[Homework Notebook (Self-Study)] Rethinking How to Engage with Information to Acquire the Power of Information (Part 3)

[Related Article ①]
Please refer to the previous article below.

Now, if we consider biological information from this point, such information is what living organisms read from their environment, and the way it is received and transmitted is arbitrary and fluctuates depending on the individual.

Furthermore, information is acquired by living organisms from the environment as certain patterns, accumulated, synthesized with newly acquired information, and then accumulated further.

Whether it is information in the mind or genetic information, it accumulates historically and temporally.

For life, information is the pattern that creates patterns for living organisms.

This is considered to be consistent with the famous phrase by cultural anthropologist Bateson, who defined information as "a difference that makes a difference."

However, it is said that Bateson did not distinguish between living and non-living things, which is considered a weakness.

By the way, social animals must communicate in their daily lives.

This is because it is the most correct strategy for survival.

Therefore, social animals transmit the biological information they have obtained to each other using some form of external symbols, such as language, gestures, or vocalizations.

Language is the prime example of this, and in itself, it is nothing more than a mere symbol.

However, if the meaning indicated by those symbols is unstable, communication cannot take place.

It is necessary to reach a social consensus and stabilize the meaning.

For this to happen, a normalizing power (*7) that is applicable to all social participants must be at work.

*7:
The power of normalization is a power that aims to make people normal, or standard.
The normality and abnormality that serve as norms in the power of normalization were born from academic disciplines made possible by the accumulation of knowledge about humans that accompanies the exercise of power.

Concrete means are carried out through activities such as education and dictionary compilation, and as these accumulate historically and temporally, the meanings of symbols become stabilized.

Roughly speaking, this is social information.

And machine information is what we generally consider to be information.

In other words, it is the mountain of symbols accumulated in computers.

Our journey of re-compiling existing academic disciplines while viewing the mind from the perspective of information is, for various entities such as machines, animals, humans, and humans under the circumstances of transforming from an information society to a digital society, as follows,

1. Does it possess a mind?

2. If it does possess a mind, how does that mind handle information?

It is important to always keep thinking about such questions and issues (problems) as a set with your own answers to them.

Talking to someone about them and trying to come up with your own answers.

In order to change the environment around us into a better state, it is important to be conscious of these two things, break out of a state of mental stagnation, and decide on and execute the actions that should be taken as a first step toward a solution (or progress).

So, what does it mean for a machine to have a mind?

In the world of philosophy, which seeks to elucidate the essence of things, logic has been studied as a method of thinking, but in the 19th century, it became independent as a discipline, and new logic also emerged.

Currently, it is divided into symbolic logic, which has a stronger mathematical character, and logic that is not symbolic logic.

Symbolic logic is a discipline that studies inference by symbolizing language, and it is also called mathematical logic.

Symbolic logic is the foundation of "mathematical foundations," a branch of mathematics, and many mathematicians as well as logicians study symbolic logic.

The logic covered by symbolic logic includes "propositional logic (*8)," "predicate logic (*9)," "modal logic (*10)," "intuitionistic logic (*11)," and "quantum logic (*12)," etc. There was a time when the dream that the world could be expressed in rigorous descriptive logic within the Western intellectual tradition, and that it could be deductively inferred through combinations of these, seemed realistic.

*8:
Propositional logic is a field that focuses only on the truth or falsehood of propositions, not their content, and studies the laws regarding truth and falsehood.
The goal of propositional logic is to provide a method for determining the truth or falsehood of a given proposition.
To this end, propositions are divided into multiple elementary propositions and viewed as being combined by conjunctions such as "and" and "or".

*9:
Predicate logic is a logic that starts from location = place = predicate and discusses the subjects or objects (entities) contained within that place.
For example, it starts from the location = place of "shining" and discusses what the shining thing encompasses as the same thing.

*10:
Modal logic is a logic that deals with necessity and possibility, such as "~ is necessarily true" or "~ is possible," which are called modal and are not the subject of so-called classical logic.
Modal logic can be seen as a type of intensional logic where the truth value of the whole is not determined by the truth values of the parts.
Its history is old and can be traced back to Aristotle, but its formal treatment as non-classical logic began after mathematical logic.
In modal logic, generally, two operators are added to standard logical systems: the necessity operator □, which means "~ is necessary," and the possibility operator ◇, which means "~ is possible."

*11:
Intuitionistic logic is a logic derived from intuitionistic mathematics proposed by the Dutch mathematician Brouwer, and it is a formalization of the modes of inference allowed in intuitionistic mathematics by his student Heyting.
Intuitionism is a position that recognizes only constructive proofs as proofs, and does not accept existence proofs in the form of "it is a contradiction to assume it does not exist."
Therefore, fewer things can be proven in intuitionistic logic than in classical logic.

*12:
Quantum logic is a system of logic created based on the fact that logic different from ordinary logic holds in the world of quantum mechanics.
It is expected that if this field matures, quantum logic will contribute significantly to the development of quantum computers, just as classical logic was important for classical computers.
However, at present, it is difficult to apply the theory of quantum logic to quantum computers.

It begins with Aristotle's propositional logic and Frege's predicate logic.

In a syllogism, the logic of major premise - minor premise - conclusion is a strictly correct logic with no loopholes.

If propositions are set strictly, all things in the universe can be deduced from them.

Under this premise, if all information is described mechanically, it seems as if the world can be grasped through calculation.

When this met the power of computers, the idea of so-called AI was born, and in fact, enormous effort has been poured into AI even today.

However, the question we need to ask here is whether we can consider that such an approach itself might be fundamentally wrong.

For example, questions like the following can be considered.

Question 1: It is said that AI improves its own intelligence and functions, but if it cannot understand its own capabilities and problems, wouldn't it be unable to reinforce its weaknesses or improve its abilities?

Question 2: Even if AI can derive countermeasures from accumulated knowledge, wouldn't it be unable to think about the impact that those actions might have?

As a counter-evidence other than the above, one can cite the example from the world of mathematics where Hilbert's dream of a formal logical system—that all reasoning could be done from appropriate axioms—was refuted by Gödel's incompleteness theorems (*13).

(*13):
Depending on how one views mathematics, it is sometimes classified into:
1. Logicism (attempting to reconstruct mathematics in the form of symbolic logic by symbolizing logic: Russell, etc.)
2. Intuitionism (not bound by logical forms, considering only what can be concretely (formally) verified as correct, and not accepting the law of excluded middle: Kronecker, Poincaré, Brouwer, etc.)
3. Formalism (adopting an axiomatic method by thoroughly using symbolic logic methods: Hilbert, Bernays, Ackermann, etc.)
After that, in the 1930s, Hilbert's dream of the "axiomatization of all mathematics" collapsed due to Gödel's incompleteness theorems, but mathematical logic still occupies an important position today as a field that studies the "mathematical structure of logic" and the "logical structure of mathematics."

Also, while it is possible to deny that approach based on the frame problem of intelligent robots that AI aims for, and the cognitive closure suggested by autopoiesis, it is considered more important to acquire correct knowledge about AI and become a human who can use AI correctly.

Machines do not have a mind.

Humans do.

The mind is said to be an autopoietic cognitive system built upon the history accumulated as a living organism.

Then, do animals, which share the same evolutionary history as humans, have a mind?

The mind is a system that encompasses consciousness.

Why does consciousness exist?

From an evolutionary perspective, it is said to be because it is advantageous for survival.

Given the premise of environmental change, life must be able to withstand those changes.

In order to continue responding to a constantly changing environment, the mental system perceives based on neural information and prompts various organs in the body to respond to the environment through metabolic information (such as hormones).

If so, it would not be strange for animals, which have walked the same path of evolution as humans, to have a mind.

To conclude, there are also arguments that animals have minds.

Of course, it is thought to be a weaker mental system compared to that of humans, but while earnestly responding to actual situations, animals also selectively perceive situations in an instant and choose their actions.

Bats instantly select effective patterns from ultrasonic reflections coming from every angle and appropriately avoid obstacles.

This is in contrast to intelligent robots that freeze up, unable to make any action choices.

[Related Article ②]
Continuing below ↓.

[Reference Books]
"Fundamental Informatics: From Life to Society" by Toru Nishigaki

"Fundamental Informatics Continued: For 'Living Organizations'" by Toru Nishigaki

"New Fundamental Informatics: Life Beyond Machines" by Toru Nishigaki

"Intelligence Connecting Life and Machines: An Introduction to Fundamental Informatics" by Toru Nishigaki

"Design Management Strategy: Winning in an Information Consumption Society" by Norishi Sato

"Introduction to Information Design: Expression Techniques for the Internet Age" (Heibonsha Shinsho) by Yasushi Watanabe

"Success Value Workshop: Information Concept Design - Communication Design Starting from 'What You Like!'" by Shie Nanase

"Information Editing Skills: The Power to Survive in a Networked Society" by Kazuhiro Fujiwara

"Theory of Cyber-Space Design" by Akiko Watanabe