The following is a rough transcript which has not been revised by The Jim Rutt Show or Brendan Graham Dempsey. Please check with us before using any quotations from this transcript. Thank you.
Jim: Today’s guest is Brendan Graham Dempsey. Brendan’s a writer, poet, and farmer, and the director of research for the Institute of Applied Metatheory, as well as the director of Sky Meadow Institute, an organization dedicated to promoting systems-based thinking about the things that matter most. Welcome back to The Jim Rutt Show.
Brendan: Hey, Jim. Thank you so much for having me back.
Jim: This will be fun. We’ve had some great conversations. I think the first one was episode 172 where we talked about his book Emergentism. Then the most recent one was episode 293 where I reacted to a Facebook post, if I remember correctly. And the episode was called “Cosmetelology and Emergence Vector.” Now there’s a hell of a thing to come out of a Facebook post. Between the two, we basically talked about the first volume of the series, which today’s conversation will be about the second volume, and that was on the book, The Evolution of Meaning and Universal Learning Process. That was volume one of the series that Brendan’s working on called The Evolution of Meaning. Today, we’re going to be talking about the second book in the series called Psyche and Symbolic Learning. So let’s hop into it.
You mentioned “meaning” 351 times in volume two, believe it or not. One of the things I love to do is find some keywords and count them. In volume one, you frame meaning as essentially adaptive information that helps an entity stay viable in its environment. When I hear “meaning,” which can mean anything, I sometimes take the two poles. At one extent, meaning means “Hey, it’s light in the east at 5:30 in the morning, it means the sun’s gonna be up in an hour.” That’s kind of meaning in your volume one sense. And then other people use meaning for things like “What is the meaning of life? Why do we have something and not nothing?” There’s a hell of an extent between basic meaning and extended meaning. So what do you mean by meaning in volume two?
Brendan: The nice thing about doing a book series is that you can really go through and unpack things sequentially. In volume two, I’m presuming folks have engaged with the setup and the framing that I’ve offered with volume one. You did a good job summarizing the basic concept there of adaptive information—information that links entities to their environment in such a way that maintains and enhances their viability.
In volume one, I try to ground that in some information theoretical work. I think of Artemy Kolchinsky and David Wolpert, Carlo Rovelli—those folks have done some really great ways of using information theory to talk about meaningful information. That’s still what I’m trying to carry forward here in this through line: a consideration of meaning as that kind of information that an entity is correlated with in terms of its environment that bears causally on its viability. The processing of that information is what allows increasingly complex entities to stay far from equilibrium, to get the energy they need from their environment, to avoid entropic dissolution essentially, and that itself is a complexifying process.
You mentioned two really important meanings of meaning. One is sort of almost semiotic reference in some way, and the other is this more existential meaning of life. In this volume, I get into a little bit of how those are linked. But generally speaking, I’m really focused on the latter. Semiotics and signals and signifiers—all of that understanding of how people relate to reference in the world—plays a really important part for maintaining your viability as an evolutionary entity. But in service of the deeper sense of meaning, which is that things are intrinsically meaningful to an entity if they bear on its viability, if they threaten it, if they help it, if they increase its chances of flourishing or decrease them. That’s the sort of meaning that I’m interested in probing, and this volume opens up the exploration of that at the human culture level.
Jim: Let’s talk about this opening up. Volume one basically staked out a four-level chain of things to think about with respect to information processing regimes: the structural, the genetic, the neuronal, and now the symbolic. Talk a little bit about how what move you’re making from volume one to volume two when you move from the neuronal to the symbolic.
Jim: Now let’s talk about this opening up. Volume one basically staked out a four-level chain of things to think about with respect to information processing regimes: the structural, the genetic, the neuronal, and now the symbolic. Talk a little bit about what move you’re making from volume one to volume two when you move from the neuronal to the symbolic.
Brendan: Well, that’s really huge because this volume is a zoom in. Volume one is a kind of big picture setup that gives my understanding of the cosmic framing of evolutionary history as a sequential process of increasingly complex information processing regimes. There I’m drawing very heavily on and am much indebted to the work of Greg Henriques and his Unified Theory of Knowledge framework, who has updated our understanding of the big history picture. Whereas in the past, some people had gotten parts of this story and understood some really important junctures and joint points, I think Greg’s model does the best at really articulating what each of those are and grounding them in a solid theoretical basis.
But since Aristotle, and certainly before then, people have had a sense that there’s some kind of difference expanding across scales when you move from, say, mineral to vegetable to animal, et cetera. And so there are some genuine insights there, but trying to get that scientifically rigorous—to root that in some solid theoretical framework—has been an ongoing process in scientific intellectual history. And the big picture, big history, complexification story that models like the Unified Theory of Knowledge tell situate four major complexity levels.
So out of some kind of information-energy implicate order, you get the first one, which is matter, and then out of matter emerges life, out of life emerges mind, which in this case means really like animal bodies with active bodies and nervous systems navigating their 3D space, essentially what you see showing up with the Cambrian explosion around 530 million years ago. And then out of mind, out of what becomes animals with complex nervous systems, you see culture, which is the emergence of human persons who are themselves a kind of subset of animals, which is a subset of life and so on.
These four major levels are what I outlined there. And what’s great about the UTOK framework is that these are all explained relative to information processing regimes. So at life, you get a new complexity level because you’ve got genetic information being processed. At mind, you’ve got neuronal information, and at culture, you’ve got symbolic information and language and some of the more advanced semiotic processing that goes on there. So it’s a very helpful taxonomy of levels.
In volume one, I lay that out. But then I say at the end of volume one, now that we have the big picture and the background here, let’s zoom in on the culture level specifically and look at how complexification occurs at that level. And that’s really going to preoccupy the rest of the book series. So volume one is very much the big picture. Volume two then zooms into the cultural level. And as a helpful orientation as well—we can talk more about this—in some ways, volume two and volume three go together because in order to look at complexification at the level of culture, you have to look at the individual and the collective kinds of information processing and learning dynamics that show up. So volume two is dedicated to the individual level of how individual human minds process symbolic information for meaning, for meaningful information to maintain their viability.
Jim: Well, you do make a very strong point that within especially within the so-called cultural frame, to talk about the individual without also understanding their coupling to the wider context is actually an incorrect way to think about it.
Brendan: Yeah, and I think it’s really crucial at many levels. We very much culturally inherited this notion of the atomized individual that you can get this person in a sense that’s separable from their cultural environment and socialization processes and somehow treat them in their atomistic individual context. And I think that what we’ve learned over the past hundred years in particular is that that’s just not a viable approach at all. You have to situate human beings and what it means to be human within human enculturation and socialization processes.
Greg’s work also helps center that because if we’re looking at language as that aspect, then language is inherently a kind of transpersonal collective phenomena. As Wittgenstein said, there’s no private languages. So as we get enculturated into personhood by learning language and developing in our symbolic imaginaries, that is what forms our egoic structures as individuals, and those two things are really fundamentally inseparable. So you really have to take an inherently transjective approach here of the individual and their objective space and how they relate to understand what the human is. And in order to do that in this book series, I just break that up with book two focusing on the individual, and book three will focus on the collective society level.
Jim: Gotcha. The work of Greg Henriques certainly goes throughout the book, and I have done podcasts with him on all of his books. So those who want to learn more about UTOK without having to read the books—they are good books—can catch four or five episodes on The Jim Rutt Show. So that’s actually my next definition I wanted to get into before we dig into the structure of the book itself, and that is Greg’s elaboration of justification. You talk quite a lot about justification in the book. It’s one of the key components of the argument. So why don’t you explain for the audience what justification means in this context?
Brendan: This is an exciting point of connection between, or you could say convergence between, a number of models that I thought was a really compelling insight. Justification is in the UTOK framework, really at the heart of what Greg calls justification systems theory, which is the joint point sort of change that leads to the arising of a distinct ontological plane of complexity of culture. Just as further down the stack, life sort of emerges once you get the Darwinian biological evolutionary understanding of diversification, natural selection, that sort of thing. Once you get at the mind level, the understanding of behavioral investment at the culture level, you get justification systems.
There’s a shift that occurs from the cognitive animal mind plane to the cultural person social plane, and that is mediated through symbolic language. At the cognitive mind plane, animals have communicative gestures, sounds, grunts, all sorts of signals and referencing. But what they lack is grammar syntax and the ability to make propositional claims in a sense. There can be a sort of sound an animal makes when a particular predator is by, but there is not an animal saying, “there is a predator right there” or something to that effect.
One of the arguments that Greg makes with the UTOK model is that with that transition from just communicative animal signaling to something like symbolic, grammatical, propositional claims, you get a new kind of evolutionary pressure and dynamic that shows up because you get questions and answers. Someone can say, not just the sound for a gazelle and kind of orient in a direction. A person can say, “there’s a gazelle.” But once you have the capacity to do that, your interlocutors or people around you can say, “Well, how do you know? Are you sure? I don’t think so.” And “What gives you the reason to say so?” et cetera. So he frames this as a sort of negative space that opens up once you get more advanced grammatical propositional language that forces justification to occur. You can’t just make a claim. You have to then back it up. And in many ways, that is the driving factor for human cultural and intellectual evolution, and that’s sort of at the core of the argument that I want to make.
Jim: Greg does stipulate that this produces a ratchet effect of greater and greater systems of justification. I created a nice little example from the early stage, which is, originally it might be “elk”—essentially, a longer form version of pointing. And then “elk over hill”—declarative sentences only. And then let’s imagine Ogg who wants Gog to go chase an imaginary elk so Gog could screw Ogg’s wife. So Gog says, “elk over hill.” And then Ogg says, “How do you know? What’s your evidence?” because he’s had Gog do him before, do him like a dog. And so he has to then question him. And then Gog either is a good liar or he’s not. And this battle goes back and forth with respect to the evidence. And then Ogg and Gog have different views of each other thereafter, and there may then become a cultural norm against lying for the purpose of screwing the other guy’s wife. So you can easily see how this dynamic emerges once language reaches the level of the propositional.
Brendan: Certainly. And there are—that’s a good example of sort of evolutionary, competitive dynamics that might emerge. But you can also imagine the collaborative dynamics that emerge through justification. If you’re trying to build something together or you’re going on a communal hunt, you need to be able to communicate and justify the claims that you’re making in order to make the best argument for why the group should go over here or why this piece should go in this part of the axe or that sort of thing. So collaboration, competition, it leverages the novel symbolic information processing mechanism towards all sorts of potential evolutionary adaptive gains. And I would also say, I mean, there’s a kind of notorious infamous question around debating the origins of language and trying to do that move. I forget what nineteenth-century scientific society it was—
Jim: Yeah. The Royal Society banned papers on the origin of language.
Brendan: Yeah. They banned the question. Yeah. They said, no thank you. And so, you know, we’ve gotten a little bit more open to people exploring these things, but there’s still an understandable reticence around trying to just build these theoretical castles in the sky based on a hypothetical “where did language come from?” And I just wanted to make that point because while I find justification systems theory very attractive in terms of explaining something hypothetically about the emergence of language, I don’t think that that is necessary to account for the value of the model itself. Wherever language came from and whatever various functions it might have served, we know that we’re justifying primates. This is what we do, and we know that that unfolds in all sorts of different ways and that we use that for evolutionary purposes. So whether it’s used sort of ideologically as an explanation for language’s origin is sort of, it could go either way, but certainly, I think that this is a very credible way of understanding how—
Jim: Yeah. I thought that was a smart move on your point, not to go into the morass of the history of language. Though, you also miss one of the things I think is kind of cool. There’s like an argument of Robin Dunbar’s that these gossipy examples like the sort I gave may have been the first arms race. You know, there’s nothing that fixes mutations in evolution like sexual competition. That’s how peacocks get huge tails, rhinoceroses get big horns, deer get giant antlers—because they get laid more, damn. And that’s how you run the math. That’s how you propagate a particular genetic strain. So it wouldn’t surprise me that the early bootstrap for both language and perhaps the gigantic encephalization of humans—I mean, humans are not that different from chimps except our brain-body weight ratio is three times higher, which is like a crazy increase from a species that’s right next door. And it may have been this arms race, probably around sex or food. Food or sex. Sex has far more effect than food. So I always thought that’s kind of interesting. And it not only does it grow the brain, but it also is an evolutionary pressure on the capacity of language itself for expressivity. Right? The guy who’s a little bit better at expressing, wooing, for instance. It’s just so interesting to think about how this idea of justification and the arms race of “he said, she said, they said, we all said about what they said,” is just an amazingly interesting thing. When I once read that justification theory in Greg’s book, first time I ran across it—I don’t think he actually invented justification theory, but he’s unified it better than anybody else—it really clicked for me as a truly fundamental aspect of what’s going on with our species.
Brendan: Yeah. I’ll just add to that. One of the things that I try to do in volume one is situate a kind of meta-theoretical understanding of complexification through a particular set of dynamics, namely variation and selective retention. And I didn’t invent this. People like Bobby Azarian have talked about this. Gary Chico, you know, people in the EvoDevo community and universal Bayesianism and universal Darwinism—these ideas have been around for a little bit, but I find them very compelling. And when you can understand that this kind of algorithm is operating across scales of complexity in similar ways, then it’s not just that language in a sense is a driver of sort of genetic evolution. It’s that language creates a novel layer of evolution, cultural evolution that is playing out in a Darwinian manner, but at the level of language and memes. And so again, this is Richard Dawkins’s point about memes and all of that that’s come out of that thinking. But these are in a sense universal architectural patterns that drive complexification across different scales of complexity, and it avoids the problem. Some of that sociobiology stuff that tends to want to reduce too much just to biological evolution and genetic—what I call genetic learning. There’s learning happening across scales. And when learning unfolds at the human cultural level through language, you have a runaway explosion of cultural development in a way that isn’t possible lower down the complexity stack, and that’s sort of what this book is going to zoom in on.
Jim: Yeah. Though I do like to point out that the answer is always both, right? There’s social evolution, there’s genetic evolution, and then there is the very interesting mutual reciprocal effect. I was actually quite happy to see that you mentioned Baldwin. Here’s somebody who’s not talked about enough. The Baldwin effect is essentially evolution for learning, right? And if learning itself is a competitive dynamic—which in many environments it is—evolving for better learning, perhaps just in a domain, but it doesn’t really matter, is itself a very interesting example of where the two are unentangled. They’re basically looping together.
There’s some evidence that human mutations have continued to accelerate actually. You think, well, our life’s been simpler because we can just go to the Safeway and buy a steak. We don’t have to go chase a gazelle across the savannah for two days until it exhausts itself and then cut its throat. But there’s a whole bunch of other complications we’ve had to deal with. Agriculture has a different set of complications and a whole different stack of learnings with different skills.
So there appears to be a propagation of new genes five thousand years ago, for instance. And I don’t think it’s been long enough yet for the record to show what literacy has done, or maybe it is. But I would expect at some point you’ll see genes selected for literacy. Though maybe not anymore, now literacy is about to die, or so they say. Graduate students of the future will have the rise and fall of the literacy gene. And the one that will replace it, the one with the big puffy lips. Why did that ever become a beauty marker? I don’t know. The ugliest goddamn thing I ever seen in my life.
Anyway, let’s go on to our next definition before we hop in, and it’s sort of two parts. The real definition is hierarchical complexity, which I would argue is the central theme of the book in some sense. But before we do that, let’s do a short gloss on complexity itself, which by the way you used 367 times, more often than not, not with hierarchical. So, when you say complexity, what do you mean?
Brendan: Complexification, the sort of verb form of complexity, is happening across all these different scales of cosmic evolution. In terms of understanding just complexity as a basic idea, a really simple way to talk about complexity is that it is the coming together in coordination of multiple parts to form comprehensive wholes that have qualities that aren’t in the parts themselves. There’s a number of different ways that complexity scholars debate exact definitions, what metrics to use, all that sort of thing. But just intuitively, if people can understand that you’ve got part A and part B, you can coordinate them together into a dynamic that then forms something—let’s say whole C—that wasn’t available to any of the parts in isolation, but is now available to the whole because they’ve been brought together.
Complexity is what we see all around us, and it’s what is increasing across cosmic evolution. Because as you get parts coming together to form novel wholes that then themselves can be parts in still higher order wholes and so on, you get this sort of potentially recursive complexification dynamic that is what we see across big history. If you just want to use the example of atoms coming together to form molecules, molecules coming together to form minerals, and then planets—you’ve already got some level of organizational complexity there. Once you get the emergence of the first cell on a planet, then if there’s reproduction of cells, you get multicellular organisms out of single cells, and so on.
I find it a really powerful and helpful idea because it’s a unifying concept. You can look at culture, can look at biology, you can look at psychology, and there’s complexification dynamics unfolding in those different registers and domains. So that’s complexity. Happy to say more about that if you want before trying to then relate that to hierarchical complexity.
Jim: There was one word I noticed you didn’t use was emergence. Was that intentionally?
Brendan: Not necessarily. You can talk about complexity without necessarily having to emphasize the emergent properties that come along with these kinds of wholes that are greater than the sum of their parts. Obviously, emergence is really crucial to my thinking. I wrote that book “Emergentism” that you mentioned at the outset. I think the thing about emergence that’s really valuable—that the Utah framework does really well—is that it helps understand these joint points in cosmic evolutionary history where something genuinely novel comes online based on complexification that’s happened to bring things together at a lower level. When you get life out of matter or you get mind out of life, those are emergent joint points that really divide nature in a significant ontological way, and that’s very important. But I don’t think one has to dive into all of the nuances and philosophical questions around what we mean by emergence to just appreciate what we mean by complexity because I think it’s a lot more intuitive.
Jim: Okay. That’s good. Now let’s take a relatively short whack because, like I said, it’s—I would argue it’s the theme of the book—is hierarchical complexity.
Brendan: What I want to do is after setting up this kind of big picture of cosmic evolution unfolding through different levels, complexifying at these different levels, zoom in on the culture plane to look at the information processing occurring there as a complexification process as indeed other forms of learning lower down the stack are as well. When we look at the human cultural level and we study human learning, we are in the domain of essentially developmental psychology. And over the past hundred and fifty years, as that field has progressed in its understanding, various models have emerged that help us understand better and better how humans themselves actually learn. And hierarchical complexity is the kind of end result for now of that process in that field. It’s the construct that Neo-Piagetian developmental psychologists use to understand how skills develop and how capacities grow across the human learning process.
And the reason it’s called hierarchical complexity is because it is also a complexification process. So let’s say you have the ability to move your hand over here and then move your other hand over here. Well, if you can do those things in isolation, that might be you could think of those as two parts. But if you can coordinate those two movements in a way that produces a new kind of action that can, let’s say, reach a particular kind of goal, then you’ve actually complexified your sort of sensory motor capacity to achieve your goals and enhance your viability.
As we get into the level of human thought that begins to really surpass other animals and you get into representation and symbolic thought, we start to see how this happens with concepts. Like a really classic learning example is learning through play. That’s an idea that you can say. What does it mean learning through play? Well, you have the idea there that you’re playing, but playing is a means by which you’re learning something. That’s a concept, and it makes sense. Now you can’t have that concept until you first had the concepts of learning and play. So learning through play presumes familiarity with these lower order concepts. Learning through play is a higher more complex idea because it is based on the coordination of lower order ideas that have been brought together to produce a qualitatively new idea.
And so what developmental psychologists basically have been tracking through their models and studies is how new kinds of concepts come online that then themselves become coordinated to form higher order concepts and how those higher order concepts themselves start to get coordinated with similarly higher order concepts to form even more higher order concepts and so on. So that’s why it’s hierarchical because it builds up from what came before and complexity because it’s a coordination of parts yielding more comprehensive qualitatively distinct wholes.
What I find really amazing and spectacular about the insights that have come out of this field is that these processes by which the human mind learns are the same basic architecture that learning works through at all levels of cosmic complexity. The universal learning process that I outlined in volume one is an evolutionary process of variation and selective retention, and these get coordinated at higher levels to produce more complex phenomena. Well, that’s exactly what our minds are doing all the time. So if you’re really good at a particular skill or you’re very learned in a particular field or domain, that’s because successively you’ve been building up more and more coordinated complex and abstract concepts out of lower order ideas. And you can actually measure that in terms of hierarchical complexity. And a big goal of this book then is to look at the learning process at the human culture plane through the lens of hierarchical complexification as sort of zooming in on that level.
Jim: I first ran across hierarchical complexity in the works of Hanzi Freinacht. And he was on the podcast a couple times, and we talked about it. And I went then and did my usual deep dive on the side afterwards and read about the work of Michael Commons in particular, who at a very non-semantic level defined sixteen levels, I believe it was, of hierarchical complexity. And I think the key thing about that was his non-semantic approach could apply in theory to anything. I wonder about that in humans. We’ll get to that a little later. So let’s continue on with where you’re pointing—you gave a little history of the idea. We don’t think we have time to dig into that, but it basically came up with a constructivism approach. Why don’t you talk a little bit about what is your take on what’s actually going on there with constructivism? Or at least what the theorists say and what you believe, and they too may be a little different.
Brendan: Well, constructivism can mean a couple of different things. What I’m referring to is a kind of developmental constructivism. There are different kinds of constructivism—people have probably heard the phrase social constructivism, radical constructivism. The basic idea of any kind of constructivism is that the mind in some way fashions, shapes, or forms the world as we experience it. If you want to go all the way back to Kant in a sense, that move from thinking we’re directly interacting with reality as it is, to actually needing concepts and categories in our brain that predefine the world for us.
In the case of radical social constructivism, these might be totally arbitrary. What I find of value here is a kind of middle way—certainly not the radical social constructivist approach. I find that to be very unhelpful and counterproductive, and unfortunately, a lot of postmodern thought tends in that direction. But we also have to avoid a kind of naive realism that what we’re experiencing is somehow just reality as it is, unfiltered. There’s clearly a way in which we are getting a mediated experience of whatever that reality is.
I’m a realist. I think there’s a world out there, and this whole framework helps to understand the relationship between these two things. My good friend at the Institute of Applied Metatheory, Nick Hedland, has a framework he calls visionary realism, which is an extension of and continuation upon ideas of critical realism from Roy Bhaskar. This realism is actually very important, and getting beyond postmodern radical social constructivism requires that we actually say, yes, there is a real world. But just because we say there’s a real world doesn’t necessarily solve our question about how we have knowledge about it.
What a developmental constructivist approach does is it takes an individual and situates them in a world, but it says that we need to develop our categories of understanding about that world as we interact with it. They’re not radically arbitrary because if you bump up against a wall, it’s going to give you resistance. In Piagetian terms, you’re going to disequilibrate—you’re going to fall out of equilibrium in a homeostatic dynamic way. And so then you need to accommodate to that. You need to actually move around this obstruction and counter this resistance.
The world is always impinging on us, and through that, we craft our mental models and representations of the world in a dynamic relationship with it. So we’re still getting constructed knowledge of the world, but it is in relationship to something that’s out there. That is how you can actually have a sense that we’re gaining better and better knowledge about something—to what degree do our mental understandings or representations of the world adaptively work in our environment? That’s the big normative question about knowledge. A developmental constructivist approach helps us understand what we mean by knowledge, how knowledge can be better or worse, how knowledge is about informing viability and flourishing of an organism in context, and all that plugs right back into the stuff I talked about in volume one.
Jim: And knowledge can mean something not just like “what’s the capital of Paris,” but as the very actively engaged grandparent of a two-month-old, I quite resonated when you talked about “oh, this arm and this arm”—that’s what they’re doing at two months. In about three or four months, they’ll be taking them together and picking up a toy. That’s a higher level of understanding about how this body and this world work together.
Brendan: And that’s exactly what Piaget and Baldwin before him, and the developmental psychologists since then, especially the experimental ones, have been looking at—studying how these kinds of capacities and skills grow and develop. That was really some of the seminal literature on these fields of when does a child actually gain object permanence, when does a child realize that a thing that was there a second ago still exists in the world just because they’re not seeing it.
If your grandchild were a little bit older and were just starting to learn to walk, you’ll see an evolutionary process unfolding there—variation and selective retention. They’ll try something, it won’t work. They’ll try something by adjusting that a little bit, it’ll work a little better. They’ll try something based on that, it works. Great. Oh, but now they’ve fallen over. It’s this iterative process of continually seeking the adaptive problem solution set in a given environment to achieve a particular end. When it works, bingo. You’ve got it. Now you’ve got a category that you can use and build off of.
That’s where the complexification comes as well. This whole walking thing works really well—I bet I could walk and dance and sing, and you can start having more and more complex action patterns. And this moves all the way up from sensory motor behavior to representational and abstract conceptual thought.
Jim: And let’s do a little sidebar here on constructivism in the sense of our relationship to reality. It’s quite hilarious to me in the history of human thought that anybody not drunk ever believed in idealism. And that it became foundational to this ridiculous metamodern stuff, or at least, there is a grain of truth in metamodern and postmodernism, which is be skeptical of grand narratives. But when it also goes to “well, there is no reality” or “we can’t know reality,” I go, what? It’s the kind of belief only a professor could profess. No actual person—I say, how many postmodern plumbers do you know? Not too many.
Where I think we did actually figure it all out once was with Kant. People used to think we were getting a direct readout of reality. But I think since Kant, the key thing is, no. We don’t have a direct readout of reality. We have perception that’s processed in various ways. Various structures are built—Kant didn’t know where they were built exactly, but built somewhere inside of us. And we have a model of the world that we are constantly constructing. When you’re two months old, you may not even be able to see objects. You may just be seeing a raster. I don’t know. And over time, you develop a whole series of tools which structure this flow of perception into something that’s more and more useful. It seems to me just so obvious—how could anybody doubt it? The fact that our model of the world is useful or we would have starved to death a long time ago. That seems to be a pretty clear proof that our constructed representation of the world has to be pretty close.
Brendan: I think that’s right, and I think that is actually the metamodern turn out of the postmodern, where that anti-realist sense took hold. The metamodern turn is moving away from that. It’s trying to reground a sense of reality while taking into account the constructivist insights. Kant was right to a point, but in many ways, this epistemological debate has been ongoing and continued to become more and more ramified and clarified.
Yes, Kant gives us an understanding of the constructed nature of reality, but what he doesn’t focus on is how those constructs are themselves informed by the external world, have an evolutionary history that’s been shaped and molded by that world. They have an ontogenetic adaptive learned value to the individual relative to that world. And so Kant’s image, at least taken and interpreted in some particular way, is just a partial view of this. Like many things that the metamodern turn is doing, it’s appreciating the insights there, but it’s also appreciating the other insights of realism and getting a kind of higher-order synthesis. That I think really is what developmental constructivism allows for us to get at.
Part of why this is so important though, and where this is going to be going in my line of argumentation, is connecting this up from the idea explored in volume one that the constructs that we use are evolutionarily mediated. In Thomas Nagel’s “What Is It Like to Be a Bat?” a bat’s knowledge of the world is going to be very different. It’s not that the world is necessarily a different world than what I’m experiencing, but the sensory inputs and capacities that bat has to adaptively navigate the world are going to be radically different. We have an umwelt—we have a way that the world out there gets mediated through our biological inheritance and all the other aspects, particularly for humans, of a cultural inheritance and interpreted in particular ways.
The reason why this all becomes incredibly important for the project that I’m engaged in is because I’m interested in worldviews, and worldviews are people’s developing frameworks of reality that they use to adaptively navigate their worlds in social contexts. If we can appreciate the genuine insight that, yes, in a realist sense, there is a world out there that we can have better or worse knowledge of, and the constructivist insight that our understanding of that is under construction, we can have the picture then that human worldviews themselves are evolutionary products. There is a memetic form of collective and individual evolution unfolding that’s developmental, hypothetically and potentially. There is actually a way in which human knowledge of the world can be approaching reality in some ways that are more and more adaptive for human beings in their lived contexts. And that means that, again, we’re out of postmodern radical relativism. We’re in a space in which human knowledge can actually grow and progress and become more adaptive. And this book series ultimately is about charting that developmental progression from the earliest of human cultures all the way.
Jim: Up to the present. That should be very interesting. I know you’re going to do society next. Make sure you let me know so we can get you on when you do that. Now one of the things that’s, I suspect, controversial, and I have my own thoughts about it, is you lay out a number of stage theories in various domains. Let’s do two things. One, why don’t you discuss some or all of them—Kohlberg, Kagan, maybe Piaget very quickly. And then you’ve charted out in the book that they’re surprisingly similar in their layers and various metrics. They’re more commensurable than you might think even though they’re in different domains. And then address the big question: Are these layers real, or are these just more or less continuous phenomena that someone’s drawn six or 12 or 13 lines across? I know that’s a big giant question.
Brendan: Let’s start with some of the stages and measures that you talked about. Let’s start with Piaget because he’s been really the most seminal figure, I think, in this field. He very famously talked about four major stages of development that he called the sensorimotor, preoperational, concrete operational, and formal operational stages, which is basically from birth to around 12 or so.
What he identified were these qualitative shifts from—well, as the sensorimotor suggests—entirely pre-verbal operations at the level of physical behavior. Then at the preoperational level, once language has kicked in, you have what he characterizes as very fantastic childlike thinking. This is going to be, you know, five, six, that kind of age, and sort of pre-causal thought. Even as early as a child starts learning to talk and thinking about the world, they don’t use logical connections in the way that show up later in the life cycle.
So if you ask, “Why is the sky blue?” a child might say, “Because it’s high up.” We wouldn’t see that as a causal explanation, but there’s a kind of juxtaposition of thoughts there that is presented as a kind of explanation, which gets us back to justification. That’s one of the important themes here—as Piaget probed these developmental stages, he was asking for people’s justifications for explaining their thought. What he found was that there are patterns in the way that people justify and explain their thinking at these different stages.
Famously, if you put a ball of clay on a table and roll it out into a sausage-like shape so it’s really long, a child will think that now there’s more clay. Whereas at the concrete operational stage, they’re able to see that actually, yes, it did get longer, but it also got skinnier, and those balance each other out, so there’s no actual additional clay there. That’s a logical advance from preoperational to concrete operational child thinking. That’s a genuine change, a qualitative shift. These were the initial insights used to develop these stage models.
By the time you get to formal operations, you’re able to take the basic logic that you can work with concrete objects and do them entirely hypothetically in your head and start using variables like L and W for length and width. So when you see that when you multiply L by two, you have to divide W by two and these kinds of things.
That’s the progression that Piaget identified, and there seemed to be a lot to this. There were also a lot of problems with it in terms of how it was theorized and these notions that there were formal logical stage structures in the mind. There’s a whole rabbit hole we could go down in terms of the problems that have accrued as people have interpreted or misinterpreted Piaget. But giving the short version, there seem to be some really good reasons to think that the mind progresses not in a willy-nilly way, but through a sequential set of stages that build on themselves over time, and that you can’t get to the next stage before you’ve acquired the skills of the previous stage.
Piaget focused more on the logical end of things. Someone like Kohlberg came around and picked up the Piagetian program but was interested in other domains of development, specifically morality. How do people’s thinking about morality and moral questions change as they get older and develop? He found a similar kind of repeatable invariant sequence of basic stages through which people’s thought progresses. He also clarified and formalized some notions of development—that there’s a hierarchical integration of lower-order components into higher-order components, and this is the means by which thought develops and progresses. His stage sequence has been validated through cross-cultural studies and, when properly translated into local contexts and cultural milieus, is shown indeed to be universal and invariant in sequence.
Jim: Well, let’s stop there. Because as you know, I sent you an email on this. I did a little side research when I read that to see if that was true. At least some researchers say stages one through four of Kohlberg appear to be universal, but stages five and six may well be very culturally dependent. And Kohlberg being, you know, a dead white man, he basically looked at it probably from a Western perspective when that might be overreaching. What do you say to that critique?
Brendan: Well, I mean, you know, of course, he might have been white at the time, but he wasn’t dead. And so he had that going for him. No, I think that there’s something to that. I think that stage six, he admitted to be very hypothetical and found only basically in philosophical texts. So we’re really talking about a five-stage model.
Whether or not stage five is a human universal is an interesting question, but I guess we’d have to get clear what we mean by the question. Do we mean we find it everywhere? You don’t have to find something everywhere for it to be a universal. Something can just be not in a place. Like for example, people who look for regularities, let’s say, in the way that industrialization unfolds can find certain patterns—wherever industrialization has led to certain this or that, well, we see x. Well, just because you go to a place where industrialization is not as far along as in other places, it’s not going to be there, but that doesn’t mean that given time, it won’t then show up.
As social scientists, I think what people are looking for are general kinds of regularities, not law-like certainties, but enough of an idea or dynamic that we can, with sufficient confidence, say that there’s something to this being structural and sort of causative in some significant way and not radically arbitrary.
So I guess what I’m getting at is what would need to be teased apart there—and here’s where actually some of the hierarchical complexity findings and methods can be really helpful—is what we would actually want to see is if there’s a level of structural complexity showing up that content-wise doesn’t match the way that Kohlberg described stage five. These models like Kohlberg’s and others are described in terms of their content—the ideas that show up at particular stages. So stage five is very sort of self-society framed. The individual recognizes that they’re an individual in a social collective, and there’s a kind of social contract element, and that’s the justification pattern for their moral reasoning.
Now those ideas require a particular level of complexity to hold in your head and make sense of and reason through, but there isn’t necessarily a reason why you couldn’t be operating at that same level of cognitive complexity but have a different notion of moral reasoning. Therefore, stage five would be content-wise not a universal, but the structural idea of the complexity of that thought might reveal similar kinds of ways of thinking that we could then reasonably call stage five.
This would get into how we could use leptical scoring to try to probe some of these questions. But in short, I would say that there is a significant degree of universality demonstrated cross-culturally through these models. And there’s also more work to be done to expand the scope of that and to apply new methods, particularly leptical scoring and hierarchical complexity, to improve these models and make them more universal and see what other kinds of things show up at the higher levels of complexity.
Jim: Yeah, I thought it was an interesting question. I think my mind is open, but I do think this move you just made is actually a good one, which is probably correct about hierarchical complexity even though the semantics are different. Structurally, it’s analogous with different semantics hung on the tree essentially. Just that in the same way, you can say lots of different things with a three-level quasi-recursive, multi-clause sentence. Right? You have the structure, and then you can say lots of things.
Brendan: Yeah. This is a really important question though that is, I think, really at the core of a lot of the questions that this book series is going to be getting at. Because while I think there’s some range of variability we can expect to see there, I don’t think it’s wide open. Right? I do actually think that because as we learn, we grow and we learn about what’s more adaptive in relationship to reality as we experience it, that we are constraining the possibilities of more complex moral reasoning, if that makes sense. Right? It’s not like you’re going to get up into the higher levels of moral reasoning in terms of complexity and see just as many people saying, “Yeah, you know, it makes just as much sense to nuke the world and take the people’s houses and do whatever you want and be hedonistic or whatever.”
And in fact, my interview with Cheryl Armon, who’s another model featured in this book—she was a student and a colleague of Kohlberg’s—and her data basically says this as much that actually when you are seeing what shows up in these higher complexity levels, they do tend to converge in particular directions. So there’s something constrained. You could say there’s a kind of attractor at these higher levels, which is, of course, to rule out psychopathology and these kinds of, yeah, let’s say, narcissistic and other kinds of issues that show up still for people at high complexity levels that are going to be still in the data. But in terms of if you’re going to have a functioning society and they’re you’ve got educated people and they’re living in that society, navigating it adaptively and finding sort of meaningful information and knowledge about it at the upper registers of complexity, there are certain things that work and that don’t, generally speaking, in those scales of thought. And I think that that’s what these models tend to zoom in on. So there is variability, but it’s constrained variability.
Jim: Alright. Let’s back up just a little bit, and I’ll make another—we’ll—
Brendan: Make another point which we made in a little email exchange too. Just give a very quick Kohlberg scale, and then, the somewhat scary thought of what the data shows about where Americans tend to be on the scale. Yeah. Sure. Okay. So Kohlberg basically had three major tiers. There’s what he calls the preconventional, the conventional, and the postconventional, and each of those three tiers is broken up into two stages each.
So stage one is what he called the punishment and obedience kind of moral reasoning level. That’s basically people making decisions and determining what’s right based on are they going to get kicked in the face? Are they—what do they need to do to basically make sure that they aren’t experiencing pain and can kind of look out for number one? That’s kind of punishment and obedience. It’s a very kind of just basic, hedonistic, egoistic approach.
Stage two, you call the individual instrumental purpose and exchange level, which is sort of now it’s still egoistic and hedonistic, but at least there’s this instrumental factor, which is sort of like you have now the ability to say, “Oh, I’ll do this so that this good thing will happen to me.” And you can be a bit more strategic about looking out for number one. So it’s not just sort of ad hoc and do whatever you do to make sure that you’re okay. You can actually be a bit cunning even or strategic and scheming for getting your perceived needs met. And so all those are both of those are preconventional levels.
You enter the conventional level, which is stage three with the showing up of a sort of what he called mutual interpersonal expectation or relationships and conformity. So this is where people really get socialized into their community in a real way, and they actually start to mutually consider the well-being of their loved ones, their friends and family in a way that is sort of like, “Oh, okay. Yeah. It’s not just about me. It’s about us.” And so there’s a kind of conformist level there that shows up. So it’s like, let’s look out for us, and this tends to be very us versus them and very much a sense of, yeah, trying to looking out for number one, the number one there is now kind of—
Jim: Classic tribal thinking. Right?
Brendan: Yes. Exactly. Stage four is what he called social system and conscience maintenance. So here you’ve got someone in a system who is basically recognizing that the maintenance of that system is important, and also a deeper sense of individual responsibility in terms of conscience—like, I could do this, but I really shouldn’t because it would be wrong in a kind of theoretical or abstract or principled way. And so it’s not just that we do things because we’re the group and we’re awesome and they all suck, it’s because this is a particular way that in order for us to keep being who we are and doing what we do, we have to have some rules and expectations in place. And so in some ways, it’s kind of an extension of that conformist view, but it also starts to get more into a deeper sense of internal conscience and morality and a more abstract sense of the social system.
Then you get out of that, the post-conventional levels. Now I already said stage six, which is universal ethical principles, was pretty just hypothetical and found in some philosophical works. So it’s really just here at stage five. And this is what he called prior rights and social contract utility, which is basically thinking not just of society as society maintenance, but actually a prior-to-society standpoint. Like, what are the things that we would need to be in place for a successful thriving society to exist? And the recognition that we actually do inhabit socially constructed environments, but that these are in place for our well-being and for the collective good. So that’s kind of a rough outline of his stage model. And, yeah, a lot of the findings show that in terms of the American context, very few people—very, very few people—are at stage five in their thinking about moral reasoning and decision making. Most are at the conventional level somewhere, but a very large number are also at the preconventional level.
Jim: That’s the thing that scared the shit out of me. I was totally shocked—depending on who you ask and what source, 40 to 50 percent are at the preconventional level? Could that be true? I mean, it’s just like a mind-boggling thought.
Brendan: I find that a bit high, but I’m sure numbers vary a little bit on this. One of the things that becomes really important is to sync these data up with hierarchical complexity scoring and that sort of thing so we could get better information. One of the difficulties is when you use content matching strategies for these stage models, people can vary. It’s hard to get interrater reliability. So some of those models aren’t going to be as reliable in their findings relative to other kinds using just the complexity bit. But, yeah, my guess is certainly that the vast majority use a conventional kind of style of thinking. And what’s really difficult—and this was Robert Kegan’s whole point in his book “In Over Our Heads”—was that modern society is predicated on these higher levels in terms of what is expected in day-to-day functioning and to understand the systems that we live in and why they’re set up and structured the way that they are.
And what he found was that in similar kinds of ways, most people are at that conformist level of mutual, relational tribal thinking. I actually wrote a blog post about this before the election because it’s very clear to see these dynamics emerge in election season. But, yeah, this is a huge collective problem that we face in our contemporary society of people being able to have the complexity to see why things are the way that they are and why they should be the way that they should be. And what we’re seeing with, for example, a lot of what’s happening right now with the institutional breakdown and decay and the undermining of these long-standing rule of law kinds of ways of thinking—people don’t seem to understand why those are actually good ideas. And they seem like a lot of unnecessary bureaucratic nonsense and namby-pamby sort of good intentions. But there’s a lot that goes into those systems of law and jurisprudence. And when we appreciate the ideals and principles that they’re based on, they make more sense. But what’s disturbing is that a lot of people aren’t getting that. And in terms of the complexity required to get it, yeah, they’re in over their heads in Kegan’s sense.
Jim: Yeah. For instance, due process—it’s expensive, but it’s hugely important. And if you aren’t able to operate at a level of abstraction that understands why the concept of due process is a very powerful dynamic, then it’s “well, just take those child molesters out and shoot them.” Right? Or take the college student off his campus and ship him to some horrific prison in El Salvador. Right? When if you do that, you’ve just destroyed one of the fundamental foundations that have held our society together for a long time. Now, not to say that due process couldn’t use some improvement, but to just say, “Whoa, this gets in the way, slows things down”—bad. I’d say, oh, good. Not good. Now let’s turn this around. I have actually read a few people who have proposed this, which is maybe we have fucked up being in over our heads, and maybe these stages are relatively immutable. And perhaps we should redesign society to be a better fit for stage three and stage two people.
Brendan: I think one of the important things about the developmental stage theories and why I find them so helpful is that they’re not immutable in the sense that, oh, someone’s just at a stage and sorry. I think that a lot of very dark ideas emerge out of some of the misuses of IQ theory, which is so rooted in a kind of genetic inheritance idea. When you’re basically telling people, “Sorry, you don’t make the cut, you’re just hereditably too stupid to get things, and so you’re inherently lesser in society,” that’s a terrible way to consider all of this.
I do think some of the controversy that surrounds stage theories ironically is because people think that those are the kinds of claims that they’re making, which is actually just the contrary—that human development is possible, learning is possible, growing is possible. Yes, there are going to be constraints on that from all sorts of levels. Social, certainly genetic factors probably figure in there. But we’re not constrained in some kind of genetic lottery that predetermines our entire way of being and value as people.
If we actually valued education, if we actually valued a more robust pedagogical system in our society, then that wouldn’t be just a race to the bottom of saying, “Alright, well, I guess we’re all just a bunch of tribal people who want to take people out back and shoot them.” Let’s not build it from that premise. We can actually say no—we can actually come to have more people appreciate why due process matters, and we can try to live up to the ideals that supposedly we hold and that are at least in theory at the core of our society.
I think properly understood developmental models give us a roadmap for understanding how human flourishing can increase, how everyone can find their proper and happy and flourishing place in society regardless of where they’re at in some scale, how there’s a collective need for everyone in the diversity that they bring. Because we are in a social organism that requires variation and selective retention in the sense that we thrive off diversity, and we thrive off of new ideas and more out-there ideas. If postmodernists really understood the takeaways from these kinds of models, it actually speaks to a lot of the values of diversity, open-mindedness, and tolerance and growth that a lot of people just intuitively value. But if we could get more scientific about actually building our systems to help cultivate this, we’d be in a lot better position collectively. And ironically, that’s just what we haven’t done.
Jim: So yeah, exactly. And in fact, the data on movement in any of these scales for people over twenty-five is pretty depressing perhaps. Most people don’t move once they’re twenty-five.
Brendan: Well, and again, it’s sort of like, what might be the causes for that? I know a lot of people just stop reading once they get out of college. So are these human genetic inheritance limitations, or are these social expectation constraints that lead to people flourishing less because of all sorts of social setups that we create for ourselves that then actually wind up inhibiting human growth? In Cheryl Armon’s data, she found that I think it was a woman in her sixties or seventies who wound up going to prison and coming out of it showed a whole level increase later in her life in terms of how she—a stage increase, you’d say—in terms of her moral reasoning and reasoning about the good. This is not something that gets locked in at an early stage. If people are willing to learn and grow and do the kind of hard thing of trying to accommodate more of our understanding to reality and complexify our minds, we can do that. And I feel like that’s a more optimistic vision of human potential.
Jim: Yet I would say it ought to be near the core of our design of our social operating system, but it’s not. The idea that we can all spiral up—we don’t have to be spiraling down. And when we think about the personal institutional spiral that is a society, we need to really be paying a lot more attention to that. Well, anyway, let’s get back to the book. So now let’s turn a little bit closer to the core of the argument, talk a little bit about dynamic skill theory, and then the idea of the Lectical Scale and Theo Dawson’s work.
Jim: Yet I would say it ought to be near the core of our design of our social operating system, but it’s not. You know, the idea that we can all spiral up. We don’t have to be spiraling down. And when we think about the personal institutional spiral that is a society, we need to really be paying a lot more attention to that. Well, anyway, let’s get back to the book. So now let’s turn a little bit closer to the core of the argument, talk a little bit about dynamic skill theory, and then the idea of the leptical scale and Theo Dawson’s work.
Brendan: Sure. And just to recontextualize this to remind people why I’m even getting into all this stuff—real quick. There’s a universal learning process that I talked about in volume one. This is unfolding through these different scales of cosmic evolution: matter, life, mind, and culture. I’m interested in human culture and how we can understand human culture and meaning at that level, which means we also have to understand human learning processes. And that’s why I go into all of this.
We’ve talked about the learning theories of Piaget and Kohlberg. Well, the thing that happens with those is they wind up getting very critiqued and undermined in some ways in the twentieth century. People start throwing them out and saying, “Oh, there’s too many problems here.” So there’s a fundamental reworking that needed to take place with some of the basic insights. Meaning the insights, the basic insights were there, but exactly how we made sense of them all needed some clarification. And that’s where the Neo-Piagetian movement comes from.
Kurt Fischer was a Neo-Piagetian scholar who reworked some of those insights into his model, which he called dynamic skill theory. It’s dynamic because one of the critiques of Piaget’s model was, “Wait a second. If there’s formal logics and they come online at different stages, then how come we see variability in different performances? And how come if you can understand the conservation of volume, you don’t understand conservation of density?” And there were all sorts of very specific arguments that seemed to be empirically undermined.
And Kurt Fischer was like, “No, no, no. Variation, dynamism, that’s what complex beings do. That’s what we should expect. That’s the norm.” The key was to take the Piagetian stages and not think of them as sort of these structures in the mind that kind of came online, but rather that we could develop a common scale for any degree of complexity in any particular task. So you could take a performance and see how someone performs and maybe they score at level 10 today and it’s 10 tomorrow, but it’s nine the next day. Well, maybe on that day, they didn’t eat very well or they didn’t sleep very well. So humans, like other animals and complex phenomena, are dynamic. There’s variability, and that should be baked in.
This is also important because a lot of the critiques that still get leveled at Piagetian stage models are all basically attacking a straw man that not even the Neo-Piagetians take seriously anymore. That was precisely why these models were developed. And so people will still cart out the same old critiques as though Piaget was entirely wrong when it’s like, well, no. That’s not the way it is.
So dynamic skill theory was Kurt Fischer’s model, and he basically took the Piagetian notion of the four stages, which were themselves by that point had substages. And he related this to a scale of hierarchical complexity, which had around 10 to 13 levels on the scale. It was better empirically grounded, and it was a scale that then could be understood to measure a task, a performance in any domain. And this was the other thing too—after Piaget, you got a lot of the extension of stage theory models into various domains like Kohlberg’s into morality and Armon’s into the good and Fowler’s into faith, et cetera. But you didn’t have a general stage model that you could use, and that was really what was needed. Otherwise, we just have this endless proliferation of domain-specific models. But every time you compare those various models, they all seem to kind of relate to each other. Like, Kohlberg stage three looks a lot like Armon stage three. It looks a lot like Fowler stage three. So we needed some kind of more universal metric. And so dynamic skill theory estimation is really the best model that’s come out of the Neo-Piagetian tradition and foregrounds hierarchical complexity as the scale to use as a domain-general assessment metric for any kind of performance.
Jim: I’ll jump in here with my question, maybe objection, maybe pushback, or maybe nuance, depending on how you want to interpret it. This is something that’s been lurking in my mind for years, and it pops up every once in a while. This book has been extremely fruitful, set me on many, many rabbit hole journeys and side researches and all this stuff. So if you want to be stimulated, read the book.
But anyway, one thing that I find often missing from these stories of hierarchical complexity and stages—and I didn’t really see it in the book, you can correct me if I’m wrong—is the focus on the structures without focusing in parallel on what I might call semantic richness or expertise. My thinking all along is that, particularly once you get above the lower-level stages, which are, you know, how the infant uses both hands to grab a stuffed toy or something, probably a lot of people sharpen and develop their intellectual skills in specific domains that they get richer and richer.
An example I posed to the AIs was to imagine two brothers. One’s a complexity scientist. The other is an auto mechanic specializing in repairing vintage muscle cars. The complexity scientist, when he says the word “complexity,” it has this huge history and 500 scientific papers and a hundred books and many, many people and all kinds of very complex nuanced topics. The other brother, the auto mechanic, says “complex”—it’s a synonym for complicated, basically, almost exactly one to one.
On the other hand, the auto mechanic brother, expert, world-class mechanic on vintage cars, when he says “carburetor,” it means all kinds of things about the metal and the shapes and the variations, different suppliers, the strengths, the weaknesses, how things go wrong, how they’re fixed, how they’re measured, et cetera. While the complexity science brother, when you say “carburetor,” he goes, “Oh, I vaguely recall a carburetor is a thing that mixes air and gas, I don’t know, and goes on top of the car underneath the air filter in an old car,” and that’s about all he knows about it.
And so they have essentially been developing their mental toolkits by ratcheting up through semantic richness domains and expertise store domains. I actually did chase down some rabbit holes, and there does seem to be some indication that indeed that is a significant part of how people move up, especially the higher parts of the stack. And I guess I’m a little concerned that focusing too much on the hierarchical complexity stages at the expense potentially of focusing on semantic richness and expertise is not telling the whole story.
Brendan: Yeah. It’s a great thing to presence, and I think that it’s a very oft-cited critique, but I think properly understood all that you’re talking about is entirely what is accounted for in these Neo-Piagetian models. So first of all, domain specific is what a performance will be. You can use a universal scale, but you can use that scale in both of these radically different domains, and you’re gonna get a different kind of outcome there.
And so appreciating that people are variable in terms of the domains in which they’ve developed their skill sets is absolutely key because a lot of the critique of older Piagetian models, at least the way people talked about them often was that someone was “at a stage.” And actually, there’s some degree of truth in the degree that you might tend to operate from a particular range of complexity in particular circumstances, but generally, that’s not really the right way of thinking about it. You can perform at higher or lower levels at different skills in different domains. And so the kind of global thinking that a person “is at” or “is” a stage is more unhelpful than it is helpful.
What you’re getting at speaks to that. Now, dynamic skill theory outlines we’re talking about skills, and so we can think of what a skill is in all these other different ways. There’s a more interesting nuanced element though that is in your argument here, which is we’ve got a complexity scientist and a car mechanic—really adept at the intricacies of fixing cars and a complexity scientist adept at the intricacies of theory, let’s say. You can be profoundly skilled in these different domains, but that doesn’t necessarily mean that skill in a particular domain requires a great deal of abstraction per se.
One of the things that’s interesting is that there’s also the downside that people tend to think, “Oh, you’re just operating at a representational level. Oh, well, you’re lower.” It’s like, no. Skills, that is what you want. You need representational level capacity to be like, “Okay, this is here and that’s there and that goes here,” and you don’t need to say “carburetor” and then draw on a bunch of abstract concepts about how it theoretically works. Most of the skills that we develop in our lives are probably of that nature. They’re getting things done in the world. We move things around. We understand where things go and all of that.
It’s also interesting that the car mechanic might or might not have a very abstract understanding of what goes into the car. You can be a skilled mechanic because you’ve been doing it for fifty years, and you just know from experience this goes there and this goes there. And when I did it this way that last time, it didn’t work well. Or, I’m looking at this system, and I understand theoretically and abstractly and can tell you and justify my decisions using conceptual semantic abstractions, why and how all this goes together.
What I’m getting at there, if that’s making sense, is that a complexity scientist is gonna need to use abstract conceptual terms that are reaching into the levels of abstract systems into single principles. You can’t talk about the subject matter without drawing on that vocabulary. You can fix a car with or without that. And so what you would need to get at what’s going on there skill-wise would be to analyze some kind of performance and see what the actual linguistic justifications—if we were gonna use the lexical scale to measure hierarchical complexity—that actually go into a person’s decision making to fixing the car. So yeah, there you see how this is kind of a multidimensional thing.
Jim: Yeah. It’s interesting because I actually know some top auto mechanics, and they are of both sorts. There’s some of the old school boys who just busted their knuckles so many times, they know the right way to do it by doing the 998 things that didn’t work. And there are some other, I would call them theoretical auto mechanics. They understand what a Venturi is. They understand a whole bunch about how the car works as a multiscale system that all has to be working more or less simultaneously in all linkages in time and space, but that’s a minority for sure. And so that’s an interesting way to then take my little simple example and then take it in a level deeper, and it actually does sync up to the hierarchical complexity argument. I like that. Good. Well done. Let’s now move on—time, time, time. Wish we had four hours instead of two. Talk briefly about the Lectical Scale, which I know you have been using quite a bit and you reference a lot in the book.
Brendan: Yeah. So I keep—and I’ve even been referencing it a lot in this conversation—so let me kind of introduce that. Out of the Piagetian models, we get neo-Piagetian models that advance and refine them in the eighties and nineties. And eventually, as I said, there is a recognition that what we really needed was a universal scale or metric for assessing skills in any domain. That would be sort of the holy grail to find, but how would you potentially even do that? Because it seemed like content matching was the only way to be considering someone’s complexity.
What happens in the early twenty-first century is Theo Dawson, a colleague of Fischer’s and Commons, sets about developing that kind of metric. Over the course of around thirty years, she develops a very sophisticated tool to be able to measure the hierarchical complexity of performance using linguistic text or linguistic performance. What this allows, I’ll just say, is ultimately an automated system that can tackle this problem. Because rather than needing individual people to assess and score, you can actually generate a computerized ability to track the structure and abstraction level of the words and their distributions in a performance and use that to give a very precise, reliable, and objective reading on hierarchical complexity.
To do that requires creating this vast database of indexes of terms and semantic units that are indexed to particular complexity levels at a fine-grained level, and then measuring the distribution and performance. The amount of time and energy that went into actually creating that is pretty mind-boggling. But today, it exists, and Lectica is the organization that Dr. Dawson has created that uses this measurement scale. It’s a very powerful tool that, for my purposes, is particularly significant as I’m interested in looking at the hierarchical complexity of ideas as they’re evidenced in texts at the individual and collective level.
As I was learning more about this scale and the tool of the Computerized Lexical Assessment System, or CLAS, it seemed like this was just this incredible opportunity to explore how ideas have complexified in human history by looking at texts across the human cultural record and being able to understand collective societal-level learning. Then we can sync that up to what we know about the individual scales, the individual-level learning through these developmental models we’ve been talking about because you can use the same scale to look at Kohlberg or Fowler or Armon, and make these kinds of comparisons. So in brief, that’s what the Lectical scale is, and I find it to be the cutting edge of developmental psychometrics and, I think properly understood, is revolutionary.
Jim: Yeah. Reading this book made me really interested in it too. I’ve been doing a bunch of research on it, so we shall see what comes out the other side. Well, now we spend an awful lot of time setting things up. So now let’s go to what you call part two of the book, I think. And this was new to me, and this was interesting.
Jim: Yeah. Reading this book made me really interested in it too. I’ve been doing a bunch of research on it, so we shall see what comes out the other side. Well, now we spend an awful lot of time setting things up. So now let’s go to what you call part two of the book, I think. And this was new to me, and this was interesting.
Brendan: The idea that you could link hierarchical complexity to the construction of the self. So now we’re finally getting—yeah, we’re getting into the meat of the book, really. And what I’m interested in, to say it again, is meaning. I’m interested in tracking the evolution of meaning in human culture. And so everything we’ve been talking about, again, to recontextualize all this, is a clarification of the dynamics of human learning as a complexification process in the same sort of way that cosmic evolution unfolds through complexification and learning at multiple levels of existence.
To zoom in at the culture level and to think about what it means for a human person to learn meaningful information specifically, that’s what part two of the book is all about once we have under ourselves the understanding of sort of these general patterns and all of that. From this point on, I turn to a few models that are particularly getting at the development of meaningful information. And again, tracking is all the way back. We’ve got a sense now of meaningful information that we can kind of ground in sort of thermodynamics and information theory. Here, I’m looking at that at the human level, at the individual level, and saying, alright—how do humans make meaning and how can we understand that as a complexification process?
To do that, I first begin with a couple of models that look at the development of people’s conceptions of themselves as a self, as an ego. I look at developing and evolving notions of value relative to having such a notion of a self. And then I look at how ideas develop around kind of ultimate value, ultimate concern, the ultimate environment, and essentially God and the sacred, which is the model that we get from Fowler and others.
That was sort of what I was taking up in volume two. So to begin with the self, how do we complexify our notions of ourselves? Well, one of the basic insights that I think we take from sort of the Piagetian and neo-Piagetian traditions is that when life begins, you don’t have the kind of categories that Kant was talking about sort of pre-given. You actually have to learn those. There’s an accommodation process that as you move through the world, you start to differentiate more and more things and complexify your thinking. So you show up in the world, and you’re in a kind of chaotic state of duality. There’s neither self nor world—it’s sort of all this buzzing confusion, and that is kind of the beginning of the self experience as a human being.
Robert Kegan developed a model of the kind of subject-object relationship and how that itself develops and complexifies through the lifespan. And what I did was I looked at that model. I unpack it a bit in terms of its basic mechanics and how that works. But then I also scored interview material from these different stages and found correlations to these different stages and Lectical scale. So for the first time using Kegan’s model, Commons’s model, Fowler’s model, Kohlberg’s model, and coming up with actual quantitative associations in terms of hierarchical complexity on the Lectical scale. And that’s kind of the, I would say, most innovative and new thing that’s coming out of this research that I find the most exciting because no one’s ever done it. And then you can actually begin to make certain kinds of claims about the comparability of certain developmental models to each other in terms of their complexity levels.
So to your question, let’s start with self. You start from that dual undifferentiated state, and Kegan has a five-stage model where you basically move—and I should mention too, Kegan was himself a student of Kohlberg’s, so again, a deep continuity of what emerges out of these traditions. But Kegan talked about the first order, second order, third order, fourth order, and fifth order consciousness, which is what comes online as these different principles of organization come to structure the self.
That starts at stage one with what he calls a kind of episodic notion of the self. This is young children. This is that sense of there’s this experience and then there’s this experience, and you’re not really drawing connections between them. So everything’s very immediate. You’re not making logical connections, and this is kind of just the self-concept that basically kids have up until five or six or so.
The second order self is where some of that durability starts to come online. People start having a sense of being a self, of having particular traits and qualities and needs and desires and needing to meet those needs and desires and having a basic kind of instrumental notion of themselves.
The third order consciousness is that mutual state where actually the self is now taken into a broader social context and the self is based in its relationships. It is its relationships in a sense, and that’s sort of the structuring element for the self.
From there, it develops or can develop into a fourth order consciousness, which is where the complexity of one’s relationships and who they are in different contexts itself needs to develop a kind of systemic mode of integration into a higher order orientation. So you need to not just be like a loving mother to your children or a loving father to your children. You are also a valuable player on your soccer team and a successful CEO in your company. And you can begin to play multiple roles in multiple contexts and have a higher order integration of your sense of self across all of those contexts. And that would be the fourth order sense of self.
And then finally, there’s this fifth order consciousness which is a trans-systemic notion of the self. And this is basically beginning to recognize that the sort of sense of ideological integrity that held together the fourth order consciousness version of self is itself a kind of social construct that comes out of broader systemic forces that shape these kinds of things. And so each of these kind of stacks on top of the previous and builds on previous gains. And what I was able to show in this research was that this follows a hierarchical complexification process, which in some ways isn’t a huge surprise given that Kegan’s coming out of this tradition and very explicitly framing his model in terms of complexification. But to be able to now, for the first time, have some quantitative findings that confirm and kind of place that complexification process on the Lectical scale was really cool.
Jim: That’s interesting. Now, one thing you touched on briefly in the book, maybe you can go into a little bit more here. The theme of this book is symbolic learning. How do you tie symbolic learning to this process of ego bootstrapping? Why is it symbolic per se?
Brendan: So symbolic here just means we’re talking about symbolic information processing, which again in the Unified Theory of Knowledge framework is what characterizes the culture plane of complexity and distinguishes it from, say, the mind plane, which has neuronal information processing. So you move from cognitive learning to symbolic learning, and you’re processing language. And so this is all unfolding in linguistically mediated human cultural contexts.
Now why that’s significant, particularly in the context of self-development, is because your ego is a story. And so one of the points of convergence that I found very interesting was that in the UTOK model, you’ve got the notion of the ego forming in a tripartite sort of way, which is a linguistic justification layer on top of a kind of phenomenal experiential layer. We are primates still—we’ve got that kind of cognitive processing going on and having subjective phenomenal conscious states and valence quality, all of that. But then we invent language and now have this story in our heads that is able to add a layer on top of our phenomenal experience and give some kind of stream of consciousness linguistic accounting. And that is really what your ego is doing all the time.
Because language is a kind of collective phenomena that develops in these cultural contexts and shared social contexts as we were talking about right at the outset, that means you’ve got other people in your head. You’re always justifying yourself in a sense to yourself, but like other people. And so everything that you’re kind of doing in your decision making is mediated now through a linguistic layer. And because it’s linguistic, that’s symbolic information. And so that means that interestingly, we can actually look at how people make decisions and justify those decisions using the lectical scale to give us a sense of the hierarchical complexity of ego formation, which I find really fascinating. And when you do that, you do actually find that that is indeed a significant way of reading what’s happening in ego formation is the complexification of our justification systems as our egos.
Jim: When I was reading that section on Kegan scales—the story I often tell here on the Jim Rutt Show podcast, so this is not new to most of my listeners. When I was eleven, I had been a somewhat devout Catholic as a kid and was quite fascinated, the same way as I later got fascinated with Lord of the Rings. I was really quite fascinated, particularly with the Old Testament, and I had a really good Sunday school teacher, Catholic CCD when I was in fourth grade, I think, Mr. McIntyre. Really good. Very stern and strict, but he was intellectually engaging to the reasonably intelligent fourth grader, and I really got into it.
But then I also started getting into science and reading a lot of history and things, and I just started seeing the stuff just kind of doesn’t quite all add up. And so when I was eleven years old, somewhere between sixth grade and seventh grade—back in those days, elementary school went to sixth grade, junior high school started in seventh. There was way too big a gap in freedom between sixth and seventh in those days, and a lot of us got in trouble, me included.
But anyway, during that time, I was in some liminal state where I spent like two weeks at summer going to the library researching the world’s religions. Being a little proto-scientist, I read the write-ups for lots of religions in two different encyclopedias to make sure I got some parallax. I also found—you might know this as a scholar of religion—there was big old fat book about four inches thick. It had a light blue cover on comparative religions. And I flipped through that, read fair bit of it. Not the whole thing. Must have been 800 or 900 pages or something.
Anyway, after doing all this, I stopped and thought about it, and I concluded that all these various systems were clearly man-made, and at the time, I was a little bit naive, for the purpose of controlling people, and that they were obviously nonsense. And why does everybody believe this stuff? And, oh by the way, Catholicism is one of these. It was very profound. In fact, I call it, somewhat ironically considering the topic, an epiphany. That humans build these systems. Now today, I would modify my insight to say that probably most of these systems were initially created in good faith by crazy people who happened to be very charismatic and basically have a crazy contagion and got some crazy followers. But then relatively quickly, they evolved to become control mechanisms for power and wealth, et cetera.
But anyway, so I guess the whole point of all that was, according to Kegan, that sounds like a fifth-order consciousness kind of thing—analyzing multiple systems on some general principles, et cetera. And yet, I was a fucking eleven-year-old kid. I was just an obnoxious little brat, and I liked softball or baseball in those days and eating Turkish Taffy and trading baseball cards and reading comic books. So how could—if this is true—could someone do something like that when they were eleven when otherwise they were just an eleven-year-old kid?
Brendan: Yeah. Well, I would hate to burst your bubble a bit, but I would be very surprised if eleven-year-old Jim Rutt was, you know, fifth-order consciousness based on my research findings. That would require a level of complexity on the Lectical scale of, like, sort of high level eleven, which you really don’t get to developmentally—isn’t seen before, like, eighteen, nineteen into really early twenties.
Jim: Yeah. That was my point. It seems highly unlikely I was actually at a fifth order, but I was sort of behaving as if I was. I mean, that’s a fifth-order kind of behavior, I would say.
Brendan: I think this is where the structure versus content thing starts to become a really important issue. I’ll give you an example from my research findings that I think makes sense here. It’s a good segue actually into the faith development theory model that I work with in the book and I’m also doing a lot of research on. In that model, it’s another kind of five- or six-stage model. There are ways that people can move through their faith journey that content-wise might sound like they’re at a higher stage when in fact they’re kind of representing a lower structure in doing so.
For example, in Fowler’s model, you move from a kind of conformist sort of what he calls the synthetic conventional stage—that’s stage three—to an individuative reflective stage, stage four. This is where you start thinking critically and examining evidence and this sort of thing. In content terms, a lot of people talk about this as disenchantment, as disillusionment, as a movement from belief to atheism, what have you. But once you have ideas that might have emerged at that structure, then you have content that people might pick up and deploy at other kinds of structural levels.
If you’ve known any kind of fire-breathing atheists really keen to evangelize their point, it’s actually really interesting how those structures are much more conformist and actually synthetic conventional in nature than they are individuative reflective. They’ve just hit on a symbol set, a set of ideas that they can embrace as their ideological worldview in the same way that a religious zealot would. The content’s just different.
So what I’m getting at is that we always have to be careful about knowing what the content is versus the structure and parsing those two things apart, and that these things can diagonally relate and cross-pollinate in all sorts of complex ways. Without having a recorded interview that we could analyze for Lectical score and all that, it’s hard to know retrospectively what actual level you may have been operating at. But clearly, it seems developmentally appropriate to probably be moving from the synthetic conventional towards an individuative reflective phase. You were probably a precocious thinker in the 1050-1060 range on the Lectical scale, which is sort of like moving out of stage three into stage four.
Jim: Yeah, I certainly didn’t. Was essentially making a comparison to, is it true? Are their claims true? That was really what I was interested in. And my conclusion was no, their claims aren’t true. The whole thing was evolved or built or invented for some other purpose. And that was really all I was looking to get at and didn’t care about why had these things evolved. Now, of course, I spend a lot of time thinking about such things, but that is quite interesting.
Brendan: A quick plug for something coming out of Lectica soon, called MindLog. Pretty soon, this is going to be a scoring software that’s available for people to use to chart their own individual development across their lifespan. If you had, like I do actually, some documents, some letters, some texts that I’ve written when I was very young—ten, eleven, twelve—grappling with existential questions, once this comes out, you can put that in there and see what the actual Lectical score was and start to see the developmental curve across your entire lifespan.
Jim: Yeah. With online now, that will be a lot easier for people to do. Right? Because if I was a snotty but eleven-year-old, I no doubt would have sent long and boring emails to people on this topic rather than just haranguing them on street corners. Right? That was a good review of sort of the bootstrapping of ego. And under this system, Greg would also agree with Sperry and Kegan, that ego is a human-only thing. Do you agree with that? While consciousness, most of us consciousness scientists agree, most animals, at least mammals and birds are conscious. But under this definition, because it’s rooted in symbol, it’s probably only humans or, yeah, at best, chimps and maybe elephants or something.
Brendan: No. I think it is exclusively human because to the degree that language in the kind of language that we use, with grammar and propositional claims and all that is distinctly human. I think that framing allows us to understand what we mean by a distinctly human ego and then make the distinction between a person and an animal. I certainly think that, yeah, you know, primates and elephants have very profound conscious states and emotional states and social relationships, etc.
Jim: They have cultures.
Brendan: For sure. And cultures. At least to the extent—yeah, I mean, this becomes semantic to some degree, but I think I know what you—I would agree with all that. But, yeah, to the degree that we as humans have this additional layer of symbolic information that’s able to engage in these justificatory dynamics that we internalize and then wind up sort of ratcheting up an ego internally, that’s I think different.
Jim: Okay, let’s hit quickly on Carol Gilligan’s complexification of values. That’s very, very interesting.
Brendan: Yeah. So, again, Carol Gilligan was a student colleague of Kohlberg’s, and she wanted to see something a little bit more broad than what Kohlberg was getting at, which was really about moral rightness and what was the right thing to do. She was interested in the good. So how do people make evaluative appraisals, and what kind of justifications do they use for those sorts of things? So her category was a bit broader and not limited to the moral component specifically. And I found that really interesting, particularly for my purposes of trying to track the evolution of meaning across human culture by looking at these models individually. Because what you see there is a similar sort of progression as it is through the moral stages, as it is through the self stages of Kegan. But here, people reason differently about what is good. So it starts out very kind of, again, egoistic individual—you just want to get your immediate needs met. It moves on to an instrumental sense of, “Oh, I can use this or these people to get my needs met.” And then that moves into a kind of mutual effective of, “Oh, my needs are also related to the group’s needs.” So if I’m good and they like me, then everyone’s happy and that’s all good. And it basically follows the same sort of sequence. And I was very impressed by Gilligan’s model in terms of how rigorous it was, and how well it tracked with the hierarchical complexification trend, and I have some lectical scores for that. And, again, we see these levels showing up at particular stages of complexity, which I guess if you want to get the major takeaway from the research findings of the book is that these stages are real. They’re not just pulled out of nowhere. Like there are requisite levels of complexity that are needed to think in certain ways about topics in certain ways. You can’t have a notion of collective good for society and personal integrity absent a kind of systematic level cognition. Like, words like society and collective good demand that level of complexity. And so being able to situate these models and these developmental sequences in terms of the hierarchical complexification sequence was really interesting.
Jim: Well, let me again push back a little bit on this—on the semantics versus structure, and this may be related to some of the critique of Kohlberg. So for instance, in Eastern societies, the collective as more important than an individual is something pounded in the kid’s head from a very young age. So they might not be anywhere near as high in hierarchical complexity to move the collective ahead of the individual because of the essentially, the domain specificity of what they were taught, you know, at a rote level with no higher level concept at all. How would you respond to that?
Brendan: Yeah. That’s interesting. I mean, I’m sure there are going to be cultural variations to some degree. And I think one of the questions there will always be this issue of when is a particular term or idea useful or functional to someone at the complexity level at which it’s designed to operate in some ways. Right? I mean, you can hand an eight-month-old a drill, but they’re not going to use it very well because they lack the requisite complexity to properly put it to use. But they’ll still use it in some way—they might use it as a hammer or to bang something. So people can make use of things beneath the level of complexity at which they were created, and there can be certain social expectations that they do so, that people say the right word.
But I think this is also a kind of universal experience in learning. It’s like, “Oh, I never really got what that meant until right now.” You know? Like, “I’ve been saying it my whole life, but I never really got it.” So one of the things we can do with Lectical scoring, because of its level of fine-grain refinement and precision, is actually track how seemingly the same ideas might complexify in terms of their meanings. Right? So if you were to ask someone, “What does personal integrity mean to you?” Or even to step back, if someone were to say, “Is personal integrity meaningful for you?”—let’s say everyone says yes, right? Because of course, who’s gonna say no? Now, do they actually know what personal integrity means? The only way you get at that is if you ask them why. Right? Why is it meaningful to you? And they say, “Well, you know, it’s really important to do the right thing or you’ll get in trouble.” Well, they’re revealing a structure now that’s actually not what that word is kind of getting at.
And so I think that some of these terms in different cultural contexts, like let’s say honor—maybe a five-year-old is told honor is really important, but they’re probably going to need to be around 11, 12, 13 before the idea of honor actually makes sense to them at that level. So there’s all sorts of ways that these kinds of semantic terms that we swim in culturally and are enculturated into don’t really come online functionally in a way that we can ourselves justify to others at the requisite level of complexity needed till later. That’s just one angle on a very fascinating question, and I think an important one. But certainly, there will be other ways in which cultural differences genuinely influence the kinds of meaning-making that people engage in. And one of the things that we should try to do is look for the regularities in those diversities as well.
So I don’t want to just erase what potential differences there might be, but I will say that it does seem like cognitively speaking, this complexity thing is something you can’t just get around. It’s not like you can just have a different society where other things matter and then someone gets a complex idea sooner. That’s just not really how that works—absent, let’s say, maybe conditions in which the kinds of building blocks needed to generate that kind of concept might be more immediate in their cultural environment than they are in others. There’s a fascinating plethora of angles into these questions.
Jim: Yeah. Very interesting. So let’s talk about the statistical distribution of where people are on these various curves, and your argument, which you support reasonably well with your Lectical analysis, is that all these stages that you’d investigated at least seem all to have hierarchical complexity as the independent variable behind them, or at least to a significant degree. Research I’ve looked at is, as I said, the rate of change for adults is relatively low. It happens, but it’s not that high. It has statistical distributions. So I guess first question is, do we know if those statistical distributions of where people are, let’s say, in the hierarchical complexity realm—are those curves similar in different societies, or are they different, or are they similar? Or universal in the statistics of distribution?
Brendan: Yeah. Good question. Well, starting just out with what the numbers are—based on data that Lectica offers on the general adult population, there are a couple of developmental curves, and they’re in different degrees of probability in the broader society. So if your curve developmentally plateaus—and for the record, yes, it is true that as we get older, we don’t learn as quickly and grow as quickly as we did when we were children. So there’s always this leveling that occurs, but the rate at which we plateau differs a lot depending on all sorts of factors. And so you can be—for some people, they might only level out into their sixties and seventies. And for other people, they’re basically done with change after 15 years old. So the question I’m getting at though isn’t—
Jim: So much the individual trajectories as comparing cross-culturally. Are the distribution curves of the different stages similar across cultures?
Brendan: Well, my hypothesis would be no, but I don’t have specific data on that. I was just going to speak initially to what we know about the general US adult population, which, for just a benchmark—about 56 percent are probably operating at level 10, 34 percent at level 11, and then the margins on either side of that. So if you just work from those numbers, would 34 percent of adults in other countries be at that level as well? My strong hypothesis would be no. It would very much depend. I think if you were to look at, say, Denmark, you probably have more people—maybe 45 percent—operating there potentially. And then if you look at sort of a subsistence-level country that gets really hit by war like the Congo, or places like Zimbabwe that have very strong survival values and these kinds of things, lacking a robust educational infrastructure and so forth, I’m sure they’re going to be much lower.
Now some of the research that I’m doing relative to these questions is going to take a different angle, looking at some of the World Value Survey data, trying to make correlations with developmental level and trying to see how these kinds of values shift and how we can look at global population data and make these kinds of developmental assessments potentially. It’s a really interesting avenue for consideration. The broad hypothesis seems to be pretty validated across a bunch of metrics—certainly the modernization trajectory that leads to industrialization and higher education levels in a country’s population directly affects the cognitive styles or value structures of a particular society. We see lots of data showing that as modernization and post-modernization occur, you get different sets of meaning-making systems showing up. My strong hypothesis would be that that’s also going to correlate strongly with developmental level distribution levels as well, but data is TBD.
Jim: Very interesting. So if we’re thinking about trajectory of, let’s say, our society in the future, how might we think about, especially the curve, the distribution? Do we want more people at higher levels? Do we want a broader curve? Is it important to have a lot of people at ten to provide ballast for a society? I know in your section on faith—I don’t know if it was in you or one of my side researchers—somebody conjectured that traditional religion probably doesn’t do well unless there’s a lot of people at stage three on Fowler’s scale, as an example. You know, is organized religion good for society? Anyway, an opportunity to speculate here a little bit.
Brendan: I always say we should work from wherever we’re currently at and honor people’s experiences and the diversity of people in our society across a whole range of differences. I think things become problematic if we try to push certain kinds of developmental approaches. There’s a whole thing called the Piaget effect actually in the developmental literature that shows what happens when you’re less interested in people organically growing, learning, and engaging in more spontaneous human flourishing through the kind of serotonin-dopamine cycle circular reaction of learning. And if you try to just push rote things—”oh, we gotta up people’s levels,” that sort of thing—we don’t want to do that.
It’s also the case that any complex social structure thrives off of a kind of diversity—we don’t want just homogeneity, whether that’s cognitively or anything else. So those are important caveats. But I do think that if we want to live in a society that values things like rule of law, has a more idealistic set of concerns of tolerance, open-mindedness, growth, and values that actually reflect human flourishing more, then I think the evidence points to the direction that we want to favor robust education systems that increase the level of complexity, making people members of a society in which all those things make sense to them. Therefore, they’re less likely to engage in that kind of authoritarian reflex like we’re seeing now, where all this complexity winds up eroding.
So it’s a bit of a mixed answer. I would say on the whole, yes, it’s great to have that level of complexity to live in those kinds of systems. But we also want to be careful about all the potential ways that kind of good intention can go terribly wrong. And we’ve seen that with standardized testing and overthinking what the significance of IQ tests and all this stuff does. I think what we really want is a society in which people have the ability to develop and grow freely and with robust, strong thinking minds. And I think you want to create a set of conditions rather than try to aim at a set of outcomes to achieve that.
At the same time, I don’t want to sound just radically relativistic. These are systems of complexity that are correlated with different kinds of values and ways of being in the world. So if it is the case that instrumental hedonism and taking advantage of other people to get your needs met and not considering your environmental context or externalizing things in terms of environmental degradation—if all those things actually are related to not properly appreciating the complexity by lacking the kind of complexity required to understand what’s really needed there, then, yes, of course, it would be better to have more complex minds across societies so that we could be living in a more collectively flourishing complex society together.
Jim: Well, you got five minutes to go to the last topic here. Sorry about this. Which is your major meaning systems, a synoptic map of worldviews, color coded, which I famously hate, but that’s alright.
Brendan: We kind of skipped over Fowler there, and that was in some ways directly related to this, but kind of one of the motivating forces behind this book is talking about the evolution of the god concept and what that looks like through these different complexification trends. But no time for god in this—
Jim: I intentionally skipped it because we get all we do is argue about that one. I mean, to my mind, god is a category error best expunged from our vocabulary. Alright. Maybe we’ll just do an episode on just the god concept.
Brendan: Sure. Because there’s a lot there. But, yeah, in the remaining four minutes to talk about the global human meaning systems, I think that the integral model of Ken Wilber and the kind of integrative metatheory that’s done in that tradition of which he’s a part and includes other metatheoretical models as well is really, really helpful for understanding big picture takes. And so at the end of the book, I do try to bring that in but try to give it some updates. I think that a lot of problems have emerged by people misusing developmental models by doing the color coding thing and saying, “oh, you’re green or you’re blue.”
Jim: Fuck those peoples. What I say to them.
Brendan: Yeah. And I think that all that’s really justified. So I want to avoid any of that. There is still, at the same time, value in seeing what is similar across these different models. And to the degree that Wilber was doing that with his integral altitudes of syncing up these models in the same kind of ranges, then it was like, well, yeah, we don’t want to always have to say Kegan two and Fowler two and Armin two, we can say red, you know? And to the degree that we can empirically justify that, I think that’s an exciting prospect.
The major takeaway at the end of the book is that this research does allow us to do that. So I very intentionally add a kind of subscript of HC for hierarchical complexity onto these color codes so that we can talk about amber HC and orange HC—so that we’re very clear that when we’re talking about something, we’re referencing empirical data and trying to gesture to a meaning structure that unfolds across different developmental domains, whether that’s self or value or faith or what have you. Those actually share qualitative similarities and structural similarities.
This is my attempt to give that model a little bit of an update. It’s also my attempt to give credit to Wilber—people have critiqued me for not foregrounding him enough, but he really is very important in this line of research of worldview developmental studies. This is my intent to carry that lineage forward, but also try to give it the added nuance and update that I think we need if we want to avoid the oversimplifications that tend to lead to misuses. So that’s what I try to do there.
Jim: And it’s quite interesting and a little less goofy than most of these color schemes, though I still have my objection to color coding of people, but it was good. Anyway, this is a long episode, one of the longest ones I’ve done in a while, and we still didn’t hit all the things on my list. Though you can see, the god concept is there in my notes. So I did intend to talk about it, but we got to the very end. I figured it’d be more important for you to introduce your color scheme, rather than for us to butt heads needlessly about the God concept. That’d be fun to do another episode.
Brendan: Yeah, let’s. That’d be great.
Jim: Psyche and symbolic learning, right? Is that it?
Brendan: Yep. Volume two of the Evolution of Meaning series.
Jim: Yeah. And as you can tell, I got into this damn book. I mean, I don’t know how many hours I spent reading the book, doing side research, writing software, doing all kinds of crazy things. So I want to really thank Brendan for writing the book and agreeing to come on our show and talk about it with a curmudgeonly old dude.
Brendan: No, this was awesome. Thank you so much, Jim. I really, really appreciate it. Look forward to talking about volume three. And yeah, anytime you want to talk about God and Complexity, I’m happy to go there.
Jim: Yeah. Let’s do it.