Thinking Process: Interaction between Unconscious/Conscious, Reason, Intuition, and Emotion
Handing the Baton from Unconscious to Conscious
In familiar situations, the unconscious mind automatically makes predictions, judgments, and decisions. When the unconscious mind can’t make predictions, judgments, or decisions, the conscious mind appears.
Two Problem-Solving Techniques of Consciousness
The conscious mind has two problem-solving methods: an irrational method and a rational method.
The irrational method consists of stopping predictions through resignation, making judgments with intuition, and making decisions based on emotion.
The rational method uses induction or deduction for predictions, frameworks for judgments, and satisfaction for decisions.
This rational method can be said to be the narrow definition of thinking.
Characteristics of Rational and Irrational Methods
Rational methods require time, capability, and resources. For example, if the last question on a test is difficult, there might not be enough time to answer it. You may not be able to solve it because you lack the knowledge. Even though it could be solved with a computer, you may be prohibited from bringing it to the test.
Also, it works when the subject follows a certain rule, but it’s ineffective against chaos that doesn’t follow any rules. For instance, unless you cheat significantly, there’s probably no way to figure out how to win the lottery.
Therefore, when you can’t use a rational method due to a lack of time, capability, or resources, you have no choice but to use an irrational method. One strategy could be to write anything as an answer to the last question on a test.
Moreover, if the subject’s conformity to rules is low, that is, when facing chaos, the significance of a rational method becomes thin. In such cases, choosing an irrational method becomes an option. It’s like choosing your lucky number in a number selection lottery.
Rationality of Irrational Methods and Irrationality of Rational Methods
There’s significance in intentionally choosing an irrational method, considering the given time, capability, resources, and the degree of chaos of the subject.
In such cases, while prediction, judgment, and decision-making are carried out irrationally, the choice of problem-solving method itself is done rationally.
On the contrary, problems arise when the choice of problem-solving method is irrational. You risk running out of time, capability, or resources if you’re obsessed with rational methods. If the subject is chaotic, it will end up being a waste of time, capability, and resources.
For example, in a test, it’s better to fill in all the answer sections with anything, even if it means rolling a pencil or using your lucky number from a horoscope, rather than leaving the latter half of the test blank due to time constraints. This clearly increases the likelihood of gaining points.
Also, even if you adopt an apparently rational approach, such as collecting statistics of past winning lottery numbers, it will probably be futile.
Brain Structure, and Unconscious, Irrational, and Rational
I’m not very familiar with how the brain works, but let’s try to organize it in terms of brain structure with a general image of the unconscious and conscious, rationality, and intuition and emotion.
The brain has an old part from the early stages of evolution. The cerebellum is one of them. This part is believed to govern the unconscious.
The cerebrum is a new part that developed in the latter half of evolution. The consciousness that appears when the unconscious mind cannot cope seems to correspond to the function of the cerebrum.
The cerebrum is physically divided into the right and left hemispheres. We often hear that the right brain governs creativity and the left brain governs logic. This is only an image and it’s not that the right and left brains are clearly divided by function, but rather that they have strengths and weaknesses.
Following this image, it can be thought that the right brain is good at and leads the irrational method of consciousness. Naturally, it would seem that the rational method is something the left brain excels in and leads.
Of course, the actual structure of the brain is likely not divided into such simple functions as stated here. There should be overlaps in each other’s roles and they should be working closely together. Also, it’s possible that the old brain, not the new brain, might be greatly involved in irrational methods.
However, even if there’s no clear functional division, there should be roles and strengths and weaknesses. Therefore, I believe there should be some correspondence between the structure of the brain and our experiential observations of intellectual tasks.
What is thinking?
Based on the above considerations, if we were to answer the question of what is thinking, it would be as follows.
First, from the physical hardware perspective, it can be said that the brain is thinking. To be more precise, it is the parts of the brain that become active in situations where we employ conscious and rational methods.
If we apply general knowledge, it seems that the left part of the cerebrum would correspond to this.
Next, moving away from the hardware or physical perspective, let’s capture it from the abstract concept of intelligence.
In that case, it can be said that consciousness is thinking. Moreover, it is the part of consciousness that controls rational methods, or in other words, reason, that is highlighted. If using rational methods is considered narrow thinking, then reason can be said to be thinking.
The expanse of ‘what is thinking’
However, whether as hardware or as an intelligence system, thinking is not confined to a specific part.
As hardware, the brain collaborates closely, leveraging the areas of expertise of the left brain, right brain, and cerebellum.
Even when thinking narrowly, it is not the case that the left brain leads all and purely logical thinking is carried out. Therefore, it is believed that functions of the right brain and cerebellum work together to progress thinking.
The same applies to reason in the intelligence system. Thinking is not just about pure reason, but progresses in collaboration with intuition, emotions, and automatic predictions of the unconscious.
In academic and scientific fields, it is encouraged to think only with objective reason as much as possible by eliminating intuition, emotions, and the unconscious. However, in daily life, not everyone thinks only with pure reason. Even scholars and researchers do not think only with pure reason in daily life, which is why systems such as methods of thinking to maintain objectivity, mechanisms for peer review of papers, and academic societies exist.
To draw a parallel, the left brain and reason are like the leaders of a project team. Even though they hold the reins, they are not the only ones thinking. The entire team, which is the brain and intelligence, is thinking.
If you look more broadly, just like a team, when multiple people discuss or work together, it can be interpreted that they are thinking as a group of people.
For example, even if the leader is very good at logical thinking, if intuition and sensibility are important to achieve the project’s goals, you can say that adding team members who are good at these aspects and thinking as a team is a good analogy. The point here is that the left-brained part of the leader and the right-brained part of the members are not physically connected as a brain, but they are connected at the level of language and non-verbal communication. Therefore, it is entirely possible to see the whole as a team intelligence system.
Finally
If we can understand the conceptual system structure of the brain, not its physical structure, I believe we can design the AI structure more effectively according to this conceptual system structure.
Our physical brain structure has evolved based on random changes in DNA, so it may contain overly complex structures. If so, the essence of the mechanism of the intelligence system should be able to be realized with a simpler structure. If we design artificial intelligence (AI) based on that structure, we can realize a simpler, maintainable, and scalable system.
Even if the AI designed with this simplification approach has different characteristics and qualities from our brain, it is not a failure of this approach. Rather, if these differences become clear, it will advance our understanding of intelligence systems and provide an opportunity to improve towards a more effective structure.
This approach is extremely important not only for the purpose of evolving AI from the viewpoint of intelligence function and performance, but also for AI ethics and regulation.
Having a clear knowledge of the system structure makes it easier to thoroughly analyze the risks of the system and implement effective and rational measures.
The current AI is said to be able to perform advanced intellectual work, but even AI researchers and developers do not understand why, or what mechanism allows it. From the viewpoint of AI ethics and regulation, I think it is important to strive to maintain as much understanding of the mechanism and structure as possible.
