AI-Assisted Learning: A Dialogue of Self-Discovery
Filed under AI, Learning & Development on July 9, 2025. Last updated on July 9, 2025.
Introduction: Insights in Dialogue
Sometimes, the most profound insights emerge from the most casual conversations.
The First Conversation: From Confusion to Clarity
It was an ordinary afternoon. I was sitting in front of my computer, having what seemed like a casual exchange with ChatGPT.
Who would have thought that this simple interaction would become a turning point in how I perceive my own way of thinking?
I shared my inner conflict with the AI: I often dwell too deeply in the world of philosophy but struggle to take action in the real world. This state of being a “giant in thought, dwarf in action” left me feeling deeply frustrated. Unexpectedly, ChatGPT didn’t offer empty comfort, but instead opened a new window through the lens of modern psychology and behavioral science.
It introduced me to several core concepts in behavioral psychology, helping me realize that the issue might not lie in excessive thinking, but in the way I think. Inspired, I immediately picked up Atomic Habits and read it in one sitting. The ideas on behavior and habit formation in the book were eye-opening.
Our conversation gradually shifted toward how psychology and behavioral science are applied in organizational management. Then I had a realization—I had long overlooked an important perspective: understanding psychology and behavior through the historical development of philosophy.
Driven by curiosity, I asked, “Are there any articles, theories, or models that effectively integrate philosophy, psychology, behavioral science, and management?” What seemed like a simple question opened up an entirely new chapter in my intellectual journey.
ChatGPT introduced me to Administrative Behavior by Herbert A. Simon. I had never heard of Simon before. As I began to explore his work, I was stunned by the depth of his impact. He wasn’t just a management theorist—he was an interdisciplinary thinker whose work spanned cognitive science, artificial intelligence, and economics.
The Second Conversation: Toward Formalized Cognition
Then, I began to ponder a more ambitious question: Can we use formal language to define core and meta-capabilities of individuals? Could we construct a cognitive formalization system through a self-referential, bootstrapping process?
This idea thrilled me. It wasn’t just a way to analyze my own blind spots in thought and action—it might also offer a new modeling framework for cognitive science.
During further discussions with ChatGPT, I suddenly wondered: “Is there already a research team working on a formal cognitive system?” The question filled me with both anticipation and anxiety—if such work already existed, I could build upon it. If not, perhaps my idea was just a fantasy.
ChatGPT’s response was astonishing: it mentioned ACT-R (Adaptive Control of Thought–Rational), a cognitive architecture designed to simulate human cognition. It was exactly the kind of formal system I had been envisioning. Eagerly, I looked it up on Wikipedia, and discovered that ACT-R was inspired by the work of Allen Newell. Diving deeper, I uncovered something even more surprising: Allen Newell was a doctoral student of Herbert A. Simon!
This discovery felt almost predestined—as if invisible threads were silently connecting all the fragments of knowledge I had stumbled upon.
The intellectual lineage between Simon and Newell not only reinforced my confidence in the direction I was exploring, but also served as historical validation: these interdisciplinary connections were not just plausible—they had already been made by some of the greatest minds in cognitive science.
Conclusion: Beyond the Dialogue, Within Cognition
From personal reflection, to psychological insights offered by ChatGPT, to reading Atomic Habits, discovering Administrative Behavior, exploring ACT-R, and finally tracing it all back to the Simon–Newell lineage—this journey allowed me to see, more clearly than ever, the immense value of large language models in accelerating knowledge discovery.
ChatGPT was not merely a tool. It felt like a cognitive partner—one that listens deeply, responds thoughtfully, and helps bridge seemingly distant pieces of knowledge.
This experience clearly demonstrates that AI is not here to replace human thinking, but to amplify it. With human curiosity and intuition working hand in hand with AI’s data-processing and reasoning capabilities, we may be entering a new era of learning—one that is interdisciplinary, boundary-crossing, and deeply transformative.
Perhaps this is what the future of learning looks like: behind every conversation lies a redefinition of the self, and a quiet revolution in how we understand the world.