This episode of the podcast features Dr. Zachary Stein, a philosopher of education working at the intersection of developmental psychology, psychometrics, and integral philosophy. Dr. Stein discusses the limitations of the IQ test, the nature of cognitive development, and how to think about human intelligence in a more complex way.
3:44 The difference between intelligence and IQ scores
10:21 What IQ scores measure
14:12 Generalized Intelligence
16:26 The “I” the “We” and the “it”
21:06 Does IQ Map to Success in Some Areas?
23:49 Problem Solving vs. Problem Finding
27:20 How the Brain Grows
33:56 AI and the Philosophy of Education
37:36 Developable Cognitive Capacity
40:09 Heritability and Genetics
42:56 Focus “Muscle”
45:51 Learning about Learning
49:54 Physiological Brain Development
56:45 Utopian vision of the Future
59:06 Explore Different States
1:03:00 Fear of Losing Unique, Specific Capacities by Exploring other Areas
1:05:47 Complex systems and Complicated systems
1:07:54 Intrinsic and Extrinsic Value
1:12:06 Recommendations for Understanding Capacities as a Baseline
Links from the Episode:
Daniel S.: Alright, welcome to the very first episode of the Neurohacker Collective podcast. We wanted to start a podcast where we could have these video dialogues, because we have such interesting and brilliant people in our network, who have various expertise in areas of neural science, cognitive enhancement, psychological development, et cetera. So, this is the first of these dialogues. My name is Daniel Schmachtenberger. I am heading up research and development here, and this is my first interview on this side of a podcast. So, forgive my clumsiness with it. And we are very excited to have the first conversation being with Dr. Zachary Stein. Zach is a very good friend, and really brilliant and innovative thinker.
He is philosopher of education, with a background and metatheory, integral theory, developmental psychology, psychometrics, did his work in education and psychometrics at Harvard with Howard Gardner, and that whole multiple lines of intelligence, advancing what we think of intelligence world, worked with Kurt Fischer on advanced developmental psychology, and then the integral philosophy on that, and has written books on the topic which we might get into a bit. In our topic today, is understanding what intelligence is, what IQ is, and EQ, and other kind of metrics related to intelligence. Where they’re good, where they’re not adequate. What we’re actually talking about when we talk about intelligence, what’s actually meaningful here? What are better ways of defining it and assessing it?
And then how much of it is fixed? How much is changeable? And what do we know about how to actually advance and develop what is actually worth developing here? So, this is a topic but I don’t know anyone who knows more about it the depth or the philosophy of than Zach. Zach, amongst other things, was the founder of a really fascinating organization called Lectica. A co-founder there, which is a method for advanced psychometric development across lots of lines. Looking at someone’s development, and different aspects of cognition. Their development in ethics, and their epistemology, and their moral reasoning, and how do we assess those things. How does the assessment affect the nature of what we’re assessing, all of that. So Zach, thank you for being here today with us.
Zachary Stein: I’m so excited Daniel. There’s like no conversation I’d rather be in. So, this is wonderful.
Daniel S.: So, intelligence. Let’s just dive right in. I think there are probably no scores that people have identified with as being important metrics of their capacity than IQ maybe. So, I’m curious for you to just start with the education of us. How did the IQ development, how did that score come about? What is it actually measure? How does that relate to the total picture of what intelligence is? What are multiple lines of intelligence? And how should we think about intelligence? I think everyone has a kind of intuitive sense of something that relates to processing speed and memory, and computational power, that is kind of in distinction to artistic inclination, or interpersonal inclination. So, start us off. Dive in. How should we think about intelligence? What are the problems with how we think about it?
Zachary Stein: Yeah, so it’s interesting that you start with the notion of score. Because that’s really one of the hearts of the issues here. Is that we have connected intelligence, which is something that goes on with the mind, with a particular instrument that’s been used to detect intelligence. So called, or supposedly detect intelligence for a very long time. So, I think one of the things we need to think about is the IQ test and disentangling that a little bit from our conceptions of intelligence, because we’ve reified and simplified, and I think drastically over simplified. And there’s many great histories of IQ testing. I really like Steven Jay Gould’s great work, called the mismeasure of man. And you see from reading this book that the IQ test was not an instrument of science, but an instrument of bureaucracy, and had to do with a quantitative, excuse me, the socio-political history of quantitative objectivity.
So this has to do with the use of numbers in the manipulation of people. And this is very important aspect of modernity and it was hugely liberating and things like public health. And census taking, and other areas where mathematics liberated us into this new realm of social engineering. But of course, every step forward is a dialectic to these kinds of developments. So, what you find with the IQ test, is that in France, turn-of-the-century, late 1800s, Benet was tasked by the French government to create a test that could be used to basically keep certain types of kids out of schools, and give them special attention. So, Benet with someone who specialized in a whole bunch of psychological fields, but especially the rehabilitation of the learning disabled. So, the IQ test was really just a very gross sorting mechanism comic created in France, to find those kids who needed special attention.
And Benet was very explicit, and Stephen Jay Gould gives this beautiful account of Benet’s dismay and concern at the reification of IQ. He thought this was just an instrument, just to use to sort kids in useful way, in the public interest. It’s not in any way a theory about the nature of the mind, or about the nature of intelligence. That whole idea that the IQ test measures this intelligent general intelligence, which is then genetically transmitted, that whole idea came from the Americans, who imported the IQ test at the beginning of the first world war. And at the same time, created the multiple choice test. And boom, we got large-scale industrial strengths standardized testing and that’s a gift of the World War One scramble, the preamble to World War One scramble in America.
And so, what was first just an instrument used to sort children to get them special attention with no psychological theory accompanied, that it was a-theoretical. Became an instrument that was standardized, that was used to sort adults and children, and that came loaded with theoretical baggage. About a general intelligence, and about its genetic heritability. And so there’s a long Legacy, which of course Gould out, of how this got tied into the Eugenics movement. I’m not going to get into that, because I think it’s a distraction. The key that I want to point out here, is that IQ as we think about it, has saturated the culture. But it’s not as theorized as a needs to be. I call it a mongrel concept, which is to say it’s a concept that supervenes on the actual realities of the mind.
It’s touching some things, it’s what Roy Bhaskar, the great meta theorist, the great philosopher, the late great, he called it a demi reality, which is like, it’s getting on something real, but it’s a small version of what’s real. This is the IQ. Sorry I like to compare to the GDP as a number the gross domestic product. Massively complex nationally and commonly. But again, and a scramble of the war effort to synthesize and to organize, give it one number, and put it on a linear trajectory, and use it to rank countries unilaterally, and make it the single most valuable thing. Easy thing to do with a number. But a clear over simplification. And so likewise, it’s not that you’re not getting at something, you’re getting at something, but it’s demi reality. It’s a small reality. And so, the IQ test became this, and it truncated on thinking about the nature of intelligence. And it became hypertrophy.
And a lot of people don’t realize that the IQ test was then prettied up, and complicated a little bit, taken by the educational testing service, and made into the SAT. And so, there’s this long continuous history of the use of these forms Of quote intelligence testing, not really for scientific research about intelligence, but for the organization of Educational Systems, and large scale Bureaucracies, like the army. Which was where the first large-scale standardized test was ever created, was for the Army Alpha One and Alpha Two, which were to sort the incoming millions into the American Army for the World War One. So that’s kind of the brief history of where this instrument came from. And so I’m not a big fan of the instrument itself. Now there’s been improvements to it. We have these newfangled [inaudible 00:09:18] And some problems have been solved with objectivity and reliability, which were the first big concerns.
So, I’m going to kind of skip that side piece. What I want to talk about, is the way that we’ve kind of addicted to a simplistic way of thinking about intelligence. And actually many people have an allergy to thinking about it in a more complex way. And, Howard Gardner, and Kurt Fischer who I studied with at Harvard, all they wanted to do was talk about it in a more complex way. And they have very little interest in anything like general intelligence, and thought it was actually a concept that was dangerous. Howard Gardner once said to me, that intelligence is the most political of all the psychological concepts. Because it becomes the meritocracies yardstick, and so yeah. So that’s a little bit of a preamble to like, okay, let’s liberate thinking about intelligence from the IQ. And started thinking about intelligence in a more complex way.
Daniel S.: When you say it that the concept has been very reified, obviously it has right? Even though it started out without a really clear philosophical Foundation. But let’s take groups like Mensa. Let’s take the way it’s been used in military, or any other kind of institution. Not just for rooting out who is not qualified, but also who is qualified for higher level capacities. You would think that if it didn’t map in some way to reality, the concept wouldn’t have withstood this much time. So, what is it measuring? And how does that correlate to reality? And then also, what does it not measuring? I would love to go in there a little bit.
Zachary Stein: Yeah, absolutely. And like I said, it is measuring something. Just like GDP is measuring something. So it’s not that it’s out of touch with reality, it’s an added supervening on reality in a way that’s not revealing as much as we could. So, it’s drastically over simplified. It’s kind of like taking a complex ecosystem, and giving it a single number, when in fact there are many things happening in the ecosystem which could be given different numbers. I’m so, and some institutional, text, it’s very valuable. For example, starting a huge army from scratch with a bunch of American farm boys, and you went to figure out who could potentially be a general, like in a very useful question mark to sort that. And so, this is important. But when you start thinking about, well then what does it measure?
Daniel S.: Yeah. Does that map to being a general well?
Zachary Stein: Right. And that’s what I’m saying. I’m not sure. This is a question, and then we have to go deeper and think, well then what the nature of the mind? Because, what does it measure means, well what’s there to measure? And so that’s where we need to tell the story about cognitive development, and about the nature of the mind, and how it grows, and what the nature of learning is, and what the nature of what we call intelligence actually is. Busting the demi reality to get to the actual reality of intelligence. So, my favorite phrase of Piaget, is the idea that intelligence is the grasp of consciousness. Which is to say, intelligence is consciousness operating the world. So, when we look at what intelligence is, what it has to do is, it’s these kind of skillful manipulation, or operation. First on the physical, then on representations, then on abstractions, then on principles and axioms.
Which is to say that, it’s one thing to move physical objects around in a skillful way, which humans have done since who-knows-how-long. Millions of years. But now, we are moving around principles and axioms of science in a skillful way. So, we are looking at a spectrum of cognitive complexity, that grows over time, and the Piaget that was kind of chastised in your introduction, the psychology course, that is not the actual Piaget. And, Kurt Fischer I think, it’s probably one of the most important psychologists of the 21st century, in part because he kept the Piaget in vision, of this hierarchical cognitive architecture that emerges over time.
And so, what we look at IQ is in many ways, a generalized, if you want to go there, capacity for building skills of this hierarchy. Now, what we are missing with a typical way of capturing some of those skills and saying, those are valuable, and those are intelligence, is that there’s a very wide array of skills, like a huge number of skills that you can build, and only some of those map with what we measure and IQ. So, there are many people who are radically skilled at building, really quickly, skills up this hierarchy of skill. They’re just not the kind of stuff that we measure in value on IQ tests so that’s one of the ways to slice this pie.
Daniel S.: The multiple lines of intelligence model.
Zachary Stein: Precisely. Multiple lines of intelligence. And so, if there’s anything like a generalized intelligence, it has to do with your basic capacity to build in any intelligence. And so, some people are gifted at building in mathematical intelligences, which is to say they can move up and down this hierarchy of complexity, and abstraction, they can do that in math really well. That’s measured on IQ tests. Other people can move up and down this abstraction and complexity, and let’s say at music or dance. And there are hierarchies of abstraction of dance, if you’ve seen a skilled answer, what you have is someone who’s supervening on a lot of possible moves, and building this trajectory towards an aesthetic experience. It’s very abstract thing to do. Very complex skill development. Not going to get that in an IQ test.
Also not valued in the Army and the places where IQ test find the people who do the work right. And the predictive validity I think is sketchy too. So, I think one of the myths we need to bust is that these people who do great on IQ tests actually do great in the world. This says we need to look into that, just like the SAT and the GRE. Have very minimal predictability. Minimal. There are studies that show the GRE to be negatively predictive of graduate school Success, which is to say you do good on the GRE, you actually do bad at writing a dissertation. It’s interesting. Like, I did terrible in these kinds of tests. I’m dyslexic, so this is a little personal.
I did pretty good at writing a dissertation. And so I think there’s this complicated kind of cluster of things that make us look at particular types of skill development in particular capacities, from particular lines, that’s what we value. That’s intelligence. We need to think more broadly, and in a kind of context we’re in globally, I think Hunter S. Thompson who said, when the going gets weird the weird turn pro. And this is the situation we’re in, and so we need to start looking at these much different forms of intelligence. But still thinking about growing them. And so, it becomes less about one form of intelligence, and more about many, and the functional fit, and the unique profile of the individual.
Daniel S.: Do you think it’s a worthwhile concept amongst the multiple lines of intelligence two separate ones that seem more generally abstract from more embodied? So, and this is just fitting a very rough intuition I think many people have. Say you take the mathematical line of development, and you take linguistic, and then maybe you take some orientation towards the physical sciences. And you cluster those things. And you say, computers could get fairly good at that, without simple grounding problem issues. Without sensorial grounding. But dance, and maybe certain kinds of interpersonal and naturalistic, and maybe even numinous or spiritual intelligences, kind of cluster differently. Maybe we say, we shouldn’t cluster them at all. They’re totally different things. But is there a clustering like that that makes any sense? And then is there something that we can think of as general intelligence within the more cognitive domains, that is accessible?
Zachary Stein: Yeah. I mean, that’s a great question. And this is one of the questions that drove the Neo-Piagetian audience. Because the Neo-Piagetians got to the point where they said, okay. We know there are still these levels, but it’s not like one big jump up. Many little jumps, in many different areas. Like a growing tree, many branches, like the darwinian metaphor. But it’s skill development. But they say, like you said, intuitively there’s clusters. I forget the physics and math, it doesn’t mean you’re going to be good at dance. But if you’re good and physics and math, you probably will be going to biology. So, there’s kind of near and far transfer problem, and that led to the issue of possible basic structures underlying the deeper branches in this tree of development. And so, Robbie Case, was another great Neo-Piagetian.
The University of Toronto [inaudible 00:18:05] Fisher, colleague, but he did some of the first dynamic systems modeling of these things. And I found some of these deep structures. It’s interesting, mathematical psychology. But what they showed, Robbie Case in particular, was that there was something like a deep structure to the mathematical domain. And it was a number line. And he had this incredibly simple study, where he showed if you introduced inner-city kids to the number line, before any other mathematics, which by the way they don’t get, because they don’t have calendars hanging on the wall. Their parents aren’t going talking to them about the nearest things, and they’re not playing Chutes and Ladders and a calm environment and stuff. When you show them this number line, they are doing as well in first grade as any of these kids from the suburbs, because I got the basic structure of the mathematical domain, which was in a simplified manner, the number line.
So, there are other similar basic structures let’s say, with perspective-taking that’s social. So, how Robbie case thought there was probably one for accounting mathematic spatiotemporal, and there’s probably one for interpersonal. And I think there’s also one for intrapersonal, which is to say your relationship to yourself. So, if I were to cluster the lines, I would cluster them around the classic big three, which would be the I, the we, and the it. And so, I think typically what we think of as intelligence is really facility with skill development in the domain of objective mathematical spatiotemporal realities. The kind of stuff that you push around in space and time. But there are other domains. There’s a whole cluster of domains that’s socio-ethical.
Daniel S.: But when you [crosstalk 00:19:37] abstraction from it. So, a Rubik’s Cube is moving around spatio-temporal physical thing is. But then as you move up into actual axioms, but axioms about say, physics. So, you’re now into a degree of abstraction that requires not relating with just sensorial reality, but that requires mapping to sensorial reality in a different way than the intra, or interpersonal domains will. So, that maps all the way up and abstractions of that kind?
Zachary Stein: Exactly. So imagine the tree comes up three branches go out. Each of those branches go all the way out to the axioms. And so, the spatiotemporal logical mathematical one starts with the kids learning gravity, and the ball bouncing, and all the things you do and as spatiotemporal world that PJ investigated. He mostly investigated that line. Investigated the emergence of things like the idea of causality. So, there’s the time before kids understand causality. And then they come to understand causality. Cause and effect, then you get hypothetical deductive reasoning. Which is still a higher, more abstract in that domain. But a whole other things happen in that other branch of the socio moral and ethical, and similarly with intra. But they’re all related as well. And, the branches inter-tangle at the higher levels. So, this is the view. Again, the IQ test that we think of, is over there. Sorry.
Daniel S.: We look at the objective branch, right? Mathematics, Sciences, Etc. How well does IQ map to actual proclivity there? So, say you have someone that solves Rubik’s Cubes very quickly. Well they actually be more likely to have novel developments in physics as a scientist, or might they just be great at puzzles that are already defined, but not creative intelligence within that domain? I’ve heard some stories of Niels Bohr being a very slow thinker, but having a slow process that led to profound originality. So, let’s talk about even within the realm of reasoning about objective reality. Different kinds of intelligence patterns.
Zachary Stein: Yeah, no. And this is one of the big questions in intelligence research, even those who transcended the IQ concept like Sternberg, and Gardener. There was discretion of, okay IQ does seem to predict something in some areas. But what’s interesting, and Howard wrote a book called Creative Minds, and basically this book is about this question. And it turns out that many scientists, like Einstein for example. Einstein’s reading Spinoza, and playing violin in a little philosophical reading group as a patent clerk before relativity. And then you look at other scientists who have far transfer away from the scientific domain, typically just some other area, which then gives inspiration back to the scientific domain. And this is one of the things were saying question mark too, as at the broader you are base, the healthier any of those branches become, and the more easy to transfer is.
So, you do, in a sense, can predict in a simple way, this guy’s going to be able to do those equations. And it’s got the simple kind of horsepower in the cognitive domain to do the equations, but is he going to be the innovative guy who comes up with totally new equations? Or, realizes those equations aren’t the equations you should be doing. So, that’s different than intelligence. So, creative problem finding is different than even creative problem-solving, let alone problem-solving that’s not creative. That’s routine. Which requires a lot of intelligence. Which is a whole class of problems. That are very difficult, but routine. And then, there are problems people don’t even know. So again, there’s a space of unexplored higher human potentials, and forms of creativity that I think our schooling hasn’t let us see, what happens when you take someone with a super-high mathematic like you, and teach them to meditate.
Daniel S.: You just defined a number of important concepts. Before we lose them, there’s some cross-training that you mentioned, which is important. But specifically, you define problem solving, and problem finding as fundamentally different kinds of problems. And it seems to me like, problem solving within an already existing problem domain, kind of maps to hill climbing. And problem finding maps to valley crossing, from a kind of evolutionary biology perspective, which Eric Weinstein says the first one is what we call excellent, the second is remarkable. Remarkable figures out new shit, excellent does a good job at predefined stuff. So, Rubik’s Cube is obviously problem solving. Figuring out new things that were in the unknown unknown, requires a different kind of exploration. How do you assess each of those differentially?
Zachary Stein: I mean again, the assessment question is tough. I mean, that’s the million dollar question in a way. Literally, because of the political economy with testing industry. But if you can find a way to measure that creativity. And the valley crossing hill climbing metaphor is apt. I think that’s the kind of thing we’re talking about here. We’re talking about those forms of creativity that break into new realms. And you know, I don’t know what to say about assessing it. The honest answer is, I don’t know how to assess it. I think what we know how to assess, it’s what we know how to assess, which is people working with the known.
Daniel S.: And, does IQ map more to hill climbing than valley crossing?
Zachary Stein: Definitely. Definitely. Now, I think the reason why that’s not true sometimes, is because as I said, if you take someone who’s got that, and throw it in an extra spice of something, that they may not even be in their environment, because precisely there that high IQ guy, who gets kept away from those things. He’s the kind of IQ guy who goes to just do math, and blah blah blah. Send them to the [inaudible 00:25:36], do you know what I mean?
Daniel S.: Training?
Zachary Stein: Yeah, exactly. And so, so yeah. I think that’s one of the lessons here, is that the IQ test can make it seem like that’s it, when in fact that the kind of basic ingredients, but as it were, in one of the areas. And you need to bring more to it. And that’s just I think, part of the picture. Skill development, the way Fisher thought about it, had a very intuitive way of thinking about the growth, and not just static unchangeable capacity, but growth in emergence of new capacity. And that’s the way the mind works. I think that’s the other fallacy of the IQ, and the way intelligence is often conceived, is that it’s either you’re smart or you’re not smart. When in fact, everything we know about the mind is that it’s changing literally all the time first of all. So you can be smart in the morning, and not smart at late evening, or vice versa. But it’s also changing over the course of the lifespan drastically, and I already sketched that hierarchy from the sensorimotor to the representational, to the abstract, to the principal, to the axiomatic. And that’s a spectrum of hierarchical complexity that takes literally decades to unfold, and the right socio-cultural conditions.
Daniel S.: So, I have a few questions to dive in. So, when we think about hyper specialization within a very specific line, and maybe even a specific subset of the line, versus some cross-training that leads to different kind of journalistic capacities. So let’s take a Bucky Fuller, polymath type, or maybe like a Paul Erdős, almost savant extreme specialists type. So you get someone like Erdős in math, Who develops graph Theory in a way that no one else was even close. But he couldn’t tie his shoes, or really do anything else functionally. He had obviously allocated, something had happened where all of the horsepower was allocated in a way that created real novel value. Then you see other people where they have novel value development across many fields that are obviously inter-informing each other, because of lateral thinking, and because of abstraction that is then finding generalized principles across domains. What’s the difference in what’s happening with those people, and how much of that is intrinsic versus developed, versus reinforced.
Zachary Stein: It’s so hard to tell. And I mean, the one lesson about the mind is that I think uniqueness, unicity, which is to say that you don’t know. The mind is a complex dynamic system. And so the butterfly can flap at one point, and childhood, and you get a storm in Chicago late in adulthood. And you don’t know, you can’t connect those dots. And so, it’s interesting. I think Kurt Fischer again, I keep bringing him up. He is my beloved advisor. He always tells the story of these two theoretical physicists. Two theoretical physicists are both hit by cars crossing the street. Which is to say again, Einstein notoriously was, he wouldn’t cash his paycheck. He do’s it as a slip in his book. It’s a bookmark.
And then a secretary would find it, and [inaudible 00:28:44] There’s this whole hypothesis that, when you have this hierarchy representations abstractions principles axioms, why would we need to do that on a savanna, let’s say a million years ago? Why is that a capacity of the brain? That’s a strange thing. And so, one thought is that as you move up that, your kind of recycling some of your neural material, which is to say that every move and the growth is also a loss. Or, and every time you grow up, you also lose a little something.
That’s one of the reasons childhood is so bittersweet, and you have these memories that are so interesting, because you know there was something as a child that you no longer have, that in some ways was as valuable, but I had to be lost as you grew. And that way of thinking about the mind is way more attractive to me then thinking about, well you are smart kid, now you’re a smart adult. That’s one way to think about it, but you’re also this very complex growing organism. The mind’s like an organism that literally metabolizes its environment, and depending on what at metabolizes, it grows in certain ways, or doesn’t grow.
Daniel S.: So, what you’re saying, it obviously makes sense that no matter how much muscular development we have, the moment we stop developing those muscles, they start to shrink, because they require a continuous input, that that could be the same with cognitive or psycho-emotional, or other tasks. But there’s also a zero-sum element to what you’re saying, and terms of total memory bandwidth, and complexity of processing, where if we develop in some areas, it’s almost like there has to be neuro-clastic restructuring for optimization for those kinds of things at the cost of optimization for other things. Which of course, makes perfect sense, and I think the way we usually think of it. There’s a thought that’s really interesting to me, which is a non-zero-sum. A positive some, where one can develop new capacities, while enforcing existing capacities, and just have more net capacity. More computational capacity across the spectrum. Speak to that.
Zachary Stein: Yeah, absolutely. And this was often called explicitly [inaudible 00:30:45] far transfer. And so, this is just a fancy way of saying, let’s say you are a really smart guy in mathematics, and you start to learn the piano. Now you start to learning the piano, and you’ve never played before, but you have a PhD in something, you’re going to have to be like a little kid for many weeks, many months, maybe years. Now, that could be very frustrating, and you can separate it from everything else you know, and try to build it as an independence skill, or you can find a way to interweave this new skill development with your existing high-level skill. And Fisher would often talk about bringing a structured you know, transferring it over and down. And then, you kind of get this helix model where are you’re bringing in everything that you’re growing, instead of growing things out in separate places.
And we see this all the time, so it’s like you’ll have a meditation practice that you leave somewhere when you go to work. Or you go to the gym, and then you come home, and eat shit or whatever. And so, I think there’s this issue of the segmentation, and again, just all those social cultural reasons for that. So, the explicitly [inaudible 00:31:45] far transfer, or even near transfer, is what you are saying. It’s about bringing a kind of coherence to the skill development, so you don’t have this fractured weird profile of skills but rather skills that are coherently related to one another. It’s going to be hard to pull off, because we often have to hypertrophy skills in certain areas.
Daniel S.: It seems to me to be what is thematic of all of the polymaths that we study, is that they didn’t actually categorize or segment the different areas, unless they had expertise as fundamentally different. They thought about universal reality as a much more integrated thing, and what they were studying and ecology became a model for how they thought about economics, or psychology, or biology, right? So they would then go to an abstraction level called complex systems. Or complex causation. Whatever, and then they would think about the lateral application of principles, one domain to other domains so there was of course no just met memory, because everything actually made sense and crossing inter-referenced. But that’s a learning modality thing.
Zachary Stein: Yeah, it’s a learning modality thing. Schooling is a big deal here. We wouldn’t have IQ tests, if we didn’t have the factory schools. And we wouldn’t think about the nature of the disciplines the way we do if we didn’t have the kind of post war military industrial university complex. I mean, it’s very regimented if you think about the training for example of the highly specialized engineers and doctors, and these people. And so, I’m very much a fan of blurring some of these distinctions. It doesn’t mean less than the expertise, but it means bringing more to that, and humanizing it. Always been a call of the philosopher of education, is to bring the humanities into the science departments. If only so they do better science, not so they don’t do science, but so they do they can make the creative, like the guy hypothesis brings in ancient Greek myth. That’s profound.
Daniel S.: When you see the DaVinci machine doing surgery better than any surgeon, and that we’re entering a domain in which almost every human skill that would require expertise is becoming automatable better than we do it, but the process to build the automation technologies requires not just hill climbing, but valley crossing kinds of intelligence to figure out what those domains are, and how to do them. How do you see the need for hyper specialization changing with advanced technology, exponential tech, and automation?
Zachary Stein: Yeah, I mean, I think the people at the edges of those fields don’t even really think about what the disciplinary boundaries are, or ought to be. I think we’re in uncharted territory in most of these fields. And that’s important to realize, it’s part of the broader global transformation as a global transformation way knowledge is produced. And it means supervening on the traditional research academy, in blurring those boundaries. They have to be. Systems biology. Just stay many field, and it’s two fields. Any relevant fields, it’s two fields. Mind, brain, and education. Kurt Fischer founded the mind, brain, and education Society.
I worked on that journal, this is a radically transdisciplinary field so, I think it’s an interesting period to be someone who has an expertise. So, I have training in developmental psychology, but I’m working in all kinds of fields, because the traditional model of what the developmental psychologist does has changed so radically. And that’s a story for a lot of people. So I think there’s a need and people feel it, but they’re supplementing their graduate education. With other quote-unquote non-traditional forms of exposure, which are kind of leavening that. I guess when the going gets weird the weird turn pro. And that’s exactly what you’re describing.
Daniel S.: The weird turning pro, as opposed to what was previously right? So, Now our best chess players can move in by AI. Our best Go players can be, and that exponential curve hasn’t even barely started to take off? Right so when it comes to health planning, we’re going to build tools that out hill climb us. On every hill. In terms of excellence, what used to be in terms of machines that can out play a violin or whatever. So then, and yet it is less clear as far as AGI goes, if we will get valley crossing in the same way. At least right now, right? So then, the hypothesis that education should be more oriented towards problem finding them problem solving, and then figuring out how to use problem solving utilize technology for problem solving, would you say that’s a big part of education?
Zachary Stein: Yeah. I mean, this is one of the premises of my book that’s coming out soon, is that artificial intelligence and things like basic income guarantees, and radical changes in the macroeconomic structure globally, they’re going to make education as we know it pretty irrelevant. And we’re going to have to radically rethink a lot of things. So, the thought about problem finding is actually a thought about values. That’s what’s so interesting about that. And so again, the basic issue and the philosophy of education is what is a good life? What does it mean to be a good person, or to have a good society? And so problem finding is along that trajectory of value. So again, we are back to the humanities, and we’re back to yeah. Go ahead.
Daniel S.: I’m going to resist the temptation to get into ethics and existentialism, and the temptation to get into forecasts about exponential tech, and what that means for education, and what the future of education should be. Flag, those are all podcasts I would like to do. Together. Coming back to, people who are listening to this, there might be some people who have children, are planning on having children, are really interested in their development. Obviously kind of need to address that as its own thing, but for people who like, a lot of people are coming to neural hacker right now because they’re interested in optimizing their own capacity. And their capacity roughly matches to their cognitive intelligence capacity. It also has to do with will, and drive, and creativity, and a lot of other things.
But so, for people who are thinking about their own capacity, and how they can think about it, how they can support it, how they can enhance it, you obviously said that the way of thinking about intelligence that is roughly valid, and IQ, is thinking about the capacity to develop skills more than any particularly skill. Except of course, the old shitty narrative was, that’s genetically fixed, and then just kind of goes down with age as your brain declines. As opposed to, every time you get a skill, that becomes now the knowledge there actually becomes a model for learning more stuff. So you can actually have a exponential rate of growth, for all the skills and all the knowledge you develop become a basis for increase capacity for developing new things, if you do lateral thinking and abstraction in generalization well, right?
So, a question that I have, because you mentioned a number of things. You said if you expose the kids from poor backgrounds to the number line, that they might just not have been exposed to, they start to do better. If we are thinking about adults, who already did their SATs, their IQ tests, they have some sense of kind of fixed capacity there, but they like to see if it’s not fixed. If it is developable. One, what do we think about innate versus developable in terms of raw capacity? And where there is relevance or not to that story. And then, what do we think about best processes for developing what we would roughly call the kind of, any of the lines of intelligence, and I would say particularly the ones that relate to the it, or objective categories.
Zachary Stein: Totally. Yeah, so the first question, that’s again one of these questions that comes up with the IQ testing. Which is just basically, is it innate, or can you change this thing? And I think the answer is yes. There’s clearly some genetic [inaudible 00:40:20]. It’s undeniable that if you take a broad swath of the population, and give them IQ tests, it’s going to accurately represent something. And now many of those people will not change a lot in terms of taking their IQ test.
Daniel S.: Are there any good metatheory about what that is? I saw one study on genetics that looked at people with above 170 IQ, old genome assessments, and I think what it said was, no individual snips made had high correlation, but there were patterns, [inaudible 00:40:52] patterns across the whole genome. Probably that do something like increase gray matter density, or something. Are there any kind of [crosstalk 00:41:01]
Zachary Stein: I don’t know. I think philosophically, the concept of heritability itself is complicated. So technically, I didn’t inherit my hands, because heritability has to do with correlations, and it’s 100% correlation. So yes, I’m not sure we know enough about genetics it to really speculate. And so it’s hard to know if I inherited my dad’s brain, or if I inherited my dad’s mind environment. But it’s clear that there are differences, and there are things that are harder to change, and things that are more malleable. Another reason we don’t have an answer to this question is because basic levels, like Maslow level one kind of like physical nutrition, and safe environments, and these things are not really available for many people. On the planet. And so when you get these sweeping studies about IQ differences across let’s say race or nationality, or these things, it’s like you can’t really make inferences about anything innate or genetic here, because we are looking at, malnourished. So, the nourishment of the brain isn’t just nutrition, it’s also information, and semiotic environment.
Daniel S.: And the lack of trauma and fear [crosstalk 00:42:20]
Zachary Stein: Right, totally. And so, that’s another. I’m also hesitant to say, well it’s an eight, because until we start to get really optimal basic conditions for people, it’s really hard to say. What was in their genes, and what became epigenetic from the womb. So I think we’re looking at nature via nurture, as opposed to nature versus nurture. And when it comes to changing intelligence, or growing intelligence, there’s so much. Exercise and nutrition number one. Focus, a lot of an IQ test get sat is your ability to sit still and focus.
What the 1st 1917 Army Alphas, what they were really getting at was, can this Farm Boy sit at a desk and take this test for 20 minutes? That was really the main, in my mind, what they wanted to capture. The things that allow you to focus and give attention, are very important. So, meditation is classic. But even just a concerted effort to control your own informational environment. Focus on one thing at a time, which our culture is hard to do. So, and I put that under nutrition, because that’s like, as I said, your mind is metabolic with the environment, and so I’m very careful with what I eat, even if it’s quote information.
Daniel S.: What are the psychic toxins that you want not to be eating, as far as intelligence is concerned?
Zachary Stein: That’s interesting. I think of them as kind of invasive species, and the ecology of the mind. I think advertisement is great one. One of the reasons that we are driven to distraction, because of the culture in advertising that we have. Then, in general things that shorten the attention span by design. Not things that shorten attention span because they’re naturally short, like a [inaudible 00:44:11]. But there are things that shorten our attention span by design, and so we need to avoid these things, because they teach us that that’s how information works, or that’s how learning is.
Daniel S.: So someone goes to a website where they take an article and break it up into 20 next buttons to maximize [crosstalk 00:44:28]
Zachary Stein: Exactly dude.
Daniel S.: Suggest avoiding those websites for the [crosstalk 00:44:31] has in mind.
Zachary Stein: Yeah, it’s not so much what is it. Maybe it’s a good article, maybe it’s not, but literally the action of doing that is different from sitting with a book for 45 minutes. And so, I’m saying not engage fully with the culture, but be mindful that you can have junk food for your mind you can have junk food for your body. And that’s the stuff that the culture wants us to eat. And so, you have to find the secret hidden good stuff in the back, where it’s a long article with no advertisements. And you’re like whoa. Like, it’s actually good for you.
Daniel S.: Independent of what you’re sitting, studying, just focusing for a period of time, focused in the muscle of focus, whether it’s changing neural structures and the [inaudible 00:45:19] of it, or whatever it is. There is some kind of development of the capacity for focus, probably intensity focus, and duration of focus, right? So, that’s important. But then you can be focused on very different topics, and you might say that some topics, obviously whether the information is accurate or not and if it’s factual information kind of matters. But are there certain topics that you think have more relevance or ways of studying them, or ways of thinking about them?
Zachary Stein: Well, and this is where it gets interesting, because the very next thing I was about to say that, you also need to learn about learning. Which is to say, one of the most important things you can focus on is the nature of development itself, and the nature of your own learning. So learn about the nature of learning scientifically, but also learn about your own unique learning needs and patterns. So not everyone can sit with a book for 45 minutes, but they can do 15 minutes, get up, stare into space, walk around 15 minutes, go up, stare into space, walk around. So, you need to learn how you work. And a lot of research can help with that, things like the neural hacker resources, all these things should be grist for that mill.
But one of the things that you see with people who go post-conventional, and kind of become actualizing, and move up to these higher levels, is that they’re very reflective about their own learning. They know how they learn, when they learn best. They know what excites them. They know how to follow investigative patterns independently. And so, they’re reflective. And so, they create these virtuous cycles of learning for themselves naturally throughout life, as opposed to being kind of extrinsically motivated and driven. Which is what the schools, lots of people do.
Daniel S.: So, this is a Quantified self-process [crosstalk 00:47:04]
Zachary Stein: One way to do it is to quantify it totally. And that can help. You can also mistake the numbers for reality, with the quantified-self too. So good, it’s the numbers are great if they’re measuring something that’s there. And that’s one of my concerns with the quantified-self design, do you know the measurement errors on your tools? How often does it miss-measure your heartbeat? How often does it not capture? When it says to be capturing? Blood sugar monitors for example are, not a psychometric, a [inaudible 00:47:35] .And it’s dangerous.
Daniel S.: quantified-self devices right now, because we want to curate the tools that can help people. And so far that sensitivity and specificity is not good enough for us to feel that the biofeedback optimization is actually optimizing rather than sub-optimizing. [crosstalk 00:47:51] the consumer devices. Of course, there are medical grade devices that are very good, but we are not seeing good enough correlation on many of them yet.
Zachary Stein: It’s interesting, and that’s what measurement does. And I think a lot about measurement in general, and one of the things that does is that we can trick ourselves. And it’s worse than not knowing what’s going on. Because you actually think you know what’s going on, when you don’t. And that’s why demi realities can be weird. And so, I love the quantified-self and so far as it’s reflective, and it creates that virtuous cycle. But if you’re creating a cycle on feedback that’s not accurate, then you can get off course.
Daniel S.: Someone can have a qualified self feedback that is also wrong, where? But that is actually kind of addictive kind of feel good, rather than a virtuous cycle, and they [inaudible 00:48:37]. So this is why you need layers of self-reflection.
Zachary Stein: Yeah, and the same cycle that drives learning, drives addiction. It’s the kind of [inaudible 00:48:47] Dawson’s refrain, of how loading works. You need to actually co-opt the opioid cycle, the dopamine opioid cycle, into these learning these virtuous Cycles, as opposed to things, like for example a video game. Research and design, they figured out how to capture it really well. And it’s about that zone of proximal development, or the quote Goldilocks, which is that zone that’s not too hard, but not too easy. And so, if you know about your own learning, you can put yourself in that situation the whole time, where you are not in over your head and challenge to the point of giving up, but not it’s so easy that you’re bored. And so, you’re not learning. And so that again, just an example of what’s being reflected by general learning [inaudible 00:49:31]. The ability to stay in that zone of proximal development, with most, if not all of your tasks.
Daniel S.: I’m curious to hear your thought on something. There are a few kind of neural hacking methods that have some early indicators that they elevate IQ. Using that shitty old metric, for whatever it’s worth, so there is a neural feedback study that showed multiple point increase in a week of a particular form of medical neurofeedback that was statistically significant. In adults were that supposedly doesn’t change. There’s a technology, a website called Zing up. And it’s basically censoring motor coordination activities. It supposedly drive neurogenesis, MRIs showed increased hippocampal volume, because you’re actually increasing development 4? Neurons. And it also showed elevation of IQ amongst other meaningful scores.
It makes sense, right? There’s a possibility that neural feedback, if you’re actually taking signal from the brain, feeding it back to the brain, so the brain gets a whole new sensory bandwidth, let it didn’t have to refine its own process. So you get increase signal to noise of process within the organ of computation itself. At least one of the organs of computation, that that could increase its efficiency of process and dependent of information, content information, right? Just process information. It makes sense that if you’re increasing neurogenesis, and you’re getting actual gray matter density increases, you could increase the computational bandwidth of the system. What do you think of these kinds of things? And are they things that you know of, that you think are meaningful, intelligence developing capacities that are kind of physic logically oriented?
Zachary Stein: That’s great. So, I love biofeedback. I think many forms of let’s say, mental distress, extreme states of consciousness, the things that people seek psychopharmacology for, typically from a psychiatrist, these are issues with the brain often physiological issues. Now, that means we have to treat them somehow by working on the brain. I don’t think that means you need to intervene necessarily, in some drastic chemical way. I think there are ways to do it that are, like or saying, brain entrainment, that are not let’s say cognitive behavioral therapy, but much more like letting the brain kind of perceive itself as it were, and work in that way.
I think the way you described how it probably works is probably correct now, we have to remember of course that there were moving IQ tests we’re not necessarily moving IQ. And so, I think we need to have a quality only inside of that quanta, which is to say what does it feel like after going through those types of biofeedback? Do you feel more capacitated, more lucid and insightful for example? And that’s I think, the proof is in that pudding. And also with things like predictive validity. But I think these are the most promising for many of these forms of biofeedback. I think the brain and the body shouldn’t be separated at all, and I think one of the limits to contemporary nerve science is that separation.
So, the forms of somatic practice, that get people to inhabit their bodies more, I think have a lot of potential. Because, the spatial dynamics, yoga, and Tai Chi, which bring the brain back into the body, and not out of it into some tube that’s just feedback, and so I think one of the issues we have, and one of the reasons we’re seeing kind of an epidemic how I think, cognitive under-performance, let’s put it that way. In a really nice way. Is the fact that, people’s bodies themselves are hurting, before it ever becomes a neurological thing. So, that would be some general advice is health.
Daniel S.: So, let’s go mechanistic for a minute. If someone’s body is actually hurting, they have physical pain because of their bad computer ergonomics posture, or whatever it is, then we know that pain is mediated via chemistry and nerve signals, so you’re going to be having continuous noise input into the nervous system. You’re going to have inflammatory chemicals, inflammatory cytokines that can cross the blood-brain barrier because neural information, infect all aspects of top-down neurological function, including cognitive. So, getting out of pain is a way to actually take a load off the nervous system, increasing its capacity and bandwidth to do other stuff.
Zachary Stein: That’s a much clearer way of saying what I was trying to say. That’s exactly what I meant by saying that. Yeah, please.
Daniel S.: But we can think of a lot of mechanisms right? There’s a lot of studies going on regarding epigenetics. Genetics expression from various forms of exercise, and aerobic versus anaerobic, versus high intensity interval training actually affect different gene expressions. And there’s something like 7,000 genes that we’ve identified actually have epigenetic modulation with different forms of exercise. So that means, that whatever we thought was maybe genetically attributable as innate, is also not fixedly innate. It’s changeable, and so your yoga might be affecting some of those things through the breath, through the parasympathetic processes that are happening from the slow movement, and [inaudible 00:55:02] from the vagal stimulation that might happen.
We might also see though, that there are certain kinds of benefits that high intensity interval training does, to increasing the good stress on the system, that leads to [inaudible 00:55:16] capacity that yoga doesn’t. But like, I’m going to make a distinction between things that increase capacity where the capacity was already decreased from baseline because of pathology. Pain is pathology. Versus, someone is already in pretty good health. There’s no obvious pathology, and now we are wanting to increase baseline. So, I’m curious as you forecast into the future, and you think about some of the developmental possibilities, there’s obviously pretty wild future tech scenarios that are actually getting not that far out, right?
Brain chip implants are becoming something that a lot of companies are investing pretty heavily in, where you adjust augment your processing capacity with the processing capacity of the entire cloud running on quantum computers. Outside of that, let’s assume that we don’t get that ever, or anytime soon, and we’re looking at increasing endogenous processing capacities of the system. What do you foresee if things go well in terms of us being able to have decrease stress, better medical systems, better schooling education, psychological development, what do you see in terms of the not-too-distant future human intelligence, what would the general capacity look like? And what might some of the modalities that we start in engaging in look like?
Zachary Stein: Right. So, the kind of concrete, utopian vision of the future of intelligence, would be one where the broad-based line is raised in a huge way. So, if you have a basic income guarantee, kind of integral social safety net, and some of these other social miracles that I’ve written about, we would look at something like a broad raising of the floor of quote general intelligence just because so much as a result of that. But, I think for the individuals looking at the cutting edge, I think it’s about horizontal and vertical growth, in a simplistic way. That’s kind of stereotype, but we don’t know the range of people’s multiple intelligences, which is to say, the first step for many people is just to explore lives that they have not explored. So it’s not to keep going up. It’s about going wider, and we already discussed this briefly, but I think, is something that people have the freedom to do in a way that never happened before, if some of these other things get sorted out.
Daniel S.: Wider, intentionally cross-fying.
Zachary Stein: Yeah, the intensional crossing of the line, and a space not of scarcity, where you’re frantically trying to keep your job and how could I possibly take up yoga, right? But in the space of educational abundance, where your unique skill profile that you have as potential, could actually be expressed. I think what we’re looking at now are kind of truncated skill profiles, wear a lot of potentials are not expressed for a variety of reasons. So I think the first issue is too kind of fill that out, but just to say to fill out the rest of your profile of what you’re capable of doing. And that may mean, work in a hospice care. Or it may mean working the soup kitchen, or maybe playing soccer. And who knows? But the point being that, we are limited in ways we can grow, often by the sense of educational scarcity that surrounds us [inaudible 00:58:54]
Daniel S.: No problem, go for it.
Zachary Stein: Expand horizontally. I think another thing again this is about the unexplored kind of educational frontier, another place where we haven’t explored is states. So, do a lot of it learning and skill development, but state experience, which is to say meditative states, and other forms of flow, which is another state that’s very popular these days to speak about. The exploration of state experiences, and the way these interface with capacity development, I think there’s another place for people to come if they’re topped out at a certain capacity, let’s say started bringing a state practice, which brings that capacity to operate under different state, and then you’ll find new potential emergence.
And, so that’s another thing that our schooling in society gives us explicitly, but that were seeking on the side all the time. I think it was sometimes explicitly it’s meditation, but rock concerts, movies, all these things are subtle state inducing, [inaudible 01:00:00]. So I think there’s a way that what were not as concerned with manipulating, and competing, and when there’s a sense of, as I say, educational abundance, then the value the state experiences Aesthetics experiences, aesthetic experience you know, the rapture of a sunset is a state experience. Value, and intrinsic value in those things, will become clearer, and clearer, and clearer. And it’s hard, you have to go searching for those [inaudible 01:00:34]
Daniel S.: I just want to reiterate in saying different words, which is that much of how we’ve been developing our cells is like monoculture in our mind. Right? Like, we’re trying to produce this thing, so we’re just growing hybridized GM wheat fields and our mind. And not developing a robust complex ecosystem that can actually resist foreign species when they come in, and has resilience across a lot of different capacities. So, one of the things that are wanting, is that people don’t keep trying to just optimize the total amount of wheat yield of their mind, but they’re actually seeking to optimize a lot more complex set of things, where you wouldn’t even really call it optimizing. You would call it exploring.
Zachary Stein: Yeah. And that’s, I think, good for a few reasons. One, is that the world we’re moving into as in a world where monocultures are going to survive, on multiple levels. And that analogy is so apt, because the monoculture of agriculture, came around the same time that we got these mass post-war high schools. And so, you’re looking at literally the generation of monoculture of the mind. So, that’s deep. And so yeah, so it’s about breaking out of that monoculture into this much more kind of symbiotic way of thinking about where’s my niche? And how the niche can change as a culture around you changes, as I grow, and grow more. And so, it’s very much I’m moving away from the static, of arithmetical, like in a sense of arithmetic way of thinking about the mind, into a dynamical way of thinking about the wind. So yeah, so that’s a good insight.
Until it’s all explanation, but it’s exploration in the hope of finding it, which is to say that you search, and then you find, and then also something grows that never would have grown, which may be exactly what’s needed. That’s I think the fear of the monoculture, as that’s not resilient. There’s always reasons that are literally dangerous. So if you can only do one thing, if you can only give one food to the world, or only eat one kind of food from the world, and you’re very precarious situation. So we need to all become very broad. I think the renaissance man is like a necessary for everybody.
Daniel S.: So, I agree with this, and there’s an interesting question I want to bring up. I have two friends where I’ve had this conversation and the last few weeks, who have something like six standard deviations more computational processing power than most people. Off of normal assessment curves. They also have other underdeveloped capacities as results of how they’ve developed that. And have both expressed fear in doing things that would develop those other capacities, because it’s not wanting to lose the unique capacities that they’ve developed. Or there’s a question of like, have I allocated all of my neural process in some zero sum, or even if it’s positive sum, fixed positive sum kind of way, where I am now a very useful tool. And if I were to real allocate it, a might make me feel better, but I would actually be a less useful tool. How founded do you think that kind of concern, and those outlier cases is?
Zachary Stein: I think it’s a [inaudible 01:03:52] because these are deep questions and a philosophy of education. Which is about, what’s a good person? What’s a good Society? And I think, you don’t want to put a square peg in a round hole. So, there’s a uniqueness factor, and there is a kind of, where does the puzzle piece fit factor? But, there’s something true also about that fear. This is kind of a far transfer is the word, but I remember David Lynch, the great film director, he went to do psychotherapy, and he was like, you know, if I do this will my art suffer? And the therapist was like, maybe. And he was like, nope. Not doing it. And so, he was willing to live with the wound, to do the art. And so, I think some people may be willing to live with a kind of truncated whole set of skills, and a kind of withered limb as it were, in order to have this super strong branch over here holding up something that needs to be held up.
And so, I think we don’t want to homogenize. But the question is then about, what does it feel like to be them? And there are other things that, if they could change and not lose that, they would. So, I’d have a conversation. But that’s a deep question, and I think we’re looking at a society of increasing neuro diversity, and increasing kind of unique individual niche fitting, and so we need to be careful and judicious about trying to fit square pegs into round holes. And trying to maybe perhaps make new shapes put the save more to this unique neuro profile, then to what the machine needs. And again, the machine is that arithmetic mentality of a machine, where is the dynamical mentality is one where those kind of coactive system between both. So, this is again, the educational futures.
Daniel S.: For those who don’t have the language, machine is a complicated system. Ecosystem is a complex system. Ecosystem is changing. It doesn’t have a fixed blueprint. Cannot fix predict its future states from the current state to perfectly, and it’s self-organizing. In response to its environment. Complicated system might have a lot that goes into the circuit design, to the blueprinting of it. But once it does, it’s fixed. It is not self-repairing, not self-organizing, and not adaptive. Humans understand complicated systems. We build them all, right? We understand them much better than complex systems. We’re just starting to understand complex systems.
So you’re thinking about the mind as a complex system, which of course makes sense, because the brain is a complex system. The physiology is a complex system. Ecosystem is, right? Culture that’s informing the mind is a complex system. And one of the things that it sounds like you’re saying is that we’ve been using complicated system metaphors. How do we make it a better machine, a better computer, a better robot, a better turing machine, whatever, right? For something that is actually a complex dynamic, which means ordered in fundamentally different ways. And you optimize complicated systems. You support the emergence of complex systems. So rather than thinking about reductionist metric optimization, of a complicated mind, we think about what supports the flourishing of self-development, and [inaudible 01:07:09]of a complex mind.
Zachary Stein: Beautiful. And again, that’s both the kind of brilliance of the IQ, and the tragedy, was that it’s simplified this incredibly complex thing to a single number, which was useful, was also dangerous, but yeah, the mind is not like that. It’s not complicated, it’s radically complex. It’s literally the most complex thing in the universe, aside from the universe itself. This is the brain. And so, the inside of the brain is that now, again, started to do some state practices, and you’ll see that there’s some of that. So, it’s just very interesting to think about what that future of the brain and education is.
Daniel S.: You said one thing that was so important, which was complicated versus complex, that’s one big distinction. But one of the other distinctions was intrinsic versus extrinsic value. And most of the time when we think about developing our intelligence, we’re thinking about how we can be a better tool. Either so that we can crush the competition, or make more money, or raise in some corporate ladder, like be better at some tasks that we can be externally valuable.
And that might be just because of wounded child ego that didn’t feel enough, and then being smart was our compensation strategy, so we get to be enough, and you’re asking this question of, while developing our extrinsically recognizable invaluable qualities, what is the intrinsic quality of experience of how we are developing, and just experiencing life moment to moment, and valuing that. And obviously from an educational system, valuing the child’s intrinsic experiments, as well as developing their capacities for extrinsic utility, but not mostly, just seeing them as utilities but as the future of economy, or military, or whatever. But then also, for all of us, as adults really paying attention to balance?
Zachary Stein: Right, yeah. No, absolutely. I think extrinsic motivation is part of what it means to be alive. There’s always going to be extrinsic motivation, but if that’s all you have, it can become very difficult. And it’s a classic principal in psychotherapy, if you’re totally dependent upon the world, you are very vulnerable. It’s a very precarious situation, and it feels that way when you’re trapped in a situation, tied to extrinsic value. So, freeing your goals from that, transcending but including extrinsic value. Which is to say, you get that, and then you move beyond it, and you include getting the extrinsic skill, you include that within this broader project that’s intrinsic.
Similar to that transfer thing we discussed before. Bringing it all together into a kind of coherence of development of self. So, an intrinsic part, that’s part of it. As I said, the people who become post conventional, you find them to be self-directed learners. And intrinsically motivated people, and even those who are the great example of this, is dyslexia. Right? I’m dyslexic. It’s actually true that dyslexics who succeed, the reason they succeed is not because of the special training they receive, typically it’s because they attached an intrinsic motivation through something like reading. And so, you find all these stories of high achieving dyslexics, and at some point in their childhood, they found something that they were just passionate about.
And saw the pain of school, and all of that, that didn’t matter anymore. Because they were intrinsic motivated, and by the way, along the way, they got these extrinsic things handed to them. But they’re doing them for their own reasons. And so, there’s something I think many of the people who are the valley crossers, end being mavericks, and outsiders in traditional schooling, precisely for this reason, because they’re doing it for their own purposes, and they’re intrinsically motivated. And a school demands certain extrinsic things. So that kind of separation of learning from schooling often follows from the separation of intrinsic from extrinsic.
And thus, the advice I give to most of my friends who have kids, separate learning from schooling. Learning is awesome. Schooling sometimes can be, sometimes not so much. But, if you confuse those and think, learning is what takes place in school, then you’ll never learn for the rest of your life. And so that intrinsic motivation is huge but that gets really deep really quickly. That’s the problem with intrinsic motivations, that you go directly from simple questions about what am I learning to deep questions about what’s the significance of my life? What do I really want to be? What kind of person am I already? What can I transform? These are the deeper questions.
Daniel S.: To the degree that we are wanting to raise children to fill roles in a predefined society, we of course don’t want them to ask.
Zachary Stein: Great. But they have to ask now.
Daniel S.: Exactly. Okay, this has been a blast. As we are wrapping up, if people are interested in understanding their capacities as a baseline to both see what is most relevant for them to develop, and then to see if the developmental things they’re doing are working, other than IQ, what might you recommend to people as ways they can assess their intelligence, their multiple lines of intelligence their ecological complexity of thought, is lectica a useful tool? What are some other ones for assessment?
Zachary Stein: Yeah, lectica. So you can go to lectica.org, and I’m sure there will be links on the neural hacker website that we can put their. And there’s a few assessment options at lectica, which they get that spectrum from abstraction and complexity in particular, and these can be useful for some self diagnosing purposes. There’s a whole lot of uses for a lectical assessment. So, I think those are important. Addition again, it’s about the standardization of the second metrics over their value. There is an array of Assessments out there which you can use in a quantified-self type way, and so I would never discourage people from exploring those, but I think keep in mind all these lessons about measurement, and measurement of the Mind in particular. And just take them with a grain of salt.
And know that, flying blind, which is the same without measures, is better than flying with measures you trust that are wrong. That’s just true. And so, play with them, but really be careful about the one you hang your hat on. And journaling has actually extremely important developmental catalyst, which is to say witness at all. Note it all. See what’s working, see what’s not working. Pay attention to yourself, and sometimes journaling really can help with that in a fundamental way. You can do it in a structured way, and there’s whole approaches to doing that, but I found it to be valuable for people that I know in for myself. So that’s just another way of assessment. You talked about the kind of quanta and the quality. So that’s the equalitative assessment, and you can keep a running log in your own head, but writing it down helps, gets it out.
Daniel S.: Have you seen any correlation of things like, different forms of imaging? So, say MRIs that are looking at neural density, GEG’s, and different forms of psychometric or intelligence scores that you think are either already valuable, or promising of a new kind of mind brain interface science?
Zachary Stein: I mean, this isn’t really my field. I’ve been really intrigued by the meditation research that’s coming out of Madison, Wisconsin. I think that’s where it is, and that’s the, it’s interesting because it’s an ancient technology of self development, and it’s showing profound neurological, as you’d expect, but it’s just shocking to see really how stark some of these findings are. So, that’s intriguing to me. But yeah, that’s about as much as I can say. And, so I’m kind of old school methods. I think part of it comes from my caution around the assessment, which is to say, the DSM is a nightmare. The IQ tests are a nightmare. Don’t articulate yourself understanding in these languages handed it to you. Find new things to think about the self. Things like the lectica can help with that.
Daniel S.: Things like reductionist metrics and wrong metrics are a concern for you, but metrics, objective metrics about subjectivity are their own category of nightmare.
Zachary Stein: Right, yeah. And then you get the metrics that work, and then those are scary for a different reason. Because they actually work. We can just jump down the rabbit hole Dan, but we need to go.
Daniel S.: No, this is good. Zach, this was a blast. Thank you, this was a really fun first podcast for us to do, and a fun topic. And I imagine people might have a lot of followup questions regarding assessment and development, and et cetera. And we might get to follow up on those. So, thank you.
Zachary Stein: I welcome that. As a bonus.
Daniel S.: All right.
Zachary Stein: Beautiful. That was fun man.