Wendy Liu: Why I Avoid AI and Fear for Human Intelligence

Wendy Liu studied coding in the 2000s — back when you had to independently navigate archaic documentation and debug code at night until a website finally worked. Today, when major tech companies promise AI tools that will code and write text for you, the writer persistently warns: this is dangerous not only for the programming profession itself, but for humanity as such.

How Coding Was Taught Before

Wendy started programming as a child — in the mid-2000s, with unlimited access to a family computer and a simple text editor. The results were far from ideal: websites looked clumsy, functionality was fragile, but this didn't discourage her. Because she understood: she was learning a craft — a real craft that requires deep understanding, relentless patience, the ability to see the problem at its core and search for a solution.

The hours Wendy spent debugging, reading archaic documentation, working on projects she eventually abandoned — these were not wasted time at all. These were hours when her brain worked at its limit, considering alternatives, making mistakes and learning from them. This was precisely the process that develops intelligence.

Today such learning seems like a thing of the past. Why struggle with documentation when AI can write the code? Why debug when an assistant can find the error in a second?

What We Lose With AI

When AI tools write code for you, when a neural network generates text with one click, when a bot automates problem-solving, a portion of intellectual work disappears. And this is not harmless for humans. Wendy rightfully observes: when intelligence becomes a service sold by tech corporations, we hand over to private companies not only our code or text, but our very ability to think and decide independently. And every time we click 'let AI do this for me,' our intellectual muscles lose strength. This is not a metaphor. This is a real cognitive process. When you stop using a skill, neural pathways weaken. When you stop thinking through a task independently, your brain stops doing it.

What happens to a person when they stop thinking:

• They stop seeing alternative solutions — their brain gets used to AI's first suggestion and accepts it
• They lose the ability to notice errors and inconsistencies — if the system promises a quick result, why check?
• Their intuition atrophies — experience and insight come only through repeated encounters with problems
• They become economically dependent on platforms — without an AI assistant, they don't know how to start work
• They lose control over their work — an algorithm secretly decides what result to show you and in what form

Privatization of Intelligence

Wendy points to the most dangerous moment: intelligence is not merely a set of skills and techniques, it is power. And when this power is privatized by tech companies, people lose control over their own thinking. Today it seems convenient when GitHub Copilot writes a line of code for you in half a second.

But tomorrow this will become a condition of employment: if you don't know how an AI algorithm works, you simply won't get the job. If you cannot explain why the neural network chose that particular solution, a competitor ready to blindly trust the system and follow its course will displace you. This means your value as a specialist will be measured by your ability to obey, not think.

What This Means

Thinking should be difficult and hard. It is precisely this complexity, these hours of disappointment and frustration, this painful path of trial and error — this is what makes us human. Not consumers of services, not users of interfaces, but people capable of independently comprehending a situation, making a decision, creating something of their own.

Wendy Liu is not saying that AI is a bad tool. She is saying something important: we must remember that what is most valuable in us is our attention and our ability to think. And if we allow this to be taken from us, if we voluntarily hand it over to corporations, we will lose far more than the time spent debugging code.

We will lose ourselves.