Everyone welcome to nontrivial. I'm your host, Sean McClure. In this episode I'm going to talk about skill, specifically, how skill is not what you think it is. I'm going to take a look at our perception of skill and what I think is wrong with that perception. Specifically, how it's rooted in the idea that he deep foundation of knowledge must come before we can be considered skilled at something.
I'm going to take a look at where that perception comes from, how we are schooled into believing that a big foundation must precede our ability to Excel at something. I'm going to take a look at how that holds us back in our careers in our personal growth and then dive deep into how we go about changing that perspective. I'm going to frame skill as the ability to solve complex challenges. We're going to look at how that something that nature does all the time.
How is something that we as people are naturally good at doing and in doing so, hopefully demystify what skill is. So I think it's going to be really interesting episode. It's going to be some good deep conversation about complexity and abstraction and how problems are solved. And how to go about changing our perspective? and I think it's going to be overall really interesting, so I hope you enjoy it. Let's get started. So I want to start with our perception of skill. What do we think skill is?
Well, you know high level definition is pretty obvious. It's the ability to be good at what we do. If I'm creating something for the world, releasing it on a regular basis, then as other people observe what I've created, if they're getting inspired by it, you know, motivated by it, wanting to create their own things based off what they see, and believing that you know what they're observing is the result of someone who is obviously pretty good at what they do, then that is how we think of skill.
And in today's economy, you know we need more of that, right? We want to. We need to continually take on new skills, because that's our ability to contribute to the economy. To get jobs an in some sense be recognized. And ultimately, you know, feel fulfilled about what we do. Because when we build things when we create things and other people are recognizing them and be inspired by them, that makes us obviously feel really good.
And that, you know, kind of obviously motivates us to go forward and continue to create things. So scale is an important topic. And it's something that we want more of going forward. But we have a perception of that skill where we put it up on a pedestal and when we look at the skill of others, if we are not directly involved in that particular domain. So if I'm looking at, you know, a painter, do what they do, and I am myself. I'm not a painter, then I'm going to have a sense of awe.
About How they arrived or how they created the thing they created. And that's a good thing, but that sense of all you know, I might find that self. I might find that motivating for myself, and that might actually inspire me to take on painting. Or maybe it inspires me in a different way, unrelated to painting. But, you know, related to what I do, and so that sense of awe is not a bad thing. It's a good thing. It's motivating.
But there's something at the heart of that sense of awe that's got something wrong with it. And and I'd argue that it's based largely around our ignorance of what skill is if. If we are not skilled in a particular area and we see someone who's really good at it. You can almost get a bit of anxiety about it if you wanted to take on that scale yourself, because you're thinking of it as something that requires a lot of deep knowledge and years and years to get to that point.
And even though I'd really like to have that for myself. Uh, you know we're going to find the time to put that to put that kind of effort in. am I going to be able to understand those concepts? do I need to pay for a bunch? Of course is to get those concepts. What does that look like? And so that perception that skill requires? You know this big foundation before getting started can actually. Hold us back in a lot of ways, even to the point where we don't get started, so I want to.
I want to kind of dig deep into that perception. That sense of all that we have again in and of itself is not a bad thing. I think you should be inspired by things you look at, but you shouldn't be intimidated by it because the intimidation is not coming from the right place. It's not coming from a proper perspective and I want to be clear, this podcast is not a motivational pitch. I'm not trying to get you motivated now. If it does motivate you, that's great.
That's awesome, but I really just want to look at skill for what it is I don't want. You know the worst thing is to be held back in life because of an incorrect perception of something, right? You need to jump in, find out what it is, and then make that your baseline going forward. So I'm going to kind of set the scene here. Let's say we're walking into a museum. And we're going to observe a painting going back to that painting example.
And as we walk up to the painting, and it's a sailboat, and it's on an ocean, and it's very realistic looking. You have, you know, waves that are kind of overlapping with each other and say one of them crashes into the boat and splashes back. And so you've got this kind of frothy water coming back. And maybe you've got light. Partially, you know, getting transmitted through the wave, and so it's got this translucent quality to whatever. So it's a beautiful painting.
It's a nice replication of nature of a scene. It almost looks dynamic and. If I look at that, I'm thinking. That obviously takes a high degree of skill to achieve. Which is true, it does right if I'm not a painter of myself or specifically not involved in this type of painting. Uh, you know, not an expert in this type of painting, then I'm looking at that and saying that. That takes a lot of skill to achieve. And and that's obviously true, and the paint it could be could be anything.
Can be clouds. Could be water, could be pine needles in a forest. It could be something like CGI. Let's say I go to a theater and I watch a movie and we all know kind of what CGI looks like, right? It's very realistic, but we can still tell. Typically when a computer has been used to achieve something could be a large crowd of people in a movie and all the individuals in that crowd seems to be moving independently.
And if I don't know anything about computer graphics, I'm going to look at that and think. That must take a lot of skill to achieve, I mean. Because I know it's CGI, I'm thinking you know what are they doing? Are they programming all those individuals in the crowd? Independently, I mean how are those all like individual programs that somehow come together? How do you code something like that? You must have to be very very skilled to achieve that.
Maybe it's one of these animated movies like Shrek or something and they have a field of grass and you know there's some obviously computer animation being involved here, but it looks like there's millions of blades of grass and there again moving independently and they kind of solution the wind and it's very realistic, and if I'm not Privy to Privy to how computer graphics work, I'm going to look at that and buy my own ignorance.
Kind of put the skill that it must require to achieve that on a pedestal, right? Because because I don't know what goes into achieving that, it must take a deep, deep knowledge of programming and the understanding of you know how light hits a surface and how it refracts and Diffracts and wraps around and reflects and whatever it's doing, and the wind and you know the physics that are there. It looks amazing. It must take a large degree of skill. Let's use one more example.
Say you're on Twitter and somebody is solving math equations with ease and it looks amazing. Now you might not follow people who solve math equations on Twitter, but some people do. And if you're looking at someone doing this on Twitter or otherwise it, you know they're manipulating equations and their relating it to reality there, working it through, and then they get to some result and then they get to say something about the result. And man isn't that.
Isn't that cool like it must be so nice to be. That's killed in something like mathematics. A lot of us remember that from high school days and probably got sick of math and never touched it again. But wouldn't it be neat to be to be that good at something like math so? You know the painting, the CGI, the math? If it's something that you're not already good at, OK, and you're observing somebody, do it.
Then you have a sense of all about it and you kind of put that skill up on a pedestal and you might want to achieve that yourself. Man, I would love to paint. I would love to do computer graphics and make these little animated videos. I would love to whip through equations and then see you tease out some kind of interesting meeting about how that rigorous math relates to life. 'cause that would add triggered maybe to something I'm trying to defend whatever it is looking at.
Skill people, painters, sculptors, scientists, mathematicians. We have a sense of awe and admiration for what we look at, but it has that downside It can create a lot of anxiety and ultimately prevent us from getting started. There's a certain friction there in life when we look at the scale of other people, and it's based around this perception that it takes a lot of deep knowledge. To get to that point. So is that true? I mean, it seems to make sense when you here, but is that true?
Does it require a lot of deep knowledge? Up front. Before you can be considered skilled at something, let's go back to the painting. Let's say we found out who the artist was, and we asked if we could sit down with them and learn how they do what they do. Specifically can that artist. Show us their technique, their approach would how they created this specific painting. OK, I'm looking at this wave and it looks very realistic and it's got this translation quality to it.
I'm assuming that you have mastery over all the details that go into creating a wave, so I want to see you actually produce this thing well. If you sat down with them, you would realize that that idea that you have to have a lot of deep knowledge to create the thing even as a skilled individual. Is not true. And here's why you would realize that if you look at them, create that wave, you're going to find that they take their brush and they obviously dip it in whatever color they want.
Let's say its oil on canvas, and then they use these blunt irregular strokes to achieve the effect of a wave. In other words, it's not that they're coming in and they're getting every angle of the water, and they have some deep understanding of the behavior of how water moves and how the light hits it, and there's somehow, you know, articulating with their brush all the angles of the water. Shading the lighting. You know as if you were almost specifically drawing the wave detail by detail.
You know and then coloring it in and then producing this very realistic impression of water. That's not what they're doing at all. They're using these blunt or regular strokes that if you were to just look at it, don't look like they be painting something like a wave at all. It's got no detail to it. It's almost ad hoc in nature. You know they bring the brush to the campus they lifted off. Now they're skilled at what they're doing. They're wielding their tool with years of experience.
But it is not. With some awareness of all the details that must go into producing a wave in many ways. And here's the point. In many ways the artist is not aware themselves of how the wave is being arrived. Now I know you got to think about that for a second, maybe more than a second, 'cause it seems to kind of not make sense. Well, how could they not be aware? I mean obviously they know what they're Well, yes and no. They are. They are creating the impression of a wave.
In ways that they know how to, they've they've discovered through practice that these blunt or regular strokes, and these dabs in this kind of ad hoc ability to touch oil to canvas and lifted off at a certain rate, will produce what looks like a wave. It is not having knowledge of all the different facets of the water in the angles in the lighting and getting everything just right. It has this certain.
Unknown or uncertainty to it where the artist is not fully aware of why this technique leads to that result. And that's true. They know what they're doing with respect to the. Motions that they're using. They know that this motion leads to a wave, but if you ask them why that motion leads to a wave and less they try to really force a narrative, they're not going to be able to tell you. And that is really the point. Let's go to the CGI example.
Somebody who creates a crowd with computer animation. And all those individuals look like they are moving independently and actually they are moving independently to a great degree. There's this kind of stochastic or random nature to their movement. But the artist or the designer who went into program? Right, the the software to get these people moving the way they do, they don't know. Exactly how all those people are moving the way they are. They don't have control over all those details.
If you learn about computer graphics. You'll realize that there's this underlying physics engine that takes care. A lot of that motion, so they might have to, you know, draw our design what character looks like, and then they might have to create different versions of that character, and then they will map that object onto an underlying physics engine that will then kind of assign random motion to all those different individuals. And so.
And even in the design of the characters, you might say, well, they must have designed all the different costumes and get them all looking differently. Well, in some sense, yes. And sometimes no. They probably had kind of these templates to use to effectively map costumes onto an individual, but then they could apply again some kind of, you know.
Change to the to the design of the of the costume and that that could be replicated over 1000 times, and each of those thousand individuals has a slight change to the costume. It's not something that they were specifically in control of, and the motion of the individuals is not something that they were specifically in control of. Now again. Are they skilled?
Absolutely, but they're wielding their tools at a high level with a large degree of uncertainty, or unawareness if you will, of how all the individual details come together to produce the final product. They don't know exactly how the shadowing in the lighting is hitting all those individuals, because a lot of that is being taken care of at a higher level of abstraction with the tooling they know how to wield those tools, but just like the painter dabbing oil on a canvas in a somewhat.
Arbitrary fashion, not completely arbitrary, but in this kind of blunt, irregular stroke fashion, so too is the CGI expert working at a higher level. And. They know how to use the tools to produce the effect, but they don't exactly know how that effect is arrived. Let's go to the math example, which the last one from previously. If you take a look at a mathematician and their wielding, you know their ability to move through an equation.
And obviously it involves taking a number of steps until you get to a final result. Well, you might think that that mathematician has some detailed understanding about all the symbols in that equation relate to each other and what their meanings are and. You know, they know how to follow a set of steps to get to the result, and that's what it means to be a good mathematician. But no, that's not quite right. What they're doing is they're operating operating at a higher level of abstraction.
They're using what is effectively pattern recognition. They will notice subsections or pieces of the formula that they've seen before. Will say, well, those two summation signs leading to an integral. I've seen that before and I know that it could equate to this. There's an expression within the expression that I recognize, so I'm going to use that as my second step.
I'm going to make that piece equal this, and then there's another kind of sub formula within the formula that I recognize I'm going to make that equal this 'cause I recognize it now. I don't know if that's the way to do it, but that's what I'm going to take. Is my second And then I'm going to start to manipulate that piece and and going to recognize something else that pops out of that.
And there's this kind of, you know, pattern, recognition, manipulation, something pops out, pattern recognition, manipulation, something pops out on and on until you hopefully get to a solution. And so the the mathematician is skilled, but not because they have some detailed understanding about all the symbols are relating to each other there noticing things that occur at a higher level, the CGI practitioner is operating at a higher level. The painter is producing a wave by operating.
At a higher level where it does not require deep knowledge of how all the individual pieces must come together to produce the final result. And so that that, quote Unquote, Blunt, irregular strokes that use that example for the painter. But I'm going to use that. For the rest of this episode to mean any domain, CGI, math, sculpting, negotiation, public speaking.
If you are an expert at what you do and you can think about your own level of expertise and if you're being honest with yourself, you'll realize it's the same thing. You don't know. How all the pieces are coming together to produce what you produce, but you know how to wield your tools skillfully at a high level? To arrive at the result. And so this is what I'm trying. To convince you of is that skill is not having a knowledge of how all the pieces must come together.
In fact, it can't involve that. When we start talking about complexity and abstraction later on in the episode, you'll realize that it's actually not possible for anybody to have a truly deep fundamental understanding. Of what they do.
Uh, to produce to produce something that we would consider the result of skill, and it's important that we understand that because again, we're working towards a more proper perception of what skill is, and we're doing that because it has implications for our lives for the project, for the projects that we take on, and ultimately for the way that we contribute to the economy and feel good about what we do.
And so I just want to spend a little bit of time now thinking about where that wrong perception comes from. Why do we think the way we do about skill? Why do we tend to put it on a pedestal and believe that there's this big foundation of details that are required, that this large level of knowledge that we must obtain high level of knowledge that we must obtain before entering the real world and taking on our tasks? and I would argue that that largely comes from schooling.
I mean, if you think about it as we grow up from a very young age school, you know the whole idea of school is. It's this institution that we go to. It has curated the knowledge from, you know, technically, centuries of people building and creating things. And as that knowledge God created, it got curated inside these institutions and put into more or less a textbook format and then is delivered to students via teachers. And so by teaching just the fundamentals as isolated concepts.
You can you know, bit by bit, build up your knowledge about what goes into something with the idea that years later when you go to start that career you can then tackle those projects. 'cause you've got this nice big foundation of knowledge. You kind of got that language you can And you understand where things are coming from and that seems to make sense, right? I mean, why not have a foundation of knowledge prior to going in tackling things? Why not have that language down? Why not yet?
You know some ability to recognize what you face in the real world. But if you think about. How that goes for you after you graduate weather that's coming out of high school are coming out of Graduate School. Whatever level of education you have. When you go into the real world, you start building your career and you start tackling projects and you start acquiring or attempting to acquire new skills. This kind of this friction between.
This background that you supposedly have an the projects that you're tackling that are new IT doesn't always feel like you really have a foundation for it. When you take a new project. Might be the first one. When you get your first major job. You have to learn a new language. You have to learn to work with people. You've got these timelines that are that are not really like they are in school.
There's all kinds of things that pop into it, and in many ways you just don't really feel that prepared and the Delta between what you learn in school and what you face in the real world is actually quite large. and I think most people tend to relate to that or believe that that's the case. Now, if your job at a school is more research oriented, that might be less so than if your job is obviously more practical.
Uh, we actually maybe building engineering things that get used by consumers, but but I think most of us would feel that Delta between schooling in the real world. And if you think about it, you know why is there such a Delta? What is it that causes the friction between this idea that we're building a foundation and then the application of that supposed foundation going forward?
I would say it feels unnatural because there's something wrong about heading into a project with a big foundation before you do the thing. OK, so let's take some examples when your kid. Think about when you're young, because that's when you're doing things in a very natural fashion because you haven't been. You know, kind of indoctrinated for lack of a better word into saying. Well, here's how you go about do something when you're a kid. You just jump in and you do it.
Think about the way a child learns to speak. They spend years mumbling before they start speaking the language. They don't spend time learning about the language and the syntax and the grammar and how to piece. You know sentences together with words. They mumble right and they use words incorrectly. They don't pronounce them, but they keep going fearlessly.
They keep fearlessly mumbling their way through the language until they start to speak it and they speak it effectively at an expert level eventually, and so they were able to reach that expert level by mumbling their way through. And that mumbling is something we can probably all relate to. Think of anything you got really good at outside of school, you had to Mumble your way through, right? It could have been a programming language. It could have been painting. It could've been sculpting.
It could have been. You know some of those other examples negotiating public speaking, whatever it is, when you're starting, you might have some natural ability, but you kind of have to Mumble your way through at the beginning, right? And so that's what's natural. That's what works. We know that works. That's how we learned all the things we learned. We were, we were children. You know how to play, how to balance, how to ride bikes, skateboards, whatever it is.
Even drawing and things like that, I mean, we mumbled our way through so. I think it's not that surprising that there would be this kind of unnatural feeling you have. When you think about taking on a new skill, but part of you is believing that. You gotta have this big foundation before you get started. It kind of causes of friction. So what does that lead to ultimately? Well, if we think about taking on new projects, we're all familiar with making excuses to not get around to it right?
We don't have enough time is the most common. Another one might be, well, I don't have enough money right now. The course that I think I need to take before getting started is actually quite expensive. And so we can come up with all kinds of excuses. and I would say that those. Those excuses not only diminish our motivation and sometimes outright prevent us from getting started.
Their rooted in that wrong perception there, rooted in that idea largely that come that largely comes from schooling that you have to have this big foundation prior to getting started. And to be clear, I'm not in this episode. You know, calling down schooling, I'm not saying or schooling is all out wrong. I'm just looking at where that idea comes from that the foundation must precede the act. And and you actually have a saying that the foundation is the last thing you should build.
And that's not to say that you have no foundation going in. It's OK, you should do some reading. You should do some studying maybe before getting started, and I can even help motivate you. But the ultimate foundation, the ultimate picture of what you do and the concepts that are important in how you understand those concepts. That comes at the very end, whatever the very end is. You know whether that's the end of your career when you retire, or whether that's your deathbed or whatever.
It's the culmination of all your practical, you know, knowledge that was garnered through. Through building real things, that's that's the only time you can really look back and say that's my foundation.
So it's not like building a bridge is not like building a building is not like building something where you know you literally need a foundation before you start laying the bricks down in life with its complexity and the informational aspect of the things we create, the foundation in a lot of ways is the last thing you should build. So that wrong perception is at the heart of, you know, eventually not getting started and losing that motivation.
And again, this goes back to what I said at the beginning. The reason why I think it's important. I'm not trying to motivate you into here's how you go tackle projects in this, although that would be a nice byproduct of listening to this episode. The reason why I'm saying This is those few things as bad in life is not doing something because of a wrong perception.
You know you know it's like not getting to know someone because you thought they were someone they were not or not taking a chance in life because you know, for reasons that weren't really real because you never spent the time to think about what that thing was. You kind of just took whatever narrative was in your mind. And you applied that and that wrong perception prevented you from a lot of opportunity. I think that's a bit of a tragedy, so we want to we want to take a look at what skill is.
And change our perspective about it and that's what I want to move into now is is. So we've taken a look at the wrong. what I believe is a wrong perception of skill, even though it's OK to be motivated and to have a sense of on other peoples work we want to. There is something wrong with that. Awe is that it's based on this idea that it must take a lot of detailed knowledge and we saw that narrative probably comes to us from the way we were brought up through schooling.
You know, we were taught that a big foundation must precede the things we build. And ultimately, that kind of leads to that. You know, making excuses to never get started. There's that friction in a life and and we prevent ourselves from jumping into opportunities that we might otherwise do. and I mean, obviously, that's a problem. We want to be able to express ourselves. We want to have our natural talents come to bear on different things in life. We want to release things into the world.
We want to motivate. Other people ultimately make life better for the generations after us. So we want to create. There's nothing more natural than that, so we gotta change our perspective about what skill is to. I think to to really do that properly. So let's do that now. Let's take a look at how we reframe our perception of skill by thinking about skill as the ability to solve complex problems. Now that statement alone doesn't sound like I'm really doing anything.
I mean, you might already believe you think of skill as you know, solving nontrivial challenge is the ability to to arrive at a solution to something complex that sounds kind of obvious, but solving complex problems has a very distinct definition over solving simple problems, and this comes to us.
From complexity science and more specifically computational complexity, when we think about how complexity works in nature and in our lives, how complex problems are distinct from simple problems, how complex systems are distinct from simple systems, then complexity takes on a very specific definition, or at least much more specific than how we casually use that word in everyday life. So when I say reframe skill as the ability to solve something complex to solve complex problems.
I'm actually talking about something quite specific and I want to talk about that. Now I want to make sure that we understand what that word complexity means, what it means to solve a complex challenge versus a simple challenge, and then I'll bring that full circle around to how I think we should reframe skill, how we should understand skill. So let's do that.
Now, let's talk about the two types of problems that we could have in life or in a game, or or, you know, in a program that we're creating whatever it is. All problems can kind of fall under two categories and that simple. And complex, so we simple challenge. Simple problems will start with that. This is something that has ingredients that you start with and some end goal that you're trying to achieve and then in between that starting point and end point or a set of steps.
What is effectively a recipe to arrive at the end goal. And I'll give example in a second, but let's define a complex problem. To show the difference, a complex problem also has ingredients that you start with at the beginning. It has some end goal that you're trying to arrive at. And in between. Is unknown. There are no specific set of steps. There is no recipe to follow that would tell you how the different ingredients are starting. Pieces come together to arrive at the end goal.
So when you don't have a specific or explicit set of steps in between the beginning in the end, that's what we would call a complex problem, and they don't have obvious approaches to reach a solution. I'll give some examples in a bit, but let's go back to the simple. Uh, an example of a simple problem so we can understand that. So let's say you're baking a chocolate cake.
The baking of a chocolate cake would be an example of a simple problem, and the reason is if we go back to our definition, we have beginning ingredients, right? We've got the butter. The milk, we've got the sugar and flour, whatever goes in the Coco, all the ingredients that go into a chocolate cake. And then we have some end goal that we're trying to arrive at. Which is the chocolate cake, something that looks and tastes good. We can serve to other people so we know the end goal.
Well, there is a very well defined way to get there. There are a set of steps that you would follow to bake a chocolate cake, right? There's not a whole lot of uncertainty there. Now, of course you could still mess it up as many of us have done. We could burn the cake, something could go wrong. We could have a malfunction in the oven. We could not pay attention, but those would be examples of not following the recipe right?
If you actually follow the recipe and things go as plan then you will get a good tasting chocolate cake. At the end. There's different recipes with different types of chocolate cake, but to bake a chocolate cake is a simple problem. Use these ingredients. Follow these steps. Have this is your end result, you will reach that goal. A complex problem.
Is not like that you are going to start with simple ingredients or sorry a set of ingredients and you do know the thing that you're trying to achieve, but how you get there is unknown. They don't have solutions that you can pick apart and say, well, here's how it was arrived at. And we see examples of this all throughout nature. In fact, nature as a creative force is constantly solving.
Complex challenges it has, you know, species that are adapting to their environment that are finding resource is that are maybe cooperating with other members of the species and on and on. There's all kinds of examples throughout nature. In fact, nature itself is largely a successful success story in the ability to solve complex challenges. So let's look at some examples. We use the chocolate cake for the simple example. Let's look at some examples of nature solving complex problems.
A common example that pops out of what we now call complexity science would be Ant colonies. An Ant colony is obviously a group of ants and it solves complex challenges all the time. In fact, the most famous example is the ability to find the shortest path between two points. Now that might not sound particularly difficult, but let's paint the scene here. We have a complex environment, right?
A terrain that is, you know, it's got trees and branches and dirt, and it could be, you know, square meters or even square miles over a large area of land. And there is some starting point where the ants will begin, and then there is, you know, some food, maybe that they need to reach and it would make sense to find the shortest path between the beginning in the end because the shortest path short of the path.
Uh, you know the more resources you could move per unit time, presumably you can get more ants on that path through time and therefore move more food. Maybe bring more back to the Queen. However, that works, so the ability to find the shortest path is actually a real problem that pops up in nature, and something that ants are able to solve really well. The question is, how do they solve that problem? And if you were to try to solve that problem yourself by coming up with a specific recipe.
You'd find that for. For any reasonably sized problem, meaning if your train was large enough, if you had a lot a large number of possibilities that you could take as your path that it would not be obvious how to solve that problem. But ants do this all the time, so let's just kind of take a tour into how they do that. So ants release pheromones. This is a chemical that the other hands can smell or taste, and they use that. To signal to other ants you know where other ants have been.
So let's say we have thousands of ants in the colony and they are going to just trek out over the terrain and start doing their thing right there walking.
They're interacting the kind of bump into other ants, and they're presumably just looking for some food source, and beyond that, the ants don't really know what they're doing, they're just you know there is innate sense to go look for food and maybe bring it back to the Queen so they're out there and there's thousands of ants walking, and they're taking all kinds of different paths. And as they do that, they're giving office pheromone, because that's what I had to do.
They just naturally give office Fairmont. Well, overtime. The pheromones are going to, you know they're going to linger in the air for awhile. Then they're going to eventually evaporate. And that's true for all the ants that are doing that are walking across the train and taking different paths. Well, think about what would happen on the shortest path versus the longer paths. The shorter path is going to have a higher concentration of pheromone lingering in the air.
Right, because the shorter path is going to have more ants on it per unit time because they go back and forth, it's shorter. Presumably you know the space isn't going to be as large between different ants, and so there's more pheromone on the shorter path. It hasn't. It has the ability to accumulate in, linger for longer amounts of time.
And there's this kind of feedback that's happening if there's more ants on the shorter path and the ants are attracted to that pheromone, then more ants are taking the shortest path, because that's what they're attracted to. The pheromone concentration is higher than getting attracted, and so more and more and start to kind of accumulate on that shortest path.
Well, overtime, you're eventually going to have a situation where the ants have solved a complex problem they have as a group, being able to discover what the shortest path between two points is, or at least the shortest path out of all the ones that were attempted. And you could imagine if it's thousands and thousands of ants, they've attempted all kinds. Of paths. Now it's important to understand that no aunt knew what was going on.
No individual Ant is particularly intelligent for all intents and purposes there. Dumb right there, just following their own. A few local what you might call interaction rules. You know, they know to walk. They know that if they bump into a nap there going to slightly change the direction so they don't keep bumping into that, and they've got some innate sense to look for. Resource is some food that they can. Either the Queen can eat or whatever, other than those very few rules the rest.
Is just letting the system do what it does, it's just letting it go with the idea that it will converge on a good solution over time. And that's the difference between a complex problem in a simple problem, or more specifically a solution to a complex problem versus a solution to a simple problem. The solution to the simple problem of a chocolate cake, which to go look up the steps and follow them.
There's really nothing else to it if you follow the steps you are going to arrive at a chocolate cake, it's going to look at. It's going to taste good. It's going to be some deviation 'cause you know nature is what it is and things might get in the way and things might slightly malfunction. Maybe you don't pay attention, but if you follow the rules and things go as You're going to get a chocolate cake at the end. With the Ant example, it doesn't go like that.
All you have or a few simple rules at the beginning. Let's say you know, walk and interact and don't bump into much and keep going and look for food. Other than that, thousands of ants will be let loose and eventually it will converge on a solution. The solution being the shortest path out of all the ones that were attempted. So these are very distinct ways of going about solving a problem, and they're very distinct problems in and of themselves.
Baking a chocolate cake is very different than finding the shortest path between two points on a complex terrain, so. That Ant Colony Optimization in fact, that is something that inspires engineers to come up with algorithms to try to solve that problem, because that's really useful in other areas. I mean, we as humans can use the solution to the shortest path problem. You know, if we're designing an application that needs to find the shortest path, maybe it's for cab drivers or Uber drivers or.
Or maybe it's something you know. In a complex warehouse that needs to do inventory a certain way, whatever the problem is that something that's actually pretty useful. We rarely do it as well as the ants do it, but we were inspired by their ability to solve that problem, and that just goes to show how sophisticated you know nature is at solving challenges, and there are other examples.
Termites have this ability to make temperature controlled environments in ways that we humans wish we could do. They have these different holes that are facing different angles in a different sizes, and regardless of which way the wind comes in, it can. You maintain the termite mound can maintain a very stable temperature. Starlings or another common example, if you see those birds flying in the air, there's thousands of them even up to a million.
Apparently it's like a swirling mass of birds, and it looks thin in some areas and thick in other areas, and they're all moving in Unison. And that's actually a solution to a complex challenge of so. One theory goes that they're avoiding predators, and by basically aggregating together and becoming a super individual. Uh, the individuals themselves are more protected, so it's a solution to a complex problem.
So none of the individuals in the group really are aware of, you know, the society they're living in there, just aggregating together following simple rules, and in aggregate, coming up with a solution to what is truly a complex challenge so. What does that have to do? Let's bring that back around now because I had examples earlier. I was talking about. You know painting and CGI, you know solving math equations. You know babies mumbling in order to learn a language. How are these connected now?
You might already get a sense of how they might be connected, but let's do that explicitly because again, the purpose is to reframe skill in terms of the ability to solve complex challenges and and now that we've defined a complex challenge and how solutions are arrived at, you should have a sense that. It's not really about the details. The Ant Colony was not following. A specific recipe to arrive at the result. In fact, it's more appropriate to call that a meta recipe. A meta recipe?
OK, so meta. Is is a higher level of abstraction where you don't know the specific details internally to the system. You're only starting at the beginning and saying look, if we just follow these general rules then overtime. In aggregate, we should arrive at a good solution and that is the approach that nature uses. It doesn't use recipes that uses meta recipes, it does things at a meta level. Same of the termites.
Same with the starlings are countless other examples because the non trivial problem that truly complex problem is not. Privy to the kind of information that would allow you to follow a set of steps like you would with a chocolate cake. Baking a chocolate cake is not a difficult problem. Finding the shortest path between two points on a complex terrain is painting to go back to our original examples is also a complex problem.
More specifically, the ability to replicate a wave realistically, and this doesn't have to be realism mean. This could be abstract painting where you're trying to impress upon someone a certain feeling you know this could be sculpting in different times of art. And of course it's not just all right. This is in science. This is in technology. This is building. Here you know giving presentations you know whatever it is you are solving, something that has no obvious recipe.
And we know this because, you know, go to any business section, say in the bookstore, and these are all books that are trying to paint a narrative around how to be successful. But of course, there's never been an ultimate business book. They just keep coming out every year. And it's been like that for decades. And that's because nobody is ever going to get a recipe on how to do it, because the world is too complex. Everyone is different. Their situation is different.
There's there's countless interacting pieces that come together to make someone's to make someone's life to you know whatever it is. Whatever challenger trying to solve, you're not going to do it by having a set of steps. OK, it's very much a narrative fallacy to suggest that there is a recipe to solve a complex problem are recipe in the way that we defined it for chocolate cake. Right, if there is a recipe, it's a meta recipe.
It's a high level few set of rules that are let loose which overtime can converge towards a good solution. So I hope you understand that difference. I hope that I was not using too much jargon there, so. So let's talk about the painting. Let's go back to that example. So we said that the painter, although we have this perception that, well, they must know the different facets of the water and the texture and the shading and how the light interacts.
And I'm saying no, they really don't know that they're using his blunt or regular strokes. They're dabbing the oil under the canvas and what they're getting good at. And here's the point. You know, what is skill? What they're getting good at? Is there meta recipe?
OK, they're not getting good at the specific details of understanding how to reproduce a wave, what they're getting good at is the muscle memory involved in doing the blunt strokes, the Dabbing back and forth, how long to leave the stroke there, and there's a number of things. And they're very, very skilled at doing this, but the point is, this is what's killed is it is in some sense a meta recipe that will converge on the solution. Just as we don't know.
We don't know in an Ant colony optimization problem we don't know what the shortest path is exactly going to look like. We don't know where it's going to be. We don't even really know how the ants got there. We know at a high level that they have this pheromone that's given often they're attracted to the Pheromone, but other than that it's letting thousands of ants let loose on the problem and eventually converging to a solution that we don't exactly know how it arrives at it, right?
If we did, we would have programmed a specific recipe to find the shortest path, and we would have put that recipe in software we would've been using that software. Specifically, to get the result, but we don't. And This is why problems that are solved at a meta level always have slightly different results. We see this in, you know, in artificial intelligence as we use it today.
This kind of narrow version of AI, deep neural networks have a bunch of starting ingredients and they have an end goal that they want to reach to arrive at maybe it's face facial recognition, right? We want to use a deep learning neural network to recognize the face. Well, nobody knows exactly how the neural network arrives at that. And This is why. Because there is no recipe to recognize a face, there's only a meta recipe.
There's only a few high level rules that you can follow, and then you iterate those rules thousands and thousands of times if not millions, and you arrive at the solution of recognizing a face. If all goes well, but nobody can pull back that black box as we call it. And say here is how the neural network did it, and This is why I said earlier that. Not only do we not know the details when we solve complex problems, we cannot know the details.
If you know the details, then you're not solving something complex. That's not an opinion, that is a definition. There's no if ands or butts about that. If you were to know every step to arrive at the solution, then you are not in a. Any complex domain you are in a trivial simple domain, OK? So the painter. Is killed, they are very good at what they do, but what they're good at is a meta recipe. It is a high level, you know, ability to use the strokes in the d'absinthe, colorings and whatever.
It is a painter does that will arrive at a wave. If you ask a painter why that produces a wave, they will not tell you. It's not that they can't paint any kind of narrative. Excuse the pun, right? They could say, Well, you know this pressure seems to deep in the shading in this area, and if I lift it off quickly, I get almost a bit of a spray that comes off. And that's where the froth comes from.
But they can't break it down to exactly why this technique would lead to a wave, and in fact no two ways are going to look exactly the same either, and that's another example of only being able to operate at a high level. So that's what skill is. It's the ability to operate at a meta level to get good at a meta recipe to not have an understanding of what all those details are. OK, let's quickly run through those other examples. CGI right?
We said that you know the producing something that looks very detailed. It's got millions of blades of grass moving independently, and it you know it reacts to write. Sorry to the wind into the light in a way that looks very realistic, but the artist, the practitioner nobody on that team putting that movie together. Knows exactly how it arrives at that their operating at a meta level and things converge toward the solution. Even solving a math equation.
Right now that's a bit of a funny example, because in some sense there is an exact recipe to get to the result of a math equation, but think about how you're starting out. Think about somebody viewing an equation that they haven't actually seen before. Well, they don't know the set of steps to get to the solution. They're going to try to discover those set of steps. So even if there is an exact, you know chocolate cake style recipe to get to the result, they don't know.
It would be kind of like being a chef. That's coming up with a new recipe. Well, you're going to burn your new cake, and you're going to make all kinds of mistakes, and it's going to be a disaster until you discover what that recipe is. So at the beginning, it is a complex challenge because you don't know what is in between those starting ingredients. And the end using high levels of abstraction, you're using a kind of meta recipe that will eventually converge you towards a solution.
You know that last example I had earlier was the baby mumbling. OK, again the baby is not aware of the details. It doesn't know the syntax and the grammar. It doesn't have some academic style understanding of what makes a language. You don't learn languages by studying languages right? You can go study languages and that's interesting. And through that process you'll probably learn a lot that might help you eventually learn language, but to learn to speak an actual language.
Is achieved at by mumbling you need to go mumble you need too and mumbling is a meta recipe right? It is of course it is right. It's not doing nothing, it's going in with a few. You know I'm going to try to try to force my mouth to get the consonants and vowels sounds out and it's not going to be right and it's going to be dumb. For most of that time, right? Most of the paths attempted by the ants are incorrect.
Until it converges towards a solution, the mumbling will eventually converge towards your ability to speak a language. It's all the same thing. It's the ability to solve a complex problem. It's done at a meta level using a meta recipe. Only a few details are known, and overtime those converge towards a solution. So that idea of meta recipe is at the heart of how I want to reframe skill, how I want to change our perspective of skill. Because if you do that.
Then it very much goes against that narrative of having a big foundation prior to getting started on the task. You know, going back to that. That schooling narrative. Where will you have to take all these concepts in isolation? You have to know what those individual pieces are. And then if you really, really understand that you'll be able to blend those together to create something new and take on a skill.
Other than the simplest of problems, that's just simply not the case, and we know it's not the case. 'cause nowhere in Is that happening? Nowhere in computing science? Do you have examples where exact end to end recipes are leading to truly complex solutions or solutions to complex problems? It doesn't happen anywhere. For what we understand. It's absolutely impossible, and that's why I say.
The ability to solve complex problems can't be about the details and therefore your skill cannot be about all those details. OK, so a massive foundation prior to getting started is not needed and so let's bring that full circle. We think about, you know. If we have this new perception of skill. Then you need to take that into into your awe of work.
So if you're going into the museum and you're looking at that painting, or you're looking at that Professor Whip through an equation, you're looking at the CGI in a movie. Maybe that's a skill you want, and it's great to be inspired by it, but by no means is it out of reach. By no means is it something that requires a ton of detailed knowledge. It requires you getting better at the high level meta recipe through time, and I think that's a great message because it means we can all embrace.
Our projects we can all get started. We can all mumble our way towards being very proficient at what we do. That's not a motivational pitch. That's just reality. That is the right way to think about skill. and I just want to end off saying that there's nothing more human than creating. I believe that, right? Like that's what we're meant to do were meant to create things, bring something into the world before we die, make it better for the next generation.
It's the best way to learn and it's not just learning how to get better at what you do. You learn so much about life through the act of creating, right when you build something. Um? You learn philosophy right? Because you start teasing out universal truths about what works and what doesn't and how to get better at what you do. And of course, if we can inspire others with what we create, then that's just the best thing ever so. Thanks for listening. I hope you got something out of that.
This is the first episode of nontrivial I I'm happy to receive some feedback, you know. Did it make sense? Was it interesting topic? You can find me on Twitter, handle shaunee McClure sea, an underscore, A underscore McClure on a McClure jump on Twitter let me know what you think. You have ideas for other episodes, you know maybe that's something I can do. Happy to take input and thanks for listening so I'll see you next time.