Final week, I discovered myself hunched over my laptop computer at 10 p.m. (hey, that’s late for me!), wrestling with a coding downside. After hours of frustration, I stepped away and made a cup of tea. After I returned, I did what any self-respecting technologist in 2025 would do: I backtracked, reformulated my query, and requested ChatGPT for assist.
I’m continuously requested questions like “Ought to my children study to code?” and “What expertise do they really want on this AI world?” I ponder about this too. I imply, if AI can now write code higher than most people, ought to we nonetheless be instructing children to do it? How can we put together them for the long run, particularly as issues are shifting so rapidly?
Maybe counterintuitively, this AI revolution would possibly make a liberal arts schooling extra precious. A poetry main learns tips on how to categorical humanity. A historian learns classes from the previous. A philosophy pupil learns to query assumptions and moral frameworks. These timeless human expertise turn into much more essential as AI handles the technical heavy lifting. With these foundational talents to know and categorical the human situation, what’s potential with creativity turns into boundless.
The Finish of Coding Is the Starting of Downside-Fixing
As AI begins writing code, we’re coming into what my buddy Tim O’Reilly calls “the tip of programming as we all know it.” We’ve gone from punch playing cards to meeting language to C, Python, and JavaScript—and now we’re simply telling computer systems what to do in plain language. That shift opens the door for extra individuals to form know-how. The long run isn’t about realizing code; it’s about realizing what to construct and why.
Stanford researchers, together with Noah Goodman (who’s each a pc scientist and a psychologist finding out human cognition), not too long ago printed a fascinating paper inspecting how completely different AI methods strategy problem-solving.
What makes Goodman’s perspective so precious is his twin experience in how minds, each human and synthetic, work. His paper reveals that the pondering patterns that make sure AI methods extra profitable mirror these of efficient human problem-solvers: Essentially the most profitable methods confirm their work, backtrack when caught, break large issues into manageable subgoals, and work backward from desired outcomes.
It’s a profound discovery: The talents that make people efficient problem-solvers will stay precious no matter how AI evolves. It made me understand that these cognitive behaviors—not coding syntax—are what we must be nurturing in our kids.
5 Important Expertise Children Want (Greater than Coding)
I’m not saying we shouldn’t educate children to code. It’s a helpful talent. However these are the 5 true foundations that can serve them no matter how know-how evolves.
1. Loving the journey, not simply the vacation spot
When homework appears unattainable or a LEGO construction collapses for the fifth time, it’s simple for youths to get discouraged. However instructing them that setbacks are studying alternatives builds the bounce-back potential they’ll want in a quickly altering world. The capability to soak up real setbacks and proceed ahead—discovering one thing new even once they don’t attain their preliminary aim—is perhaps the only most necessary talent we are able to nurture in our children.
Creating a love of studying helps them to see powerful issues as fascinating puzzles somewhat than scary roadblocks. This doesn’t simply apply to educational topics. Real curiosity concerning the world prepares kids to adapt constantly. Essentially the most profitable individuals I do know aren’t those that memorized probably the most information or mastered one particular talent; they’re those who stayed curious and saved going by means of fixed change.
We frequently discuss intrinsic motivation as a prerequisite for studying, however it’s additionally a muscle you construct by means of the educational course of. As kids sort out challenges and expertise the satisfaction of overcoming them, they’re not simply fixing issues; they’re growing the motivation to sort out the subsequent one.
2. Being a question-asker, not simply an answer-getter
Once you’re a pupil, you’re judged by how effectively you reply questions.…However in life, you’re judged by how good your questions are.—Robert Langer, MIT Professor and Cofounder of Moderna
Anybody can ask AI for solutions. Those that ask considerate questions will get probably the most from it. Good questions stem from understanding what you don’t know, being clear about what you’re actually in search of, and framing them in a means that results in significant solutions.
One of the crucial highly effective metaskills we may help kids develop is self-awareness about their very own studying fashion. Some are project-based learners who have to construct one thing with the intention to perceive it. Others study by means of dialog, writing, visualization, or instructing others. When a baby discovers how their mind works finest, they will strategy any new topic by means of the lens that works for them, turning what may need been a battle right into a pure course of.
When a baby asks, “Why is the sky blue?,” they’re doing one thing highly effective: noticing patterns, questioning what others take as a right, and in search of deeper understanding. Kids who study to ask good questions will direct the world somewhat than be directed by it. They’ll know tips on how to break large issues into solvable items—an strategy that works in any discipline.
3. Attempting, failing, and making an attempt otherwise
When fixing issues, scientists don’t transfer ahead in a straight line. They make guesses, check them, and sometimes uncover they had been mistaken. Then they use that info to make higher guesses. This try-learn-adjust loop is one thing all profitable problem-solvers use, whether or not they’re fixing code or determining life.
When one thing doesn’t work as anticipated—together with an AI-generated reply—children want to determine what went mistaken after which attempt completely different approaches. This implies getting snug with saying issues like “Let me attempt a distinct means” or “That didn’t work as a result of…”
Whether or not they’re troubleshooting a tool or navigating on a regular basis challenges, this mindset helps them strategy issues with confidence somewhat than giving up.
4. Seeing the entire image
The largest challenges we at present face, from local weather change to healthcare, require understanding how completely different items join and affect one another. This “big-picture pondering” applies equally to on a regular basis conditions, similar to understanding why a classroom will get noisy or why a household price range doesn’t steadiness.
This mindset is about recognizing patterns and understanding how altering one factor impacts all the pieces else. It helps us anticipate unintended penalties and create options that really work.
After we educate children to see connections somewhat than remoted information, we put together them to sort out issues that AI alone can’t remedy. They turn into administrators somewhat than followers, capable of mix human wants with technological potentialities.
5. Strolling in others’ sneakers
In my latest op-ed for the Chicago TribuneI argued that effectivity and empathy aren’t opposing forces. They want one another. This precept is particularly necessary as we increase the subsequent technology.
Expertise with out human understanding results in options which may look good on paper however overlook the actual individuals they’re meant to assist. I’ve seen this firsthand in authorities methods that course of individuals effectively however fail to acknowledge their dignity and distinctive conditions.
Kids who develop deep empathy will create applied sciences that actually serve humanity somewhat than simply serving statistics. They’ll ask not solely “Can we construct this?” however “Ought to we construct this, and who will it assist or hurt?” They’ll do not forget that behind each information level is a human story, and that probably the most significant improvements are people who strengthen our connections to 1 one other.
The Actual Future: Amplifying Human Creativity
These 5 expertise converge in what I see as probably the most thrilling side of our AI-augmented future: democratized creation. As extra individuals acquire the flexibility to form know-how, even with out conventional coding expertise, we’ll see an explosion of native, purpose-driven options.
As I not too long ago wroteI helped put collectively ai/teenagersthe primary world AI convention for and by teenagers. I needed to study from the primary AI-native technology, which intuitively understands know-how’s potential in methods many adults don’t.
Think about a world the place younger individuals not solely use know-how however actively form it to resolve issues of their communities, designing accessibility instruments for buddies with disabilities, creating platforms that join native assets with those that want them, or constructing academic experiences tailor-made to completely different studying types.
This future isn’t about AI changing human creativity; it’s about amplifying it, making it potential for extra individuals to deliver their distinctive views and options to life.
Let’s Construct This Future Collectively!
The fantastic thing about this strategy—specializing in resilience, questioning, adaptation, methods pondering, and empathy—is that it really works no matter how know-how evolves. Essentially the most technologically superior future nonetheless wants individuals who can embrace challenges, ask significant questions, study constantly, see connections, and perceive one another.
In some ways, we’re returning to the perfect of a classical schooling for the AI age. These expertise kind a contemporary trivium—not grammar, logic, and rhetoric however maybe curiosity, creativity, and compassion—foundational talents that unlock all different studying and doing.
Let’s work on this as a neighborhood! I’m crowdsourcing concepts, actions, and approaches that assist develop these important expertise. What different expertise do you assume we must always concentrate on? I’m wanting to study with all of you.
