About Study in AI Era

With each industrial revolution, the lives of ordinary people have improved significantly. Just as the gap in living standards between the rich and the poor has narrowed compared to the past, I believe the AI Era is minimizing the productivity gap between average individuals and talented experts. AI, acting as a teacher or mentor, can orient us within complex projects and systems.

learn by doing

As noted in the article AI Enhanced Development:

"This doesn’t just make me more productive: it lowers my bar for when a project is worth investing time in at all... Which means I’m building all sorts of weird and interesting little things that previously I wouldn’t have invested the time in."

In the past, when we wanted to start a project, we first needed to master the basic knowledge of that specific field. For example, consider a computer beginner who wanted to build a website to record his learning journey. He would have to spend at least a few months studying frameworks, REST APIs, Nginx, etc. Even if he didn't give up, trying to follow tutorials step-by-step would often lead to being haunted by numerous bugs caused by environment issues or indentation details.

That was my experience two years ago. But now, with the help of AI, the process is different. When I want to create a website, Gemini outlines the total project structure. As I move forward, I can ask for details about the next step. When I get stuck, AI ensures I don't stay stuck; it offers multiple choices to solve the problem.

assisted learning

Simon Willison discusses this in Rust, ChatGPT, Copilot:

"I think one of the most exciting applications of large language models is to support self-guided learning. Used the right way, a language model such as GPT-3 can act as a sort of super-smart-and-super-dumb teaching assistant..."

The author used ChatGPT to learn a new programming language—Rust. He mentioned using AI to help understand error messages and record where he went wrong, effectively building a mental model of the topic through dialogue.

However, I must mention significant concerns. Without deep thinking and strong memory retention, we risk becoming overly reliant on AI. We may lose the feeling of "flow"—that state of deep immersion and challenge that comes from solving difficult problems manually.

Furthermore, the widespread use of AI may lead to an era where "no one cares." Previously, many technical experts shared their ideas and experiences on personal blogs, earning revenue from advertisements. Now, their visibility is lower than in the past. As fewer humans share genuine experiences online, the quality of data available to train future models will degrade—a phenomenon known as "Model Collapse." If the internet becomes flooded with AI-generated content, the quality of information we receive will eventually decline.

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