The Common Structure of Human Thoughts and Knowledge Structure
Researchers ask for the common thinking pattern shared across continents, tribes and eras, and the common structure for all domains of knowledge. The answer is a network of concepts.
MKIC-FABLE-2026-02
A group of researchers in Computer Science, Information Technology, Artificial Intelligence, Psychology, Neural Networks, Statistics, Mathematics, Physics and Philosophy came to my house, after visiting my website.
Doctor, could you please explain the common thinking pattern of people across continents, tribes, ages and eras — and the common structure for all domains of knowledge?
A Common Thinking Pattern
“Children all over the world think and behave alike,” I said. “Adults also address their basic problems similarly, irrespective of their culture, faiths, politics and ages. Why can we understand the thoughts or teachings of great men even five thousand years ago, or from the Classical, Middle or Modern ages? The answer is simple: they and we think, understand and perceive according to a common structure. There is a striking similarity between them.”
“Doctor,” they replied, “based on your theory, we can help you prepare a diagrammatic representation, block diagrams, and a mathematical formula and equation for the common thinking pattern or structure.” And they prepared them.
“Thank you so much for your work,” I said. “It will help researchers conduct further studies and bring out new mathematical models, formulas and equations.”
A Structure for All Domains of Knowledge
“What about the common structure and methodology for all domains of knowledge?” they enquired.
“All domains of knowledge are arranged the way in which we think, using mathematical logic and cybernetic principles. Knowledge itself can be considered a network of related concepts, organised according to mathematical logic and cybernetic principles.”
Concepts can exist at Micro, Elementary, Basic, Advanced and Sophisticated levels, because of their dynamic, multidimensional and exponential nature and structure.
“Here is the basic difference between Artificial Intelligence and Natural or Human Intelligence. Any domain of knowledge can be represented with the help of 10 Core Concepts, each Core Concept dividing into 10 sub-core concepts, and so on.”
Where AI and NI Diverge
Some of them said: “We are programmed to think according to data consisting of zeros and ones. We find it difficult to grasp your model of thinking structure and knowledge structure. Data structure is linear, static and limited-dimensional. Algorithms and architecture based on that data structure are the foundation on which the entire IT and AI are built. Now we can clearly distinguish between AI and NI.”
The AI experts in the group told me: “Doctor, with the help of AI, we can translate the entire discussion into mathematical models, or into the form of a scientific paper.”
After thanking me, they left with the assurance that they would associate with me in further advancing Knowmatics, Augmented Natural Intelligence, Dynamic Knowledge Banks, Distributed Knowledge Factories and Outlets, and AI-NI-KI integration.
This fable illustrates the common structure of knowledge — a network of concepts organised by mathematical logic and cybernetics — and the 10×10 structural blueprint at the heart of Knowmatics.
The same structure underpins how MKIPL turns individual expertise into standardized knowledge products.
Do you think in data, or in concepts?