Dimensions of Explicit Knowledge: The Unfolding of Linguistic Systems and Poetry

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When you read a sentence, the concepts that the words refer to come to mind. Even in a short sentence like a poem, rich concepts unfold. Why is this?

In this article, we will delve into explicit knowledge to approach this reason.

Explicit knowledge, represented by language and charts, is knowledge in a form that is easy to interact with people. Therefore, we communicate using language.

Our brains enable us to express concepts in words. And when reading a sentence, not only the concepts written in the sentence but also those that are not written come to mind. This is because not only do words represent concepts, but mechanisms that indirectly unfold concepts also work in the grammatical structure and other language systems. Furthermore, these multiple concepts interact with each other, and other concepts unfold as well.

For example, consider the sentence, “My umbrella was dancing.” You might imagine yourself holding an umbrella and dancing, and your heart soaring. Even on a typically gloomy rainy day, if you are dancing, what happy thing must have happened?

In this way, even a single verse of a poem can unfold images in your mind.

Furthermore, by digging into the nature of explicit knowledge, we can see a fundamental similarity between DNA and language.

The way that concepts are richly generated and interact from sentences is similar to how life phenomena arise from DNA. DNA creates the ecosystem of living things, and language forms a forest of concepts. This similarity is not simply that they look alike, but that they share common principles.

Now, using explicit knowledge as a clue, I will explain the unfolding of sentences and the commonality with DNA in more detail below.

Pattern Recognition and Association

Our brains have the ability to think of concepts. There are two ways to do this: pattern recognition and association.

Perceiving a specific object causes the concept corresponding to the perceived pattern to come to mind.

For example, by looking at something in front of your eyes, concepts like whether it’s an apple or an orange, red or green, stationary or rolling are recognized.

Not only visually, but also in sound, smell, taste, and touch, concepts are recognized.

By seeing or thinking about the encapsulated model, the concept wrapped in that model comes to mind. This is association.

For instance, when designing a house, you might create a small house with cardboard. When a soccer team thinks about formation, you might represent the 11 players with small stones. These are models. Although not actual houses or soccer players, looking at the models helps you imagine the shapes and arrangements.

To recognize patterns, you must learn them. By perceiving an object with a pattern repeatedly, you can learn the relationship between the pattern and the concept. Once the relationship between the pattern and the concept is learned, pattern recognition becomes possible.

Association requires remembering the model that encapsulated the concept. Unlike patterns, models are simplified, so associating them with concepts can be relatively easily remembered. By associating and remembering the model and concept in advance, association becomes possible.

Words as Models

Explicit knowledge is a model. A model abstracts the concept of the subject by encapsulating it.

There are two types of abstraction. One is inclusive abstraction, which wraps the concept of the subject into a capsule. The other is inheritance abstraction, which extracts a common concept by trimming different subjects’ details and encapsulates it.

Representative of explicit knowledge as a model is a word in language. Words have the property of models and include words, phrases, and idioms.

To be precise, the label attached to the encapsulated model of the concept is the word. Words like “apple,” “red,” “run,” are labels pasted on models of each concept.

Words and models, and the encapsulated concepts are associated and remembered. With this memory, when you see, hear, or think of words, the associated concepts are associated. In other words, when you recognize individual words, concepts come to mind.

Simulation of Mechanism

Our brains can not only think of concepts but also imagine mechanisms.

A mechanism includes laws that act on models containing concepts. Due to this action, the shape, movement, and nature of the model change, and it’s dynamic. We can sequentially imagine the behavior and changes of the model in our heads. This means understanding the mechanism in your head and simulating it.

For example, there’s a law that if you push and release a weight suspended by a string from the ceiling, it will oscillate back and forth for a while. This is the mechanism of a pendulum. I can imagine this mechanism in my head. I can simulate the movement of the pendulum. This is also the work of the brain.

By simulating the mechanism, you can predict the future or unknown things. You can also imagine fantasy or fiction away from reality. In the fields of science and academics, new discoveries are made not only by observing things and recognizing mechanisms but also by creatively assuming mechanisms and verifying them through experiments.

When designing tools, you can design better by simulating the scene where it will be used. Also, in the design of programs or systems, imagining not only the scene where it will be used but also the internal mechanism of the computer becomes essential. Programmers and system engineers have the ability to understand the mechanism of computers and peripheral devices and simulate it accurately in their heads.

Language as a Mechanism

Explicit knowledge also has the nature of a mechanism. A prime example of explicit knowledge as a mechanism is language.

Language is made up of words and grammar. I have already explained that words are labels attached to models. Grammar is the law that applies to these words. A mechanism with models labeled with words, and rules known as grammar, is language.

Sentences consist of chains of words. Grammar acts as a rule between the words contained in a sentence.

When we see or hear a sentence or imagine it in our heads, the mechanism of language works in our minds. When you see the sentence “The pendulum is swinging,” you can imagine the pendulum swinging. However, this example sentence is merely a description of the simulation of the pendulum’s mechanism.

What about the sentence “The pendulum might have been swinging”? I think more concepts such as the implication of something other than the pendulum, the existence of time in past events, the existence of an author speculating on unobserved events, will come to mind. Depending on the context, including the preceding and following sentences, it may also imply not only existence but also meaning and emotion. This becomes a sentence that makes you recognize not only the mechanism of the pendulum but also broader concepts.

There is a mechanism inherent in the language itself. By simulating the mechanism of language, we can recognize a wide range of concepts, such as implied existence, meaning, and emotion.

Unfolding of the System

Earlier, I used the expression “simulation of the mechanism of language.” You may feel something odd about it. A more suitable expression would be the unfolding of the system of language.

A system includes models and laws. A mechanism is a type of system, with laws that change over time.

Unfolding means applying rules to a model and changing the model. Simulation is a type of unfolding, recognizing changes over time.

Our brain can unfold a system with the same function as simulating a mechanism.

Looking again at the previous sentence “The pendulum might have been swinging,” if you unfold this sentence, you may think of sentences like “There was something else that was swinging besides the pendulum,” “Thinking of the pendulum in the past time,” “The author did not directly see the pendulum,” “There was something that made the author feel the possibility that the pendulum was swinging.”

This is similar to being able to imaginatively simulate the future, past, or surrounding situations of a subject if you know the mechanism. For example, when you see a swinging pendulum, you think not only that it will continue to swing for a while but also when it started swinging and who started it.

Unfolding the system of a sentence is the same way of thinking. Besides what the sentence directly expresses, thoughts extend to the periphery, including temporality, spatiality, existence, and emotion.

Utility of Explicit Knowledge

By grasping mechanisms and systems and acquiring the skill to unfold them, you can broaden your thoughts with just a little information.

Language-like explicit knowledge, when understood among those who know its system, allows the transmission of a wide range of concepts with minimal information. This is possible because words succinctly convey concepts, and grammar enables the unfolding of many concepts from short sentences.

Not only in communication with others, but also in one’s thoughts, language-like explicit knowledge is very useful.

First, if it’s explicit knowledge accompanied by notation, you can write it down and read it later. Even if you can’t organize it well in your head, writing it down helps you organize your thoughts. In language, characters are the notation.

Also, even when thinking within yourself, thinking based on explicit knowledge allows for broad and deep thoughts. By thinking using explicit knowledge and unfolding the system, you can discover new concepts and connections between concepts. And if it is explicit knowledge, it is easy to remember the newly found connections between concepts. Thus, thoughts expand and deepen.

In particular, language is the most versatile explicit knowledge applicable to a wide range of concepts. In expressing complex structures, it may be more appropriate to combine with other explicit knowledge representation methods such as diagrams or tables. Even so, the comprehensive power of language is greater than other forms of explicit knowledge.

Unfolding of Linguistic Systems, and Poetry

In this article, I delved into the subject of explicit knowledge. Explicit knowledge is not merely the memory of concepts but has evolution and development. The conclusion of this article is that this is supported by the fact that explicit knowledge has a system, and the brain has the ability to unfold the system.

From the original concepts, new concepts are formed by unfolding them along the system. Explicit knowledge functions as a medium for this, and the most versatile form of explicit knowledge is language.

By memorizing the association of words and models in a language, and learning how to unfold sentences with grammar, you can possess language skills. Then, when a sentence is given, you think of the models and concepts wrapped around the words contained in it and can think of models and concepts not directly included by unfolding sentences according to grammar.

Additionally, it’s necessary to understand the systems and mechanisms that work between those models. If you understand them, the group of concepts that came to mind will expand further by unfolding the system or simulating the mechanism.

The ability to expand our imagination from a short sentence like the line of poetry cited, “The pendulum might have swung,” comes from these workings of the brain. The breadth and depth of understanding of language and the world give birth to the ability to imagine more from a single sentence. Short poems expand a lot of imaginations because of this kind of effect.

Explicit Knowledge and Genes

Explicit knowledge represented by language unfolds vast concepts and their connections in the brain. The group of concepts created by explicit knowledge may create new explicit knowledge.

If it can unfold into broader concepts that existing explicit knowledge could not easily cover, the brain strongly remembers it. This is the action of insight. The brain reacts strongly to not forget new useful concepts.

The way explicit knowledge unfolds the group of concepts, how it’s newly created, and how it propagates to others is very similar to genes.

Genes also unfold and create organisms and life phenomena. New genes are born through interaction between genes and are selected through natural selection. Genes self-replicate, which can be seen as widespread propagation in organisms.

Both explicit knowledge represented by language and genes are systems that can unfold.

Conclusion

What I have organized in this article is the discrete aspect of brain processing. It’s something like a solid in the three states of matter. Therefore, I could analyze it with a reductionist approach, like Newtonian mechanics. This discrete nature underlies explicit knowledge.

Besides, there are aspects of brain processing like continuous fluid or sparse gas. Physically, these can be likened to fluid mechanics or thermodynamics. These might be involved in the abilities of sensibilities like emotions or intuition, and intellect like creativity or imagination, where tacit knowledge is handled.

Furthermore, the brain deals with superimposed states unconsciously. Neural networks are connected in layers, and the fact that one layer has many neurons means processing many states superimposed. This is like quantum mechanics in physics and is thought to be applied in pattern recognition and unconscious judgment or actions based on patterns.

I would like to analyze these aspects in the future.