Transcript of Episode 113 – Zak Stein on Hierarchical Complexity

The following is a rough transcript which has not been revised by The Jim Rutt Show or by Zak Stein. Please check with us before using any quotations from this transcript. Thank you.

Jim: Today’s guest is Zak Stein, a writer, an educator, and a futurist working to bring a greater sense of sanity and justice to education. He’s been on the show before. In fact we had him here three times in pretty short order episodes, 57, 60 and 62. And we worked through his very interesting book, Education in a Time Between Worlds, in some considerable depth, over all three episodes. So, if what you hear is interesting to you and you want to know more about Zak’s thinking, more generally about education, go check out those three podcasts; 57, 60 and 62. Welcome Zak. Good to have you back.

Zak: It’s good to be here, Jim.

Jim: Yeah, we’ve had such wonderful conversations and got such good feedback on them. Figured, “Hey, let’s have him back again on something I’m interested in.” A little bit background on Zak; he studied philosophy and religion at Hampshire College and then educational neuroscience, human development, and the philosophy of education at Harvard. He’s the co-founder of Lectica, a company we’ll talk about a little bit, a nonprofit dedicated to the research-based justice oriented reform of large scale standardized testing in K-12 higher education in business. So, today we’re going to talk about an interesting, somewhat narrow topic that Zak knows a fair amount about. And that’s a concept called hierarchical complexity. And before we jump in, one of the things I dug up in my research, is that people talk about hierarchical complexity, like the contrast it with non-hierarchical or so-called horizontal complexity. That might be a good place to start, to draw a picture of what we mean when we talk about hierarchical complexity. Could you tell us the difference between vertical hierarchical complexity versus horizontal complexity?

Zak: Yeah, absolutely. Let me say a few things first actually, because there’s a historical story about the emergence of the construct of hierarchical complexity, in the field of psychology, which helps to actually orient people even to this issue of horizontal versus vertical complexity. And yeah it’s worth saying, as you mentioned, this was the focus of my graduate school and my scientific training as a developmental psychologist. And so I worked with Theo Dawson who Lectica is her brainchild. And she specifically did psychometric innovation around this construct of hierarchical complexity. And I worked with Kurt Fischer who one of the foremost neo-Piagetians’, also did important empirical work, to validate the construct of hierarchical complexity. They were both colleagues with Michael Commons, who actually kind of coined the term model of hierarchical complexity. And so I was kind of stationed there studying with them, but the notion of hierarchical complexity is actually the emergence of one of the longest continuous research projects in the field of psychology.

Zak: The construct first emerged actually almost a hundred years ago with Piaget’s. If you wanted to date it, you could date it with Piaget’s publication of The Language and Thought of the Child in 1923. Before that there were shades of it in people like James Mark Baldwin, and you can find it in Herbert Spencer, and you can even find it in the natural philosophies and philosophies of mind because it is a ubiquitous property of mental processing, we’ll get to that. But the point I’m making here is that there emerged in the ’80s and ’90s, what I’ll call neo-Piagetian consensus on the formal definition of stages across lifespan development. Which is a long way of saying that this whole complex field of human development, which had hundreds of researchers in it since Piaget if not more, eventually distilled this core property that characterizes what the difference is between a baby rolling around with its reflexes in the crib and a young child able to circumnavigate the room in that lesson they will have an abstract conversation and an adult able to do theoretical physics, right?

Zak: From Cradle to Einstein, there’s this fundamental difference in developmental differences, the field of developmental psychology. And so the question like if there’s so much that’s contextual in development, there’s so much that’s social, there’s so much that’s culturally relative. There’s so much that’s a unique and particular to an individual. Are there universal things that you can use to characterize development across the lifespan, across culture, individual? And so hierarchical complexity is essentially what emerged from that set of questions. Many other things emerged too about hierarchical complexity became the thing that could be distilled into a formal psychological measurement system. And this is what Theo Dawson really, I think, did the most pioneering work in, in the field of psychometrics bring in together with this developmental construct of hierarchical complexity. And so horizontal complexity also has been researched by developmental psychologists. And it’s a basic issue in learning to say, once you figured out how to do something, let’s say, I don’t know, tie your shoes, then you can tie any number of shoes.

Zak: But if I put a thousand shoes in a room, it’s going to be very hard for you to tie those shoes. There’s more and more of the same task, more and more of the same kind of task at the same level of complexity, that’s horizontal complexity. Vertical complexity, or hierarchical complexity, it’s when you’re not just doing the same task, you’re doing a fundamental or qualitatively more complex task and that’s hard in a different way. So making a shoe is different than tying the shoelaces on a shoe that’s already made. And making a shoe is hierarchically much more complex than tying a shoe. So it’s more difficult, but is making one shoe more difficult than tying a thousand shoes in half an hour? So that’s like I don’t know. And so when you’re faced with the question of, why did a person not succeed at a task?

Zak: Why did it overwhelm their capacity? You can answer it in either way. And sometimes it’s both, but sometimes it’s one. Did they fail the math test because they weren’t able to do that type of problem, it was too complex for them? Or just that there were too many of those problems? Or that they were distracted by their phone and other demands on horizontal complexity? Or is it the case as I mentioned, that it was too hierarchically complex that demanded too much of an integration of lower order capacities that had already been made bastard? Right? So that’s some of the different. So hierarchical complexity is unfolding over the course of a lifespan and unfolding minute to minute as you’re learning, it’s a ubiquitous process and the construction of skill and the creation of new skill out of prior existing skills. So before you can tie a shoe in the sensory motor domains, you need to be able to manipulate the individual laces and you need to be able to understand some of the notions of tension and other things you learn at an almost muscular level about how to manipulate objects.

Zak: And then you apply that mastery to a very specific, higher order mastery in vertical complexity, which is to fold over the strings in a particular way to make the bows or whatever the knot is. And so that’s a basic example of that process of hierarchical integration, where the many lower order skills become the single qualitatively new, more complex skill and we can get into that. That’s the most basic thing, the hierarchical integration, which makes emergent new levels or higher orders of hierarchical complexity in skill development. So, yeah, so that’s the basic and once it was distilled as a construct, then it became possible to operationalize in educational contexts and research contexts. And specifically in the work of Kurt Fischer’s dynamic skill theory, you see what is a very abstract, almost mathematical construct as articulated by Michael Commons, put in the context of a richly dynamical embodied and embrained person.

Zak: And so I think the important thing to get that the model of hierarchical complexity is like a thermometer or a ruler. It’s not a rich, descriptive psychology, it is a uni dimensional invariant property of psychological life that’s been distilled and is measurable, but you have to put on that very abstract skeleton, a whole bunch of psychological and even biological theorizing to have that construct makes sense of human behavior in medius res, right in the middle of things. And so that’s what Kurt’s dynamical skill theory does. So often when I speak about hierarchal complex, I usually end up switching to speak about skill theory, because then you can speak about how hierarchical complexity actually manifests in human skill and behavior. So, yeah, so there’s of course more to say there, but that’s the fundamental way in, I think, is to see that they’re emerging out of a particular neo-Piagetian consensus and that has a lot of explanatory capacity and a lot of empirical backing. So yeah. I’m curious where you’d like to take the conversation.

Jim: Yeah. Just a little example that I pulled out of something I read. Listeners know, I usually spend 10 hours researching a podcast, something like that, and go every which way looking for stuff. One example they gave that sort of falls between the two perhaps, but they ruled it to be non-hierarchical, was something like taking an elevator from the lobby to the seventh floor because there was a series of discrete, a sequence as they called it, where you stand in front of the elevator and you press the button, you wait for the door to open, you walk in, you press another button, wait for it to go up, door opens, you walk out. And each of the tasks was it about the same level and they were disjoint and they didn’t affect each other in any significant way, while a hierarchical task imputed this one myself from that reading, might be for instance, disassembling making one small part replacement and then reassembling a lawnmower engine where every move depends on every other move and has a whole bunch of ancillary skills.

Jim: If you don’t lay the pieces out in the right order as you take them apart, there’s no way you’re going to remember how to put them back again. You need a mnemonic, the map, all that, et cetera. So there’s this idea of a sequence of essentially like skills, like going up in an elevator is that fall on the non-hierarchical side while something like disassembling and reassembling a motor clearly falls on the hierarchical side.

Zak: So all skills, any skill has a certain amount of hierarchical complexity in it. So for example, as I mentioned in the crib, infants often have trouble actually focusing in the foveal vision field which is to say, focusing on the elevator button is a skill. Reaching out and pointing accurately and pushing it in is a sensory motor skill which coordinates the reaching and pointing with the looking. So even in the act of going into the elevator, you are making use of skills that were built up through the process of hierarchy complexity. And that task itself is sensory motor system, right? It requires you to coordinate a bunch of sensory motor things with an overarching coordination of those things, which is the… maybe it’s a single representation even of the getting up the elevator, right? That holds in place maybe a dozen different specific sensory motor schemes, which couldn’t be completed by a very young child, even if you explained it to them and tried to help them.

Zak: But yes, of course, taking apart and putting it back together again, a lawnmower is a much more complex task than taking the elevator up. That’s definitely true. And there you’re moving up into the realms of abstraction where there needs to be a kind of a process held in mind to coordinate not just sensory motor systems of the facility with your hands and the parts to actually get the thing together, but also a whole descriptive language of what the different parts do and a bunch of things that needed to be held in mind and linguistically mediated. Usually, as you said, with diagrams and such that make that whole task kind of much more obviously complex than getting on an elevator. So yeah, that’s a pretty good example, but it’s not in the same domain really. The example I like to use is the emergence of representations out of sensory motor systems, where as a child in the sensory motor domain, you can master a tremendous amount of horizontal complexity.

Zak: Children can get themselves dressed and they can brush their teeth and they can put on pajamas and get into bed and prepare to be read a story. And so there’s a sprawling array of sensory motor schemes, which eventually get integrated into a single representation, which is bedtime. Right? And so Piaget marveled at the emergence of what he called the semiotic function, which was the emergence of a representation to capture a tremendous amount of dense, lower order materials, specifically sensory motor material. So bedtime emerges and comes to represent, it kind of gets unpacked to us. All of that sense that’s what it means, it means getting ready, all the preparation and the muscle memory and the anticipation of the story and all of that it’s bedtime.

Zak: But then next to bedtime, you get dinner time, TV time, riding in the car time and you get more and more representations, right? And then eventually the representations get brought together into abstraction. You get something like quality family time, which generalizes across all of these representations, which generalize across all of these sensory motor systems. And so that’s the notion of the hierarchical complexity stack in a single domain of basically family systems.

Jim: Yeah. Another area I dug into and I was plunking around, was I looked for intersections of the term hierarchical complexity and chunking. Chunking is a term that gets used in computational linguistics used in neuroscience, et cetera, even in writing, right? There’s a concept of chunking your text, et cetera. And sure enough, there was an intersection, it was something from Theo Dawson actually. And it’s interesting, that was probably my naive view of the essence of cognitive hierarchical complexity before I did this research, which is that as we get more life experience, we can load a lot more into a single term.

Jim: For instance, complexity itself, if someone has been studying complexity science for 20 years, when someone says the word complexity to me, it has this huge history and depth and nuance and richness, and it doesn’t mean more or less a synonym for complicated. It has 20 years worth of learning, packed into that one word. And in computational linguistics we’d call that chunking. And so we would say that, when I use the word complexity, I mean something very different than when farmer Jones down the road uses the word complexity because I have chunked a whole lot more into that bag, essentially.

Zak: Now that’s exactly right. And the hierarchical complexity says, it just goes one step further. The model of hierarchical complexity, electrical levels, the skill scale Piaget stages. You’re like, what they say is that yeah, chunking exists and there’s actually a definable kind of scale of chunking. So it’s like chunking sensory motor systems is very different than chunking two or three different theories of biological evolution into a higher order theory of biological evolution, right? Where you create new terms that can be used to basically capture the essence of a whole field, which is where you get into the kind of paradigmatic or principled levels of post formal operational thinking. And so yes, chunking is a ubiquitous property. And it even goes down into reflexes and nervous system action.

Zak: So if you think about what the eye does, vis-a-vis the visual cortex. You’re looking at a kind of signal noise, distillation comparable to chunking. And this is what early psychologists like William James and Charles Sanders Peirce, where they saw a lot of things that we would call hierarchical complexity back in 1870s and ’90s, just as a basic property of what they used to call the nervous plasm, which we would now call neurons.

Jim: The brain, what it was quite, right? And it was quite late in the day when they figured out what it was. Right?

Zak: Yeah. So Kurt Fischer argued very strongly and there’s a lot of evidence to suggest in a whole kind of sub discourse around whoops, called neuroconstructivism, which was a neo-Piagetian approach to neuroscience essentially, which organized the neurological structures are in fact organized hierarchically in terms of hierarchical complexity. So the property of hierarchal complexity the very general as articulated by Michael Commons is almost a general property of information across the biological spectrum and this has been hypothesized as well. So Kurt Fischer, again, his dissertation was done looking at monkeys and pigeons, looking at the growth of hierarchical skill, which is to say hierarchical complexity in the behaviors of monkeys and pigeons. And as I said, you can see it in the neuron. So there’s something very deep about the process of the chunking, which is the many lower order processes being brought up and integrated by an emergent higher order process that… you that’s like some kind of almost ontological thing rather than a psychological specific thing.

Jim: Absolutely. I mean, because we think about the science of complexity, it’s essentially, it’s all about the emergence often over multiple levels of complexity from simplicity. When I’m trying to explain what is complexity, the simplest example I have found is a human right? At the bottom, it’s just atoms and each atom is identical, every hydrogen atom is exactly like every other hydrogen atom, every electron is identical to every other electron leads to the ability to tell at this point, but somehow they and the carbons get together and they produce fairly complicated molecules. And then you have those molecules getting to have chains, really long molecules that gets us into biochemistry, which then somehow got turned into the metabolism inside of a cell, which maintains homeostasis so that cell could survive.

Jim: And then later reproduce probably, and then 500 million years ago somehow the cells worked up some mojo, so they could work together to be a multicellular animal, that was a new emergence. And then they started developing gradually organs and then systems of organs. And then you have entities. So you have the animals and they live in an ecosystem. So you have this emergence from, it’s still all just atoms at the bottom, but up it comes. So this is a characteristic attribute of complex adaptive systems that if the circumstances are right, essentially have emergencies from the bottom up and sounds like cognitive hierarchical, complexity falls into that same ontology is another example of the emergence of complexity from simplicity.

Zak: Yeah, and now you’ve plugged the model of hierarchical complexity into a story of cosmological evolution in a similar way that let’s say someone like Ken Wilbur has done and Kurt Fischer did, and even Alfred North Whitehead would do, which is to say that there’s a continuity of evolutionary process, specifically articulated by process foster or complexity science of the emergent higher order or hierarchical complexity. And so that there’s a continuity between the human and universal cosmological evolutionary process which is a quite fascinating proposition and of course what psychology should be doing, right? It should be telling us that there are so-called universal laws of nature that are instantiated in our experience as humans, specifically our psychological experience. So yeah, that’s one of the things that attracted me to the model actually was that it was coherent with the rest of what evolution was telling us about how things evolve.

Zak: And if you look at developmental psychology, that’s what it’s looking at. It’s looking at how does the individual human evolve. I understood as an instantiation of an organism that evolved out of a universe that’s evolving and Piaget big insight was a basically say we can not do epistemology or psychology or anything that is about the nature of the person or the human of the mind after Darwin, we can’t do that the way it was done before Darwin or Lyman Mark, Piaget was interested in the Mark, that where there is in fact a need to begin to weave the human into an evolutionary story that’s actually larger than them. And so Piaget understood himself. In fact researching biological process that had become epistemological. And that’s a fascinating proposition that out of these contingent and seemingly random and temporarily limited processes you get knowledge, which is extensible universally applicable and necessary.

Zak: So mathematics emerged out of evolution. Where was mathematics before the human brain? That’s a kind of interesting question that Piaget would ask. And it is worth mentioning that, I think uniqueness goes all the way down. This brings us far afield into the universe story as it were. But yes, the atoms are basically indistinguishable, but they are distinct in time and space. So they have unique location and even indeterminable location, which is to say that there’s a uniqueness even at the atomic or self atomic levels. And then there’s uniqueness all the way up that stack, the full developmental stack of what we would call the complex compound individual, which contains within it all the prior evolutionary stages and then whatever stages of cognate development have been attained, personality development. It’s worth mentioning in my full meta psychological model, these questions of hierarchical complexity and development are about a third of what’s important when considering the human mind. And so I just want to drop that note.

Jim: We won’t go there today though.

Zak: Yeah. We’re not going to go there today, but there’s also issues of emotion and personality and other things I wrap under the heading of installments. And then there are things under consciousness.

Zak: The heading of installment. And then there are things under consciousness, awareness, self-regulation which I class with the concept of transcendence. And then that’s paired with development, which is where, what we’re talking today. So I like that you brought up broad and that you show that the notions of emergence and the complexity science are directly relevant to the question of hierarchical complexity. And that’s what Kurt Fisher pioneered in the ’90s, actually applying dynamical systems modeling techniques from the complexity sciences to modeling human development.

Zak: So on the metaphor that the individual mind-brain is like a complex ecosystem. That it would have these organic processes of emergence and even regressions. So there’s a bunch of really interesting stuff that emerged from that. That was the core of the Neupogen Synthesis was that the emergence of mathematical models from complexity science that actually showed us stuff that Piaget had been trying to show us, but he just didn’t have the computers and the mathematics.

Jim: Oh now that you mentioned the emergence of mathematics. There’s a cognitive neuroscience that I really follow closely. In fact, I hope to have him on the show soon. I’m doing a series on the science of consciousness and he’s one of the leaders, Stanislas deHaene. He’s a French cognitive neuroscientist.

Zak: I met him. He is a wonderful, incredible experimentalist and writer.

Jim: He’s got two books which they seem mighty narrow, but they are unbelievably interesting if you haven’t read them, I forget their titles. But one’s essentially the cognitive neuroscience of reading, and the other is the cognitive neuroscience of arithmetic. It does an amazing job to show that these two things, which we were not evolved to do directly. Right? There was no evolution for reading obviously, because paper didn’t exist during most of our evolutionary history. And arithmetic, you can argue a little bit more that maybe we started needing it at some point. But he takes it all the way back to the rough sense of numbers that nonhuman animals have and things of that sort. Really, really interesting for anyone interested in that theory. But let’s not go there either.

Jim: Let’s go onto my next topic, which is something that just jumps out at me as I was saturating myself in reading about hierarchical complexity, is, what’s the forcing function? What’s the pruning rule? Why did nature have to go this way? One thing that hopped out from my mind from the things I work on is, “Damn, this looks a heck of a lot like an artifact that is a work-around for the remarkably small, short-term memory that we have.” The famous seven plus or minus two short-term memory, Millers short-term memory. Turns out if you’re not dealing with sound, as words are basically stored as sound, if it’s images it’s actually four, three or four. So our working memory is tiny, tiny, small, and to actually get a gestalt from a series of things together and working memory, it means that the only way to be able to work on more and more difficult problems is to make those chunks bigger.

Jim: So that I have seven that I can work with simultaneously. That’s got to be a driving function for this hierarchical complexity. And in pre-human animals, the number’s not seven, it’s three, four, two, things of that sort. So what do we know about the relationship between the gating function of working memory size and the emergence of hierarchical complexity?

Zak: That was, I think, probably the most common and remains the most common hypothesis about why hierarchical complexity emerged as such a strong function. Now, there’s also what we previously mentioned about the cosmological significance of these kinds of process, which means we have to ask that question in general about evolution, but we won’t do that now. But when it comes to the human mind, definitely working memory. Pascual Leone, I think was his name, had an entire theory of neo-Piagetian. He was part of the neo-Piagetian consensus in the ’90s. And he had a theory of M power, which was basically that. It was, there’s only so much memory. And the units you hold in memory become denser and deeper and more abstract and complex. That’s what basically he thought, it was the main thing that we were detecting even with IQ tests and stuff that are instinct for intelligence was more or less that.

Zak: So there’s a huge amount of truth in this, if this is true. But there’s the Piagetian insight, which it is, it’s actually the working memory bottleneck in combination with both the demands of the world, which is to say if the world was not really complex, then we wouldn’t matter that we had a working memory bottleneck. So, there’s an implicit realism here, which is to say that the world itself and the complexity of the environment we’re in is one of the drivers as is our need to understand which is just the epistemic motivation. So, Piaget made a big distinction between success and understanding. Success is the accomplishment of something that needs to be accomplished. Understanding is knowing why it worked.

Zak: There’s a threshold that’s crossed in human development where children go from wanting to succeed, to wanting to understand. And most animals don’t cross that threshold, although, but it’s arguable and specific cases or something. We think like enculturated monkeys and, and things for the most part, most animals are operating at the level of success. And there the world is mostly driving the adaptation of the nervous system to accommodate and survive. With a human you find the world drives it to a certain level of complexity. And then there’s an epistemic motivation, which can be fostered socially or not. But it is there innately, which also drives the information through the memory bottleneck.

Zak: And again, the memory bottleneck alone is not going to do it. You need the complexity of the world. And specifically what’s weird is the abstraction of the world. That’s, what’s so odd. And this is what’s interesting about mathematics is why do our mathematical models look like the world at all? Like why is there correspondence between them when there is? And so this notion that yes, actually there’s implicit realism, but it’s a critical realism in the [inaudible 00:30:24] sense, within Piagetian and framework, he was an Epistemologist first. So yeah, working memory as a kind of functional explanation, yes. But there’s a deeper epistemological motivation and the universe itself being able to be disclosed, right? That we can ask of nature, evermore complex questions tells us something about nature.

Jim: Yeah. And also it’s interesting that the universe is at least as far as we know, lawful. If the patterns were random, truly random, then there would be no point in investing in the biological costs to being able to try to extract these abstract patterns useless. Right?

Zak: Precisely. And this is directly relevant to childhood and early childhood socialization environments, which is to say that, “yeah, if there’s not a lot of complexity in the environment, then the nervous system doesn’t expect complexity.” And if there’s it doesn’t seek out, it just can do what it can do. And if there’s not a lot of consistency and this happens a lot in parenting styles, then you just give up on trying to make sense of it.

Jim: Yeah. We try to process noise, the signal you extract it just a statistical random attribute, not useful for anything. Oh, by the way, just before we go on, just cause I have to, Right? I actually use that argument to come down on the side of realism versus idealism, that because of the fact that we have invested all this cost in machinery to process reality, reality must actually exist. Otherwise, we wouldn’t have. So that’s the ruddy in answer to the idealism versus realism philosophical question that goes back at least 2,500 years, but let’s not argue that one today.

Zak: No we won’t, but it is relevant because that’s really where Piaget was trying to come down. And then of course he also was a moral realist and an Epistemological or constructivist in the domain of sensory motor objects. So this question of how is it that universal laws of logic, the law of non exclusion emerges in childhood at a certain point. Basically whether or not the kid has been formally trained in logic, but it’s a property of the world, and especially of social interaction and expectations around language use. So these very interesting questions that emerge about deeper than the issues of hierarchical complexity and its measurement, about how the mind is propelled to higher and higher levels of inquiry and deeper and deeper forms of knowledge. And that’s ultimately what the field is about.

Zak: What hierarchical complexity does, it allows us to kind of place the universe of potential knowledge on a spectrum of complexity. And that helps us diagnose the quality of the knowledge and also helps us to teach and understand the emergence of knowledge. When there are two competing theories in there at the same level of complexity, that’s different when there’s two competing theories in there at different levels of complexity just is. And similarly with different parts of yourself, people don’t just move from one stage of hierarchical complexity to the next on all domains, they move in very specific skill demands. So you can have ideas about certain things you do that are much more complex about the ideas you have about other things you do. This is very common.

Jim: Yeah, I warned people who are real simple stage thinkers, those color people the spiral people, they say, you’re –

Zak: Oh Spiral Dynamic?

Jim: I’ll say, “Shit, I’m orange in this domain, blue in that domain and aqua or some god-damn thing and another right? I’m all over the place, and everybody I know is all over the place.” So this idea that we’re in some color coded lockstep sequence, seems to me kind of simplistic. One last step, just a little deeper theory here before we’ll pop back up and kind of get down to more applied examples, or at least tangible examples. And this is from Theo, actually, Theo Dawson, and it gets at something I think is interesting and important. I’d love to get your sense of it, which is, and I’m reading from her paper. Hierarchical complexity refers to the number of non-repeating recursions that coordinating actions must perform on a set of primary elements. Actions at the higher order of hierarchical complexity are defined in terms of the actions at the next lower level, A and B organized and transform the lower order actions and see produce organizations of lower order actions that are new and not arbitrary and cannot be accomplished by the lower orders themselves.

Jim: So here we bring in the ideas of recursion and essentially top-down causality, which is quite interesting. Two very important and slippery concepts.

Zak: Hmm, totally. Yeah, that’s interesting. And you should, I assume you’ve had Theo on the show, if not, you should, because she may be directly quoting are adapting some of the very formal language that Michael Commons used to clarify the model of hierarchical complexity almost as a mathematical psychologist. And so, as we’ve been describing throughout this, you have a process where there is a task, let’s say, tying the shoe again, Right? And to get that done, you need to be able to control and organize a sequence of lower order tasks. And that higher order sequencing and organization will change the way the lower order task is operated. Then if you were just operating the lower order task, without it being integrated into a higher order task. So if you were just manipulating strings randomly to manipulate strings, that’s very different than using the sensory motor skill of manipulating strings to specifically tie a knot.

Zak: And so that goes all the way up and all the way down the complexity ladder, which is to say where the complexity scale that the notion that there’s a certain number of lower order elements that need to be integrated into the higher order element. And once that occurs, they’re not the same old elements they were before they were integrated. And there’s many ways we can talk and get into the examples of that. And the recursion is just about a formal scoring criteria and that’s important to get that there’s the theoretical conversation we’re having now. And then there’s the looking at an actual linguistic performance or task that’s been accomplished, and assigning it in order of hierarchical, complexity or electrical level. And if you’re going to do that then it’s not about all of the random arbitrary, horizontal complexity that they didn’t need to put in.

Zak: It’s about the number of non arbitrary recursions that need to be integrated into the higher order element to give to a specific score. And now we’re getting kind of down into the weeds, but yeah, that was a very formal mathematical definition, which means that you can apply that to computer programming and other areas where just information processing systems in general need to be understood in terms of their hierarchical complexity. So that was a good to pull out. That’s probably one of the most formal definitions, and I believe it’s from the Commons paper, we should probably cite it in there on the definition of the stage itself in Neupogen Theory, which was a key innovation by commons there.

Jim: Yeah, as a computer programmer guy, that’s probably why it appealed to me. I knew exactly what she was saying right? So it made it all crystal clear. Now, as I promised, we’ll pop back up out of the deepest theory space, and now let’s actually talk tangibly about this 15 level stages of hierarchical complexity, that seems to be Michael Common plus other people worked on it. Tell us a little bit first at a high level, what it’s about. And then if you could compare and contrast it briefly with some of the other thinkers in the space, like Piaget, Kohlberg, maybe even Gardner’s multiple intelligence, and then we’ll pause and discuss that. And then we’ll kind of dive into the 15 levels.

Zak: Okay. Yeah, so as I was saying, there’s the model of hierarchical complexity, which is the model developed by Michael Commons. At the same time he developed that model, there was this kind of broad neo-Piagetian and consensus around that general set of levels. And so you have Fisher’s skill levels, Michael Commons orders of hierarchical complexity, you have Dawson’s electrical levels, Robbie Case had a set of levels before that you had Kohlberg’s levels, Cheryl Arman’s levels, Keegan famously has levels that are similar to the complexity scale, but not identical. And so when you say 15, yes, there are 15 within the Commons model. Fisher, but again, that’s, if you put a cap on it and if you don’t go below the human sensory motor, right? So the question of how many levels, for example, I think is the wrong question to ask, and even the tour of the levels were, here’s what it’s like at this level. And here’s what it’s like at the next level. That’s useful only in part, because in fact, as we can discuss as that get into, despite what a lot of developmentalists say, development’s always very domain specific.

Zak: So to speak about what it’s like to be at a level is actually needs to be specified away from these general stereotypical ways of characterizing it and into more specific ways. So, Commons is a very useful orientation. I prefer to use Fishers levels because it’s a system of tiers and levels, and it’s very useful, but it echoes Commons and they’re almost identical. And Dawson’s did the psychometric refinement to make the electrical level, which I think are the measurement standard for hierarchical complexity measurement would be found with electrical levels. And again, they’re basically as a morphic with the skill levels, which are isomorphic with Commons as levels, but they’re not identical. They’re not the same, but they’re triangulating something. Again, a kind of realism here.

Zak: So with Fisher, you have these three tiers, which are actions, representations, abstractions, and then above abstractions, you have principles. And those would correspond roughly to Commons is sensory motor, which would be actions. And then operational and primary concrete stuff would be representations. And then he has formal abstract and systemic, which would be in the abstract tiers of Fisher, and then his meda systemic brings us in the Fisher’s principled here. But what you have to understand is that actions, representations, abstractions principles, you have levels within levels. You have sub levels and you have the capacity to do what’s called micro developmental research, where you don’t look at behavior in terms of like, quote, unquote, whole stage transition, but in terms of micro developmental process. So again, there’s a fractal like property to the quality of hierarchical complexity, where the closer you look in that still set skills being constructed at a particular level, you can see that there’s constructions and levels within levels.

Zak: But the basic tour is something like you begin with sensory motor and you begin with single actions. You begin with the ability to, for example, you focus on your mom’s face, right? And then you can eventually you have sensory motor mappings or mappings of actions where you coordinate the ability to look, with the ability to reach, to knock something off the table, right? And then you get sensory motor systems where you coordinate systems of sensory motor skills. So now you coordinate looking with reaching with grasping, with bringing to the mouth and drinking, right? Like that’s pretty complicated based on the fact that the first thing I had to do is be able to just look and focus and isolate and get object permanence. So, that’s an example of skill development within the sensory motor tier.

Jim: Yeah. Let me jump in here just for a second, because I’m getting a reeducation in all of exactly that. I have a, my wife and I, and our daughter of course have a six month old granddaughter. We’ve been seeing about once every four weeks. And of course in this day and age, we get pictures and movies and FaceTimes on a more regular basis. And we’ve just been watching our granddaughter go through just these stages first, flopping her hands around at random and then moving them with one of them kind of purposefully. And then the two of them together kind of purposefully, but kind of clumsily. And guess what she’s doing now is grabbing a sippy cup and bringing it up and drinking it finally, right? It’s quite amazing, a step, by step, by step. It’s quite a stout.

Zak: Totally. And it’s amazing to see. And in fact, you can see it in infancy and toddler hood and childhood. And that’s why PJ is thought to be like a child psychologists, but it’s actually because development and especially hierarchical integration takes place much, much more rapidly in the younger ages. So that in a matter of weeks or days, sometimes you’ll see major hierarchical reorganizations that bring up a whole new skill capacity. Now later in life, it can take years because you’ve basically mastered so much that you would have to be confronted with some kind of really new and much more complex demand from the world to be growing more. But the kid of course has mastered nothing. So even just grabbing the cup is an incredible hierarchical integrative accomplishment and requires emotional motivation and social reward and a whole bunch of other things to get that development going.

Zak: So, so the sensory motor world is this big sprawling world, and it is important not to move through quickly, too quickly through the sensory motor. And this is one of the problems with screens and very early childhood development. Very well researched to show that kids deprived of the ability to explore complex sensory motor environments are developmentally delayed, which is to say, once you start to build sensory motor skills, you need to build as many as you can across as many diverse sensory motor niches as you can be exposed to. And that’s literally the bottom of your pyramid upon which you build your representations. Right?

Zak: When we worked with Theonie, when we were doing research in Springfield, Massachusetts. Some urban schools and some kids, we were doing research on physics concepts about rubber duckies in bathtubs. And what happens if there’s a rubber duckie sitting there and you create a wave and you send a wave towards the rubber duckie. Will the rubber duckie go back or come towards you, or just go up and down. And this was a physics question, and it was at the level of about abstraction to get, but you could do a lot of work with it at the level of representations, but it required having actually had some experience in a bathtub with a floating object under reflective conditions of observation, which is to say, to learn about the effects of your sensory motor behaviors on the world. They hadn’t had that opportunity.

Zak: And that showed us what psychologist. Of course, I’ve known a long time that pre-verbal exploratory, sensory motor stuff is important. And the continued engagement with those lower wrongs of the skill stack, which is to say, continuing to use and explore and widen your sensory motor repertoire, even after you’ve moved up into representations and abstractions. But again, the young child and this is the, he spoke the first words, what are the first words, right? Like that’s the emergence again, usually the semiotic function. Sometimes it emerges earlier with pointing and other things, but you get whole sprawling sets of sensory motor experience summarized in a single utterance or gesture. And that’s the emergence. And this was to Piaget the most miraculous thing. Cause it was really the thing that sets us apart from animals. And if it’s not precisely there, then it’s around there and we can talk about that, but that’s really beside the point in this conversation anyway. So you emerge into the representational tier, which is operational, and then you move through the primary and the concrete, if you’re in the Commons model.

Zak: And then again, it’s kind of like your head pops up and a whole world becomes available, the world of using linguistic signs to represent non present realities. Right? So you can start to entertain counterfactual. You can start to lie.

Jim: Talk about Santa Claus.

Zak: Yeah, precisely. And you can start to have these really complex narrative architectures to your experience. And that’s, what’s so interesting. And so the similar process, you begin with one or two representations, mommy, doggie, bedtime, right? And then you get more and you can map them together. You know, mommy water means like “Mom, I would like some water.” And so you can map them together. And then you start to have very, eventually this many mappings and kind of like a rich.

Zak: Mappings and kind of a rich beginning of language and then there’s what we call representational systems, where you get the ability of young kids to tell almost endless descriptive stories. So, this is the age at which they’ll have baseball card sets and they will be able to memorize vast expanses, at least I mean nowadays God, I just dated myself I’m not even sure if kids have baseball cards anyway today.

Zak: But the example of the kid who actually is incredibly… Can talk endlessly and tell things that are actually very complex stories from one perspective, from a horizontal complexity perspective, the kid is now containing a tremendous amount of visual memory, linguistic vocabulary, just numbers of words. And then, all of that complexity representations eventually gets summarized into abstractions.

Zak: And this is where you get the Piaget and Formal Operational Levels what Commons calls abstract and formal and here it’s different. Most representations refer to things that can be basically simply pointed to in the world. Remember representations “chunk” will contain sensorimotor experience and process.

Zak: So, you know you’re dealing with representational language when what’s being talked about is basically can be made present or just like almost taking a picture of or something like that. Abstractions are not that way. Abstractions are by definition, integrating many examples of representations into higher order things. And so, you make bedtime out of the sensorimotor array of getting ready for bed and brushing your teeth, et cetera, et cetera. You make quality family time out of thinking about the things that bedtime and dinnertime and riding in the car time and TV time have in common or don’t.

Zak: And quality family time isn’t something you can directly point at because what you’re going to be pointing at is TV time or bedtime or car time, so it’s a higher order more abstract thing. And what’s important to get is that many of the essential things that allow civilization to exist, exist at the level of abstraction. But abstraction is not guaranteed by the existence of the human nervous system. Abstraction requires education. And so, you can get by just basically operating at the beginning of the abstract levels.

Zak: And the argument would be that that would make democracy impossible. That in fact, do hypothetical deductive reasoning to entertain plausible versus implausible, to understand how democratic process works to justify law and things of that nature just simply require a formal and systemic as Michael Collins’ language or abstract mappings, abstract systems.

Jim: Yeah, let’s pause here for a second if we would, and let’s try to bring it down to an actual example, like say for instance, at the forager hunter-gatherer level and that’s obviously, there’s some things they do, they have great hierarchical complexity in making tools and organizing a Mammoth hunt and what have you. But in terms of organizing their society, the governance layer, are we saying that the sub-Dunbar number, we need less hierarchical complexity to make our governance work? Is that a reasonable statement?

Zak: Yes. The more complex the principles that organize and allow the organization and coordination of the society, the more hierarchical complexity is requisite of at least certain members of the society. And this is something that Jurgen Habermas looked at specifically taking up from Kohlberg who took up from Piaget. Basically arguing that yeah, that’s one way to think about the evolution of societies is to think about what’s the requisite complexity necessary to pull off the social coordination the society is attempting to pull off.

Zak: Now, this shouldn’t be confused with saying that the experience of the hunter-gatherer wasn’t potentially as abstract and complex as our experience. It’s just to say that it would not have been requisite to hold the society together that certain members achieved that. So like religious ritual, kinship ritual, sensorimotor capacities in hunting and sensory acuity. And there’s a bunch of other things that in fact, we would find ourselves probably greatly disadvantaged when encountering that type of human nervous system, which is to say the hunter-gatherer or indigenous nervous system.

Zak: And you could argue that because our society has become so complex, we’ve become too complex that we’ve created individuals who have had to become warped into highly complex specialists to the detriment of their humanity, in order just to keep this thing going. And so, yeah, it’s this kind of like an arms race between the task demands of the civilization and the capacities of the humans. And I think there was some tipping point where we started to create things that outstripped our capacity to continue to maintain. And so I talk about that in my book as the kind of echo and educational crisis that in fact, the task demands of just living as a citizen have outstripped what we can kind of like on average expect people to be able to accomplish. And yeah, so that’s a very important dynamic to track.

Zak: It’s important not to fall into the trap of applying hierarchical complexity to cultural evolution, unless you do it very well the way Habermas did. Because there’s also a lot of talk among people who use color-coded developmental language, looking back at cultures before modern cultures, even ancient cultures and then pre-modern and medieval and modern and they turn the history of civilization and the evolution of cultures itself into a kind of as if that was a story similar to the story of the individual, developing human. That the indigenous people were like children, and that the medieval people were like young adolescents and then we modern people are like adults or something. And so I think that’s a bad… It’s a misapplication.

Zak: Now you can do hierarchical complexity analysis of historical documents and this is what Habermas did with constitutions basically in Europe. To show that no, actually yes, this is a demonstrably more hierarchically complex way of conceiving the legitimacy of one’s government and political process. But it’s actually, I think very difficult to know what, in terms of like cognitive development specifically and I would say in my model especially in soul, [mind 00:55:11] and transcendent dimensions of the human psyche, what those were like in cultures so old that they’re intrinsically almost foreign to us and incomprehensible.

Zak: So while your analogy works to the hunter-gatherer thing, I’m also hesitant to actually to weigh in there. But I can say in at least recent modern history that again, Habermas and even Piaget did some work here. Showing that, yeah, we’ve become more complex as a civilization. And that has put greater educational demands on the civilization and therefore greater complexity demands on each individual. And I think that goes without saying. Technology drives that too, of course, it’s not just the demands of the legal process and being able to kind of like reflectively consent to be governed because you understand what it means to be governed, which by the way is like a very abstract thing. I’m not sure a lot of people realize.

Zak: But so there’s that which is the demands of the state to a greater complexity to be a citizen. But then we’ve just had industrialization and specifically digital technology proliferation, which has not legally demanded that we become more complex, but has made us have to handle a great deal more complexity. And the internet, I think in particular has us up against the wall in terms of this whole like chunking and working memory limitation and complexity thing.

Jim: Too many signals. Too many signals.

Zak: Too many signals. Yeah.

Jim: Before we’re going to go back on, rising up the hierarchy, but before we do that because you made a couple of comments I thought it would be a good time to insert something I actually had later. And that’s the relationship between hierarchical complexity and kind of somewhat bogus concept, but had some merit, general intelligence Spearman’s g kind of thing. They’re not the same, but there seems to be some relation between the two. And certainly there’s at least a pretty strong correlation when you give those two classes of tests. So maybe talk a little bit about in your view, the relationship between general intelligence, Spearman’s g whatever we want to call it and hierarchical complexity.

Zak: Yeah. So it’s a good question now, and this would be a great reason to have Theo on, because I know she’s recently been poking around and looking specifically at what the correlations are. And you’re right, that there are reasonable correlations and as I mentioned, past quality own and other others within the Neo-Piagetian consensus kind of did work trying to basically explain the findings of the IQ testing movement in terms of the explanatory concepts of Neo-Piagetian frameworks and I think that goes a long way.

Zak: My concern basically, and I write about this a lot in my first book is that ideally the model of hierarchical complexity allows for a much more complex way of understanding what we want or what we’re trying to understand with something like general intelligence, right? whichever intelligence does is similar to what like GDP does, right? Where it’s a summary statistic based on a pretty narrow range of indices. Whereas hierarchical complexity, if you’re understanding and applying it right, you would never apply some person a hierarchical complexity level. You would assign a particular task that they accomplished a hierarchical complexity level. And that’s a huge difference.

Zak: So general intelligence is often used and spoken about as if this entire person is basically smarter than that entire person. And you’re not saying like in this domain of the linguistic and spatial manipulative and mathematical intelligence, he’s smarter than this person. But that guy’s an auto mechanic and the other guy could never fix a car. So in the auto mechanic realm that guy’s actually smarter. You just say, no, no, no, as a whole person, this person is smarter than that person. And that’s just bullshit. And it’s bullshit that’s actually a holdover from a eugenics and a very misconceived way of understanding the nature of human psychology and the genetic transmission of intelligence.

Zak: So that’s why I’m just like kind of a little bit constitutionally opposed to that way of conceiving intelligence. Not because it was associated with eugenics, although that’s a problem, but because of how it oversimplifies radically and actually invites us into what Bhaskar would call a demi-reality. So, because of the IQ test does correlate with hierarchical complexity in particular domains, it means that there’s a moment of truth in it. And so we’re getting some signal from the IQ test, but then we over-amplify that signal as if it’s the entire signal the psyche is going to send us. And so we create a demi-reality where we live in a world that you can just simply categorize people according to one number that represents their intelligence.

Zak: And that became a really a popular way of doing psychology and remains a popular way of doing psychology. And it’s an anathema to a much more complex Neo-Piagetian approach, which also studies the development of intelligence. That’s the thing like this is about one’s ability to succeed in operating upon the world and to understand the nature of the world. But the model of hierarchical complexity allows us to say things like, yes, in the domain of physics, this guy’s incredibly doing like paradigmatic reasoning, but in the domain of small engine repair, he is doing sensorimotor work. Whereas his mechanic is doing abstract work.

Zak: And that’s just something that’s true. And this ties into my notions of teacherly authority and the dynamic and contextual and distributed nature of teacherly authority, as opposed to the centralized and bureaucratically standardized processes of teacherly authority and expertise. And so this is yeah, very important to get. So I think general intelligence is a demi-reality, which contains enough true signal to not be useless, but not enough richness of signal to be something you’d want to use to understand yourself and other people or to organize educational organizations or things of that nature.

Jim: Yeah. That’d another to plunge into on another day, that’s interesting you mentioned that you strongly recommend against saying a person is level nine or whatever. One guy I’ve had on our show three times, Hanzi Freinacht, who’s a sociologist and political philosopher, has written some books for what he calls political-metamodernism. Throughout those books, he basically constantly is using the Commons 15 Level model and saying this percentage of people are this, is percentage of people are that. We’ve got to work around the fact that only 1% of people reach level 12 and 0.6% reach level 13. Is that just entirely bogus or can you say in some sense that there’s something to that?

Zak: In one sense it’s bogus. In one sense it is bogus, because those are not numbers that are reliably empirically generated. There just hasn’t been enough hierarchical complexity research to be able to speculate about large populations that way. Theo Dawson has the largest database of existing hierarchical complexity data. And she does have some numbers that make some recommendations to generalize about, okay, what percentage of people have been shown to be able to reach this level? So that’s a generalization across the population about kind of like highest demonstrated skill capacity. But it’s not a claim about that those people are at that level. And so to say things like that I think is quite vexed, but you can say things like, for example, there’s a job in an organization which requires you to be able to manipulate abstractions in complex multivariate ways. That’s like a requisite task demand, which specifies the lowest order of complexity that someone could actually do that job at.

Zak: So you can start talking about kind of like what are the generally emergent task demands of society and how well are people adapting to those? It’s an approach that [Kegan 01:03:40] took in over our heads, which basically says, “Well, regardless of where people are at, this is what they’re being asked to do and look how complex we’re not, that is.” And so think about what people are being asked to do when they read the news. I would argue that they’re being asked to continue to return to that newspaper. They should be being asked to engage in an extremely complex and reflective way with the world mediated by a reliable reporter, but instead they’re giving a much simpler task.

Zak: So I think you can make generalizations about hierarchical complexity, how it’s relevant and if you have enough measurement instances of a single person, you can sometimes say, “Hey, we’ve never seen him perform above this level in any domain we’ve ever tested him in.” So you can start to talk about something like consistency of performance within a developmental range, the zone of proximal development. But yeah, I’m very hesitant of people who want to classify whole populations or whole persons as being at a level. Yeah. I’ve complained about that with Hanzi Freinacht, I think it’s a resuscitation of the kinds of developments you saw with the IQ test in particular. Because it becomes a very powerful social sorting mechanism and the kind of bludgeon which is the opposite of the way that it should be used for social purposes.

Zak: So yeah, my hope is that nothing comes of the wedding between hierarchical complexity and political activism, quite frankly. Because it’s yeah… Even putting aside issues of measurement and that’s, if you’re going to have a political movement built around identifying reasoning along the complexity scale, then you need to be able to actually really reliably, invalidly make those assessments. So there’s a whole issue of measurement, but then there’s a deeper issue of just how does one use politically psychological constructs responsibly. So yeah, and so that’s well, these are concerns nothing right now’s bad is happening in terms of the model of hierarchical complexity being misused, the way IQ tests were used. But you do have these kinds of generalizations which I think is just basically stereotypical reasoning. So yeah, so that’s my sense there.

Jim: That’s great. I’m sure a fair number of our people our audience who’ve read Hanzi and as I said he’s been on three times and people are interested in what he has to say so I love’d to hear your perspective on it as well. Let’s go back to the list essentially, and let’s skip over some of the lower ones and maybe start off with something equivalent of Commons level six. And just give people a sense, try to make them as tangible as possible with an example of what might be at that level and the next level and levels above that. And then try and do it fairly quickly and maybe if we could have one domain where you give an example for each level that could be helpful.

Zak: Right. So I’ll go starting with primary through the concrete to the abstract to the formal, the systemic to the meta-systemic. Which would be in Fisher, we’d be moving from representations to abstractions to principles. And I did some of this already, but you can imagine in domain like moral development where the early levels are egocentric and essentially punishment and reward-oriented and based on obviously demonstrated representation like what’s happening.

Zak: So fairness is a big deal on the playground, but fairness on the playground has to do with like, okay, looking in each kid’s hands and seeing if there’s the same amount of M&M’s in each kid’s hand. And if one kid got a lot more M&M’s than another kid then that’s just simply not fair or simple at a slightly higher level, let’s say, if we’re on a playground where kids are in middle school, then you’re up in abstraction. And then they’re creating abstract rules where fairness has to do with is the rule fair? Means, does the rule promote this abstract idea about what the game is supposed to be? Which is that it doesn’t make it so that some kids are basically completely disadvantaged and always lose, which would make it not a game, but something else.

Zak: And so you move from just a very concrete kind of like simply definable notion of fairness to an abstract notion of fairness, where there’s a set of rules that we’ve agreed to. And the violations of them aren’t violations of like physical reality, they’re violations of a social reality, that we are all aware that we’ve constructed in making the rules. And then you can move to a principled definition of fairness, which is where… And this brings us up through the systematic into the meta-systematic which is like John Rawls’s work. Justice is fairness where you actually have a multi-systemic integration of several different fields of ethics into a single theory of justice built around a notion of fairness, which actually transcends and includes those prior two notions.

Zak: It does have to do at the end of the day with who’s holding what food in what hand, but it comes all the way up through the social agreements of the society to the principled constitution that set the parameters by which the lower order norms are played out. So in the domain of moral judgment, you move that route from a kind of like concrete representational, situationally-specific notion to a more kind of like we’re conforming to a set of agreed upon rules to a abstract principled stance from which you can norm the norms of the convention and make rules about the making of rules.

Zak: So that’s how I kind of have the moral development stack. And that would be you could look to Kohlberg for that kind of notion and that rests on top of again, the deeper architecture of this process of hierarchical integration. And that’s kind of how one way to think about the model of hierarchical complexity is that you can take it as we did. I’d like to go into many different domains and then rationally reconstruct a learning sequence across the complexity orders. And so that’s what I just did. I rationally reconstructed a very rough learning sequence about the nature of fairness across multiple complexity levels. And so with a universal ruler, which is to say a universal measure of hierarchical complexity, you can then make domain-specific learning sequences. And so you can find a bunch of examples of those like in Theo’s work and in other developmentalists who’ve published them. So hopefully that was useful kind of what you were looking for.

Jim: Yep. That’s exactly what I was looking for. Something that gave people a sense of what these higher levels felt like and looked like. Almost tempted to go down a sidebar, but I don’t think we have the time. I just going to say, what about the difference between deontological and consequentialist ethics here? But we’ll do that another day.

Zak: [inaudible 01:11:05] Kohlberg would answer that for you.

Jim: Exactly. Anyway, now let’s move further down to the tangible, you were involved with founding of Lectica and you guys developed systems for evaluating tasks and then measuring people’s ability on specific kinds of tasks and saying that for task of this sort, this person can handle this level, but not that level. Talk a little bit about what actually goes into that? How’s that pie bake to be able to do that? And again, as tangible and as example-full as possible.

Zak: Yeah. So again, it’s like should definitely have Theo on as a follow-up to this because she has her finger right on the pulse of where the state of the assessment development is at Lectica. I can tell you about the principles behind the way Lectica assessment came into being. You had that history of psychology I mentioned from-

Zak: You had that history of psychology I mentioned from Piaget through Kohlberg, to Fisher, to the Neo-Piagetian consensus. And all along you had practices for determining which level or stage a performance was at.

Zak: And Piaget built his, Kohlberg had his scoring system, Fisher had his skill analysis, Commons had his model of higher complexity. Theo had the electrical assessment system. And so what all of these are, are ways of basically looking at open-ended human performance, usually linguistic performance, like what I’m doing now, just speaking.

Zak: And looking through the surface level of what’s said, the content, for the deeper hierarchical structure that’s being expressed by being able to do that.

Zak: So how hard is it, in terms of non arbitrary recursions and hierarchical integrations? How many of those am I doing right now? Am I speaking this abstractly and complexly? The answer is a lot, which is why you can only do it for so long and it takes a lot of blood sugar.

Zak: So what Theo did, and her stroke of genius really, was to take a standard psychometric tools that have been developed, specifically the Rasch model, which is a psychometric technique for scaling, and apply them to the model of hierarchical complexity to basically bring those scoring procedures, which had just been developed for research purposes by psychologists, to bring those into a formal enough form to actually make a standardized assessment of cognitive development.

Zak: Not a good enough for research assessment of cognitive development, which is what they had all been prior, and which basically all of them remain, but a good enough for prime time to compete against the SAT standardized assessment of cognitive development.

Zak: And that’s what Theo did. And that’s why I joined her in helping her create Lectica. And so there, what it is, is a standardization of the human rating process, which is to say, we really refined the hell, Theo did, out of the model of hierarchical complexity, and the skill scale, and et cetera. And then a deepening of the technologies that surrounded the administration of the assessment.

Zak: We built standardized developmental assessments that could be administered through the internet. And now Theo has worked out an automated scoring system so that we can actually use machine intelligence tools to automate at least certain parts of the Lectica analysis.

Zak: The goal there was basically to replace the standardized tests, the multiple choice curriculum constraining, no child left behind, race to the bottom standardized tests, to replace those with developmental assessments. This was the goal.

Zak: And those look like richly developed assessments that were diagnostically useful in the classroom. So that’s the main thing to get, is that a standardized test says you pass or fail. A Lectica assessment says here’s what you understand. And here would be the next best thing for you to learn. It’s a diagnostic. And it can be diagnostic because it’s based on an empirically grounded, rational reconstruction of a specific learning sequence.

Zak: We would say to the kid, hey, you understand fairness, in terms of those M&M’s in the hand. And that’s wonderful. And here’s a couple other things, at that level, that you probably also understand, or if you don’t, they’ll be easy to get. But what you don’t get is this thing right at the edge of your understanding, that there’s something more general, that the same idea applies to M&M’s as would apply to Doritos, as would apply to the time your brother gets to play video games versus you.

Zak: The idea that if we know how the learning sequence works, then we can actually figure out where you are in the learning sequence, and give to you, basically, precisely the next thing that would be best for you to learn, to continue to grow in your hierarchical complexity.

Zak: That’s the nature of the Lectica assessment. And we developed them for the K-12 system, and encountered tremendous complexity with the standardized testing industrial complex, if I can call it that. But we’ve also developed them for adults, specifically leadership management, business context, and government, where we’ve found a real need on the part of a whole bunch of different sectors to find a way to determine just how complex they are in terms of their thinking and skills.

Zak: And then even more importantly, how to diagnose areas for growth, how to understand skill development in areas like leadership decision-making, and ethics, and things like that.

Jim: Zach, next let’s… I’d love to drill into this because my business career, I spent a tremendous amount of my time thinking about the people side of business, and specifically identifying leaders, identify potential leaders, developing leaders, et cetera.

Jim: I’d love to dig in a little bit to the work you guys did at Lectica on applying this concept of measuring hierarchical complexity in the business world, in the task of leadership identification and development. I’d just be fascinated with that. I’m sure I have a million questions.

Zak: Yeah. And this is where I began the work, actually. It was, I met Theo when I was an undergraduate at Hampshire. And she had been hired by the National Leadership University, which was basically an intelligence agency organization, so like NSA, CIA people, to do leadership development work, specifically on identifying and growing leaders in the intelligence community.

Zak: The first stuff I cut my teeth on, as a complexity analyst, was on these leadership development interviews, hundreds of them. And what’s really interesting about it is that, obviously the idea that hierarchical complexity is this dimension of human development. And it goes from the crib to Einstein. And so you would want your leaders to be obviously very complex.

Zak: And it’s also obvious, as we mentioned, that the world itself, specifically the demands made on people in leadership positions, in a place like the NSA, for example, or a major organization, or a major urban school district will be just qualitatively more complex than they would have been probably even five years ago or 10 years ago.

Zak: There’s a complexity gap between the task demands of most leadership roles and the capacities of the leaders. And so we tried to set in and differentiate that complexity gap across a couple of domains. Like where is it, the complexity? Is it that they don’t understand operationally the complexity of the stuff they’re doing? Or is it the social complexity, the perspective taking complexity?

Zak: And that’s where we ended up focusing. We found a lot of differential between people’s ability to handle the kind of, let’s say, engineering problem solving side of their jobs, and that the struggles emerged in the domains of perspective taking, perspective seeking, and perspective integration.

Zak: We built a whole series of learning sequences around perspective taking in the domain of leadership. And Clint Fuhs, who was a close student of Ken Wolberg, did his dissertation on that work. And Theo’s continued to advance it.

Zak: So there what you have is a set of a really well specified learning sequences about just how leaders transform in their understanding, moving from being able to take just one perspective, or not even take any perspectives.

Jim: That’s frankly, most of them on day one.

Zak: Exactly. This is what we found. And what’s interesting, and this again, speaks against the idea of classifying a whole person at a level, it’s precisely the people who have the most highly developed areas of expertise, where they’ve become very abstract and complex in one specific area, it’s precisely those people who usually have a complexity deficit in other areas, and are unable to see it.

Zak: Because they’re so complex in one area, they sometimes try to apply those skills to another area and think it’s working when they don’t even realize that they’re in a separate domain.

Jim: I’m going to give you just a quick sidebar example there, for many years I worked providing technology into the investment industry. And one of the truisms of the investment industry, that the world’s worst investors are medical doctors, because they’re great in their domain, way above average and skill. They think they can apply those same set of pattern matching algorithms to the investment world.

Jim: And it turns out, for some interesting reasons, they don’t want apply. But they would never admit it. No, the only ones possibly worst are dentists, who have the same cognitive model, but are about 10 IQ points less intelligent. There’s a found knowledge out in the field that would collaborate your findings.

Zak: Yeah, well there’s another issue, and again, this is what we’ve sometimes ended up calling the Expertise Fallacy, doctors in particular are not great thinkers. But this has to do with how medical schools work, and how insurance agencies constrain a doctor judgment patterns.

Zak: So anyway, we looked at perspective taking, perspective seeking, perspective integration. And these are distinct. And you can be good at one without being good at others, but you can’t be good at perspective integrating without being good at the other two.

Zak: There were many leaders who took perspectives. So they could imagine what it would be like for this person to react to their decision. But they never actually, in any of their responses, suggested seeking out the perspectives of their employees. So we started to do a lot of work around perspective seeking, and the complexity of perspective seeking strategies, which is a very interesting sub domain of leadership development.

Zak: We also did work on leadership vision. And so that’s another area. Just what is the complexity of how the leader understands their self as a leader, and what that job is like, and what the organization, mission, vision, et cetera.

Zak: But we found that not nearly as predictive of success. And we did some work, the large municipality where there were 360s involved, to look at the correlations between complexity growth and improvement, from the perspective of the 360. And the perspective seeking, perspective taking, perspective integration, and in a sense, complexity in general, were predictive of improvement on the 360 scores.

Zak: Yeah, there’s something to be said about understanding leadership from the perspective of this complexity deficit, that the task demands of the world are greater, that we’re in over our heads, as Keegan said. That’s absolutely true. But then you need to differentiate and specify just where is those complexity deficits occurring?

Zak: And so that’s the work we were able to do. And then with the assessments, you’re able to invite someone in to an open-ended essay that they fill out and write. And they receive a quite complex diagnostic report, which is full of educational, basically, supports and offerings.

Zak: The idea is not that you do leadership assessment for hiring firing, you do leadership assessment for the sake of promoting leadership development. That was always our stance. And it remains the case, that the main value proposition of the Lectica assessment is the diagnostic function.

Zak: Now, again, if you can specify the complexity of the role, and the task demand of the position, then you can set a minimum threshold of complexity that needs to be identified for even being considered to being hired. So you can do the go, no go simple sorting mechanism thing with Lectica assessments. And we have some who do that.

Zak: But as I mentioned, because we’ve reconstructed these learning sequences around perspective taking, and ethics, and other various domains where there could be complexity deficits, you can actually use these things very diagnostically. And of course, if you can do one, you can do a team. And you can look at how teams work in terms of complexity differentials of team members. And so there’s a whole bunch of doors that open in leadership development work when you’ve got a suite of measures that are both diagnostic and accurate, and are not Myers-Briggs or IQ tests.

Zak: These are much more well tied into the ecologically valid aspects of the job, which is to say, when you read a response to one of our assessments about how this person would make a decision on the job, it tells you a tremendous amount about them, not whether they’re introverted, feeling, or whatever. You know what I mean?

Zak: I think it’s important to understand too, that metrics and psychometrics in general, permeate leadership development. And a lot of professional development work is characterized by a consultant bringing in a measurement instrument, usually of psychological properties, but sometimes of network dynamics and communication dynamics in a company.

Zak: There’s a power dynamic there which needs to be tracked. And I write about this a lot in my books, because I write about measurement, and the politics of quantitative objectivity. The same thing happens in medical diagnostics. So it’s very important that the practice in which the measure is embedded is appropriate. Because you can use measures as just a bludgeon. And this is how medical measures are used, often, and how leadership measures are used, where it’s an extensively third-party expert that now gets me the expert, who’s in front of you, to basically do my regimen.

Zak: And this happened with IQ tests, and happens with SAT tests, and other things, where the ability to present a quantitatively objective index begins to basically really distort social practice. This is just to say that, yeah, we have these diagnostics, but we also require people to be trained in their use so that people just can’t go out there and use Lectica assessments. There’s a certification process, which is an educational process, which gets into some of what we talked about here, but also more specifics around appropriate use and educational affordances of the assessments and things of that nature.

Zak: That’s a little bit of how it looks. And again, my sense is, yeah, having Theo on for a follow-up would be brilliant, because there’s a way in which, if people have heard all of this, then she can just jump right in and talk about ongoing research and the power of some of the assessments.

Jim: Yeah. That’s very interesting. I’ll just react to that a little bit. Kind of interesting that you found that perspective taking was actually the limiting factor, or at least those strongest signal.

Jim: And I’m going to toss out a hypothesis having grown up in the business world from 1975 to 2000 more or less. There was a period when theories of management were undergoing a very rapid change. 1975, most companies were fairly rigidly hierarchical with a small fan out. Typical rule of thumb was, any manager shouldn’t have more than five to seven direct reports.

Jim: And if you do the math, at an organization of any size, they’ll tell you have to have first level managers, second level, third level, fourth level, the famous General Motors, US Army, Catholic Church model.

Jim: Later, as we started moving into the late eighties, and the nineties in particular, the theory came around that you should flatten the organization, get rid of many levels of managers, which actually make sense in one level, because it takes longer for information to move up the chain to where a decision could be made. And too many decisions had to go up too many levels before they could get made.

Jim: In some companies, they started having managers with having as many as 20 direct reports. And if you think about it from a perspective taking measure, if you have to think about five people that work for you and their perspectives on things as they relate to the whole, because each of those five people have some specialty which relates to the whole, that you’re responsible for, that’s much less difficult than taking 20 perspectives that relate to the whole.

Jim: So I wonder if that very rapid change in management structures, essentially, is what put the stress on perspective taking.

Zak: Yeah, that’s interesting. We never really… I think there’s a lot of things that contributed to it. And what we also found was that it wasn’t that they couldn’t do it.

Zak: Sometimes they couldn’t, right, because there’s, as you said, there’s the number of reports. There’s actually the complexity of the perspectives of their reports.

Zak: Sometimes there’s too many and they can’t do it even if they try. But we often found that it was salience, which was that it just didn’t seem relevant to take the perspective. As soon as they were prompted to take the perspective, they could begin to do it. But it just wasn’t a part of their habitual operating.

Zak: And so it does say something about the environments that people are socialized in. And specifically, I think two things, one would be non-democratic nature of work environments. And the other would be zero-sum competition as characterizing work environments. Both of those things make it so it’s kind of like, I don’t really need to take your perspective, and I might not even want to, unless it’s strategic, in which case I wouldn’t really seek it because then you’d know I was looking for your perspective.

Zak: So I think there’s a bunch of things that, in most corporate environments, would dis incentivize and lower the salience of some of the most important forms of perspective taking and seeking.

Zak: But then there are other, completely structural constraints, where it’s just, this guy just has too many reports. And the reports that are reporting to him are too complex. Like for example, imagine you have a six person team, but they’re all PhDs in different fields. And you’re trying to integrate that into a synthesis. That’s different from a team of six, all of whom are making espressos.

Jim: I mentioned that, I actually ran a business research la. At one point, we had about… Actually, I think we had about 30 PhDs. And for exactly that reason, I very much narrowed the management fan out so that the manager only had four reports. Because I conclude there’s no effing way that a regular business manager, and then we did decide that we needed business managers rather than other PhDs, ain’t no way they could even have a hope of being able to process more than four.

Jim: And that was our team’s size, one manager, four researchers. That’s kind of interesting. And the other thing I was just thinking about, as you were relating this, the idea that when you’re unfortunately in a bad faith game theoretic situation, like a lot of big corporations, perspective taking has a very strange valence, and is less valid in some sense. If you can assume the actors at both ends of the perspective taking are operating strategically, in game theoretically, rather than in good faith.

Jim: One of the things I always pushed in my own companies, first rule of the company, absolute intellectual honesty at all times. And hard to get. But if you build it in from day one, you can approximate it.

Jim: And that is so different than the normal games people play in corporate America. And it allowed us, our small companies, to out-compete some big boys, big time.

Zak: Yeah. And it’s important to get that the Darth Vader move’s always possible, which is the highly abstract and complex person who does a lot of perspective taking, but for the wrong reasons, and for strategic advantage.

Jim: Oh yeah. High function sociopath, nothing quite them.

Zak: Yeah. And there’s a lot of misunderstanding in developmentalism in general, that the higher levels are always better. But this is not true.

Jim: We just had a good example of that. It was good that our want-to-be dictator was not very effective. Right? A good example.

Jim: Anyway, Zak, this has been incredible, just as I hoped it would be. You’ve taken us on a long journey that makes this idea that a lot of people talk about, I think Hansey had a lot to do with popularizing the hierarchical complexity, and you’ve taken it from a vague generality and put a lot of specificity on it, and given us a lot to think about.

Jim: So I want to really thank you for coming. It was just like the last three times, a wonderful episode.

Zak: It was great. I’m happy.

Production services and audio editing by Jared Janes Consulting. Music by Tom Mahler at