After Exams, Do Not Just Chase Majors: What Children Need In The AI Era

After Exams, Do Not Just Chase Majors: What Children Need In The AI Era

After high-stakes exams, many parents begin asking a new set of questions. This year, many of those questions are about AI.

Parents around me have asked things like:

• Should my child learn programming? Is computer science still a safe major?
• My child is in primary school. If AI becomes so strong, is it still worth doing math competitions?
• AI translation is already good. Does English still matter?
• If AI replaces human work, will my child have a job in the future?

On the surface, these are four different questions.

Underneath, they are the same anxiety:

In the AI era, what direction should we prepare children for?

My answer is direct:

Do not always think in terms of “training” a child.

Training often means pouring yesterday’s experience into the child. But the one certain thing about the future is that it will change faster.

A child trained only by fixed experience may struggle in a society that changes quickly.

What parents should do is stimulate and practice a child’s ability to improve independently, learn independently, and adapt independently.

This does not mean children should stop learning skills. It does not mean tutoring and practice are useless.

It means parents should not treat one skill, one major, or one short-term rule as the only moat for a child’s future.

In the AI era, the real goal is not one fixed skill. The real goal is whether a child can keep learning, adapt quickly, and solve real problems together with AI.

Four Questions, One Anxiety

The four questions parents ask can be condensed into one:

If the future changes so fast, will the path I choose for my child today expire too quickly?

That is the real anxiety.

The computer science question is about whether today’s hot major will be rewritten by AI.

The math competition question is about whether a current advantage will remain an advantage.

The English question is about whether translation tools make language study unnecessary.

The jobs question is about whether many familiar roles will disappear by the time the child grows up.

These questions are worth asking, but they cannot be answered only at the surface level.

If parents only chase surface answers, they will keep chasing new labels: programming this year, robotics next year, large models after that, and some new term a few years later.

The more stable direction is not a single skill name. It is the child’s underlying ability to face change.

1. Should Children Learn Programming? Is Computer Science Still Safe?

My judgment is: yes, children can learn it.

But the focus should not be spending huge amounts of time memorizing how to write specific lines of code.

What is worth learning is the logic behind programming: how to decompose problems, how implementation works, where system boundaries are, and how to let AI help you build better.

In the future, the risk is not that people who cannot write code will have no chance.

The real risk is that people who can only write code will become more fragile.

Why?

Because writing code itself is being changed quickly by AI. In the past, the ability to write code line by line was a major advantage. In the future, the more important ability is to define the problem clearly, judge whether AI’s code is correct, split a real need into executable modules, and find bugs and boundaries.

So if a child learns programming, do not only focus on syntax and exercises.

Help the child understand:

• how a problem is split into parts;
• which steps can be handed to AI;
• where AI output may go wrong;
• how to verify the final result.

That is more important than simply writing more lines of code.

2. If AI Becomes So Strong, Is Math Still Worth It?

This question does not seem directly related to AI, but it is important.

My judgment is: first ask why you are doing it.

In the short term, if math competitions help with admissions, exams, or specific educational rules, they may still be useful. But I do not think every short-term rule will remain stable forever.

In the long term, mathematical ability is still important. Math is a foundational ability for research and complex problem analysis.

But children need two more basic abilities.

First, the ability to work with AI on research and problem solving.

Second, the ability to identify the key problem.

In the future, many non-critical parts of a problem will be handled by AI. What will separate people is whether they can judge what is worth studying, where the real bottleneck is, and which information is only noise.

So the future is not “math becomes useless.”

The future is that math must combine with other thinking abilities to solve problems efficiently.

3. If AI Translation Is So Good, Does English Still Matter?

My judgment is: yes, English still matters.

But the reason changes.

English is no longer only for reading materials page by page or getting information manually. AI can already do a lot of that.

The new value of English is whether the child can audit AI’s English-source summaries and troubleshoot when something looks wrong.

In the future, English is not only a tool for acquiring information.

It is a tool for collaborating with AI more reliably.

Because the information that needs to be checked and traced will not be only in Chinese. A large amount of it will still be in English.

That is the new value of English: not who memorizes more, but who can confirm information, identify errors, and trace sources at critical moments.

4. If AI Replaces Human Work, Will Children Still Have Jobs?

My judgment is: many jobs will certainly be changed by AI, and some will be replaced.

But the real danger is not that AI takes all work away.

The real danger is that a child only knows how to wait for tasks, follow procedures, and produce standard answers.

AI is very good at those things.

Children in the future should not compete with AI on pure execution. They need to learn how to direct AI, judge AI, and use AI to get real work done.

The future is not “there will be no jobs.”

The future is that people who cannot collaborate with AI will find it harder to get good work.

You can think of it this way:

Many past jobs rewarded people for executing rules well. Many future jobs will reward people who can solve problems when the rules are changing.

Those are not the same ability.

The Real Direction: From Pouring In Experience To Building Adaptability

The answers above all point in the same direction:

Abilities and roles based on old rules, fixed processes, and past experience will become easier to replace.

But the ability to sense change, adapt to change, direct AI, collaborate with AI, and solve changing problems will become more scarce.

So the task is not to pour experience into the child.

It is not to train the child into a fixed template.

It is to stimulate and practice:

• independent learning;
• fast adaptation;
• active problem solving;
• collaboration with AI to finish real tasks.

These abilities do not grow from slogans. They grow from daily family practice.

Three Small Practices Families Can Start With

Parents do not need to design a huge educational system on day one.

Start with three small practices.

1. Do Not Only Ask For The Answer. Ask About The Process.

When a child gets a problem wrong, do not only ask:

Why did you get this wrong?

Ask the child to review the process:

• What was my first thought?
• At which step did I start going in the wrong direction?
• If I used another method, could I find the answer faster?

This is not only training one problem. It is training the ability to notice mistakes, adjust methods, and adapt.

2. Let Children Do Real Small Projects.

Real projects force children to search for information, make judgments, adjust plans, and finish something.

The project does not need to be complicated.

It can be planning a family trip, researching a topic they care about, making a short video, or designing a small family activity.

These things may not look like traditional studying, but they train children to face real constraints: limited time, incomplete information, changing needs, and imperfect plans.

That is exactly the kind of ability the future needs.

3. Let Children Use AI, But Require Verification.

AI can explain, organize, and inspire.

But the child still has to judge:

• Is AI right?
• Where might it be wrong?
• Can I explain the answer in my own words?

AI can help children move faster, but the sense of direction must grow inside the child.

If a child only copies AI’s answer, the child has not become stronger. They only have a more convenient copying tool.

The valuable part is learning to think with AI, verify with AI, and finish real tasks with AI.

This Is Not About Creating More Anxiety

After exams, parents naturally think about majors, grades, classes, and career paths.

Those things still matter.

But a more important question is:

Can the child keep learning, adapt quickly, and solve real problems together with AI in a fast-changing world?

The future gap will not come from who was filled with more fixed experience.

It will come from who adapts faster and upgrades themselves more actively.

This article is not a college-major recommendation. It is not saying every family should follow one path.

It is a reminder:

Do not bet a child’s future on one fixed answer.

In the AI era, fixed answers expire.

But continuous learning, fast adaptation, and active problem solving will become more valuable.

Kunpeng AI Takeaway

Many parents now ask, “What should my child learn?”

The better future-facing question is:

Can my child keep learning when the thing to learn keeps changing?

In the past, education gave people a sense of safety because the path looked clear: study this, test that, choose this major, enter that organization.

AI is changing that path. Not every path will disappear, but many paths will be less stable than before.

So the long-term investment is not one forever-safe skill.

It is the child’s response pattern when facing a new problem:

• Does the child search for information actively?
• Can the child judge information quality?
• Can the child use AI without blindly trusting AI?
• Can the child review failure?
• Can the child turn one experience into the next ability?

That is the deeper ability worth building in the AI era.

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