What Is The Model of Hierarchical Complexity? 4

The theory that is today the Model of Hierarchical Complexity was first pres­ented by Michael Lamport Commons and Francis Asbury Richards in the early 1980s. It builds directly upon the Piagetian model and the work of Kohlberg and can be consider­ed as neo-Piagetian (although some call it “post-Piagetian”), bec­ause it large­ly suppo­ses that the Piagetian model (with cogni­tive stages) is corr­ect, but that there are sev­eral stages above what a normal human adult achieves, high­er stages that only a minority of the adult popula­tion reach. According to the neo-Piagetians the study of these stages can ex­plain a lot about humanity and society.


The following is a slightly edited extract from Hanzi Freinacht’s book ‘The Listening Society: A Metamodern Guide to Politics, Book One’. This is the first book in a series on metamodern thought, a work of popular philosophy that investigates the nature of psychological development and its political implications. What you will read below is from the chapter on cognitive development; a chapter that introduces the reader to the Model of Hierarchical complexity and the creator of this theory Michael Commons.

Commons first formulated the theory after having taken a year off from work to study mathematics, where the language of abstract algebra helped him to describe the formal relationships between the different stages.

Once this formal relationship was in place, the different stages could be described with generalizable orders of complexity. The order of complex­ity is the complexity of a certain task (such as getting three green balls, a task in which you must coordinate the shape, number and color with the verb “get” – this is stage 5, Sentential, in the model below). The MHC research program is based on task analysis and is thereby depen­dent on the inventions of tasks and dilemmas to test people – it is a branch of experimental psychology. But once you know the stages well enough, you begin to be able to understand at which stage people operate when they do things in everyday life as well (and, yes, you also begin to be able to see which stages your fellow researchers operate at and what order of com­plex­ity their work is).

All the other theorists had built their theories by observing the devel­op­­ment of children or adults. Com­m­ons and Richards mapped the stages math­ematically – and then found that the data mapped their theory much more elegantly and precisely than any of the other theories. Besides, you could use the same models for animals. Clearly, they were on to some­thing important.

Initially, Commons and Richards themselves failed to see the wider impli­cations of their theory. They had primarily devised it as a response to critic­ism of Kohlberg, as some scholars did not believe in there being higher stages than what a normal adult human being reaches at ages 11-14 (the formal-operational stage). But Commons and Richards’ model, in all its reductionist crudeness, took on a life of its own, and impressive results started appearing: people – and their behaviors – mapped onto the diff­erent stages with an almost frightening prec­ision and consistency.

I am not going to discuss the evolution of the model, but just skip to the la­test version of it, now in 2017. The model covers everything from germs and amoeba right up to Einstein. But it does not, as we will see, descr­­ibe exist­ential depth, i.e. it doesn’t account for the Buddha or Kierke­gaard.

The Stages of the MHC

So – sixteen stages, let’s go baby (we’ll revisit the four most relevant ones, stages 10-13, in the next chapter; in this list I have underlined them):

0. Calculatory Stage (molecules)

  • Can distinguish between 0 and 1 (something versus no­thing), much like a digital computer.
  • Can only react to stimuli without any distinguishing for strength of react­ion; “organisms at the edge of life”, like DNA itself.
  • Humans pass this stage long before we are born; indeed, before we are even conceived.

1. Automatic Stage (cells)

  • Can react to stimuli depending on different quantities, but only by automatic response and never through learning.
  • No coordination of different stimuli, there is just a single stimulus-response.
  • Single cell organisms; humans pass the stage before we are born.

2. Sensory or Motor Stage (amoeba)

  • Can react in different ways to different stimuli, and can co­ordi­n­ate two stimuli responses (but not invent new respon­ses). Move body parts.
  • For instance a leech, if you both shine on it with a lamp and shock it with electricity several times, you can get it to respond to just the lamp as if there was an electric shock.
  • Amoeba, slugs, mollusks, early human fetus.

3. Circular Sensory-Motor Stage (insect, fish, newborn human)

  • Can reach, touch, grab, shake objects, babble, make single sou­nds (phonemes).
  • Can move body parts after having perceived objects and can recog­nize things.
  • Most predatory fish, insects, newborn humans. (Note that cogn­itive stage can be the same even if brain size, cogni­tive speed and perhaps the degree of “sentience” vary greatly. Counter-intuitive but true!)

4. Sensory-Motor Stage (rat, small baby)

  • Can do a series of movements that are calibrated after one an­other and build upon one another to achieve something.
  • This includes putting several sounds together so that you can form a morpheme, at least in the language-prone spec­ies of hum­ans (you can use combinations of sounds to “ex­press something” but not yet use a full word consistently).
  • Rats, young baby humans.

5. Nominal Stage (pigeon, one-year-old toddlers)

  • Can find relations among concept and make them into words: single words, exclamations, knowing the meaning of a word. “Nom­inal” because you can name stuff.
  • Can begin to understand what other organisms “mean”.
  • Laboratory pigeons, one-year-old toddlers.

6. Sentential Stage (two/three years old)

  • Can put words together into sentences, and see a series of simple tasks that need to be coord­inated, imitate a sequ­ence.
  • This allows for the use of pronouns like I, mine, you, yours it, etc.—these being more abstract than names of things.
  • Parrots (as famously described by Irene Pepperberg; train­ed parr­ots can go up to this stage), cats, toddlers around two to three.

7. Pre-Operational Stage (three to five year olds)

  • Can make simple deductions (but not spot contradictions), follow lists of sequential acts, and tell short stories (by coord­inating sev­eral sent­ences).
  • Can use connectives (in humans): if, then, as, when, etc. Puts toge­­ther several sentences into a “paragraph”.
  • Dogs and small children, three to five years old.

8. Primary Stage (five to seven years old)

  • Can do logical deduction and use empirical rules; adds, sub­tracts, divides, multiplies, proves, does series of tasks on its own.
  • Can relate to times, places, can count acts and relate to separate actors. Can construct relatively coherent narra­ti­ves (“groups of para­graphs”); these create accounts and ideas about what’s going on.
  • Chimpanzees and rhesus monkeys; in humans, five to sev­en year olds.

9. Concrete Stage (seven to eleven)

  • Can do long division, follow complex social rules, takes on roles and coordinates self with others.
  • Can create meaningful, concrete stories and keep the same story intact and consequential over time. Puts together groups of para­gra­phs into a story. Can thus keep track of inter­relations (which is the best tool, and how would you test it, etc.), social events, what happ­ened among others, reasonable deals, history, geography.
  • Normal in humans at ages seven to eleven, but also a signi­ficant portion of the adult population. In the famous bonobo chim­pan­zee stud­ies of Frans de Waal, there are ex­amples of concrete stage behav­iors, such as testing sev­eral tools to determine which is the best one.

10. Abstract Stage (ages eleven to fourteen)

  • Can form abstract ideas and thoughts: single, generalized varia­bles that fall beyond the concrete sequences of events in a story—can make and quantify abstract propositions.
  • Relates to categories and uses “cases of events” to incre­mentally im­prove the understanding of these categories.
  • Humans eleven and older, a significant part of the adult pop­­ulation, about 30%. No known non-human animals.

11. Formal Stage (ages fourteen to eighteen, if at all)

  • Can identify relations between abstract variables and re­flect upon these relations, devise ways to test them, etc. Solves problems using algebra with one unknown, uses logic and empiricism.
  • Can speak a full, rich language with self-reflection, uses logical seq­uen­ces of connectives: if this, then that, in all cases.
  • Fourteen years and onwards. The most common stage in adult hum­an beings, about 40% of the adult population—only a mino­rity go bey­ond this stage.

12. Systematic Stage (eighteen and above, if at all)

  • Can identify patterns among linear relationships, thus for­m­­ing syst­ems of relations among abstract variables and how these inter­act. Can thereby also solve equations with sev­eral unknowns. The first “post­formal” stage, i.e. it was not described by Piaget, but imp­licated in Kohl­berg’s work.
  • Begins to discuss legal systems, social structures, eco­systems, eco­n­o­mic systems and the like.
  • Can ­be found in about 20% of adult humans, usually after age eight­een.

13. Metasystematic Stage (early twenties and above, if at all)

  • Can compare and synthesize several systems with differing logics, put together “metasystems” or conclusions that hold true across diff­er­ent system, reflect upon and name general proper­ties of syst­ems.
  • Understands that things can be “homomorphic”, “isomor­ph­ic”, etc. This means that you can see how one system can be changed in corr­espond­ing or differing ways to an­other system.
  • Can be found in about 1.5% of the adult population, usu­ally only after early twenties.

14. Paradigmatic Stage (mid-twenties and above, if at all)

  • Can deal with several very abstract metasystems to cre­ate new ways of thinking of the world, new paradigms, new sciences or bran­ch­es within sciences.
  • Has a fractal way of thinking, so that the universal princ­iples found are applicable to many different levels of analysis and ph­enomena.
  • Prevalence unknown, but if the pattern holds and every stage seems to increase with about a standard deviation, it should be a little more than one adult in a thous­and in a normal population, mostly at ages 25+. This makes it rare, but still some three million people in the wor­ld (one thou­sandth of the functional adults above 25). Although the stage is theo­re­tically formulated, there is no reliable test for it.

15. Crossparadigmatic Stage (late twenties and above, if at all)

  • Can deal with several paradigms to create new fields.
  • Examples are: Newton’s reformulation of physics, Dar­win’s the­ory of evolution, Einstein’s theory of relativity, the invention of quant­um physics, the invention of chaos ma­th­e­matics and com­plexity, the invention of computing, the invention of postmodern philosophy, the invention of the holistic “integral theory” of Ken Wilber, the inven­tion of string theory, the invention of the MHC theory.
  • Prevalence unknown, found only in adults older than twen­ty and who have privileged circumstances. It most often shows up ar­ound 30. No reliable test for this stage.

What you get here is a model of cognitive complexity that places hum­ans and other animals on the same scale. This kind of thinking leads us towards quest­ioning some of the “speciesist” assumptions of our day and age: that there would be anything “special” about humans.

Admittedly, there are some things unique to humans, such as our pro­pen­­sity for language use – which appears to be a certain genetic property; in 2009, researchers transplanted such genes to mice and heard them make more intere­sting squeaks. This is also in line with what Noam Chomsky’s lin­guistic theory would suggest; that we should view lang­uage as a biological pro­perty of hum­ans.

Commons’ theory naturally focus­es on language (words, sentences, in­crea­singly complex grammar, narratives, concepts…) because it is mostly used to study humans. But the MHC stages or “orders of complex­ity” are per­fectly possible to describe in non-linguistic terms, such as abstract alge­­bra, which is what Commons initially did. So even animals that don’t speak (like the pig­eon at stage 5 Nominal) can display behaviors at equal or higher orders of complexity than e.g. young hum­an chi­ldren, even if kids talk and pigeons don’t. Speech is a useful tool when it comes to accomplishing complex tasks, but it is not in itself necessary for cognitive complexity (or sentience, for that matter: having subjective experience, feelings, etc.). This should insulate us against ling­uistically based species­ism, where humanity’s “special­ness” is legitimized by the fact that we have language use.

Before we go on, let’s just note again that cognitive stage according to MHC is not a moral order – we have noticed for instance that human new­borns can be described at the same stage as an insect (stage 3 Circular Sensory-Motor), but we’d hardly ascribe the same moral value to the two. Moreover, you can see variations of MHC stage in animals of the same species. This goes for newly born cubs ver­sus fully developed adult dogs, as well as indiv­idual differences where some dogs out-stage their fellow canines. Irene Pepp­er­berg’s parrot was trained, after years of hard work, to go up one stage from 5 Nom­inal – where it could get a ball (out of several options, with cubes, rings, etc.) in order to claim a reward – to 6 Sentential, where it could get “two yellow balls”, etc. The parrot just had to think for a very long time to fig­ure it out, its brain being much smaller than a human one. This means that a human at the same stage, but having a far “higher IQ”, would reach the same conclusion as the parrot, just at a much faster pace.

So we are not taking anything away from the fact that members of two diff­­erent species, who are at the same stage, can still be very different from one another. Just consider the fact that some species have mate selection by means of bloody tournaments, like baboons (and a relatively short-lived rock n’ roll lifestyle alpha male gets all the punani and offspring, be­fore he is violently dethroned), and others through pair-bonding, like bonobo chimps (most of the population procreates and guys help out with the kids) – with humans being somewhere in between, judging from our phy­siological traits such as moderately larger males than females and med­ium sperm com­petition (as implied by testicle size, and, uhm, I guess by our sexual behavior). These species (bab­oons, bon­obo chimps and humans) are behaviorally and psych­ologically quite diff­erent from one another even if their cognitive stages partly overlap.

Of cou­rse, such species-specific traits shape behavior, and of course there is plenty of evolutionary psychology to account for much of what goes on in humans and other animals. But still, the complexity of those behav­iors can be descri­bed with the help of our new friend – the MHC – and that puts all animals on the same scale, a scale on which adult human beings, surprisingly perhaps, differ vastly from one another.

This last part is both counter-intuitive and con­troversial. So let’s examine it closer.

Stage 10 Abstract

Who? Emerges at ages 11-14. Observed only in humans.

How many? About 30% of a normal adult population in modern coun­tries reach and stay at this stage throughout their lifetime.


To “be at this stage” means to display only behaviors and cognitive opera­tions of this order of complexity or below – i.e. that you produce original thoughts, reasoning and behaviors which are maximally this complex. However, of course, your development doesn’t stop at age 14 just because your MHC stage does. You still learn, develop and change in other ways throughout your lifetime.


Remember: in terms of language use, stage 9 Concrete means that you can put together many different paragraphs into one overarching narrative and name that narrative: the Iliad, etc. But whereas Homer’s Iliad con­tains a lot of succinct and interesting human understanding, you don’t find it abstracting variables and defining them.

The pre-Socratic natural philosophers, however, did exactly that: the essence of the world is water, suggested Thales; Heraclitus held that only change is constant, and so on. The ancient Greeks obviously could per­form many actions that were of stage 10 Abstract or beyond: ship build­ing, plann­ing trade and conquests, administration, navigation and so forth. But philoso­phy that corresponds to stage 10 Abstract was not yet present in early litera­ture and drama, and only showed up with the pre-Socratics (about 6th century BCE).

I chose the example with Greek literature and drama and the birth of West­ern philosophy simply because you here have a clear shift from expli­citly expressed thoughts at stage 9 Concrete to stage 10 Abstract ideas or variables. Of course, this shift is possible in many other non-explicit and non-linguistic forms.


At stage 10 Abstract, we can invent our own abstractions: not just chairs and tables, but furniture; not just furniture and domestic appliances, but “all movable objects you put in a home”; not just home and office but all indoors environment – and so forth.

This is not just mimicking words like “furniture” used by others, but act­ually creating novel abstract concepts or variables themselves.

The stage 10 Abstract thinker can then use quantification of these var­ia­­bles: some of the furniture, some of the time. This can refine the varia­bles, make new distinctions and let the abstract concepts acquire new meanings.

The abstractions are taken from stories about concrete things, people and events. These abstractions – furniture, love, justice, animosity, weight, vol­ume – take on meanings that go beyond the particular story they are a part of.


Let’s invent a variable to try this out: the ruggedness of mountain cliffs. We can have more or less of it, relate it to time, say that this variable causes mountains to be difficult to climb, etc. We can name the variable a new word: blefuscity (it’s a made up word).

Unlike the word “ruggedness”, blefuscity only denotes ruggedness in the way that mountains are rugged – not the way that a person can have a rugged look. “High blefuscity” means that the cliff range has many sharp edges and “low blefuscity” means it has fewer such edges and that it is smoother.

Now blefuscity takes on a life of its own, beyond the singular, concrete story. But in the next story we tell (let’s say it’s a story about mountain­eering), we notice that the cliffs are hard to climb but undeniably have “low blefuscity”. The mountain slope was steep and smooth. So we make a dist­inction between “blefuscity” and “steepness”. We have thus refin­ed the mean­ing of “blefuscity”, but it can always be further refined or challenged.

And so – the world we live in soon becomes a world of abstractions, a world of abstract concepts that have definitions and quantifiable proper­ties. When we conceptualize reality at this stage, narratives still matter (this and that happened, I am from that place, etc.), but they are hinged on abst­r­ac­tions: “a story about love”, etc.

Whoa. So that’s pretty good. And the only creature that has ever been observed to do this is Homo sapiens (but we can probably count in the Neanderthals and other hominids). We can name, relate to and quantify a world of abstract things.

Shakespeare would have said: “Oh, wonder! How many goodly creat­ures are there here! How beauteous mankind is! O brave new world. That has such people in ‘t! MIRANDA. How amazing!”


What the stage 10 Abstract cannot do, however, is to describe regular rela­tions between different such abstract ideas.

We can still, however, by means of a shared language, take part of the ideas that other people produce at higher orders of complexity. (We can also, if guided through the sequences of actions, perform tasks that are up to two stages above; we’ll get back to that).

By definition, if we never ourselves have displayed original behaviors high­­er than this stage, we are said to “be at” stage 10 Abstract.

Let’s return to our example with steepness and the invented abstract variable “blefuscity”. For instance, very high steepness tends to create an even slope, which then means low blefuscity (few sharp edges) – which still makes for a very difficult climb (whereas our stage 10 Abstract thinking would have us believe that low blefuscity should make the climb easy).

This means that we easily land in false conclusions because we alternate between using steepness and blefuscity in our thinking, but fail to clearly and distinctively formulate the even more abstract rule which guides how we should use the two variables. We fail to see the formal relationship between the different abstract variables.

Why is this a problem? Because, as it turns out, the world around us – and inside us – behaves in ways that are so often not sufficiently and pro­ductively described by a single abstract variable. This means that, as stage 10 Abstract thinkers, we will very often respond to the world around us in simplified manners: in black-and-white, either-or ways. In everyday life that may be more than sufficient. But unfortunately modern people, at least as a collective, have to deal with much more complex issues than creating, choosing and quantifying single variables.


As mentioned earlier, the MHC research is based on “task analysis”, i.e. the idea that every task has an “order of complexity” that can be analyzed: getting through a maze is more complex than walking down a road and so forth. The order of complexity is not the same as “difficulty”, which is much more context bound. Now let’s look at some tasks in everyday life that would require stage 10 Abstract thinking. We will get back to a corres­ponding list of tasks when we discuss the higher stages.

  • Writing a conclusion in an essay that ties the whole thing together.
  • Pointing out the common denominator in a few different stories (love story, story about deceit and revenge, the same moral of the story).
  • Inventing new words for things that are not concretely present.
  • Driving a bus (following traffic rules and keeping in mind the length of the bus and other factors that are out of your sight).
  • Simple nursing (categorizations of patient behavior and reporting back to doctor, quantifying several medical variables, relating to these rather abstract variables, etc.)
  • Non-investigative journalism: reporting events and abstracting what “the story” is.
  • Accurately drawing 2D objects (without conceptualizing new styles or art forms).
  • Artisanship or building that requires a planned idea (but no engin­eer­ing or physics calculation).
  • Creating a map, or reading one without assistance.
  • Teaching kids to read and write.


Our stage of hierarchical complexity also affects how we think about poli­tics and society. Regardless of political persuasion, we can think more or less complexly about political issues. Let’s look at some stage 10 Abstract argu­ments of different political hues.

  • Anti-racist argument: Racism is bad: it is a self-contained and self-expla­n­atory essence that spreads by itself unless you stop it, causing discrim­ination and possibly tyranny and war.
  • Conservative argument: The Arabicness inherent to Arabs gives them traits that are irreconcilable with Western civilization.
  • Feminist argument: Feminism means to stand up for women and crush patriarchy.
  • Libertarian argument: The less state control, the better.
  • Green argument: Human greed causes crises and destroys the envi­ron­ment.
  • Day-to-day politics: I am frustrated both by high taxes and low spend­ing; by both high unemployment and low starting wages.


As stage 10 Abstract thinkers, we cannot see the general rules that govern when our abstractions should apply, when they can be expected to have cer­tain properties and so forth. This means that we will tend to focus on one single variable and want to either increase or decrease its quantitative value: less immigration, lower taxes, more love, more dialogue, less greed etc.

If confronted with a counter-argument (e.g. that more dialogue also means more time-consuming squabble, which in turn may not serve the pur­pose) the stage 10 Abstract thinker will simply insist upon having both: more dialogue and less time-consuming squabble. This is the less complex form of both-and thinking: not accounting for a produc­tive tens­ion between both sides, but simply denying that one’s argument has trade-offs or downsides.

As stage 10 Abstract thinkers we can sometimes insist upon doing things that to others is apparently counter-productive. For instance, the management department at a (modern, computerized) hospital can dec­ide to cut the budget and make a decision to close down many of the prin­ters. In effect, this may cause the nurses to walk much longer stretches to the printers farther away, in effect costing much higher wages if seen per hour and reducing efficiency – just to save some ink. In this case (which is taken from real life) the management uses the singular variable (“saving costs”) but fails to coordinate it with other variables (“cost per effective hour of work”) and in effect make budget cuts that are directly wasteful.

Have you ever been in an argument where you patiently and politely add­ress the inconsistencies of your counterpart’s argument, but they seem to repeat the same phrase or concept as if it were an answer in itself? This is probably a stage 10 Abstract thinker. At this stage we can spot obvious factual inconsistencies, but we cannot spot inconsistencies in how we apply abstract variables: for instance, lower taxes and higher welfare, please! And if you point out that there may be a trade-off, the stage 10 Abstract thinker will think that you are being vague and just playing with words.

Thinkers of each stage have this kind of complexity bias. Complexity bias means that we intuitively prefer forms of reasoning that correspond to our own stage of complexity. Explanations of lower complexity seem crude and simplistic to us, whereas higher stage explanations seem vague or counter-intuitive.

Stage 11 Formal

Who? Adolescent and adult humans. Emerges, if at all, at ages 14 and older.

How many? About 40% of adult humans in a normal, modern popul­ation.


This is the most common adult human stage and where Inhelder and Pia­get’s original model ended (this is somewhat of a simplification, but never mind). That someone is at this stage means that they perform tasks of this order of complexity – original behaviors not guided by others. Again, we don’t know what this means in terms of the organism internally, but we can certainly observe behaviors at this stage.

Even if this stage emerges in adolescence and relatively few people grow beyond it, people of course continue to change and develop in other ways throughout their lifespan.


In the history of science, understanding Newton’s three laws of motion is an example of stage 11 Formal thinking. To successfully coordinate the three laws, however, requires the next stage (stage 12 Systematic) – not to mention inventing these laws in a time before natural science was clearly established (which requires a much higher stage).

This is just to give a clear example of stage 11 Formal when formalized in scientific theory. Of course, outside of science, a lot of people were per­for­m­ing stage 11 Formal tasks: coordinating prices with demand, invest­­ments with risks and rewards, setting up rules and legal systems, building advanced structures, handling relationships between people with different interests by means of fair rules, creating ways to compare different meas­ure units and currencies, and so forth.


We can now invent our own rules or principles that describe or guide the relationship between several abstract variables. The relationships can be linear or not, but they make us see some kind of plotted line.

This means that our thinking and our actions become guided by such rules or principles: if this, under these circumstances, then that.

It also means that, because we know the rules guiding the relationships between different abstract variables, we can guess the value of an abstract variable simply by knowing the values of the other related variables. We can “see around corners” and think ahead in ways that children cannot.


Let us return to the invented variables blefuscity (the ruggedness of cliffs) and steepness. We concluded that blefuscity and steepness both cause the climb to be more difficult.

But let’s assume that, on a very steep cliff, you can only climb it if it also has high blefuscity: otherwise there is simply nothing to hold on to.

If you only study blefuscity, you don’t notice this: all steep cliffs with high blefuscity are difficult to climb, as are all not-so-steep cliffs with high blefu­scity. It is only when you compare different steep cliffs, that you not­ice that high blefuscity makes for an easier climb.

So what we assumed was a property, an essence, inherent to the varia­ble, was in fact only true under some circumstances. We have gone from a think­ing with “blefuscity and steepness” to one where we relate to “blefus­city and/or/if steepness”. And our whole view of the situation changes.

We have invented a rule that describes the relationship between three var­ia­bles: blefuscity causes greater difficulty under low steepness and lower difficulty under high steepness. We call it “the general rule of ble­fus­city”. An elegant rule of the universe. And the stars glisten.


What we cannot do as stage 11 Formal thinkers, and what most adult people actually never quite do during our lifetimes, is to relate several such formalized rules to one another and form one coherent system of thought.

This is partly where the MHC theory becomes so counter-intuitive that it loses many adherents: it just seems implausible. The simplest systems are such things as a “catch-22” or a feedback cycle, or a balance of two simul­taneous processes. Could it really be that almost 80% of all adult humans never think such thoughts or perform the corresponding actions? I will dis­cuss this in a section after the four major stages have been pres­ented. Suffice to note, at this point, that we are speaking of the ability to create original thoughts and behaviors of that stage. This means that, in a civilization that is global and has many, many millions of people inven­ting behaviors and concepts above stage 11 Formal, there will simply be so many higher stage actions and concepts around, which can be taught and performed with help, or simply misunderstood. So we tend to not notice that a minority of people are actually doing most of the more complex inventing.

If recognizing the “catch-22” as a concept is so easy, how come there wasn’t even a word for it before John Heller’s 1953 novel with that title? You may have read or heard of Malcolm Gladwell’s 2008 book Outliers, which points out the great significance that unusual, exceptionally talent­ed people called “outliers” have in society’s development – although he qui­ck­ly and fam­ously points out that such people always have good cir­cum­stances, that they put in 10 000 hours of practice, and always rely upon some help of their friends.

Or you may know of Clay Shirky’s 2008 book on the participatory pot­entials of the internet Here Comes Everybody, where he points out that, after all, only a small minority of the users of e.g. Wikipedia actually create the content. This may also be because relatively few people have complex enough understandings of many of the topics.

I agree with Michael Commons: it appears as though most people never construct complex systems of thought or behavior. But then again, most tasks in everyday life can be successfully managed with stage 10 Abstract and stage 11 Formal behaviors or below.

The challenge to stage 11 Formal thinking comes primarily when we deal with systematic issues of society, ecology, economy, organizations, social psychology and the like. For instance, we may have problems with seeing how the messiness in the college kitchen dorm is a result of syste­mic pro­perties of sharing a kitchen, rather than as someone’s breach of the rules. We tend to think that a single rule, or breach thereof, explains issues that indeed require us to consider the system as a whole.

Paul Haggis’ 2004 movie Crash focuses on issues of race and class in Los Angeles. It’s the darling film of sociologists, even with direct referen­ces to sociological research (the lines from the opening scene are directly taken from the American sociologist Jack Katz’s ethnography on road rage). The movie shows how the many characters are by themselves rel­at­ively innocent, each being a victim of their respective circumstan­ces – but the collective result of all the characters’ perceptions and actions crea­te a tense, racist and violent society.

Let’s just say that if the script writers were at stage 11 Formal, this mov­ie would have looked quite differ­ently, with a much more linear plotline and single-cause explanation of racism.


  • Writing a conclusion in an essay that ties the whole thing together and fruitfully compares it to other texts.
  • Pointing out the patterns of how plotlines evolve in stories of different gen­res and explaining the logic to why this is so.
  • Inventing new words or expressions for processes, rules or general prin­ci­ples.
  • Driving a large truck with multiple trailers (meaning, you have to con­sider how the trailers affect one another when you drive back­wards out of a garage, etc.).
  • Medical work with independent decision making (qualifying diagnosis, weighing, choosing and applying one or several treat­ments, etc.).
  • Economic journalism: how businesses are affected by changes in the eco­no­my, etc.
  • Accurately drawing 3D objects (without designing novel styles or art forms).
  • Artisanship or building that requires a planned idea and engineering or ph­ysics calculations.
  • Creating a map, and providing correct instructions on how to read it.
  • Teaching kids to read and write, using different methods for depen­ding on the characteristics of the children.


  • Anti-racist argument: Racism results from economic and social ineq­ua­l­­ities in society and causes further inequality and discrimina­tion.
  • Conservative argument: Some cultural norms followed by Arabs may be irreconcilable with Western civilization.
  • Feminist argument: Feminism is to apply the principles of gender equa­l­­ity and to make these principles prevalent throughout society.
  • Libertarian argument: The less state control, the better, except that main­­tain­­ing law and order is necessary. To establish law and order may temp­orarily require increased state control in “failed state” areas.
  • Green argument: The lacking proportionality between our em­phasis on human interests, especially those of rich people, and the interests of ani­mals and ecosystems, is what causes crises and destroys the en­vironment.
  • Day-to-day politics: I see a trade-off between high taxes and high spend­­ing, between low unemployment and high starting wages.


Generally, because of cognitive bias, stage 11 Formal thinkers will tend to like to stick with certain principles. Of course, sometimes finding the sim­ple principle or rule that guides the apparent messiness of reality can be a mark of much higher cognitive stages (think Newton). But if people like to stick with rules and principles not invented by themselves and they tend to make linear plans about the future and tend to focus on single if-this-then-that principles, you are probably dealing with stage 11 Formal thinking.

In politics, stage 11 Formal thinkers generally have a penchant for clear ideologies or doctrines: socialism, libertarianism and the like. They are likely to repeat one common wisdom, e.g. the conservative idea that things often go wrong when you try to be utopian or the radical idea that most social change has come through struggle.

Remember, this is the most common stage. Adult middle class people in a modern society will very often be of this stage of cognitive complex­ity. At this stage we don’t really produce our own theories or solutions, simply foll­owing the rules and habits set out by others. We can of course still be intell­igent (high IQ), artistic, imaginative, skilled and so forth.

Stage 12 Systematic

Who? Adult humans, or late adolescents.

How many? About 20% of a normal adult population in modern count­ries.

Intuitive example from science? Darwin’s theory of evolution (Darwin him­self was higher stage, of course).


As stage 12 Systematic thinkers we can coordinate several formal rules or simple equations (not necessarily in formalized, mathematical language, of course) to see how they form a larger system.

We can hence solve equations with several unknowns. You may rem­ember equation systems from high school math. This is a simple form of system, where we relate two linear equations to one another and thereby solve them (or determine that they cannot be solved or have different possible solutions).

But most people can pass these tests? Yes, of course: under the circum­stances where someone is walking us through the steps. But does our brain spontaneously and repeatedly create thoughts that relate to such syst­ems? In about 20% of us, it does. In most of us, it doesn’t.

If you look around at how our politicians and the electorate reason on various issues, or indeed even how much, if not most, of academic research is conducted, you notice that it does not really reason beyond stage 11 Formal models.


So we had the thing with blefuscity (ruggedness of cliffs), steepness and the difficulty of the climb: “the general rule of blefuscity”. Now let’s add another rule: the climber’s characteristics. The climber can be tall or short (with cor­re­sponding length of arms) and she can be a good or bad climber.

Are we just adding more factors to our equation? Is this not just more of the same? No. We are looking now at something completely different: how the entirety of the system (the climbing of the mountain) is affected by the interactions of two quite different sets of variables.

Let’s say that the climber generally is better at climbing if she’s taller. But then it turns out that this only holds true under some circumstances: some­times shorter arms and legs are better. Shorter legs are better when there is very small distance between each crack and protrusion in the cliff.

So now we have to break up the variable “blefuscity” into three const­ituent parts: the frequency, sharpness and size of the cracks/protrusions of the rock. At very high frequency (low distance between the cracks), short­er arms make for a better climber, and at medium or low frequency (grea­t­er distance between each of the cracks), longer arms are advant­ageous.

Also, the better the climber, the more she can use blefuscity to her adva­n­­t­age. In fact, the best climbers actually are demotivated by long, easy climbs, thus in practice climbing the more difficult mountains with great­er vigor and skill.

This makes us re-evaluate the “general rule of blefuscity” that our friend at stage 11 Formal formulated (that blefuscity makes for a more diff­i­cult climb unless it’s a very steep climb, in which the reverse is true). It turns out to be not-so-general after all: even steepness can make for an easier climb, because, together with the right kind of blefuscity, it motiv­ates the climber and breaks up the climb into manageable and interesting parts.

Here, at a view from stage 12 Systematic, we see that neither blefuscity, steep­ness nor indeed “difficulty”, were what they seemed. They are all so much more contextual than we would have thought.

Of course, in a discussion, the stage 10 Abstract thinker may appear more certain and common sense: blefuscity makes for a difficult climb! The syst­em­atic stage 12 thinker may seem less sure of herself, having to think longer, to explain herself more technically and wordily, but she has never­theless a much deeper understanding. And she can make for the best mountaineering. And she alone can formulate “the theory of mountain­eering”. Glory days.


But even as stage 12 Systematic thinkers, we are limited to thinking of one system at a time. We don’t see that systems follow fundamentally different logics.

So at the stage 12 Systematic we tend to want to squeeze everything one and the same coherent system, not being able to compare different syst­ems with quite different properties. If we are engineers, we tend to believe that the world consists of systems resembling engineering, if we are socio­logists we believe it is made up of social constructions and tend to misinterpret and under­value e.g. biology and psychiatry – and so on.

The main problem of many of the adult development theorists, from Jane Loevinger and Susanne Cook-Greuter to Robert Kegan, stems from the fact that their authors are at this cognitive stage. This is why their minds smash development into one unified model of one-dimensional development. They fail to see that there are different forms of develop­mental systems and that the logic of one such dimension cannot unprob­le­m­a­tically be applied to the others. These thinkers tend to have great existential depth (as discussed in the following chapters), but that does not cancel out their cognitive shortcomings.

So stage 12 Systematic cannot solve deep, wicked issues that span across sectors of society and the sciences. The high esteem that “inter­disciplinarity” holds within academia these days is really a vaguely form­ulated grasp for stage 13 Metasystematic solutions. Simply mixing panels with different scien­tists is only lip-service to the complexity of our day and age.


  • Writing a conclusion in an essay which criticizes and goes beyond the thinking presented in other comparable essays (teaching at uni­ver­sity level, I can say that only a few students manage to do this, even among the ones who study very hard).
  • Inventing a new form of plotline or genre within literature.
  • Inventing new words for theories, systems or “principles about prin­ciples”.
  • Overseeing the traffic system in a city, reducing risk, bottlenecks and poll­u­tion.
  • Medical work with applied critical thinking within science, com­paring different research results and perhaps putting forward novel theories and methods.
  • Critical investigative journalism: being able to see cracks and loopholes in the system and putting these in focus.
  • Accurately drawing or otherwise representing multidimensional obje­cts (including by successful use of the multiperspectivalism of (post-) modern art).
  • Artisanship or building that requires the creation of novel methods, app­lying physics or engineering in unconventional ways.
  • Providing instructions for creating good maps and how to provide instru­c­tion for reading them.
  • Comparing and inventing different methods for teaching kids to read and write.


  • Anti-racist argument: Racism is an emergent property of all soc­ieties and interacts with things like inequality. Blaming and pointing fingers is gene­rally unproductive and one should instead try to add­ress the long-term issu­es that may be causing ethnic tensions under these part­icular circum­stan­ces.
  • Conservative argument: There are challenges in reconciling West­ern and Islamic culture which depend on how these categories inter­act, rather than flaws inherent to either category.
  • Feminist argument: Feminism means to work towards a long-term equi­librium where self-reproducing inequalities have petered out and peo­ple of all sexes and gen­ders have less reason to feel insecure and frustrated.
  • Libertarian argument: State control and policy implementation tend to have unexpected and unwanted consequences as society is always more complex than we recognize. It is therefore good to be restrictive with reg­ula­tion and policy.
  • Green argument: There are serious systemic flaws in our economic syst­em that cause crises and may lead to ecological collapse.
  • Day-to-day politics: Public spending should carefully follow and counter international trends – this optimizes the labor market. But the labor market can unfortunately not be expected to function per­fect­ly; it always lets some people down.


Stage 12 Systematic thinkers will tend to have less rigid opinions but more rigid argumentations. So one way to spot them is simply to ask them quest­­ions about their opinions: if there are few rules of thumb and clear conclu­sions, but much weighing of different factors, it may be stage 12 Syst­ematic.

The stage 12 Systematic thinkers are often more inventive than others, so if the person has made unconventional innovations, this may indicate this stage.

But perhaps the easiest way may be by means of their cognitive biases: stage 12 Systematic thinkers tend to believe that the world consists of systems and their properties. So you find a strong bias towards explan­ations of this kind: structures, patterns, regularities, the economy, the biological body, Darwinian evolution, the gender norms and so forth.

Stage 13 Metasystematic

Who? Adult humans from early 20s and onwards.

How many? Only about 1.5-2% of a normal adult human population.

In the history of science and philosophy you might find ideas that embody this stage of complexity in relative recent branches such as general infor­m­­ation theory, cybernetics, complexity science, chaos theory, the systems sci­en­ces, metatheory (theory about theory), Wilberian integral theory and per­haps epigenetics. Of course, just studying these sciences doesn’t mean that the student is automatically a stage 13 Metasystematic thinker. And most of the innovators within these fields are of still higher cognitive stages (14 Para­digmatic or 15 Crossparadigmatic).

I will present this stage more briefly. The point is that the stage 13 Meta­systematic thinker is capable of com­paring the general properties of systems, naming these properties and reasoning about when they general­ize or not. Let’s jump right to the invented example.


We can observe then, that it is not blefuscity (and its sub-factors), even com­bined with steepness, that determines how good a climb (how much value, recreational or practical) we get. Nor is it the characteristics of the clim­ber that determines the climb. Rather, it is a property of the system as a whole: how well-aligned the different variables, across both systems (cliff and clim­ber), are to one another, with regard to value created by the cliff/climber syst­em as a whole. So the overall alignment of the system deter­mines the climb: not any single variable like blefuscity. Our previous ideas about ble­fus­city reveal themselves as “true, but partial”.

So we have added a term, alignment, to describe the system as a whole. Let’s expand that term: how much can you adjust the different variables so as to increase their alignment? We are now introducing an invented meta-syst­em­atic term: alignability.

The cliff/climber system has low alignability (a property of the system): it is difficult – or it has high cost – to change any one variable (to, for instance, make the cliff less rugged), and the different variables effect al­most no change upon one another. The low alignability of the cliff/ clim­ber system will only produce value in relatively few cases.

Compare this to another system: the market economy. Each of its parts is much more dependent on the other parts. Things like supply, demand, distrib­ution sys­tems, and legal frameworks change all the time. Because of the market system’s high alignability, it aligns into value-creating (and there­by behaviorally self-sustaining) equilibria all the time. It is not logic­ally necess­ary to have a market to produce food or to create other value – so there is no logical necessity for why markets should be so much more central to most humans than is mountaineering.

The reason that markets are much more prevalent and important is that there is a certain property of this system that e.g. mountaineering does not have: high “alignability”. If it were mountaineering that had such high align­ability, it would be more central: we could just align its different parts in ways that created more value. The market can steer the right people to the right mountains, with the right equipment and most other people to other acti­vities, such as skiing.

There is a long stretch between the stage 10 Abstract concept of “ble­fus­­city” and the Stage 13 Metasystematic concept of “alignability”. We have made a major climb, into more abstract heights, viewing the world from a much more ele­vated conceptual vantage point. We have traveled away from concrete reality: whereas “blefuscity” is an abstract concept, you can still see it with your eyes, feel it with your hands. And we have arrived at a much less tang­ible world: the “alignability” of systems and how it creates value.

We have also made conceptual leaps: from discussing relatively con­crete and small matters, to grasping a wider world.

And we have abandoned the topic (mountaineering). That’s what a cogni­tive advance often looks like: that which seemed so important at an earlier stage seems less so – and more contingent – when viewed from a higher cognitive vantage point.

From here, let’s go straight to the political reasoning examples.


  • Anti-racist argument: Racism emerges as different cultures and status hier­archies interact, where ethnic markers are used in order to increase one’s position in the status hierarchy. It should be pre­vented by the crea­tion of both greater psychological security and by the facilita­tion of prod­uctive dialogue about cultural differences.
  • Conservative argument: Liberal values prevalent in Western coun­tries may be more functional in late modern society than the more traditio­n­alist values of many Arab Muslims, but for the successful integration of these different cultures one must take the perspectives of all parties seri­ously.
  • Feminist argument: Feminism is an interest group movement as well as a social justice movement. As an interest group movement it must be weigh­ed aga­inst other interests and perspectives. As a social justice move­ment it must be coordi­nated with other social justice issues such as class, ethnicity, global inequality, other gender issues (including men’s issues), and the exploitation of animals and nature.
  • Libertarian argument: State control and policy implementation always interact with other societal systems and are dependent upon these for their successful functioning. It is thus important to care­fully weigh state regul­ation and policy against other possibi­lities: markets, culture, and civil sphere. State regulation is often not the best path ahead.
  • Green argument: The logic inherent to the economic system is funda­mentally alien to the logic of the ecosystems of the many bio­topes. This means that there is no self-regulating feedback cycle directly present bet­ween our eco­nomic and technological expansion and the eco­syst­ems upon which we depend. This lack of feedback means that we have to drive the ecosystem to collapse before the market self-adjusts. We must thereby create some other feedback, e.g. by means of policy, pub­lic awareness or cultural development.
  • Day-to-day politics: Public spending can be high or low, where higher spending is generally made possible by strong institutions such as rule of law, policing, democracy and free press. This keeps corruption down and allows for public support of spending and makes spending less wasteful. There is no one answer about high or low taxes; you have to coordinate it with the other societal systems.

Note that the different political stances at stage 13 Metasystematic gen­e­r­­ally have more in common with one another than with the corres­pond­ing ideological positions at the earlier stages. This has important implic­ations for metamodern politics.

And that concludes our brief guide to the four most important stages of cognitive adult development. There is more to it, but that’s all you need to know the basics.


Hanzi Freinacht is a political philosopher, historian and sociologist, author of ‘The Listening Society’, and the upcoming books ‘Nordic Ideology’ and ‘The 6 Hidden Patterns of World History’. Much of his time is spent alone in the Swiss Alps. You can follow Hanzi on his facebook profile here.

4 thoughts on “What Is The Model of Hierarchical Complexity?

  • Kristoffer Rønn-Andersen

    I find this section really interesting and it has for sure spurred some thoughts, about thoughts :P

    I am curious to hear your thoughts on how different types of artificial intelligence fits into the MHC. Especially at which stage one might place a general AI. I have often had difficulty trying to evaluate how advanced AI actually is, because AI might perform complex tasks, but most tasks are formulated by humans, so I might be overestimating the degree to which the AI itself is actually doing the complex part.

    Also how is the percentage (%) calculated? Is it based on the specific stage being reached say once every day by a specific human or is the criteria just that a person has reached it once? I find this quite important when evaluating the speed at which AI might impact the workforce.

  • Daniel Voisin

    Well Jesus. Now I’m going to have to spend a whole bunch of time reading all these articles.

    Interesting stuff for sure. Honestly reading things like this make the day a little harder to get through because I’d rather be thinking about this.

    Still someone employed to handle highly upset people on the phone all day this type of stuff is actually very useful. When you can identify you’re dealing with someone on a lower stage of development you can empathize with them and their frustration much easier.

    Look forward to learning more and hope I don’t become too much of a bother because I tend to ramble and act like a Socrates.

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