Originally written in Traditional Chinese: AI 時代的孩子，不缺答案，缺的是做出東西的經驗
At the end of September, a Hong Kong survey asked 1,166 secondary school students to rate themselves on eight AI competencies, on a 5-point scale.
Ethical awareness, practical application and human-AI collaboration each scored 3.81. The lowest was "AI creation": 3.22. It was also the only one where the higher the grade level, the lower the score.
Students are good at using AI to find answers. Yet they feel less and less able to make something with it.
At home, I have seen the opposite picture.
One day, my wife took our two sons to run a stall at a school fair. What to sell was their idea. How to sell it was their call. Then she put them at the front of the stall to talk to customers themselves.
That day, their business model changed three times. By the time they packed up, they knew what sold and what did not. One afternoon, one full loop.
Nobody taught them the words "business model." The customers did.
Asking grows knowledge. Making grows capability.
AI has made asking extremely cheap. So what separates students now is not who asks the most. It is who can turn an answer into something other people can use.
Students in the AI era are not short of answers. They are short of experience making things.
This is not about turning children into entrepreneurs. What I want is one complete loop: finish something, hand it over, get back one piece of real feedback. The loop can be small enough to happen at home.
Three rules I give parents:
- The student picks the topic, from their own interests: a game guide, basketball plays, a Pokémon team. Adults may not call it unserious.
- The student writes the method first. You can ask questions, but you cannot write it for them.
- What they make must be handed over. Give it to a classmate or a cousin, and bring back one honest piece of feedback.
Throughout, AI is an assistant, not a contractor. The student writes ideas first, then asks AI to fill gaps and find weak spots.
At that stall, customers never gave my sons answers. Only feedback. AI can give answers. Feedback has to be collected in person, on the front line.
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