Hey, everybody. Welcome to non trivial. I'm your host, Sean McClure. Human society has always applied filters to select who should be in a particular group. Now, this is both evolutionary and required for good social dynamics, but we also apply filters institutionally, using systems of meritocracy to vet candidates both in academia and industry. I argue that these institutional filters are far too narrowly defined to account for the complexity and high dimensionality of human intelligence.
I argue that today's complex world suffers from such narrow filtering, elevating a kind of dumbness in society. What we need now more than ever are problem solving groups composed of diverse individuals, filtered not by standardized tests and whiteboard exams, but by their ability to contribute to collective problem solving. Let's get started. As we go through life, we often encounter filters. Filters in the sense of who's getting allowed, let's say, into a group and. Who is not, right?
We do this socially. We do this in terms of group dynamics. If we go to a party or. Some event, we're going to pick up. On body language and kind of social cues and different signals, and we're going. To gravitate towards some group and groups. And maybe not gravitate towards others. And we kind of filter people based. On different things, like similar interests, or maybe the way they look, or maybe whatever it is, maybe some of them are kind of subconscious, maybe other ones are more explicit.
But we're filtering all the time. We want our group of friends probably. Not to just be everybody or anybody. We want it to be people again with similar interests or people that we can relate to, people that maybe have. Similar goals to us, maybe people that motivate us socially. We're filtering all the time. And I think from an evolutionary standpoint, that's always been the case and that's needed.
It's very much part of social intelligence, people being able to aggregate into groups and to solve problems. We're always filtering, always filtering, always filtering. Certain people with certain people tend to aggregate and solve certain types of problems. And that's just the dynamics of society. We do that ourselves, and people are doing that to us.
And then when we think about that more kind of on an institutional level, whether that's the academic system or industry, right when we apply for jobs and we want to kind of move up in a world, we're being filtered that way too. Because obviously organizations don't just want anybody to walk through the door. They want certain people that are going to have the right skills and the right attitude, the right level of focus, or whatever it is, the education system. They want to move people up who.
Are dedicated to studying a particular subject. Matter and that hopefully have some passion. For it and that a range of. Other things, maybe have the capacity to. Teach it or tutor it or publish. Original research in that area or whatever it is, right? So we're always being filtered. And as we go through life and. Think about the skills that we want. To have or should have to help. Move us up through life, it's based on those filters, right?
We know that the institutions that we enter and that we want to be. A part of are going to be. Separating the wheat from the shaft, so to speak. We want to be part of the part that stays. Right? We want to be considered the skilled, the good, the appropriate candidates that are walking through the door so that we. Can keep elevating ourselves through those institutions. Right?
Again, whether that's academically speaking or something in industry, that's the attitudes we take on, the skills that we acquire. Maybe we're taking courses. Whatever it is we're learning, a lot of that effort is directed towards the filters that exist in society. Right? And what I want to talk about. Though, are those institutional filters, the societal filters that have kind of always been there, the evolutionary ones.
I mean, those exist for a reason, and they're largely good because people need to aggregate together to solve problems. Virtually all of human intelligence is really a social phenomenon, all right? It's not so much the individual. It's the fact that we get together in groups. And those social filters play a role in how people get together and operate. Among those social dynamics, those are kind of unchanging, I guess, or at least they change over a longer time span.
But the institutional ones are the ones that we're putting in place through policies. And through almost a bit of kind. Of social engineering, if you will, because we're actually saying, okay, we're going to set up this institution, and here's what we think smart is. Here's the system of meritocracy that we're. Putting in place, and this is what. Makes a good candidate, and this is what makes a bad candidate.
And anybody who's part of kind of the management level of these institutions has to make those kinds of decisions. So the question now is, are these good ones? Right? Again, from an evolutionary standpoint, those kind of are what they are. They change over a longer time span. But the ones that are put into place through our institutions, through policies, these. Are basically reflecting kind of the zeitgeist. Or the spirit of the day in terms of what we think smart is, right?
Like what is smart, what is good, what is appropriate? And that's where we can run into. A lot of potential problems, because who's. To say that that definition is particularly correct or good? Or maybe it was good 100 years ago? And if we're still kind of using. The same system of meritocracy today, is that appropriate? A lot of things change through technology. And through the culture even. And just whatever it is, right? The world changes.
And is what was considered smart 100 years ago, is that appropriate to consider. What is smart today. So I want to talk about the. Kind of institutional meritocracy filtering that we do in society and how I believe. I'm going to argue that it's really. Really inappropriate today based on where we find ourselves in terms of how we add value to the economy, the skills that actually produce value.
And I think it may have made sense kind of in the Industrial Revolution, the way we kind of defined meritocracy and what was smart and what was not smart, and how we filtered people and raised certain people up. But now in this world, we're kind of coming what I would consider more full circle in terms of the types. Of skills we're looking for.
Soft skills are far more important than they used to be, arguably more important even than the hard skills because so much is getting automated away with our. Technology and we're seeing the rise of. What artificial intelligence is able to do. And this has been true really for decades. If you look at successful people and the ones that really rise up, it's. Not because of some specific kind of. Narrowly defined type of knowledge.
It's more broad, it's more social, it's more organic, it's more analog, all that kind of stuff. So I think that. Well, let's just jump into it. Let's think about how institutions are filtering people today. And the two main examples would be academia and then industry. That's kind of the world of filtering, right? Academically students will get filtered based on standardized tests, right?
So if you do well in the exams, you're going to do well and then go on to have more presumably prosperity down the road. And if you don't, then you're kind of held back and maybe that kind of well, it does kind of dictate what you're able to do in the economy, right, what type of job you can get and all that. So there's the academic filtering and then there's what comes after academia, which are the institutions that we go get jobs in, right? So the software company that you're going.
To go work for, or maybe it's. The non governmental organization or whatever institution you're working for, they are also applying filters and what is a good candidate and what is not because you got. To get the job. And I think those filters are largely outdated because they are very, very narrowly defined, right? Narrowly defined in the sense that if you have to come up with an idea of what it means to be. Smart, well, what is that? Well, you're going to create these tests basically, right?
And you're going to start testing people's. Knowledge and you're going to maybe try. To create a situation on the page and say, okay, well, what's the problem? What's the problem? So obviously just kind of go through. The different courses you could take, right? So if we're focusing on academia, it would be like mathematics, right? So you'd have these different math problems. You'd have the word problem version of that.
You'd have equations, you'd have to kind of derive them and then you get the answer. It's black and white, yes or no. And then you get into things like physics, which kind of bridges obviously the real world with that mathematics. And then chemistry starts to get a little more conceptual Schwal but it's still based on a fair amount of physics and then biology above that which is much more kind of, let's say, memorization but a lot of concepts and there's a little bit of math there.
And then you got the social sciences. But whatever it is, in order to assess someone's knowledge or appropriateness or smartness. Quote, unquote it relates to kind of. You have to define that quite narrowly that we find ourselves in is not black and white like that. It just isn't. It's got all kinds of gray area. It's not a narrowly defined thing. There are very few, if anything, in. The real world that are truly black. And white like that. Right? There's so many factors to account for.
There's a broad spectrum of possibilities. There's the way the situation unfolds based on who's in the situation and what's going on. The number of variables far surpass anything you could capture on a piece of paper through an exam. So if we look at the way. Filtering happens in academia it is by. Definition an extremely, extremely narrow version of. What you would find in reality.
Now, during the Industrial Revolution where we were starting to really make machines and things were very deterministic and you could pull back the layers and see all the pieces bumped into each other, it kind of made sense to maybe define smart like this because it was a very kind of debugging world. Meaning if you were to go work for a job you were expected to kind of pull back the layers of the system and look at how it all causally adds up and then kind of debug it, right?
And so that kind of hyper focused, narrow, very well defined kind of knowledge was respected and rightfully kind of considered good. I mean, that was a good thing to have. If you had someone who came in and maybe they were like super creative and super passionate. They had all these ideas that might not lend itself that well to trying to peel back the layers on a machine and understand how the pieces are not working correctly, let's say. And that's not just for tangible machines.
I mean, even in the business organizations. Let'S say at the time maybe were a little bit more deterministic, a little more well defined. But as we go through life and as things get more and more automated we start to increase the complexity of the things around us. I would say that world is not really the world we are in anymore. And if you look at people over. The past few decades who are successful. They don't really follow any kind of well defined plan.
If you go to the business section of a bookstore, they're just constantly coming out with different so called recipes and everybody's got a different way, a different story that's never ending. So obviously there is no recipe, there is no way to do it. It's a very complex, real world situation. And this notion that there are narrowly defined skills that are going to dictate whether someone's appropriate for the job is just becoming less and less relevant, right?
We operate at a much higher level of abstraction now. We don't really operate in a world where you peel back the layers and debug and nitpick the things. I mean, even in computer programming, this is becoming less the case. It used to be all about debugging. All about deterministic code.
And that code is now becoming more of kind of just the scaffolding you put in place to house things like artificial intelligence, which work by more of kind of a constellation of algorithms in ways that we don't fully understand. It's much more black box, it's much more opaque. And so the skills that are needed are much softer. They're more human, they're more analog, they're more organic. And that's where we're headed, right?
We're kind of coming full circle on the skill sets of humanity because that's how we used to be, right? Arguably, it was much more organic and analog and interacting with people. And then we kind of had this industrial revolution where it became very technical. And very kind of Stem related. But now the pendulum is almost swinging back to more of this kind of organic analog, thanks to the technology that is becoming much more automated.
The skills that are important today are not really about super logical or super kind of deterministic or peeling back the layers and debugging the code, so to speak, or debugging the pieces. It's far more opaque and complex and human. Actually, even though the technology has progressed more, I would argue it's actually much more human. And so the reason this is a bit problematic is we kind of come. To the realization that we are filtering in a really bad way, right?
Academia is filtering based on very narrowly defined tasks, based on the way standardized tests work, right? The only way you could really put a piece of paper and mark in a black and white sense is if you really, really strip away the context and the complexity of real world situations and narrowly define things. Now, again, maybe 100 years ago or. Even 60 years ago or so or. Definitely industrial revolution that made a lot.
Of sense because of the things we were building and the way we were working. Although still, that was probably largely problematic because I still think the most successful people really weren't like that. Right? They often deviated from that kind of very narrowly defined, super logical, almost emotionalist path. They were far more organic. They were kind of had kind of the crazy ideas.
But now more than ever, as we operate at higher levels of abstraction and use technology where so much of that. Low level stuff is being automated, this. Is really a bad way to filter society. This being giving exams and narrowly defining tasks and assuming that's going to lead to the type of people that should enter the workforce, whether they're staying in academia or going to work in industry. And on the industrial side of things, we see the same thing.
I mean, if you think about a lot of the software companies today, still. The way that they try to vet. The programmers is by having these stupid whiteboard exams. And I say stupid because there'll be. Things like how does an array work and how does the first in last out kind of stuff. And if you have a stack, what happens to the memory or garbage collection and all these kind of low level things that just really don't have anything to do with computer programming anymore. I'm sorry, they don't.
It's just not what you're doing in computer programming anymore. I mean, there might be the OD person doing some very specific niche, C. Plus plus, but by and large people are using libraries. They're using rest APIs. These are these high level abstractions.
And now with AI around the corner, where so much of that code debugging is now being automated, whatever deterministic code you do right, is very much just kind of the scaffolding that's holding much more automation in place, whether that's through AI or managed services that are in the cloud and all this kind of stuff. So these whiteboard exams are, okay, we're. Going to test your knowledge in a very narrowly. It's this kind of regurgitated textbook, quite frankly, nonsense.
I mean, yes, I know that's still under the hood, but you're just not doing that kind of thing in software anymore. If you are, that's probably a sign that you're in a dying field or a dying part of the software industry. But this isn't just software, right? If you go for any job, just. About any industry doesn't know how else. To vet the candidates other than in. That kind of narrowly defined sense, similar to how you would do it in academia.
Now, I'd say it's a lot better in industry because at least in industry, you sit in front of the person and you have a bit of an organic conversation and you can pick up on that body language. And so that's such a critical part because the person has to enter the culture of your organization. And so you can kind of pick. On those more kind of timeless evolutionary filters that the humans have always employed. But there's still a lot of that. Kind of, okay, we're going to give you a test.
And even the personality, some organizations put these personality tests in place to try to place you into a bucket of the type of person and that's going to separate you either as being appropriate or not. Or maybe it kind of determines where in the workforce you are. And I think even organizations will do this even if you already have the job, if you're in the organization, they might try to place two different places. Everything is just so narrowly defined. We're stuck in this kind of old.
School paradigm of kind of standardized tests, and we know that there's this kind of sweeping distribution of human behavior, but it's only on, let's say, kind of the right side of the tail of that distribution that we think that's where the good stuff is, and we kind. Of want to separate the other stuff, right? So let's just do a quick recap. I said at the beginning it makes sense that we filter in society. We've been doing this all the time. We have to.
There's certain people that we want to be around and maybe other ones that we don't. We can't be friends with everybody. We can't just dilute our lifestyles across the entire population because we need to. Gravitate towards people that help us and. Social situations that are going to benefit the most people and all that kind of stuff. So we socially filter from an evolutionary. Standpoint, as we should, right? But then there's this kind of almost.
Social engineered side of things where the policies we put in place specifically the two examples in academia and in industry where we try to separate the wheat from the shaft and try to really get the right candidates into the institution. And the question is, are we doing that correctly? And arguably if it's always kind of been too narrow but in terms of meritocracy, you kind of have to come up with something. But I would argue that today it's. Really, really problematic and quite counter.
Those narrowly defined kind of tests that. We put people through to try to separate the good from the bad I. Would argue is actually elevating the wrong people. Now I think it's elevating the wrong people. It's looking for the wrong skills. It's putting people in positions of power. Who maybe shouldn't really be there because. The type of quote unquote smartness they. Have is kind of outdated. In fact, it's really outdated. It's too narrow.
It doesn't account for the complexity and the swirling mess of context that constitute real world situations. Right? People always act kind of surprised when somebody's really successful and it turns out they dropped out of university or it turns out that they have this kind of quirky personality or it turns out that their path doesn't look anything like you would have predicted. This is always the case. Always the case. I'm not saying they always dropped out. A lot of people don't.
But they always have this very circuitous, complex, nontrivial path towards success that doesn't look like anything that we were told that meritocracy, as today would suggest, is what success looks like, right? Like, if you think about the systems that we have in place and the way that we filter people, okay, well, that's the smart person. Those are the ones that are going to go on to do good things. We don't really see that a lot, right?
You see, not that people aren't coming through academia and aren't coming through the system, but they always have this kind. Of story or this path or lack. Of path that runs really very counter to how you might think it would have happened. And people kind of act surprised, but. I don't think it's surprising at all. I think that the filters that we put in place are not really good assessment of skill and of talent and all the more the case today.
So I think now it's becoming so problematic that we're actually filtering the wrong people. I think we're actually filtering genuine smartness out of the population, at least out of the population of people that kind of have the power and that are in the institutions and that are making decisions that affect people's lives. And I think that's kind of really the point, right?
The people that rise up in academia are making decisions that affect a lot of people's lives because that folds back into the meritocracy system and how people kind of are allowed in and not allowed in, and industry, who's getting the job, who can contribute to the economy, who can find contentment in their lives. The people that kind of affect people's lives like that are in positions of power, are being raised to those positions through very narrowly defined filters.
And I think that's highly problematic in past episodes. One thing I like to say is that nature uses the full distribution, right? So we understand that if you kind of think of that bell curve, the stupid contrived bell curve that almost exists nowhere in nature, but we pretend like it does, that bell curve is something that we use to standardize tests.
So we say, well, the average student is going to be at the peak, and then the really good students are going to be to the right of that and the poor students are going. To be to the left of that. But the problem with this is it assumes, it assumes that human intelligence works on the level of the individual, which it really doesn't. It works on the level of the group. It's not supposed to be an individual that is particularly smart or capable.
It's supposed to be a group of people that are smart and capable, a group of people that get together, that sit all across that spectrum or all across that distribution. There's people that are in the peak, there's people that are on the right and there's people that are on the left. And one isn't actually better than the other. Nature is tapping into all parts of the peak, all parts of the tails of that distribution. It's using the full spectrum.
We see this in complex systems, we see this in societies. If we take an intellectually honest look at how hard problems get solved, the entire distribution is used. So what it's more about is about getting people together into groups to solve the problem, not trying to filter society based on a thin slice through the right side tail of the distribution and saying, let's just elevate those people.
That's a type of social engineering that's highly problematic, that fragilizes systems, and it's not going to have good outcomes, particularly as we get more and more complex with the technologies that we build and the types of real world situations that we find ourselves in and the skills that we need people to have. We need to stop artificially taking a thin slice through that distribution and only elevating those people up. I think that's going to be very, very problematic going forward.
And it already has been, actually, quite frankly, for many decades. I think we're elevating a lot of stupidity, quite frankly. Not that the people are themselves stupid, but because we're only filtering a thin slice to that of that right. Nature is high dimensional, reality is high dimensional. We need the full spectrum. Okay, so what can we do about this? Well, I think we need to again, again. So let's just go back, right? I said we do need to filter. We've been doing it all the time.
We can't just let everybody through the door. It makes sense that there's some, hopefully, level of meritocracy to what we do. But then I said it's so narrowly defined because of the way that you have to kind of really dramatically lower the dimensionality of what you do when you put it on paper.
So when we do standardized tests, when we have these kind of stupid whiteboard exams for software companies, whatever the industry or company or organization is, as soon as you go to try to make things black and white, it's very artificial, it's very contrived, it's very sterile. It's stripped of the real world complexity. And that's just not how life works. So it's no surprise that we look at a lot of successful people.
They never seem to follow those kinds of paths and we need to get away from that. But the problem is, because we're doing that, we're elevating a lot of the. Wrong people in society, very narrowly defined. Kind of very low dimensional thinking. And I think that's going to continue to kind of damage or fragilize the systems that we put together, the organizations. It's too low dimensional. We need to tap into the full spectrum.
If we look at complex systems and we look at nature, that is how it happens. And so what can we do about it? Well, I think the filtering that we do at the institutional level through academia and through industry has to be more about groups. Are people going to be able to get together in groups and solve problems effectively? Don't just test the individual on narrowly defined tasks. Give them something real, a project, right?
More project based type learning which I know has been attempted in different areas, but more real world solution that has to be solved. And this calls into question whether or not we even need an institution. But if we do need an institution to filter, have actual projects, real problems that are being worked on in groups, it's not assessing so much the individual's capability other than that individual's capability to work effectively as a group, because that's really what it's about.
Regardless of where they sit on the spectrum, whether they're, like, hyper nerdy, hyper introverted, or maybe they're extroverted. Maybe they like detail, maybe they don't like detail. Maybe they're vocal, they're not vocal, whatever that personality trait is. Maybe they have really good memory, maybe their memory is not good but they're super analytical. Maybe yada yada yada there's all different kind of mixes and matches. The answer is not to narrowly define a particular type of intelligence.
It's just to step back holistically and say does that individual enter some group and in that group effectively help solve the problem? Right? And not even trying to say what is the role of that individual? Forget the role. Does their presence in the group improve or not improve the ability to solve the problem? Were they just part of a group that did solve the problem? And by solving a problem, we're not talking about some stupid low dimensional exam on a piece of paper.
We're talking about building something, building an actual solution that solves an actual problem. Something that is real world. Okay? So that's all I wanted to say in this episode. We know we got a filter, we got to have some kind of meritocracy. But we do this way too narrowly right now. And I think that's problematic because I think we're elevating a lot of stupidity, a lot of low dimensionality into positions of power, into positions that affect a lot of people's lives.
And I think that's problematic. It's going to cause a lot of problems down the road as we build more and more complex technologies and find ourselves in situations that benefit far more from organic analog, real world holistic, full spectrum thinking as opposed to the narrowly defined nonsense that we've been doing for. The last few hundred years, right? And I think the way that we do need to filter is think about just people in groups solving real problems, building real things.
Not paper exams, not black and white. Yes you got it right. Yes you got it. No you got it wrong. Not just low dimensional kind of black and white situation. Something that is built by a group. And either people are working in groups effectively or they not. Or they're not because that's. What's real. And that does not depend on where you sit in the spectrum of so called intelligence, whether you want to use the stupid bell curve or some other curve. We don't need the distributions.
We need to step back and appreciate that there is a full spectrum of behavior that people have and that they can all contribute and they're either willing. To or not form groups, build something. Real, and let that be the test for whether or not people should excel and find prosperity in society. That's it for this episode. Thanks so much for listening. If you'd like to support Nontrivial, you can go ahead and click on the Support the Show link that is found in the description of any episode.
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