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Conceptual Minimum of a Modern Person: Learn Once, Use in All Projects.

The acquisition of cognitive methods at the top of the intelligence stack usually requires a certain level of mastery of the methods that are below. If you are not familiar with what concept theory is, not acquainted with logic, with ethics, then studying rhetoric will not be available to you. Let's remind the sequence of levels of today's intelligence stack (the set of methods may change! Development does not stand still! Moreover, there may be alternative variants of the intelligence stack already today, evolution implies the existence of many types, including many types of theories/explanations/disciplines):

  • Systems Engineering
  • Methodology
  • Rhetoric
  • Ethics
  • Aesthetics
  • Research/Understanding
  • Rationality
  • Logic
  • Algorithmics
  • Ontology
  • Concept theory
  • Physics
  • Mathematics
  • Semantics
  • Coherence
  • Conceptualization

To a crawling person, jumps and dances will not be available, you need to first pump up muscle (tools), and to the brain to learn the methods of muscle control (discipline). Preparation for action is needed, learning the method, gaining mastery. Action will not happen right away. Only after the body is ready for action can you learn some patterns of complex sports and dance movements.

Education in particular and learning in general (education is a specialization of learning aimed at strengthening the fundamental/universal/general intelligence, that is, learning the methods of thinking of the intelligence stack) is also organized in a certain sequence (curriculum learning), knowledge grows bit by bit, not "one big piece at a time."

Arithmetic is studied before integrals, without knowledge of the multiplication table of higher mathematics, you will not master it - arithmetic is a prerequisite for higher mathematics. First readiness and automatism/fluidity in thinking for more basic cognitive skills, and then readiness and automatism/fluidity at more applied levels of thinking - and so on several levels.

First you need to be able to articulate thoughts into words somehow (conceptualization), then to focus attention on thoughts (coherence), then to differentiate thoughts themselves, objects of the world, and words about them (semantics), then to understand physics and mathematics - how they differ and why they are necessary, then to understand the types of objects and relations (theory of concepts), to hold a multilevel assignment of an object while focusing on it (ontology), and so on.

Of course, there can be a huge number of educational routes (educational programs/curriculum), during which intelligence is strengthened, so some sequence of learning methods from the intelligence stack becomes necessary. For mastering systems thinking, it is necessary to be somewhat familiar with not just one, but with all methods of thinking from the intelligence stack. For example,

  • In conceptualization, you will learn that there are objects to which we can give names,
  • In coherence, you will learn to write down the results of your reasoning,
  • In concept theory, you will learn that the world should be modeled through typified objects and their relations,
  • In physics the term "system" will be given,
  • The hierarchy by composition in ontology will give you systemic levels,
  • in methodology, it will be clear how one system creates another system using some method/labor/practice/culture/activity/style,
  • in engineering, it will be clear by what means we create these systems.

This is just a small piece repeated again of how knowledge/theories/transdisciplines of very different thinking methods, part of the intelligence stack, results in knowledge of systems thinking.

Systems thinking is given "in types" of high-level abstraction, it is scale-free, universal in terms of applied subject areas and not anthropocentric. Therefore, systems thinking is applicable to projects for creating and developing such different systems as a rocket plane part, an airliner, a purebred sheep, a hectare of forest, chef and robotics engineer, a firm producing diapers and an internet provider, a community of Tolkien fans and an "invisible college" in science. Sometimes a society is created as a "separate country," or this society is modified, without changing the country, but becoming something completely different ("revolution"), and sometimes a super-intelligence is created as a hybrid of computer intelligences and human intelligences.

In various projects, people are simultaneously engaged in various methods/practices with their own various disciplines/theories/knowledge/algorithms, different tools, different materials for these works. You need to think a bit about many of them to better understand your own project: each project itself includes many applied tasks using different methods, and during problem-solving you may also need to apply methods of intelligence from the intelligence stack, but there are no "spherical projects in a vacuum," a project encounters a huge number of working methods from other projects. Everyone coming from the outside to the project focuses on something of his/her own: external contractors, material suppliers, buyers, managers, intermediaries, standardization organizations, every day in the project new people appear, and with all of them you need to have meaningful conversations. You have to somehow figure out what they all do in order to have meaningful conversations with them. You need to be able to somehow understand what they are all doing in order to have meaningful conversations with them. Thinking and acting in all this diversity of activities in the project itself and its surrounding projects are organized in a similar way, and you can learn this compact thinking once, and then apply it to different tasks in one project, or even in different projects. Enhancing intelligence, including mastering systems thinking is dedicated to this compactification of thinking: you learn to think once, and then you just never turn it off.

There is a legend that talent for thinking (of any kind) is innate. Yes, genetic predisposition to a certain type of thinking exists, just like athletes to a certain sport. But it is not so straightforward: there are hundreds of genes related to intelligence, but with genetics, one cannot escape far in thinking.

So we recommend relying not on genetics, but on intellectual training: the thinking methods are not inherently in the brain, they must be learned and trained. This means that a trained "non-talent" will easily outperform an untrained "naturally gifted" thinker, who will simply not know how to think correctly. A wolf raised by wolves, the potentially brilliant Mowgli, will not even know how to speak, let alone think clearly. Inborn IQ is not of great importance (examples have already been cited), good education (i.e., learning the methods of the intelligence stack) in life means much more!

The intelligence stack is a set of the best methods of thinking in our civilization today, based on the best explanatory theories. The best (state-of-the-art) in civilization as of the current year, not in, say, 2011 (the new dawn of artificial intelligence using deep learning on neural networks started in 2012, in 2011 computers couldn't talk well or see properly!) or a very ancient year like 1980 (the year the first personal computer, IBM PC, appeared).

Decisions on the choice of specific thinking methods from the plethora of options available to humanity are aimed at thinking abstractly, adequately, consciously, rationally, systematically, practically/proactively, and not in a "barbaric" way, ignoring all accumulated civilization's cognitive experience. These decisions on the choice of scale-free (universal for different system sizes and different time scales of system existence) and non-anthropocentric (not specific to humans) thinking methods are expected to formulate the used models of thinking, initial data, intermediate and final results of thinking, and also lead to real-world applications. Conditionally, computers are also "in writing". And the "real-world application" involves intervention in the physical world, to actions: from "approaching to observe" to "go and talk" and "change to improve."

To what extent does civilization-refined intelligence, that is, thinking using the fundamental methods of the intelligence stack in the modern variants of these methods, restrain or stimulate creativity compared to raw "barbaric" thinking? Civilization's experience shows that educated and cognitively trained people usually outperform the uneducated, despite their purported "patterned thinking." Exceptionally talented self-taught "savages" are extremely rare. Yet, at scrutiny, "self-taught savages" are often well-read and educated, if their education was not connected to an official educational institution, and the patterns of their "genius self-taught thinking" were also taken from literature and adopted from knowledgeable teachers rather than invented on the fly. It is a popular legend that self-taught individuals never went to school. They did, they just did it on their own, and not "officially."

In the pursuit of a fluid application of cognitive patterns, it allows for swift execution of standardized abstract, rational, adequate, conscious, systematic, practical reasoning without intellectual effort, that is, intuitively, "automatically" - including deductive "step-by-step" thinking based on patterns found in textbooks, which does not seem difficult after training.

Only if these "thinking rails" are suddenly not laid somewhere, only when confronted with something truly new, can one switch to expensive "simple thinking, however we can", using some other searching thinking mechanisms, employing external aids such as computer modeling. Such excursions beyond familiar thinking are rare exceptions, not the rule. You are very lucky if you find yourself on such a frontier; rejoice in being on the forefront of human civilization.

But it is not a given that you will be able to invent something on this frontier. To augment cognitive patterns and enrich the repository of effective thinking patterns of humankind, it requires engaging general/fundamental thinking methods from the intelligence stack when facing new and unexpected turns in a project. For problem-solving, a blend of both general thinking methods and subject-specific method applications is crucial. The cognitive patterns are in use in the most basic forms of thinking (general logical reasoning), as well in more complex types relying on them (general engineering thinking), and in even more rapidly changing, highly specialized variants of reasoning that involve a mix of cognition/thinking and some routine practical reasoning based on well-known material.

Thinking patterns are employed in the work of an aerospace engineer, manager, investor, dolphin trainer, dancer, primary school teacher, politician. Thinking must be culturally/practically/stylishly/actively - it has to follow the method/approach. This implies that intelligence must replicate the same thinking patterns if they are the best-known patterns of thought. Weak thinking patterns you create each time "under problem" - will not guarantee effectiveness. To be smart, you need to know how to be smart. Strong thinking patterns must be learned. This is done in the form of studying thinking methods/patterns from the intelligence stack.

Brisk thinking needs to be reached in any thinking, thinking must be trained, just like any other behavior, any other method/practice/culture/style/activity/strategy.

Moreover, learned and further trained to reach fluent cognitive patterns gives the ability to carry out standardized processes quickly compared to untrained "raw" thinking, they also protect against gross cognitive errors. Once you learn the multiplication operation, you will use it throughout your life. Once you learn that the system should be considered functionally during its operation as part of the supra-system and also structurally during its creation and development - you will also use it for life.

"External project roles pay for alignment and satisfaction of interests, not for "realizing the system concept" and certainly not **for "realizing requirements," which no longer exist in modern engineering; the idea of "requirements" itself is outdated" - this material is covered in the course of systems thinking, once for all systems. If you haven't learned it and applied it in life, you can risk losing your financial stability! It is better to learn it once to avoid mistakes throughout life. Knowledge of systems thinking is highly practical; it saves time and prevents mistakes.

For a "cultured person," it is necessary to master the same compact thinking based on the methods of the intelligence stack, and it will be useful for various activities and projects. After all, a person will have to play many different roles in life, engaging in various methods of creating various systems of a certain level of organization. Each of these applied methods implies its specific applied cognitive reasoning patterns, yet when faced with a new and unexpected turn in a project, general/fundamental thinking methods from the intelligence stack will need to be engaged to solve problems.

Whether you are the founder of a sex toy market company, a space tourism project manager, or a quantum computing engineer - you will need to be organized, use logic, coordinate complex system models with your colleagues, hold attention on numerous systems, both yours and others, that are involved in your project and that are affected by your project. You will use computers with universal (AI) and not very universal (regular corporate software) algorithms. In the next project, all of this will be repeated, but on a completely different project content: all your intellect will be required again, whatever you engage in: there is no such thing as a project where everything is known, and reasoning is purely by the rules. And if there is some completely familiar action, it won't even be called a project!

Thinking as an activity of the intellect for problem-solving, for understanding the complex and ever-evolving world, is universal, it will always be with you, and systems thinking is part of this thinking minimum of a civilized person and civilized AI. Although systems thinking can also be part of the thinking minimum of a civilized organization, as systems thinking is collective, it integrates intelligence within organizations, enhances intelligence and organizations as a whole.

It is essential to consider that we are talking about the best of today's methods (state-of-the-art) of thinking. The basic thinking methods are relatively stable (the changing time can be counted in hundreds of years: for how many centuries was Aristotelian logic in use before it was discontinued?), but in the 21st century, the basic methods can change during a long human life, so one needs to be on top of it and retrain on time. It is surprising, but not many know that Aristotelian logic and its syllogisms are a thing of the past, and now there are multiple versions of mathematical logic. Logic has ceased to be considered the foundation of all mathematics, changed as well as mathematics and mathematical logic (more details on this in the "Intelligence Stack" course, in the sections on mathematics and logic).

The understanding of intelligence itself, scientific thinking, causality relationships, logic as probabilistic inference, and even systems thinking have significantly evolved in the 21st century. If you study these subjects through textbooks published before, say, 2017, you might be surprised how they no longer reflect the current state of thinking methods based on these disciplines. Do not learn "old stuff"! Do not learn systems thinking by authors from the 1980s; check the publication years of your textbooks! In our systems thinking course, systems thinking is presented as of 2024!

In looking for a systems thinking textbook on Google, one of the first results is a textbook by NLP coaches Joseph Connor and Ian McDermott, in Russian translation. However, this textbook in English was written a quarter of a century ago, in 1997[1]! It is no wonder that it differs so much in content from our course; it holds rather ancient views on systems thinking. Systems thinking has not stood still; it has evolved intensely in the 21st century. Theoretical disciplines have all integrated systems thinking concepts more actively.

If you find yourself during deep contemplation, not taking any notes, not creating any computer models - you are definitely doing something wrong. Today, thinking occurs through writing and modeling; relying solely on the biological memory of one person has no hope. Systems thinking is no exception.

A comprehensive fundamental education is necessary not only to think civilized, but also to think quickly, and using thinking tools (interlocutors like AI and other intelligent individuals, notes in modelers, notes in natural languages) is fundamental. Just like in sports: you won't become a champion in three months, but after three years, you won't be a champion yet, but you will dramatically stand out from the "people on the street."

Yet, individuals should not rely only on the biological nature of their thinking, but also involve the computer. Even if it's not a full-fledged computer, just paper and pen, it enables the biological brain to handle attention more easily, to use a broader memory, and to exchange thinking results efficiently. Additionally, human intelligence engages the body, and this is not only about finger movements when writing or eye muscle work while reading. In the practice of coherence, where the basics of conceptualization are given, a significant connection between mind and body is highlighted (e.g., ontological confusion can be recognized by bodily sensations).

Thinking proactively, it delves into the physical world, and the body is of significance, even regarding the duration of the body as tools - telescopes, microscopes, cars, rockets, human-like robots. Human thinking has an external nature, it occurs not only in the brain but throughout the body, going beyond its boundaries (the 4E thesis ^[[Overview of an approach to thinking that goes beyond the limits of the body, including criticisms of such approaches, see in https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7250653/]), therefore, systems thinking is trained not only as a mental exercise but also while engaging tools for modeling - from simple writing in a text editor or editor businesses like notion.so or coda.io to sophisticated multiscale mathematical (multiscale, at different levels of the structure/organization scale of the modeled physical system, with different types of models for different scales) simulation modeling.

It's important to note that we should not only talk about fundamental disciplines, i.e., pure theory/explanations. We must talk about methods/work, where discipline/knowledge/algorithms are backed by tools that enhance the skill of the "naked thinking brain" (or the "naked thinking computer" when it comes to AI). People (and now even neural network computers and robots) don't work "with just their hands" anymore; they make use of tools. People no longer think "with just their brains," they use computers (and computers use other computers to help themselves, maybe even people, or even people long dead - for example, reading thinking results in books written by long-dead authors).

If you find yourself deep in contemplation, where you are not engaging any records, not creating any computer models - you are definitely doing something wrong. Today, thinking is happening through writing and modeling. Relying solely on the biological memory of one person has no hope. Systems thinking is no exception.


  1. https://www.amazon.com/Art-Systems-Thinking-Essential-Creativity/dp/0722534426 ↩︎