(This image vividly demonstrates the consequences of “digital inbreeding”: when AI feeds solely on the leftovers spit out by other AIs, all that remains is indescribable noise.)
1. Deep Insight: The Broken Ladder
To be honest, there has been an unsettling “silence” in the tech world recently. It’s not because of a lack of new product launches, but because the noisy marketplace known as “Entry-Level” is turning into a ghost town.
Everyone is fixated on the parameter arms race of Large Language Models (LLMs), yet few have noticed that we are personally burning the ladder that allows humans to climb up.
Look at the data, not just the polished PR from big tech. According to research by SignalFire, hiring demand for candidates with less than one year of experience has been slashed by 50% in the past few years. A Stack Overflow survey cuts even deeper: 70% of hiring managers believe AI can completely handle the work of interns.
The logic sounds sexy: AI is cheap, doesn’t sleep, and doesn’t complain. Why hire a novice who needs half a day just to learn Git? Consequently, junior roles in design, frontend development, coding, and even legal assistance—the “novice villages” where humans used to grind for experience—are being rapidly taken over by AI Agents.
But there is a massive logical BUG here: Without the privates rolling in the mud, where will the battle-hardened generals come from?
The intuition of any senior expert is built upon the experience of handling trivial, boring, and even low-level mistakes countless times. Now, to make financial reports look good, companies have outsourced this “grinding period” to AI. This is like wanting a Michelin-star meal but kicking all the apprentice chefs out of the kitchen. Ten years from now, when today’s senior architects retire, who will take their place? Are we counting on the kids who only know how to type “please help me generate code” into a prompt box?
This isn’t just an unemployment issue; it is the severing of the chain of human skill inheritance.
2. Independent Perspective: The Stargate Paradox
A more interesting (or perhaps terrifying) perspective emerges when we stretch our view to the scale of civilization. You’ll find we are enacting a classic trope from the sci-fi series Stargate SG-1.
In the show, humans on many planets guard god-level technology left by an ancient advanced civilization (the Ancients). They can use it, repair it, and even worship these machines, but they completely lack understanding of the principles behind them. Once a machine breaks, or a situation arises that isn’t in the manual, they are doomed.
Current AI development is turning us into those “indigenous people.”
All current AI large models are essentially a “compression” and “reorganization” of the massive amount of knowledge humans have accumulated over thousands of years. That is our ceiling. If my worry comes true—that junior practitioners disappear and humans stop producing new, original knowledge derived from painful thinking—what will AI eat?
The answer is: It will eat its own regurgitated waste.
There is a specific horror term for this in academia called “Model Collapse.”
(The research by Shumailov and others is like a slap in the face: If AI continues to train on synthetic data, it will become like an inbred royal family, eventually birthing a generation of deformed “Habsburg jaws.”)
Recent studies in Nature have confirmed this: When AI models begin training on AI-generated data, they rapidly forget the “long-tail” information in the data distribution (those rare but precious real-world details), eventually degenerating into meaningless, mediocre noise.
If humans stop exploring and rely solely on AI to ruminate on the knowledge of past generations, we will not only fail to create new knowledge, but the existing knowledge system will also slowly disintegrate. A few generations later, we might be bowing down to servers, unable to write the first line of the algorithm that created them.
3. Industry Insight: The Education Placebo
Look at our education system. Major tech giants are rushing to give AI to universities for free, calling it “empowering education.”
Don’t be fooled. This isn’t empowerment; it’s distributing free “mental crutches.”
Students today turn to GPT for essays and Copilot for code. It looks incredibly efficient, but what is the cost? Research by Duke Learning Innovation points out that this “cognitive offloading” is leading to a cliff-like drop in students’ critical thinking abilities.
The learning process is essentially the painful process of the brain building neural connections. If you save on the pain, you save on the ability.
In contrast, the medical industry remains sober. In many top hospitals, doctors are very cautious about AI. Not because they are conservative, but because they have found that AI will “solemnly talk nonsense” (Hallucinations). An OECD report points out that AI hallucinations could lead to a loss of clinical skills. Doctors understand that on the life-and-death operating table, you cannot count on a chatbot that is essentially guessing probabilities.
The education sector should learn from the vigilance of the medical field. Current “AI-assisted learning” is, to some extent, mass-producing “high-score, low-ability” button pushers. When these students graduate and enter a society that doesn’t even have entry-level jobs, the picture is too grim to watch.
(This is the irony we face: All knowledge is at our fingertips, but the brain is atrophy due to a lack of exercise.)
4. Unfinished Thought: The Human Premium
Of course, I am not a Luddite calling to smash machines. AI is irreversible, and there is no need to reverse it. But we must consider a new possibility.
Perhaps in the future, “created by pure human thought” will become an expensive luxury label, just like “hand-made” is today.
- When all code is AI-generated, the programmer who can read underlying assembly language and manually debug will be a scarce, top-tier resource.
- When all articles are GPT-flavored boilerplate, that piece of human writing—even with typos, but full of emotion and flaws—might be worth its weight in gold.
We may enter a stratified society: the bottom layer consists of “happy consumers” fed by AI, and the top layer consists of a very small number of “Architects” who not only know how to use AI but, more importantly, know how to think when there is no AI.
The question is, which one do you want to be?
5. Reflections
In this carnival of computing power, let’s retain a bit of cold sobriety.
Efficiency is not the entirety of civilization. Sometimes, it is precisely those clumsy trials and errors, those sleepless nights of struggle, and that “low-level mental labor” deemed inefficient by AI, that constitute the hardest base color of human wisdom.
Don’t let AI become the only interface for your brain. Occasionally, unplug the internet cable and use your carbon-based brain, which has survived millions of years of evolution, to think about a stupid question.
That might be the only ark that saves us from becoming “Stargate remnants.”
