platinum level rating by Guidestar Links. In this episode's show, notes will take you to published articles on our outcomes, a number of helpful tools, and downloadable resources which are all free always. Please Visit us at CenterForGlobalInitiatives.org and be sure to watch our video at Patreon.com DrChrisStout to learn more. Thanks. Welcome to another episode of Living a Life in Full. I'm your host, Dr. Chris Stout. Life depends on learning. We spend decades in school acquiring an education. We take pride in mastering a craft or a sport or a game. The things we do in our careers, or even just for fun, are enjoyed to a large extent because we feel we're capable of getting better at them. We yearn for mastery, but learning can be elusive. We may spend hours studying and still not do well on an examination. Improvement can be fickle if it comes at all. Sometimes we improve effortlessly and other times it can be a slog. Many of us spend years hitting a tennis ball, playing chess, or working at our jobs and not reliably getting better at any of them. Why is that? And more importantly, what can be done? In Scott Young's new book, Getting Better at 12 Maxims for Mastery, he explores the science of skill acquisition, illustrating the basic principles that can help us get better at the things that matter most. Scott was a prior guest on the show in episode 37 when we discussed his Wall Street Journal bestseller, Ultralearning he is also a podcast host and a computer programmer. Since 2006, he's published weekly essays to help people learn and think better. His work has been featured in the New York Times, Pocket and Business Insider, as well as being on the BBC and at TEDx. When he does, he doesn't promise to have all the answers, but he does give us a good place to start. Hey Scott, welcome back. It's good to have you back on and catch up.

Oh yeah, thanks for having me, Chris.

You bet. So I think you've really kind of become quite well known in the learning space, as it were, which is super, super cool. And tip of the hat, could you maybe give us a Cliff Note summary of ultralearning back then and blog and maybe tee up listeners for us for your latest work?

Right, right. Yeah. So I've been writing for a long time. I've been writing since the early days of the Internet, 2006 and I've been writing since I was a student in university and I started writing about kind of college oriented topics, how to study efficient sort of learning methods. And then that kind of after I graduated I started doing some of these intensive learning projects which brought me some a little bit of Internet fame. I did one project called the MIT Challenge learning MIT's four year computer science curriculum over 12 months. I did another project with a friend where we traveled to four countries to learn four different languages. And the kind of crux of that project is that we weren't going to speak English in each country that we went to. And we called it the Year Without English. And I've also done projects learning artistic skills, quantum mechanics, other things that are sort of documented publicly and that culminated in my 2019 book Ultralearning. And then since then I've been kind of doing this like deep, deep, deep dive into a lot of the academic research behind learning, educational psychology, cognitive psychology, you know, trying to tie together a lot of sort of diffuse literature on how people acquire skills and learn better. And that has come together in this latest book, Get Better at Anything, where I'm trying to really document what are the principles that you need to understand, to understand why we get better, how we can get better, and also what are the things that prevent us from getting better so we can avoid them in our pursuits.

I think that's so great. I appreciate the kind of Tim Ferriss or who is the other guy that wrote the or that edited the Paris Review. I'm blocking on his name, but it was sort of, you know, to be able to do these deep dives. I mean, certainly there could be people and maybe there are people that do this and just don't share it publicly. But the fact that you deconstruct it, go into these deep dives and honestly, you know, Scott, it's like a benefit for the rest of us, you know, to be able to see, you know, because they almost seem like, gosh, this seems like an impossible task if someone just offered it up and said, you know, let's, you know, get a go to MIT virtually and cram and do this. But, you know, you demonstrate that it is. George Plimpton is who I was trying to think of. But you're kind of like the contemporary version of a George Plimpton of doing these things and then, you know, sharing them, you know, quite full throatedly. And, you know, you also, you do the background and do the research to back it up and then, you know, present them in a very tidy way with your writing and particularly your books. So what, I mean, this isn't just like a common kind of thing for most people. What, what was your, what spurred this interest in learning and expertise? Competency, deconstruction?

I don't know. You know, it's funny, whenever people like ask you, like, why are you so interested in this? And then you have to sort of reflect on it because to me it just seems so obvious why aren't you? And then it's sort of like, why. Why is everyone else not right? The thing that I really try to get at because, you know, you use, you joked a little bit that I've become a little bit, you know, known for this sort of learning how to learn topic. And it's just surprising to me that it's like such a small topic compared to other things because learning is just so obviously central in our lives. Like, you know, if we were just really good at a lot of things, right, or we were much better at the things that we spend a lot of time doing, wouldn't life just be better? So to me, I guess that's the, that's the thing. This is just such an obvious thing that I get sucked into now in terms of like why I've maybe specialized in it or why I've spent so much time in my kind of career focusing on it. Some of that is, I think, my own deep interest in it. I've always been interested in reading and learning things, and that's been a big personal motivator. But then also, I think, just my own personal history. I mean, I started blogging kind of when that was just becoming a thing and I was a student and it was like, sort of like what can a 20 year old credibly offer any advice on? Well, like I was a good student, I can offer advice on studying. Like I was going to tell, you know, middle aged divorcees, like how to manage their relationship, find a relationship or you know, here's how to manage your personal finance. Right, exactly. From a broke 20 year old. Microwave food. Yeah, yeah, from exactly. So, so that kind of got me started on there. But then, you know, like, I think most people who find their passion in life, I think, you know, you realize, oh, actually I am a little bit of a weirdo here and maybe I can specialize this in a way that other people might not. And, and I mean it's, it's just, I've just been enormously grateful that I've been able to do this weird thing for a living. I mean it's, it really, it really wasn't a job at all when I started doing it. Like it was very much like, that's not a thing now it's kind of a thing, but it's still kind of, you know, like I remember reading somewhere that the average like high schooler, their professional aspiration is to be a YouTuber, which makes me a little sad. But as someone who has sort of essentially, I don't know, I'm not much of a YouTuber, but essentially has that job. I can understand. It is a really great thing to be able to just spend your life learning things that interest you and then sharing it with other people.

Well, and you also have, you know, obviously such an audience for it as well. I mean, it kind of brings, I do a lot of work with venture capital and private equity and startups and things and kind of the, you know, the mantra with a lot of startups is for founders like scratch your own itch. And that's sort of what you've done in a sense. And you're kind of, I mean, you've become your own brand and you're kind of your own little startup in that as well. So I guess I need to context, contextualize it in my head that that makes perfect sense. So, you know, kind of speaking of this, then kind of earlier in your career you connected up with Georgetown computer science professor Cal Newport. How, how did that come about?

Very early on.

Yeah. How did you two connect? Because it's, I mean, knowing from Cal's work too, I could see the parallels. But tell us how that happened.

So I want to say that we first got in touch, I'm like, late 2006, early 2007, so we're talking like real, real ways back. I mean, I think he had written. He had written, definitely had published one book. I want to say he had either published or he was about to publish his second book. So now he's written like, I want to say seven. Maybe he's written eight. I actually have to count.

Yeah, I was going to say he's

written quite a few now, at least.

Right.

Yeah, it's getting up there. It's getting up there. He's more prolific with the book writing than I am. And he. So he was like an author. And it was very student focused too. Like he was a grad student at MIT at that time and a mutual friend of ours, Ben Kasnoca, I'd like sent Ben Casnocha some little guide that I'd written about studying. And Ben Kasnoca, who's. He's like a very hyper connected individual. He was just sort of like, oh, you should know, Cal Newport. And so Cal put us in touch and I think the kind of meeting of minds was that, you know, Cal was a little bit more established in the student advice space. I mean, he was also a neophyte back then, too, but he was a little bit more established than me. He was a bit older than me, but he. He was just starting his blog and I had been blogging for like a year, which now in retrospect seems like nothing, but I've been blogging for slightly longer than him. Right. And. And so he was just getting his blog started and so he was just sort of curious about, like, what we were doing. And we kind of connected on the student advice space because we, I think, have very similar mindsets around productivity, learning, and just, I would say, life outlook in general. I mean, I'm. I'm. You know, we obviously have some differences, but there's certainly a considerable amount of overlap in, like, how we think about things. And. And then, yeah, we've just, we've been good friends and we've collaborated on a number of projects together. You know, about 10 years ago, we began working on a course called Top Performer, which was sort of tying kind of like my sort of interest in learning and Cal's interest in kind of career development. He had written a book called so Good They Can Ignore youe, which was about why you should focus on skills instead of passion if you want to build a great career. And so that was like a natural meeting of minds. And so we built that course which was really pop. And more recently we worked on a course together called Life of Focus, which obviously Cal Newport's best known for deep work and slow productivity and these sort of later books. And so obviously Life of Focus very much ties into his brand. But I mean, I think I have my own insights to provide there given that a lot of the sort of public facing projects I did are kind of like the, you know, requiring a lot of focus type of work. And so we work together on that one too. And I mean, I don't know, hopefully we're going to keep working together in the future. I mean, it's been a nice collaboration over these years.

That's great. Well, and again, big thanks me as proxy for your audience. Thank you for doing that because it's the rest of us that get to benefit from both of it. And you two guys together, I would imagine kind of just as like a little nuclear power plant or something. I can just picture it. So. So okay, well, good. Thank you. I just an itch that I wanted to scratch about that. I was so curious. So now I want to shift, if you don't mind, to do a little deeper dive into your new newest book. But before we do, and as I typically do on the show, I first want to share what some others have had to say about it. Barbara Oakley, author of A Mind for Numbers, said, Scott Young knocks it out of the park with Get Better at Anything. This concise guide will help no matter what you are learning or teaching. Cal said, the ability to effectively learn hard things is like a superpower. In this phenomenally wise book, Scott Young reveals exactly how to obtain it. Diego Forte, author of Building a Second Brain, said, Get Better at Anything is a masterclass in accelerated effective learning. Learning grounded in seeing how others are succeeding, experimenting with and testing new ideas in the real world, and most important, being open and receptive to the feedback that inevitably comes back. Almost everything we do depends upon learning new skills, new attitudes and new behaviors. This book is an indispensable guide to mastering that skill for a 21st century rocked by change and uncertainty and kind of small world wise. Two prior guests on the show. Brad Stulberg, author of Practice of Groundedness, said, full of fascinating insights and practical tips. Scott has written an excellent guide to getting better at getting better. And Derek Sivers, author of how to Live, said, by far the best book on learning available today. The best method by the leading expert, actionable, intriguing, inspiring. Read it now before learning more to be super effective. Holy smokes, Scott.

It's hard to follow that.

No kidding.

Thank you, everyone.

Right. Thanks for being on the show. Go buy the book.

No, I'm very grateful that these people said nice things about it.

Well, you know, and honestly, I mean, you know, because seriously, buddy, I have to agree. It's a solid, well researched piece. And, you know, I'm a PhD in psychology. And I mean, I know as we talked off Mike before, the whole, you know, just learning theory and. And all that, the stuff that you went through, I mean, I, you know, I spent a while, you know, like, just in the index of your book is like, yeah, that's, you know, it was. It was the greatest hits of, you know, the thinkers in that area. So do you. Do you see this as a natural progression or a next work built on ultralearning, or what kind of audience did you have in mind?

Yeah, well, I mean, again, I guess we got to go back to the scratching your own itch idea. I mean, I feel like I always do everything I do for myself first. And that's like. Sounds really narcissistic when you say it out loud, but it's more just that I feel like it's very easy to write in a kind of pandering way that, like, well, I wouldn't read X, but yeah, some, you know, those dummies will read this. So I don't like to do work like that. I like to do work that is the kind of thing I would have liked to have, that would have existed that, like, I could have read that would have helped me. And so one of the things that I found, I think, and you know, given your background in psychology, you're clearly aware of it. Like, learning as a discipline is pretty diffuse. There's a lot of different separate threads of inquiry. And often they kind of like, have even contradictory sort of messages, for sure, but they deal with totally different experiments, paradigms, kind of like research journals. And so synthesizing a picture of how people learn, synthesizing a picture of what things we can do to learn better, what are the obstacles to learning can be challenging. And I think for the average person, I mean, it's just difficult to. To integrate that. And so I kind of started with doing the research in this direction. It was sort of one of these things where, like, I started pulling on these threads, and then you just kind of. It keeps unraveling and raveling, raveling. So it took me a number of years to just read everything and then kind of like, okay, how can I sort of refactor this into something that someone could Actually like digest in a popular nonfiction book. And so to me, this book is just trying to give you these fundamental mental models for how, how learning works and what are the factors that influence it and how you can think about it. And in particular, what are some of the key kind of like leverage points, like, okay, well, this is an area where I can actually make changes and try to get improvements. And so that's sort of how I've organized the book into these broad three factors of seeing, doing and feedback. And then within each, I have kind of these maxims that highlight a particular area of research that I think is important with some, like, kind of key findings and takeaways. So that was sort of the. The idea was just that I wanted to write a guide that, you know, for someone who's maybe not going to read through all the textbooks and monographs and random psychologies, meta analyses like, like I did over the last four years, you know, someone who's just like, okay, just tell me the synopsis. I wanted to try to provide that. And, and so I don't know, hopefully, hopefully the people who are reading it will, Will agree that I did a good job.

Yeah. And I have to take a quick side note here. It just struck me with what you did with Ultralearning with your computer science, MIT degree proxy kind of thing. I think now you should submit this as your. I'm not sure what university would be best with it, but as your proxy for a dissertation, because the work and the research you went through, it is, you know, it certainly qualifies for that.

So, I mean, it's very much, it's very much aimed at a, like, a popular audience, though. I think I like. You know, one of the things that I have a little bit of a difficult time with academia is that, you know, often the questions that drive academic research are not the questions that drive popular interest in these things. So there is this issue of translation. So I don't really see my role as being like, you know, akin to a researcher, even someone who's doing even, let's say a literature review of kind of a space, but being more someone who is going to try to like, okay, but what does this mean for someone who is trying to learn or trying to teach or in that kind of setting. And I've always tried to have one foot grounded in that kind of space. And it can be hard because I think, especially if you immerse yourself in this research, like, you get invested in these little, like, picadillos that, like, people get really, really like fussy over yo. Yeah, you know, you want to surface these sort debates and you know, you talk to researchers who are like calling each other names and stuff on the phone and you're like, oh, this is like this human story is so interesting. But like to other people they're like, okay, yes, but right, right. I don't understand that and I don't care. So, you know, you have to try to find a balance.

Yeah, I agree. And again, yeah, I didn't mean to spook anyone to say that this is a, you know, an academic tome or anything like that. I just meant from the aspect of the amount of serious work that you did in the background. And in medicine we have something called translational research where it sort of takes what SC science says and then makes it applicable in the real world. And you've kind of done what learning science, if you will, or psychological science and things that we can, you know, put put into play ourselves. So that might be a good kind of jumping off point. So the, the in the title or you know, the, the subtitle, in a sense, the 12 maximals. But before we get to those which I want to deconstruct with you, you talked about already the three factors. Could you maybe step us through the. The sea, do, feedback and what those are all about.

Yeah, so the basic ideas and these are sort of like what I take to be like the broadest factors that influence improvement. The first one is seeing, which is the idea that most of what we learn comes from other people. And so our ability to solve problems, to deal with challenges, depends critically on what we're able to learn from others. You know the old saying of like Newton saying, you know, if I could see further, it's because I stood on the shoulders of giants. I mean that is how all of us learn all of the time. We are a cultural species and being able to learn from other people is very important. And indeed the factors that either enable this or inhibit this can be major determinants of how much we learn. The second factor is do or practice or, you know, actually taking action. Because, you know, obviously just watching someone play tennis does not make you good at tennis. You need to actually do it yourself. But the kind of practice matters. And so one of the things that I thought was fascinating going through research is that there's all this detail about like, exactly what gets better with practice. What are the factors that influence how effective practice is. So there's, you know, in this, if you can think of like it's a dashboard and there's all these little dials that you can turn that will get you different results for your practice. There's a lot of those little knobs that if you turn them in different ways, you can get better results. And it's probably clear that in most pursuits they're not turned the right way, that we're doing things in ways that are going to eventually result in us either slowing down or they're going to have stumbles along the way. And then finally feedback. And feedback. I take in the broadest view, not just the teacher marking up your essay with a red pen, but feedback from the environment. So a snowboarder going down a mountain is getting feedback from the mountain itself. And that is a very important part of that skill. And so there's indeed lots of skills that are impossible to learn without the right feedback signals from the environment. And so understanding feedback, understanding how it gets incorporated into our work and, and even indeed drives our emotions with learning, I think is very important as well. So these three sort of topics are huge, but I think they are also good starting points for sort of cutting up this task of learning into some separate processes and, and procedures.

That sounds great. So you also, I like your, you, you have a good use of metaphor within the book too. You talk about problems are like mazes. Could you yeah, maybe like, you talk about the solving them with a three part approach. Could you maybe share some examples of what you mean by that?

Yeah, so I mean, I think it seems like a funny way to start a book on learning, but really if you think about it, all learning is problem solving. All learning is taking something that you don't know how to do and kind of finding a solution to solving that problem or that category of problem if they're, you know, it's multiple instances of the thing. And so we can obviously think about this in a sort of purely intellectual sense that when you are like, you know, to use a maze example, you know, figuring out which directions you have to take through the maze to get from your start to your end point. And so this, this sort of metaphor that problems are a search through a problem space was first proposed by Alan Newell and Herbert Simon in the 1970s in their groundbreaking book Human Problem Solving. And so they kind of created this theory which is still to this day, I think a major component of our understanding of how problem solving works is that there is this sort of search process of like trying to find the right way through the solution space. And it's easy to think of this as like a purely intellectual exercise. And indeed A lot of the early research was done with like, math puzzles and chess and things like that. But even if you take this concept a bit further, I mean, when you are learning, let's say, a sport like gymnastics, in a sense, that's what your body is doing, is that it is also trying to find a search space of like, all the, like, different parameters, of like, how your muscles are moving in order to do motion efficiently. Now, you might not be conscious of all of that, but this is the work that's going on. So really what learning is, is about, like, how do you fine tune the methods, the sort of parameters of whatever you're doing to efficiently sort of search through this space of possibilities. And one of the major kind of findings of this is that, like, the space of possibilities can be enormous. And so finding an efficient way to get through that becomes very, very important because you're not going to just be able to do it through trial and error.

Not enough hours in the day, so to speak.

No seconds in the age of the universe even.

Yeah, yeah. So then what's, what does one do? Does one take some prior experience or how, how do we do that?

Yeah, I mean, there's different methods that people use to solve problems, but one of the major ones that I think is important to surface is that for a lot of problems, what we do is we learn through observation. So we see other people, how they solve the problem, and we use that information to guide our own search. So sometimes that can be in learning a particular method for solving a problem. So, you know, someone at some point probably taught you how to do division and maybe you even learned the little, you know, the little long division thing. Maybe it's been a while since you've done it. But like, you learned the little long division algorithm. And so in this case, someone taught you a method and the method works all the time, and you don't need to do any search, you just have to apply this method that you learned. So I've taken, you know, what could have been a very difficult, you know, potentially vast space of possible ways you could consider this problem and reduce it down to just do this. And so that's one way that we learn, is we learn methods for dealing with problems, but a lot of problems don't actually have methods. And this is another thing that was a kind of surprising finding, you know, in this study of problem solving and algorithms and this kind of stuff, this idea that there are some problems, indeed most problems don't actually have a solution. Like, you can't give a Method to solve them reliably was sort of a surprise. This is something that a lot of mathematicians, a lot of great thinkers, thought we would find something like this. And it turns out that it's impossible. It can't actually exist. And so what we do instead is what is called heuristic search, which is where we use rules of thumb, or we use things that work most the time, but not all the time. And so a lot of our problem solving, what we're actually doing is sort of this kind of collection of these heuristics, collections of things that we've learned that work in certain circumstances. You know, so, you know, you have problems with your computer, you've probably learned the heuristic, okay, turn it off and turn it back on again. Right. Like, it doesn't work all the time, but it works quite a bit of the time. And then we have other sort of, like, you know, tools for, okay, well, we're going to make a little mental model of this sort of thing so we can figure out what. What the malfunction is. And so this idea is that a lot of this knowledge of heuristics, just like it is with methods, again, comes from other people. And so I started the book off with this chapter because first of all, we have to understand that learning is this search through a problem space of finding efficient ways to proceed through it. But then also because it is so tied to this idea of seeing, this idea of, you know, if we had to learn everything from scratch for ourselves, we would just be at a total loss. And there's indeed a whole anthropological literature on, like, how, you know, people who have been thrown into unfamiliar cultures or environments are just, like, miserably equipped to survive. And it's just because they don't have this accumulated knowledge of learning from other people, of, like, what to do to make. To make a life in that particular environment. And so I think this is a very important fact about the human brain and about, indeed, our sort of our being as human beings.

Yeah. And I think, you know, it's interesting, too, to kind of think that from a historical kind of perspective, too, like apprenticeships or, you know, the variety of kinds of things. I mean, it wasn't like universities existed, you know, from day one kind of a thing, you know, either. And I find just myself, like, I have actually a separate YouTube channel on learning, but it's all kind of around, you know, weird stuff. And it's. The weird stuff for me is like, motorcycle geeky nerdy stuff.

Yeah.

And it feels like when I'M doing some kind of repair, the better I can understand. Even if I'm totally unfamiliar with the wiring schema, the motor, whatever is up with it, you know, like, once I start to get that level of understanding of how it ticks, how it works, how whatever the problem is that it's not doing that I want to solve, to have it start doing, you know, also, you know, adds, you know, to that, that kind of aspect of it. And once you've done that a few times, even with different years of bikes, brands of bikes or whatever, it gets to that generalizability, that heuristic to say, well, if it worked like this on this, it may also, you know, work like this on this other, you know, bike or whatnot, or probably, you know, living or working circumstance, you know, with a co worker. You know, I had a boss that used to do this and yeah, that's kind of the same thing. So, you know, one of the things you talk about too is navigation in problem spaces. And you, you have some steps for that of framing the problem and, and picking and whatnot. Can you maybe share what those three steps are and kind of maybe an example of how that might work for people?

Yeah, I mean, the most important thing for solving a problem is choosing the right way to represent the problem. You know, even before Newell and Simon did their groundbreaking work on human problem solving, the Gestalt psychologists, they had this whole idea that, like, a lot of what we do when we are solving problems is just essentially just seeing it the right way. Like, it's perceptual almost. And, and so they're the, the right way to solve a lot of problems is you have to, like, think of them the right way. And so there's a whole line of research on these kind of like, insight problems where basically they don't require a lot of moves. You just have to see the problem in the correct way. Like, one of my favorite ones is the, the problem of trying to affix a candle to the wall. And you're given a candle and a box of tacks. And the key to it is to realize that the box is not only a container for the tax, but you can also use it as a platform. So you can use the tax to pin the box to the wallet and then put the candle on the box. And so this is one of those things that it's just, it requires looking at the problem the right way. Like, if you look at the box as just. Well, it's sort of like this kind of useless paraphernalia that's associated with the tax. You're like trying to tack the candle to the wall and it's breaking because it's whacked and you can't do it like that. Right. And so this idea of being able to see the problem the right way is very important. So it's not just about learning the moves that you have to do, although you have to do that as well. But you have to learn, like, what's the right paradigm? What's the right way of looking at this? So again, again, we go back to the original point I made. How do you get these ideas? Well, you mostly look at other people. How do they solve the problem? How do they think about the problem? What are the mental models they apply to it? And so as you gather more mental models, as you gather more ways of looking at it, you can have more opportunities, more ways to shift your thinking about solving the problem. So in your motorcycle example, I mean, as you see more and more motorcycles, you form this kind of abstract mental model of like, what is a motorcycle? And how do the different parts interact? And so if you encounter an unfamiliar motorcycle, you know, it has to kind of conform to this general sort of property. Like, maybe it's not exactly the same, but it's got to generally conform to that. So if it's like, oh, it's making a weird sound, well, it's got to be maybe a connection between this part and this part. Whereas for me, who knows nothing about motorcycles, and I go there, I mean, this is just a bunch of metal and wire and stuff, so I can't form that representation. And so I'm dealing with the much less helpful representation of here's just some physical stuff that's like, you know, mushed together and how can I get it to work? And in my case, the problem space is enormous. In your space, it's quite a bit smaller, and you can probably profitably find the right way to solve it pretty quickly. And really, this progression of undifferentiated mental model, which is just very generic, and you just try different things out and see what works to one which is highly specialized, has from past experience, from observation, from other people, this is the exact way to represent this problem. So you can minimize the number of moves you have to make to solve it. I mean, that is the progression of expertise in virtually all fields.

Like chess master. Master electrician.

Exactly.

You know, it makes me think of with your I love that candle example too. Yeah, there's something. I don't know if it would have come up. I can't remember, but from the book. But in my training too, we. We learned about things called perceptual sets. And it's where you think, you know, you sort of see this.

Einstelung. Yeah.

Yeah. Thank you.

Okay, thank you. So.

And that kind of aspect, and so that. But I think breaking outside of that and then that just makes me think about two other things. Just real quick to toss in. I'd like your reaction. Feedback to it. One is it also seems like the more. And this is, I'm not generalizing to everything, but just to learning, like, the more diversity you have of exposures to things, then perhaps the greater, you know, the quicker ability you have to develop your own heuristics about whatever your focus might be or your problem might be. And then also from just. I don't know if necessarily you think about this as learning or problem solving, but, you know, just the whole creative aspect of not having perceptual sets, having exposures, you know, to other kinds of things, you know, a lot of the things that you talk about in the book just also seem like they would be, you know, petri dish, fertile ground for. For creatives of, you know, from writers to artists to engineers. What, what are your thoughts about that in the context of learning?

Yeah, it's really interesting, like. Well, to go first to your, Your example of like, the perceptual set, which, you know, you have to use the German when you're referring to this, because all those gestalt. Yeah. Before the war or so it was einstelang and you know, this kind of stuff.

But.

But it means the same thing. But yeah, the, the idea was that essentially they, they. They felt like a. Sometimes skill can be a barrier to creative thinking. And if you think about this, this makes sense because a lot of what the brain is doing when you're acquiring expertise is taking stuff that you know how to do and making it so that you don't have to think about it while you're doing it. So think about driving a car, right? When you first start driving a car, you're like, okay, hands at 10 and 2 and like, where's the gear shifter? And, oh, you know, like, if you're driving a standard, you got to make sure you, like, release the clutch and like, all of these little things take a lot of your mental bandwidth. But as you continue to drive, you know, maybe you're even listening to, let's say, a podcast, and you don't even. You're thinking about the podcast and you're not thinking about where Your hands are, or how to press the gas or the brakes. And so this is a very beneficial effect of learning that you sort of routinize or you proceduralize some of these components of the skills. But the Gestalt psychologist also pointed out this can have a drawback, which is that you can reinforce a habitual way of doing things that preempts reflection. So I think his name was Alexander Luchins, he was one of these Gestalt psychologists. He did this sort of famous study where it was just algebra problems, but they were kind of conceptualizes that you're trying to get a certain amount of water in a, in a jug and you have like these containers of different volumes, right? And so this is just a paper problem. It wasn't actually giving people jugs to like pour water or something. But the idea was, okay, I'll give you some sets where the way that you solve the problem is you scoop two of the big one and then you remove one of the little one. And that's how you solve every single problem. You do like seven of these in a row, right? And then I'll give you a new problem and this one you can solve by just. And I'm going to get the exact details wrong, but instead of doing the two scoops and then remove one, you just have to pour one of the big ones. So it's much easier than that. But almost everyone does the two scoops and then the one out thing because of course they, they've done seven in a row, which. That's the way to solve it, right? So they don't think, okay, what is the what like from first principles? What's the best way to solve this problem? They do what they're doing. And so, I mean, in this example, it's a little silly, but it does show that there can be unintended consequences of doing a lot of practice for something in that if you practice something that ends up being the equivalent of the two jugs, remove one sort of procedure, you may end up getting really, really good at something that's not so efficient. And so this, this idea of this kind of tension between practice being necessary to get really good at things, but also practice sometimes having this unintended consequence of inhibiting your ability to learn the best method or to get really good at the best method shows up frequently in a lot of these studies. So, I mean, the psychologist Anders Erickson, he grounded his whole principle on deliberate practice on a version of this idea, which was that, you know, you do your job for 10, 1530 years. By a certain point. Most of the stuff you're doing is quite habitual. A lot of those things are habitual. Even if maybe when you learned it, it was the two jugs, one out equivalent procedure. I mean, the one I like to bring up to people, because this is a common example of this, is how many people, when they're typing on a keyboard, hunt and peck with two fingers or one finger, right? Now, when you started doing it, that was the only way you could do it. And so you learn to do it that way. And as you keep practicing, you get faster, you get more efficient. Maybe you're even pretty fast hunt and peck typist, right? But it's never going to be as fast as doing the, like, the way you were supposed to learn in typing school, right? Where you have your hands on the home row and you do the, you know, each finger. It can't be because you're, you're only using two fingers and you're looking at the keyboard. And so this, this sort of bottleneck can be an issue with, with mastery of difficult skills, where at a certain point all of your practice learning, sort of the inferior way of doing things can actually get in the way of creative thought. It can get in the way of, you know, reaching really high levels of performance. So there's this interesting tension about practice. And your idea about the perceptual set, I think, really illuminated that.

That's. Yeah. And, you know, I had a guest on the show a few months back, Eduardo Brassino, I don't know if you know of his work, but he talked about and has a book called the Performance Paradox. And that's exactly, you know, spot on with what you were just saying, you know, when practice really doesn't make perfect. And you, I think in your book, if you can share it with us, you had an example of, like, how the 19, 1940s jazz scene kind of relates to that. Share, share that with us.

Yeah. So, I mean, this is a sort of a related point, but there is a large literature on the role of variability in practice, producing more flexible performance. So a lot of these early experiments dealt with this problem, what they call contextual interference, which is a real nerdy term. It basically just means, basically just means that when you practice in a way where you're mixing up what you're practicing, you learn slower, but you learn better. And this was sort of seen as almost paradoxical in kind of early memory. Researchers thought this was sort of weird because interference was sort of widely seen as this, like, issue with Learning, like if you learn the word, you know, water in Spanish, for instance, and you like agua, and then you learn in French, it's, it's oh. And then you can mix them up, right? They can kind of interfere. So if I'm trying to speak Spanish, then maybe the French words popping into my head and I'm like, no, no, I don't want that one, I want the Spanish one. And then it's going to be harder for me to speak. This is interference. This is a kind of a well understood memory phenomenon. And so there was an idea that, well, if you learn to do, let's say one skill, you know, you learn to do like one particular type of tennis serve and then you learn to do a different skill, then there might be some interference. Like when you're about to do a forehand, you know, the part of your brain that knows how to do a backhand is firing and it's going to interfere. And this does happen as you try to learn both of those skills at the same time, there's a bit of interference. But the interesting thing is, is that if you practice in this way where you sort of alternating or you're mixing up the skills, you do learn more slowly, the individual techniques. But if you have to learn a new technique or you have to get tested after a longer period of time, your performance is often better. And so this was sort of seen as paradoxical. And so this idea that variability might improve. Flexible thinking. I thought like a great analogy for that was the role of improvisation in jazz musicians. I mean, this is a form of musical art where the idea of never repeating yourself or very rarely repeating yourself, or, you know, riffing on things you've passed down, but not doing it exactly the same way is really central to the craft. Which you can like contrast that with the, you know, classical pianist who's, you know, Beethoven hasn't changed for a few years, right? You're just doing it, you're doing it, you're putting your own spin on it, but the notes are the same, right? Whereas, you know, someone who's just standing up at a jazz club and they have to do something that's original. Each time puts a different kind of strain on the performance. And so it was very interesting. I had this great ethnology of jazz musicians by Paul Berliner called Thinking in Jazz. And he's a jazz musician himself and he spent a lot of time talking to, you know, some of the greats of the bebop and, you know, cool jazz era, like Miles Davis and Charlie Parker and all these. These people, and he. And he got to immerse himself in that world and see what were the things they were doing to learn to play jazz. And. And so this kind of mixing things up and having this variable practice was pretty clearly prominent in a lot of these different training techniques. And so I thought that was an interesting sort of parallel where, you know, obviously the jazz musicians aren't necessarily reading some, you know, dusty monograph on contextual interference, but they are doing this in their practice.

I love that. Well, and it just kind of speaks to maybe the generalizability of humans in general. You know, activity, culture, you know, whatever. These. These certain kinds of things might be somewhat hardwired into us no matter what the activities are that we're doing. This kind of makes me think about, too, all these paradoxes of things. But you also write about that to get better, oftentimes we need to unlearn what we already know. So can you talk about that philosophy and then maybe what are some unlearning tactics or where we might want to put those into action? Right.

Well, I mean, we've already sort of been talking about in this context of, like, if you spend a lot of time getting really good at kind of the wrong skill, then it can be hard to make changes. Now, it's funny we talk about unlearning because, you know, obviously this word comes up a lot, and I'm not sure if you're aware of it, but, like, it is kind of a controversial word within psychology because there's a lot of people who kind of hold to the view that you actually can't unlearn anything, that what you do when you're unlearning is you're creating a new memory that sort of suppresses the other one. And so it's kind of always there a little bit. So if you learn. You know, the example I use is Tiger woods, who sort of quite famously, or maybe shall I say infamously, decided to change his golf stroke when he was sort of at the peak of his. Of his professional game, which is not a move without risks. A lot of other professional golf players who tried to make sort of drastic changes to their. To their swing created a lot of problems for themselves. And the idea here is that when he learns a new swing, it's not like the old swing is getting deleted from his brain. It's just he has to learn a new pattern, and he has to reinforce it so that it becomes so habitual that it's more likely to override the other one. Even in moments of pressure and stress, which, which can be hard to do. So, I mean, I think the starting point is you want to try to avoid unlearning if possible. Like, if it is possible to learn the right way to do things from other people, that's going to put you in a better position. I don't want to make people overly paranoid about it because I think sometimes you can have this sort of paralysis almost of like, well, I better not do any practice until I find the absolute best method. Which is not the suggestion I'm making.

Gotcha.

But rather, I think if you're learning a skill, I think sometimes it does pay dividends to invest a little bit of time ahead of time to be like, what is the right way to learn this? What is the methods or approaches or ways of thinking it? Or like, pitfalls to avoid that are suggested by people who have a lot of experience in the craft. So, you know, if I was, I don't play piano, but if I was going to learn to play piano, the first thing I would do is like, I would go online and I would look at like, what do experienced piano teachers say? Okay, all the students do this and they have to like, coach them out of it. And so like, let's not make that happen in the beginning. And so that's a sort of a starting point. And then the other thing I think that you need to do is engage in this process of deliberate practice. So again, we talked about Carl Anders Ericsson and his original work that this was sort of central to expertise and world class performance was this ability to have focused practice sessions under the guidance of a coach or someone who can sort of stand back and say, this is what you need to work on and you're focusing your attention on some small aspect of the skill that you'd like to improve. And you're doing it under conditions of immediate feedback or feedback that's relatively prompt so that you can see whether or not you're doing it correctly. And his deliberate practice research, I mean, it got picked up by Malcolm Gladwell and his book Outliers. It kind of spawned this 10,000 hour rule. And I think the most common misconception about it is the idea that, well, it's just about doing something, just do something for 10,000 hours. And it was pretty clear from the research that that was very much not what he was saying. Like, he was not saying that you do something for 10,000 hours and you become world class. That it, it indeed the whole thrust of his research was like, why do so Many people who spend 10,000 hours doing something are pretty mediocre at it. And his explanation at least was that this quantity of this specific type of practice, which has been known for a long time to be central and improvement in kind of these sort of like well practiced domains like chess and athletics and music, that this, this type of practice he thought was really key. And indeed there's other examples he gives of where, you know, like he working with people under these kind of regimes and they make pretty large improvements over the kind of person who is, you know, not doing this kind of practice.

Gotcha. Yeah, I don't want to go into this rabbit hole for me, but I also, I just want to say that it just as you're saying that it just also brings to mind a lot of things in psychotherapy in particular, like cognitive behavioral therapy too. And part of it, you know, because I don't want to go into the. Because there's one thing about like having a traumatic experience or ptsd, but there's the emotional sequelae that, you know, that kind of, you know, is part and parcel of it. But you know, there are ways then like, because I used to work with kids and families and there's a lot of learning and unlearning, you know, that kind of had to be done in those kinds of sessions. So, you know, so when you like talked about, you know, getting a coach or something like that, it sort of reminded me of you know, the, just the whole psychotherapeutic processes as well and you know, people's motivations and understanding, etc. But one of the things also kind of, I think in this area was one of the things you wrote a lot about was the benefit of constraints. And I think again, maybe, you know, a lot of what we talk about or have been talking about, there are certain things that made at first blush seem like paradoxes or ironic or something. But so people think, well, you know, why, why would a constraint be beneficial to my learning? Could you unpack that for us and talk a little bit about, or give some examples of what that means?

Yeah, I mean, well, again, going back to our original picture of the kind of the power and drawback of practice is that if you spend a lot of time doing something, you make it more habitual and you make it bit more effortless. And so in a sense you're gonna, you're going to rely on that well learned procedure whenever you can rely on it. That's just sort of your, you know, your, your brain has this fantastic reward circuitry. You Know, with the basal ganglia and the dopamine centers where it's always trying to figure out, like, what's the most efficient move to make in this situation. And it's, it's doing these calculations to figure out, okay, do this, do this. And so because of that, it's very difficult. You know, you can kind of override it in, you know, with a lot of attentional effort. You can kind of like direct your attention to do something in a way that feels weird or feels hard. But, you know, obviously that's difficult to sustain. Another way of doing it is if you change your environment so that the way that you would do it is not an option, then you can force yourself to train this other habit pattern. So I'll give an example again, because we. I've already brought up touch typing as my kind of little trivial skill that people, that people learn. But I mean, when I was learning to touch type, the teachers, one of the ways that we would do this is they would tape a piece of paper on top of the keyboard, and you kind of slide your hands under this paper, so you're clicking and clacking, but there's like a piece of computer paper on top of your hands. And why do you do this? Well, because obviously the easiest way to know whether you're typing the right key is to look at it and see that the letter is right. However. However, this ingrains a different kind of motor pattern, at least in the beginning where you are looking at the key and then you're typing it in. Whereas if you have it covered, you have to retrieve the position from memory. Or rather, it's almost a kind of a muscle memory. Like it's a procedural skill of where the right key is. And so putting the paper over that kind of short circuits this sort of somewhat less efficient intermediate response of looking at the keys while you're learning it. And the answer is, you're just going to make more mistakes in the beginning. You're going to type the wrong keys, but eventually you're going to learn the right keys and you're going to do it much faster. And I mean, I learned this, I don't know about grade nine or 10. There was a typing class in school, and I remember taking it. And now I've gotten to the point where if someone asked me, like, okay, you know, what is like a password or something that maybe I type a lot, but I don't actually see on the screen, so I don't have another memory representation of this password of something I do A lot. Often the only way I can retrieve it is to, like, pretend like, my hands are on a keyboard and do the little motion. I get it, like, oh, it's this.

Yeah, yeah, yeah.

And that's so weird that, like. But it's because. Because I'm not seeing the password. Maybe I set it up, you know, years ago and I just type it. It's one of those things where, like, the actual memory of the password has sort of been kind of decayed or it's faded away, whereas all that's left is this really highly entrained procedural memory. So it is a kind of funny example, but, I mean, it does show how you can use constraints, in this case, the paper, to sort of guide you away from that right approach. And another example, I'll just give one more just for quick help. This is something that I have not personally done, but I heard about a friend who was in a school where they did, like, fairly elite level squash instruction. And one of the things they were trying to get them to do is to hit. Hit the ball in the center of the. Of the racket. Like, that was a big thing because, you know, the racket's pretty big, but you really want to aim to hit it only in the center. So what they did is they gave the kids these rackets that basically only have a center. They're very, very small heads, and that's what you got to play with. And, you know, it's very difficult to play with that, but it does train this particular skill of only hitting it in the center. And I mean, obviously it's. Your performance goes down, but it forces you to be more accurate with, like, swinging it exactly where the ball is instead of, you know, approximately where the ball is, which would get you, you know, a hit, but it wouldn't be as good in those circumstances. So there's lots of ways, I think, particularly with motor skills, with physical skills, where you want constraints, because a lot of the nuts and bolts performance of skill is not in your conscious awareness. Like, it's. It's easy to say, okay, you're doing this algebra problem, all right, yeah, but don't do that method because it's not going to work. And you're like, okay, I'll remember not to do that method. It's not going to work. But if you are, again, swinging a racket or something, you can't tell, okay, you know, left anterior belt. Do not. Do not contract at the, you know, 10th millisecond, because you're going to, you know, you can't do that. Right. So. So you need to actually modify the environment to like retrain those sort of unconscious motor programs or unconscious parts of the procedural skill that are very difficult to just adjust with introspection alone.

I think any of us that have ever watched a kung fu movie understand

exactly what you're talking about.

So yeah, I talked about metaphors, but one of the ones you don't like is thinking about the mind as a muscle. Tell us why.

Well, I don't know. This chapter has probably got me more flack from regular readers than any other chapter because it's like my one, I smuggled in one semi pessimistic chapter book. And so. But I love debating it so I included it anyways. But anyways this book started. One of the like sort of starting points for the research was I was really reading a lot of research on transfer because this idea, I had encountered it when I was doing research for Ultralearning. But there's this idea that when we learn skills they tend to be fairly specific. And so people who do a lot of practice in one thing tend not to show a lot of improvement in very unrelated domains. And this tension between, you know, learning being general and learning being specific and how general is it and this kind of thing really fascinated me. And so I spent like this enormous amount of time going through the research. And again there is a lot of open questions and a lot of like real naughty philosophical problems that you know, I of kind I can't resolve and have not been resolved. But one of the things that was very clear is that a lot of people operate with this mental model. And that's what it is. It's a, it's a picture of how the mind works, which is that we have these sort of broad faculties like reasoning and memory and you know, critical thinking is another one, problem solving is another one. And that if you do some kind of specific practice that will strengthen that just in the way that if you went to the gym and you did like, you know, pull ups or something, you were just strengthen your arms that that would help you with all sorts of other things. And this has a really long history in psychology. This is not a new problem, this is a very old one. But the research is almost, almost unequivocally against this idea. And so I thought this was an area where the popular perception really was at odds with what I think the vast majority of the research showed. And so my kind of like go to kind of paradigmatic case of like this is that model breaking down is the Idea of brain training. So brain training, I mean, I don't know if you like, I don't know whether they advertise anymore since the FTC kind of gave them a slap on the wrist. But there was these Lumosity ads for the longest time. And every time I go to any website, there would be like, you know, one of these blue brain icons and about how like, you could get their app and improve your cognitive abilities. And implicit in this is this idea that if you practice their little phone games or whatever they are, that is going to improve you in all the things that you really care about in the various other areas of your life. And so the, this sort of implicit idea that the mind was like a muscle was based on this. Now the FTC actually find them for this. And there's a lot of studies about brain training. And the vast majority, even among people who are kind of like optimistic about potentially getting brain training to work, the studies and the published research is pretty, pretty bad. Right? So I think. So this, this is like brain training, I think, is a dead end right there. You don't, don't like, do it if it's fun. Like do crossword puzzles if it's fun, do Sudoku because you like Sudoku. But don't have these expectations that this is going to like, stave off Alzheimer's or make you some kind of super genius. But then there's sort of other kind of, of sister ideas to this one, which is that, like, you know, I was in the, I was in the subway the other day. I think. No, no, I was at a community center and they had an advertisement for a chess club. And the motivation for the chess club. They very cleverly worded that chess is like correlated with all these good cognitive abilities. And essentially they're saying to parents who have some status anxiety about their children that enroll your kids in chess because then they'll be smarter and school and this kind of thing. And I would say again, you know, chess is a fine game. There's nothing wrong with learning it. I think, you know, there's. I definitely, I learned a lot of things that are not, you know, practical for a career. But there is this, again, this assumption that I'm going to go to chess, I'm going to spend all this time doing chess and it's going to make me better in these other things.

Yeah.

And I linked to a nice literature review which finds that, you know, while there is this kind of research bias of like, people who really like chess, chess tend to do these kind of Studies on whether chess improves performance. It turns out, it turns out, you know, if you're gonna have Scott here throwing cold water on your idea here, but it turns out that, like, the better the quality of the study, the lower the effect. And that like, you know, if you do a little bit of statistics, it's probably not that different from null findings. So I think again, I don't want to say it's, you can go too far in that direction. Say there's no transfer for anything. And like, and that's obviously false too, because, you know, people who get their PhD in physics go to work on Wall street, well, it turns out that the math is the same. So there's a sort of trivial explanation for why that works. And so I think, you know, to be a little helpful because I'm being very downer on all these ideas. People like to be a little helpful. I think a better metaphor, if we want to think about what, what does it mean to get really good at a broad set of skills is you got to think about your mind as being almost like a library. And if you have more, more books in it, more procedures, more ideas, more tools, then you are going to be more generally intelligent in all sorts of situations. And I personally think this explains the sort of common finding that additional years of education increase one's iq, because essentially what are you doing when you have a broad based education? You're giving people lots of different tools and each tool is specific. It does only help you with certain, certain kinds of problems. But if you give people tons and tons of tools, it turns out then you throw them out in the wild. In real life, there's just going to be some overlap with some of those tools. And so I don't want to be too pessimistic about it, but I do think that if people could move to the toolbox metaphor or the library metaphor and away from the muscle metaphor, they probably make better choices in their, in their own practice and education and certainly in their children's education, where a lot of this is very prevalent.

Hear, hear. Yeah, same thing. I mean, I just for myself, I mean, part of that too. Think, conceptualize it in terms of curiosity, you know, and you sort of like never know. And I, there's people. It's not exactly coaching, but I always, I frequently tell people that no matter what experience you have had at what prior job or what prior training or what prior education, that oftentimes you never know when those things may combine and conspire to benefit you, you know, in the next project or the next, whatever it is that you find yourself dealing with. So I also, I want to talk about you. You talk about scaffolds and like the difficulty, the sweet spot in completion exercises like scaffolds. Could you talk a little bit about what that is?

Yeah. So this is another little interesting kind of tidbit of a much larger debate in research. But, but there is this tension between kind of this idea that you learn better through observing other people and you learn better through understanding something yourself. And so this has been a long standing kind of thread that's run through educational psychology. So there's like whole books where people kind of argue about the different parameters of it, but the basic idea, you can understand it in two ways. So one, we've already talked about this idea that most of what we know comes from other people. And certainly if you have to reinvent the wheel, you're not going to build very good wheels like our world. Our knowledge is very complicated. It's beyond the capacity of even the smartest person to reinvent even a small fraction of it. Right. We're very reliant on learning from other people. But on the other hand, the brain has these interesting mechanisms where if you, let's say, practice something without looking at it like, so I gave the example of the typing on the paper as a bit of an example. But. But another example could be if you try to remember something from memory rather than looking at it again. So they've done a lot of this in research on practicing retrieval. So retrieval, testing and this kind of thing. It turns out that your memory strengthens more when you practice remembering it than when you look at it again. So the average student in the library hall who's just like looking over her notes obsessively again and again before the exam, is actually studying inefficient. What she should do is, you know, she's read the notes, she should close them, get a blank piece of paper, try to write down as much as she can recall, and then go and check and see what she missed. That's a better process for remembering it. So clearly the active learning, the sort of having to dredge the information up from your mind has this mnemonic benefit. And indeed, trying to solve a problem yourself can have some benefit too, because it forces you to sort of like not just, oh, this is the solution, but to like, you know, do this process of like generating the mental model and being like, okay, what's wrong here? What do I have to fix? And what are the issues? And so this kind of active thinking, again, can be kind of suppressed. If you just sort of like, oh, you just follow this shortcut and that gives you the answer. And I don't understand why. And so there has been this sort of tension of like, how do you find the right balance between the two and the right answer? And this thing that seems most apparent to me from reading all of this research, from people who have conflicting viewpoints on this is that the difficulty really matters. So if you make a problem too hard and you can't find the right solution, that's going to be inefficient. But if you make it so easy that you are not having to involve yourself in active thinking, you're not actually having to, you know, retrieve memory, you're not actually having to do these things, that's also a disadvantage. And so this idea of finding the right sweet spot for a lot of skills seems to be very important for math, maximizing our improvement. And indeed, it seems like a more general problem that many of the subjects we want to learn are at the wrong level of difficulty. Many of the skills we want to approach are at the wrong level of difficulty for where we are. Either they're too hard, which is very frequent in the beginning, that you want to start learning something and the book you pick up is just too hard, or the, you know, you start learning a sport and like, the people you're playing against are too good and, you know, you need to actually work on simplifying things, getting more instruction, watching more demonstrations, you know, this kind of thing. And then there's also the opposite problem where it's too easy and you're relying too much on your old habits. You're not challenging yourself enough. So this, this fine tuning, this difficulty sweet spot, I think is a, it's a very central part of learning of, like, how do you get exactly the right difficulty so that you can avoid these sort of dual problems of things being too hard and things being too easy.

I like that. So one of the other things that I thought a little bit surprising, so maybe this is again where you need to, okay, take me by the hand and get the big crayon so I can learn. But you've also talked about that it's a problem that most don't train for mastery but for competence. Could you say more about that?

Maybe you could elaborate a little bit. Is this from a section of the book where

I think the issue, I mean, my kind of interpretation of it is that the, like, passing the test, so to speak, like getting through something. So I can demonstrate that I have competency in this. But indeed, you know, maybe, you know, a month later, I'm kind of fuzzy on, on, you know, what it was that I, you know, just passed this so that, you know, the, the maybe the insinuating of true learning versus maybe a superficiality to it, if that makes sense.

Right, right. Well, I, so I can think of a few different possible threads that this might refer to. I'm trying to think of exactly where I've talked about this before, but one idea I could talk about is related to Robert Bjork, who we sort of already talked a little bit about his research with the variable practice and also the retrieval. But he had this sort of idea that there ought to be a distinction between performance and learning. And so performance is what you can measure. So it's like giving someone the test and what was their score. Learning is the durable changes in your brain that result in this skill long term. And so one of the things that he notes is that there is often a tension that interventions can raise performance and actually make learning worse. And this is obviously a problem because if performance is the only thing that we see as educators or as students, we tend to, just given the choice, tend to do things that optimize performance. So we already talked about that in the context of variable performance practice. You know, you're, you're on the tennis court, you do your forehand, you do it 18 times in a row, then you do your backhand, you do it 18 times in a row. When I test you on your forehand after that, you do it 18 times in a row, you're going to have a better forehand than when you are mixing it up. So your performance is better. But if I test you a week later, the mixed up schedule tends to do a bit better, or it often does better. And if I give you a different shot, so it's like, okay, now we're going to do, I don't know, people who are listening here are going to realize the shallowness of my tennis knowledge. But like, we're going to do like a serve or something, which is a totally new kind of shot. Then it turns out that the mixed up practice schedule does better. So this is an area where there's a tension between performance as we can measure it immediately after some kind of intervention and learning, which is this sort of durable, you know, invisible effect. And so similarly, you know, another example would be if we are spacing out our learning. Right? So the classic student trap is that, you know, you study three days before the Exam, you study non stop, you just chug Red Bull and you don't get very much sleep. You study, study, study, study, study, study, study. You go into the exam room, you write it down, you get a good grade and then like one week later you forget everything. Yeah, and this is a well documented effect. I mean, cramming tends to result in very quick forgetting. And it's because if you study something a lot in a really short period of time, temporarily, these memory traces are elevated, they are very salient, it's very easy to access them. But over a longer period of time, it's much better. If you had sort of rationed it out and you had kind of studied each concept over, you know, you started studying at the beginning of the semester, let's say not just at the end, and then sort of dripped it out so that by the time you're reaching the exam, maybe you're studying a little bit more so you can get a bit better grade. But, but you've done much of your studying throughout the term. So that, that way the memory is a little bit fresher. So this is again another area where the student who's going into the classroom who's saying, I only want to get an A plus, I don't care about this topic at all. Well, she's probably going to cram, right? Because that is actually optimal for just passing the exam, even though it's like terrible for everything else. Whereas a student who's like, actually, I want to know this, I want this to be useful in my life, like I'm paying money to learn this, like I want to get an education is going to, at least in theory, more be biased towards this sort of mastery protocol. So I think there can be these tensions between what will drive performance and what will drive mastery. And we need to be cognizant of them because they seem to be illusions. They seem to be situations where if you ask people what works better, they tend not to give the correct answer. And so this is one place where, you know, we can be kind of seduced into using something that is performance enhancing but not learning enhancing.

Gotcha. And it might have also just been my vocabulary of kind of thinking, because when you say performance and I'm thinking competence, I could see competence and mastery as being seen as synonyms, but I get the distinction now. Are you good for a couple more questions?

Yeah, of course.

Good, good. A couple more things and I want to kind of shift gears a little bit. But one of the things that I enjoyed from the book was that you Talked about how stories can be better than advice. Could you talk about why that is?

Yeah. So this was an interesting kind of parallel because about 10 years ago, as I mentioned, kind of the very start, I did this course with Cal Newport called Top Performer. And, you know, I was not aware of the research that I cite in this particular book. So this is just sort of an interesting case of parallelism. But we had all these students in the course, and one of the things we were trying to do is get people to engage in some kind of deliberate practice on a skill that would improve their career. And when we did these, like, little tiny pilot cohorts where we're working with small students to see how this advice actually plays out, one of the findings was that people would pick skills that just, I mean, at least to Cal and I, from a distance, seem to be like, not skills that were like, super relevant to improving their career and the ways that they profess to want to improve their career. Okay, and, and so we decided, okay, you know what we need to do? We need to get people to do research. So before you figure out what skill you got to do, you got to actually, like, ask around people who are proximal to you in your career. So they should be just maybe two to three steps ahead of you. What are they actually doing? What did they, you know, what do they suggest? Okay, so then we get to the second iteration. We get people say, okay, go and find these people and do a little interview and, you know, see what you should be working on, gather this information, this intelligence. And then we ran into a second problem, is that when people ask for advice, they get terrible advice. And so they would be like, let's say you're an architect, right? And you're, you know, you're just, you just graduated, you just got your master's and you're going to an architecture firm and you talk to someone who's like a senior architect. You know, like, they're like five, 10 years ahead of you, maybe in the, in the field. And you talk to them and you ask them, and like, people were reporting advice, they're saying things like, well, you know, you got to work hard and you got to be a team player and like, just the most generic clarity. And it's like, I can get any self help book. Tell me that. Right? I asked you because you're an architect, because you've been in this business, you've been in this company, like, you know, tons of specific things that the self help book doesn't know. And so the thing that we found was that the problem wasn't that the senior architect in this particular example doesn't know what would work and what doesn't work. They have that knowledge. Rather it's just so obvious to them that they often don't tell us to the other people, right, the person asking and because they frame the question of like, well, what would you do if you were me? Are these, these like super generic terms? It just naturally suggests a generic answer. You know, like if I can use like the Chat GPT example, it's like if you ask it like a really generic question and it gives you this kind of boilerplate, but you ask it like a hyper specific question with like the correct terminology, suddenly it's really smart and it gives you like the correct answer. So it's a similar kind of thing here that, that if you ask this kind of bad question, you're going to get a bad answer. And so what we coached people instead was to do what we called a journalistic interview where the focus wasn't to ask for advice at all. Instead it was just to say, ask this person what they did in their career, like walk them through from kind of where you are now to where they are now. So just sort of say like, okay, so you worked here and you worked on this project and then you met so and so and then you transitioned to this company and all those kinds of things. And in doing so, they often surface the actual advice you need. They surface. These were the key decisions and this is why I made those decisions. And so this was a sort of a long standing idea that we had kind of learned from practical experience. So it was very interesting when I was reading this, this book on cognitive task analysis, which is this sort of tool in the psychologist toolkit for like interviewing experts and figuring out what the mental models and knowledge bases and things like that that they're using to make decisions. So they kind of came to the same conclusion that don't ask people like just okay for advice or don't ask people for what this sort of, you know, this is how you're doing this particular problem. Instead get them to walk you through what they're doing or solve a problem in front of you. And this puts them in the right mindset so that now they're surfacing this stuff that is obvious to them, but it's not obvious to you. And in the cognitive task analysts job description, I mean that's what they're trying to do. They're trying to surface the stuff that is really obvious to the expert. Not just the soapbox beliefs that they'll often espouse if you ask them what people should be doing or this kind of thing.

Right. Because I mean, it's just sort of become so ingrained in their common experience or their DNA that it just doesn't, it seems so ridiculous to have to even say to somebody, absolutely. Gotcha. Well, well, I'm going to ask from a personal question here, more so about me than you. I'll get to your questions in a second. But what's the impact, in your opinion of age on learning since I'm kind of hitting the upper bounds here?

Well, you know, it's interesting. So this is a question I get asked a lot. And several years ago I did a little kind of mini deep dive looking at a lot of the research on aging and cognition. And I mean, I'm summarizing at a very qualitative level. So I think if you go, I think if you go to my website and you look or you just Google how does age change how you learn? Scott H. Young or something like that, you'll find this article and I have links to the research. So you can kind of, if you're, if you're interested in my, you know, less fuzzy summary right now, you can, you can dig into that. But the finding that I got from it was that there is a decline. So certainly it seems like fluid intelligence, which is this construct that we often associate with like being able to solve new problems that don't rely on a lot of experience relatively quickly. This tends to peak in early adulthood. Crystallized intelligence often peaks younger. And crystallized intelligence is more a function of like how much knowledge you have. Crystallized intelligence often peaks as well, but it is a much slower decline. And indeed I suspect that the reason it declines at all is just because culturally speaking, the average adult kind of shifts from a learning mode to a doing their job mode and so they stop acquiring new knowledge. Whereas I think if you were, you know, had a kind of scholarly bent and you continued to learn, your crystallized knowledge would probably go up. That's my, that's my non evidence based theory of that. But, but if you look at the older, older age, there does seem to be a drop off and it seems to have a very wide variance, which seems to make sense if you view the idea that there's, there's people who are getting some amount of dementia or some kind of cognitive affliction in their later age, which is severely kind of pulling down the average. So it seems like there's plenty of People who are in their 80s and 90s and are, you know, almost as sharp as they were when they were in their 50s and 60s. And there's other people that, you know, they have regressed tremendously. And again, you know, I was very down on brain training, which is obviously one of those things where, you know, people like to point it as potentially helpful for people if they're worried about age related cognitive decline. Again, I view the right antidote to that viewpoint is learn broadly because, you know, we want to have the cognitive reserve of having lots of tools in our toolkit, even if some of them are getting a bit rusty. But if I were to say, you know, what would be from the evidence, to me, seems like the best possible thing that you could do to stave it off is keep your body healthy. Because everything we know about the brains related, like cognitive decline, is that, well, the brain is an organ of the body and it's supplied by the vasculature and blood vessels and this kind of stuff. So the same things that would make your liver sick or your heart sick in many ways are often influencing brain health as well. And so, so I would say, you know, if you want to train your brain, probably the best thing to do is to, you know, go for a jog or do something like that and keep yourself in physical shape. So I think the, the overall picture, I think is that it is true that there's probably a bit higher levels of some of these measures when you're younger, particularly fluid intelligence, but it does not appear to be the case that like these large, steep declines are a necessary feature of aging. It seems to me that it's probably a mixture of sort of poor health that happens in older age, possibly also linked to just our general sedentary, you know, kind of unhealthy lifestyles that we have here. And then also it seems to be, I believe the crystallized intelligence is at least somewhat related to the idea that, you know, we stop our kind of intensive learning after university. And so I think if you wanted to be at least on a crystallized intelligence, this sort of vast reservoir of knowledge and skill, I think that could probably even go up. And indeed, if you look at the career trajectories of successful people in knowledge intensive domains like history and English literature and stuff, they often peak in their career quite late, which makes sense if you. The idea that, you know, this requires just a lot of learning over the lifespan.

Yeah, that's good. It gives me, gives me some hope. So, all right, so I'm going to Shift the gears. I know we're kind of running long on time, but I have a couple of things, if you don't mind. I'd like to talk maybe more on a personal level. But you talked about, like, your early collaborations with Cal. Who's influenced you or your work the most or served as a mentor for you? Scott.

Oh, man. Oh, that's hard. I've had so many people that, you know, it's hard to pick just one. It's a little bit like that, you know, what's your favorite book? And I was stammered that because it was just sort of like, oh, my God. Oh, my God. How do you pick favorite?

Right, right.

So, I mean, there's been lots of people who've had an enormous influence on me. I think in this whole world of online writing, self experimentation, blogging, this kind of stuff, I can point to. Really early influence of mine was Steve Pavlina, because he was one of the, you know, kind of the people that showed me, okay, people can do this blogging thing online. And he was also really big on the kind of publicly doing these self experiments. And I just. I really gravitated toward that as a. As a medium of expression. Later, I would say that Josh Kaufman, who wrote the Personal mba, Benny Lewis, who had his fluent in three months projects, I mean, these were just people who were kind of in the milieu when I was doing some of these projects myself. And they were definitely inspirations for me. Cal Newport has been, you know, a mentor for many years. I mean, he was the guy who gave me the title Ultralearning. Like, I mean, I remember we were sitting down. I think we were filming one of the sessions of Top Performer. And we're sitting down, and he's like, okay, here's what you do. You're gonna write it. It's gonna be called this book. And, like, you know, and it was just. I mean, how many people get Cal Newport telling them, okay, this is exactly what you should write. It'll work out well, yeah. On camera. Well, yeah, I think it was. I think it was a pause, Jerry.

Okay.

There's no video record of it, but it was. It was just him kind of offhandedly drawing on his, you know, lifetime of his experience writing popular nonfiction books. I mean, I've also had, you know, lots of other mentors. I mean, Ramit Sethi was someone who was influential for me in the beginning of just, like, how do you. How do you turn it into, like, something you can actually live off of? Which is no small feat doing this Online. And then, yeah, I don't know, I'm missing lots of people, but there's just been so many people who have influenced me in this sort of professional space. And then intellectually there's so many people that. But I've relied on their work even when I've had either none or fairly sparse interactions with them. I mean, Anders Ericsson, I think I've had like one, maybe two phone calls with him before he passed away. And like, he's had an enormous influence on my work. The psychologist John Anderson, you know, his work in understanding skills and trying to synthesize a lot of research on skill acquisition has been really big. You know, I make a lot of reference to the psychologist John Sweller, Paul Kirchner. I mean, I don't know, just the list goes on. But so many people who have shaped my thinking around these topics.

That's a, that's a very nice highlight reel. So now, now, now to the From Ultra Learning to Ultra Personal. So I think since the last time you and I talked, you now are a dad to two children.

Yeah, I'm not sure when we would have talked. Maybe I would have already. My son would have already been born. I'm not sure. But yeah, so I have a four and a half year old and a one and a half year old.

Okay, well, maybe it was right, right around that time, then if my.

Maybe around that time.

So tell me, how does someone that does ultralearning, writes Wall Street Journal bestsellers, manage their time and two children?

Well, I mean, I gotta say, like, I think sometimes I come on these calls and people's like, you know, how do you do it? But I'm incredibly fortunate, you know, like, I've been able to create a career that's had a considerable amount of flexibility doing things that I actually like doing. And so when I think about myself, I think about just how lucky I am compared to the person who, you know, is working, let's say, a really demanding office job. And they have to be leaving out. Like, I can, I can wake up and I can, you know, sometimes I can spend an extra half an hour with my kids in the morning if my wife wants to take a shower or something like that before I come into the office. So it makes a big difference, I think, in terms of how it's affected my learning. You know, I think it's shifted the kinds of projects I pursue and what I work on. I was thinking initially that, you know, oh, well, I'm not going to have as much time. I'm not going to be able to do those things. And certainly I haven't had the time to do the really, really intensive projects that I used to do. But the funny thing is that I feel like it's so part of my personality now that even I wrote this last book. I did all the research while I had one kid, and then we had another one in the middle of writing the book. And it's just sort of funny, I think that I ended up reading a ton when I was doing research for this. So it was sort of a mini ultra learning project as well. And so I think the shift has really been. Yeah, I've been more focused on different kinds of projects, I think, like the learning languages and traveling the world or, you know, trying to get sort of some equivalent to a degree program. These were very much, I think, projects of my twenties. And now that I have the kind of family life, you know, I have a different kind of approach to things. You know, I'm drawn to different kinds of projects. And so, I don't know. We'll see. I mean, I always feel like you have to live in the season of your life. And so for me right now it's a different season than maybe when I wrote some of my earlier material. But. But that also has new opportunities as well. I mean, children are just such fantastic learning machines. Just to witness that, I think is something very special.

Yeah, you'll get to see it in practice, in vivo. So that's very fortunate. Well, listen, thank you for this time. What's next? What's on the horizon for you? Just the living in the moment and kind of seeing how things go. Obviously you're still promotion phase with get better at anything, but anything in particular to give a shout out to or.

Yeah, well, it's funny because, like, as we're recording this conversation, so I don't know when it will be published live, so it might already have begun. But I'm starting a new project which I'm calling Foundations. And the idea is that I want to spend a month out of the year coming up focusing on sort of 12 kind of areas or central sort of pillars of life, as you could call it, that are. That are an area where I want to do a deep dive into the research and I want to make some behavior changes for myself. And I'm also working with a group of students because I want to see how these ideas play out with other people as well. So this is sort of my new project that I'm embarking on and it's a fun one. Because it's applied. I mean, I started out doing learning projects where the thing I was learning about was not learning. And I've done so much of the latter that I'm excited to just sort of like switch from reading, you know, academic treaties about, you know, cognitive psychology to now I'm like reading about, you know, more practical stuff, but trying to apply a lot of the lessons I'd learned previously about learning and then also behavior change. And so this will be an interesting project, but as I said, you know, it's just in its infancy, so it's too early to say anything too specific about it.

Well, and so now I'm going to ask you a specific question anyway.

Okay, sure. All right.

Are you the guinea pig or the. The students? The guinea pig or who's in the lab coding?

Both. I mean, I think I'm definitely the guinea pig. So I've actually already started the project three months ago because we were going to create material that we were working on around it. And now I used to do these projects, sort of like write about them as exactly as they were happening. And now I actually have like a little bit of like half an editor that, you know, if we're making video, there's a guy who has to do the video. And so to be nice to those people and not make it a hellish year for them of being like, okay, you know, get this out by tomorrow. We've done it so that I've got this sort of three month window. So I am, I am more the guinea pig than the students. So each month I'm kind of figuring out things, and then after the month is done, I'm kind of solidifying my advice and then that's going to be for the students. But certainly the students who are joining me are also embarking on a bit of an experiment as well. I mean, I do think I'm not trying to do anything too radical in terms of advice or suggestions. I feel like really my strong suit has been trying to synthesize a consensus rather than trying to be the contrarian for a lot of things. But I feel like what is going to be the. The real. Where the rubber hits the road with this project is just sort of seeing, well, what are the actual difficulties? Because it's very easy to talk about this in hypothetical terms, but it'll be very interesting to see, you know, what are the sticking points? What are the things that. And you know, as we mentioned when we were working on the original Top Performer course, sometimes the thing you think is going to Be the problem is not the actual problem. And so I really, you know, working with people in courses has been one of the other things I've been very fortunate and privileged to do because you get to see a lot of the nuances that, I mean, again, they don't show up in an academic paper where someone did a very tightly controlled experiment. I mean, the actually working with people has been one of the highlights of my career. So I'm very excited about this project, which is probably when this is airing. It'll have recently begun. So if you check out my blog, there's probably going to be some updates about it.

Good. We'll put that in the show notes too. That is very cool. That's good. Well, we'll just consider this a scoop then. So, Scott, thanks for the time today. What are some of the best ways for listeners to learn more, connect, get your books, et cetera?

Yeah, so you can check out my website at, at scotthyoung.com S-O-T T H Y-O-U-N-COM and that has links to my books, blog, podcasts, newsletter, tons of free stuff there. And then also you can check out the book Get Better at Anything. And also my previous book, Ultra Learning. They're available Amazon, wherever you buy your books. Audible. If you're not tired of listening to me already, you can hear my voice for another few hours while I narrate the thing.

So that's very cool. Cool, that's good.

Was that a tough process, the narration? No, I love the narration. I mean, it's always fun because you work with like a director and they like, you know, tell you the right way to pronounce the thing that you wrote. I mean it in the nicest way.

You were kind of jamming on that German there, so.

Oh, oh, yeah, yeah. No, that's been. My joy is realizing that I have been mispronouncing foreign words because there's a lot of, like, obscure academic researchers names and so. Well, the joke with the director for this one was that there's an enormous amount of Dutch names. I didn't realize the Dutch. The Dutch have made such a contribution to psychology until we actually had to say their names. And then it's Jerome van Morenborg and Adrian de Groot and, you know, all these, you know, people, you have to like, get, get the right inflection. And I don't speak any Dutch, so that was a fun class.

Yeah, I have a hard enough time with English myself, so.

Yeah.

Yeah. Well, again, thank you so much for taking the time to be on. It's good to do a round two. And like I've said a couple of times before, I'm just going to say it again and winding up that the work that you do is really a gift to all of us that get to enjoy it and get to listen to your voice and get to read your work and it really just is such a benefit to us all. Thanks so much for being on.

Thanks for having me.

And as a reminder, listeners can read a summary of this episode and link links to the show notes via my LinkedIn Top Voice Companion article along with past guests as well. I hope you enjoyed this conversation as much as I have and I hope it will help you in your journey to living your life in full. Living A Life in Full is a production of Stout Media, a subsidiary subsidiary of Gordian Knot, LLC. Assistant producer Gracie Wong Music Dan O' Brien executive producer and host Dr. Chris Stout to learn more, stop by our website at lifeinfull for show notes and please recommend us to your friends and subscribe on your favorite platform. And as for the obligatory disclaimer, this podcast is for general information uses only and does not constitute the practices psychology, medicine, nutrition or other professional health care services, including the giving of medical or psychological advice. No doctor patient relationship is formed. Lastly, and perhaps most importantly, I take conflicts of interest seriously. For all of my disclosures as well as show notes, please see livingalifeinfull.org podcast and my LinkedIn profile. Thanks and until next time.