"Curiosology"—What is the True Nature of the Energy that Drives Knowledge?: [Column] The Science of Thinking (Shiko no Kagaku)—Let's Enjoy "Thinking"! (Part 11)

The Science of Thinking, Part 11: "Curiosology"

—What is the true nature of the energy that drives knowledge?

1. What is curiosity?

"Why do people want to know?"

This is a question that has been asked in every field, including philosophy, psychology, neuroscience, pedagogy, and even AI research. Curiosity has generated knowledge, advanced technology, and supported human evolution itself. However, exactly what it is and where it comes from has not been fully elucidated.

When I posed the question "What is curiosity?" to an AI, I received the following response.

From the AI's response, we can see that "curiosity" is not just an emotion, but an important function related to survival and learning. It also touches on the difference between intrinsic and extrinsic curiosity, as well as the workings of dopamine in the brain, explaining it from a multifaceted perspective.

However, the AI's response lacks the fundamental question of "why does curiosity arise?" and a perspective on the "limits of curiosity." There are attempts to give AI something like "curiosity," but that is merely an information-seeking algorithm and is different from human curiosity. So, what is the essence of curiosity?

Here, I would like to propose a fictional discipline called "Curiosology" and explore its structure from mathematical and quantum mechanical perspectives.

2. Mathematical analysis of curiosity: Perspectives from information theory and optimization

To grasp curiosity mathematically, let's consider information theory.

(1) Factorization of curiosity

Let's break down curiosity as follows.

• Novelty of information (N: Novelty): The more unknown the information, the more it stimulates curiosity.

• Unpredictability (U: Uncertainty): The more the future is unknown, the more people want to know.

• Relevance (R: Relevance): The more information relates to oneself, the higher the interest.

• Achievability (A: Achievability): Motivation arises when knowing is within reach.

It is thought that these four elements interact to create the human impulse to "want to know." For example, games and puzzles stimulate curiosity because they provide a good balance of moderate unpredictability and achievability.

(2) The "Curiosity Threshold" as the Greatest Common Divisor

There are individual differences in how much "unknown" a person is interested in.

• Extremely unknown things → Lose interest because it is too difficult (e.g., a beginner encountering high-dimensional space theory)

• Things that are too well-known → Boring (e.g., "2x2" for someone who has already memorized the multiplication table)

The point where these two are balanced can be called the "Curiosity Threshold". In learning theory, this is known as the "Zone of Proximal Development (ZPD)," but mathematically, it can be formulated as an appropriate range of "information entropy (H)."

3. Quantum Mechanical Perspective: "Superposition of Curiosity"

Curiosity contains both the nature of "seeking a definitive answer" and the nature of "enjoying the unknown." This state is very similar to a superposition state in quantum mechanics.

For example, let's consider the thought experiment of Schrödinger's cat.

• Before opening the box → Feeling curiosity about the uncertainty of "the cat is alive or dead"

• After opening the box → The answer is known, and curiosity converges (or new questions arise)

Curiosity is always wavering between "knowing the answer" and "the charm of the unknown," and the fact that it converges to one or the other upon observation is similar to a quantum state.

Also, by applying the concept of quantum entanglement, we can explain the feedback loop where "knowledge" and "curiosity" are intertwined, and as knowledge increases, new curiosity is born. This is consistent with the phenomenon where once a human learns something, subsequent learning accelerates.

4. The Academic System of "Curiosity Studies"

If we systematize "Curiosity Studies" as an academic discipline, the following research themes can be considered.

(1) Research Objectives

• To elucidate the mechanism of human curiosity and explore ways to optimize intellectual growth

• To enable more autonomous intellectual exploration by giving AI "curiosity"

(2) Research Perspectives and Elements

• Psychological perspective: The relationship between the brain's reward system and curiosity

• Mathematical perspective: Quantification of curiosity using information theory

• Quantum Mechanical Perspective: The Interaction Between Cognitive Uncertainty and Information Acquisition

• Philosophical Perspective: The Ontological Significance of the Desire to "Know"

(3) Specific Research Themes

1. "Curiosity Entropy": The Relationship Between Information Uncertainty and Intellectual Motivation

2. "Optimal Curiosity Temperature": Designing Information Volume to Maximize Learning Efficiency

3. "Quantum Cognitive Model": Unsolved Problems as Superposition States and Intellectual Exploration

4. "Evolution of Curiosity": Evolutionary Adaptation of Information-Seeking Behavior in Organisms

(4) Curriculum Example

• Lecture 1: Psychology and Neuroscience of Curiosity

• Lecture 2: Applications of Information Theory and Entropy

• Lecture 3: Introduction to Quantum Cognitive Models

• Lecture 4: Designing Curiosity-Driven AI

5. The Future of Curiosity Studies

If Curiosity Studies were to be established as a future academic discipline, what form would it take?

(1) Fusion with Artificial Intelligence

By combining the data analysis capabilities of AI with human creative thinking, it may be possible to understand the mechanisms behind the emergence of curiosity in greater detail. It could also lead to the development of learning environments that stimulate curiosity and systems that promote intellectual exploration.

(2) Applications in the Field of Education

By introducing "curiosity-driven learning," more effective educational systems could be built. We can expect the provision of curricula tailored to each student's interests and the development of gamified learning environments.

(3) Philosophical and Social Impact

By re-evaluating the role curiosity plays in human development and reflecting it in social systems and ethics, it is possible that an intellectual culture for a new era will emerge.

Afterword

This column was written utilizing ChatGPT. By fusing the information processing capabilities of generative AI with human thinking power, I was able to explore the theme of curiosity from a more multifaceted perspective.

While AI excels at deriving patterns from vast amounts of data and organizing knowledge, it does not possess the answer to the fundamental question of "Why do we want to know?" Perhaps it is the role of us humans to think about that.

Curiosity is the driving force behind the pursuit of knowledge and the key to opening up the future. I hope this column serves as a catalyst for new perspectives and discoveries for all of you readers.

Where is your curiosity headed?

(This article is created as part of an attempt at intellectual exploration utilizing generative AI.)