在人工智慧焦虑的时代，本文认为要让子女教育路径「防机器人化」多半是一种错觉。AI 驱动的就业取代似乎将加速，尤其随著朝向 AGI 的发展，父母面临不确定性：是否将孩子推向高需求领域或避免高风险选择。文章以南韩补教热作为警讯：尽管私下补习极度激烈并伴随严重失眠，补习最频繁的学生反而更可能出现行为上在校脱节。全球补教市场却仍持续扩张。
文中追踪职涯建议如何转变——十年前口号是“learn to code”，继而是“double maths”，而下一个标签可能再度改变。它主张教育应远离只有唯一正确答案的管道，转向好奇心、容忍模糊性与知识上的主体性。像Anthony Seldon与Rachel Kelly这类专家／作家被引用，认为父母应保护子女免于焦虑，而非投射继承的野心，并且让孩子的选择顺应他们喜欢且认为自己擅长的方向。
文中引用的研究明确指出，美国当前大学生中有42%因AI考虑过转换主修，显示既有恐惧也有早熟的自我评估。作者建议三种核心能力——适应力、从失败中学习、独立思考——再加上善良、节俭与尊重他人的社交特质，都是关键。文章呼吁以持续性再培训、学徒制度与更强的师徒技能传承来取代部分冗长且昂贵、又很快过时的学位体系，并指出目前相对“safe-ish”的领域包括教学、医疗、警政与军事，因其依赖判断与服务而非可被自动化取代的例行流程，应被视为超越短期薪资的长期价值。
In the age of AI anxiety, the essay argues that trying to robot-proof children’s education paths is largely an illusion. AI-driven job displacement appears set to accelerate, especially as progress moves toward AGI, so parents face uncertainty: whether to push children toward high-demand fields or avoid risky choices. The South Korea tutoring boom is presented as a warning: despite intense private tutoring and severe sleep deprivation, the most heavily tutored students were more likely to become behaviourally disengaged at school. Yet the global tutoring market continues to expand.
The piece traces how career advice has shifted—ten years ago the slogan was “learn to code,” then “double maths,” and the next label may change again. It suggests education should move away from one-right-answer pipelines toward curiosity, tolerance of ambiguity, and ownership of knowledge. Voices such as Anthony Seldon and Rachel Kelly are cited to argue that parents should protect children from anxiety rather than project inherited ambition, and let choices follow what children enjoy and believe they are good at.
Research cited is explicit: 42 per cent of current US undergraduates have considered changing their major because of AI, indicating both anxiety and early self-assessment. The article recommends three core capacities—adaptability, learning from failure, and independent thinking—plus social qualities of kindness, thrift, and respecting others. It calls for replacing some lengthy, expensive, and quickly outdated degree systems with continuous reskilling, apprenticeships, and stronger master-apprentice skill transmission, and notes that sectors currently viewed as relatively “safe-ish” include teaching, healthcare, policing, and the military because they rely on judgment and service rather than routinised tasks easy to automate, and should be valued beyond short-term earnings.