Last week, I found myself hunched over my laptop at 10 pm (hey, that’s late for me!), Fighting with a coding problem. After hours of frustration, I walked away and made a cup of tea. When I returned, I did what any self -esteem technologist would do in 2025: I went back, I reformulated my question and asked Chatgpt help.
They ask me constantly as “Should my children learn to code?” And “what skills do you really need in this world of AI?” I also wonder about this. I mean, if AI can now write code better than most humans, should we be teaching children to do so? How do we prepare them for the future, especially because things move so fast?
Perhaps contraintuitively, this AI revolution could make a liberal arts education more valuable. A greater poetry learns to express humanity. A historian learns lessons from the past. A philosophy student learns to question assumptions and ethical frameworks. These timeless human skills become even more crucial as Ia handles technical heavy work. With these fundamental skills to understand and express the human condition, which is possible with creativity becomes unlimited.
The end of coding is the beginning of problem solving
As I start writing code, we are entering what my friend Tim O’Reilly calls “the end of programming as we know it.” We have gone from the drilling cards to the assembly language to C, Python and Javascript, and now we are only telling computers what to do in simple language. That change opens the door for more people to shape technology. The future is not about knowing the code; It’s about knowing what to build and why.
Stanford researchers, including Noah Goodman (who is a computer scientist and psychologist who studies human cognition), recently published a fascinating paper Examine how different AI systems address problem solving.
What makes Goodman’s perspective so valuable is his double experience on how minds work, both human and artificial. His document shows that the thought patterns that make certain systems of AI reflect more successful those of the solutions of effective human problems: the most successful systems verify their work, they go back when they are struck, they break major problems in manageable sub -knowledge and work back from the desired results.
It is a deep discovery: the skills that make humans effective to solve problems will continue to be valuable regardless of how AI evolves. It made me realize that these cognitive behaviors, which do not encode the syntax, are what we should be nurtured in our children.
Five essential skills that children need (more than codify)
I do not say that we should not teach children to code. It is a useful ability. But these are the five true bases that will serve them regardless of how technology evolves.
1. Loving the trip, not just fate
When the task seems impossible or a lay structure collapses for the fifth time, it is easy for children to be discouraged. But teaching them that setbacks are learning opportunities build the return ability they will need in a world that changes rapidly. The ability to absorb genuine setbacks and continue forward, discovering something new even when they do not reach their initial objective, is the most important ability we can nurture in our children.
Developing a love for learning helps them see difficult problems such as interesting puzzles instead of terrifying obstacles. This not only applies to academic matters. Genuine curiosity about the world prepares children to adapt continuously. The most successful people I know are not those who memorized most of the events or dominated a specific skill; They are the ones who remained curious and continued to go through a constant change.
We often talk about intrinsic motivation as a previous requirement for learning, but it is also a muscle that builds through the learning process. As children address challenges and experience the satisfaction of overcoming them, they are not just problems; They are developing the motivation to address the following.
2. Be an inmate of questions, not just an answer
When you are a student, they judge you for how well you answer questions … but in life, they judge you for how good your questions are. Robert Langer, Modern Professor and Co -Funder
Anyone can ask AI answers. Those who ask reflective questions will get the maximum of that. Good questions should understand what you don’t know, be clear about what you really are looking for and frame them in a way that leads to significant answers.
One of the most powerful metashills that can help children to develop is self -awareness about their own learning style. Some are students based on projects that need to build something to understand it. Others learn through conversation, writing, visualization or teaching others. When a child discovers how his brain works better, he can address any new theme through the lens that works them, turning what could have been a fight in a natural process.
When a child asks: “Why is the sky blue?” Are doing something powerful: notice patterns, question what others give how they give up and looking for a deeper understanding. Children who learn to ask good questions will lead the world instead of being directed by him. They will know how to divide big problems into solutionable pieces, an approach that works in any field.
3. Try, fail and try differently
When solving problems, scientists do not advance in a straight line. They make conjectures, they try them, they often discover that they were wrong. Then they use that information to make better conjectures. This Try-Learn-Adjust loop is something used by successful problems, whether they are fixing the code or discovering life.
When something does not work as expected, including an AI response, the Kids must find out what went wrong and then try different approaches. This means feeling comfortable saying things like “let me try a different way” or “that didn’t work because …”
Whether they are solving problems or sailing everyday challenges, this mentality helps them address trust problems instead of giving up.
4. See the complete image
The biggest challenges we currently face, from climate change to medical care, require understanding how different pieces connect and influence each other. This “great image thought” also applies to everyday situations, such as understanding why a classroom becomes noisy or why a family budget is not balancing.
This mentality is about detecting patterns and understanding how to change a thing affects everything else. It helps us anticipate involuntary consequences and create solutions that really work.
When we teach children to see connections instead of isolated events, we prepare them to address the problems that only AI cannot solve. They become directors instead of followers, capable of combining human needs with technological possibilities.
5. Walking on the shoes of others
In My recent opinion article for the Chicago TribuneI argued that efficiency and empathy are not opposite forces. They need each other. This principle is especially important as we propose the next generation.
Technology without human understanding leads to solutions that can be seen well on paper, but forget the real people they should help. I have seen this first hand in government systems that process people efficiently but do not recognize their unique dignity and situations.
Children who develop deep empathy will create technologies that really serve humanity instead of only serving statistics. They will ask not only “can we build this?” but “Ought We build this, and who will they help or harm? They will remember that behind each data point there is a human history, and that the most significant innovations are those that strengthen our connections with each other.
The real future: amplifying human creativity
These five skills converge in what I see as the most exciting aspect of our aquatic future AI: democratized creation. As more people win the ability to shape technology, even without traditional coding skills, we will see an explosion of local solutions with purpose.
Like me recently wroteI helped assemble Ai/adolescentsThe first global IA for and adolescents conference. I wanted to learn from AI’s first generation, which intuitively understands the potential of technology in a way that many adults do not.
Imagine a world in which young people not only use technology, but actively form it to solve problems in their communities, designing accessibility tools for friends with disabilities, creating platforms that connect local resources with those who need them or create educational experiences adapted to different learning styles.
This future is not about replacing human creativity; It is about amplifying it, making it possible for more people to give life to their unique perspectives and solutions.
Let’s build this future together!
The beauty of this approach, focused on resilience, interrogation, adaptation, systems thinking and empathy, is that it works independently of how technology evolves. The most advanced technologically still needs people who can adopt challenges, ask significant questions, learn continuously, see connections and understand each other.
In many ways, we are returning to the ideal of a classical education for AI’s age. These skills form a modern, non -grammar, logical and rhetorical trivio, but perhaps curiosity, creativity and compassion, fundamental skills that unlock all other learning and do.
Let’s work on this as a community! I am crowdsourcing ideas, activities and approaches that help develop these essential skills. What other skills do you think we should focus? I am anxious to learn with all of you.
#Skills #Children #adults #world #oreilly
