Summary of the Main Content
This article begins with a very representative and real-life scenario: a mother who, after being admitted to Peking University from a mountainous area, has now risen to a mid-level position in the AI industry. Despite having witnessed firsthand the process of AI replacing human labor, she is not anxious about her job; instead, she worries so much that she can't sleep. Her two preschool children are naturally unsensitive to numbers and prefer reading stories and expressing their feelings. Knowing from her own experience over the past few decades the societal preference for science and engineering, she fears that her children might struggle to find a place in the AI-driven world.
By focusing on this parenting concern, the article exposes the biggest misconception in current online discussions about the future of the AI era: claims such as “liberal arts students will be in high demand,” “liberal arts fields are useless and will eventually be phased out,” “the government will provide everyone with money to live a leisurely life,” and “most people will end up just muddling through in a virtual world” are all based on subjective assumptions without any statistical data or real-world examples. These beliefs are essentially no different from religious dogmas, with the louder or more prestigious voices having the upper hand.
The reason people become increasingly anxious about these unfounded claims is not because the future is truly hopeless, but because the human brain cannot tolerate the feeling of uncertainty. People prefer to cling to clearly wrong conclusions rather than admit, “I don't know what the world will be like in twenty or thirty years.” This article uses quotes from Zhuangzi, the author’s own mother’s experiences, and Buffett’s investment philosophy to illustrate that by facing the reality of “I don’t know” and not trying to force past experiences onto the future, one can avoid unnecessary internal strife and move forward more steadily.
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Simplified Explanation of Key Points
1. Why are people who work with AI every day most worried about their children being in liberal arts fields?
This seems counterintuitive, but it makes sense. The author’s career path is a typical example of the success formula from the past 30 years, where knowledge of mathematics, physics, and chemistry was seen as the key to a secure future. She believes that science and engineering lead to stability, while liberal arts are more unstable. However, she fails to realize that the path she took was unimaginable for her generation; 30 years ago, no one would have thought that roles like AI trainers or live stream operators would be lucrative. Applying the rules of 2024 to predict the future of 2044 or 2054 is like using old maps to search for new lands.
2. The debates about the usefulness of liberal arts online are baseless
Social media debates often present polarized views: some claim that companies are hiring philosophers and sociologists because AI can handle data but not human emotions, while others say that liberal arts programs are being cut and that AI can write better copy than 90% of liberal arts graduates. However, the evidence cited is often anecdotal. No statistical agency can provide data on liberal arts employment rates in the future. These claims are based on personal opinions, and which one prevails depends on who has the louder voice or higher status.
3. We prefer false conclusions to admitting “I don’t know”
Psychology calls this phenomenon “closed needs”—our brains cannot handle the uncertainty of things left unresolved. It’s like when a video cuts off just as the most exciting part starts; we prefer to guess the ending rather than face the uncertainty. When it comes to our children’s future or the direction of the AI era, we can’t know the answers, but the anxiety of uncertainty is unbearable. We cling to wrong conclusions rather than accepting the reality of not knowing.
4. Applying past experiences to the future often leads to mistakes
The article uses historical examples to show that our predictions are often based on outdated assumptions. For instance, Li Ji, captured by an enemy in ancient times, thought she would be a slave, but ended up living comfortably in the palace. The author’s mother, a top student, thought her life was ruined because she couldn’t attend college due to poverty, but later became a teacher and had a stable life. Our predictions for the future are based on past experiences and media rhetoric, which have not been verified.
5. Admitting “I don’t know” is the wisest choice
Acknowledging ignorance is actually the smartest approach. Buffett divides problems into three categories: those he can understand, those beyond his ability, and those with too many variables to predict. He avoids making up reasons to deceive himself. Ordinary people shouldn’t force their children to follow a predetermined path for the future. If a child loves writing, forcing them to learn programming is pointless. By accepting the uncertainty and leaving open possibilities, we can help them avoid mistakes.
In summary, facing the unknown with openness and accepting the reality of not knowing is the most practical approach.