I recently became a parent, which has made me look backward as much as forward. I have been thinking about my own childhood, and about the lessons, habits, and struggles that shaped the person I became.
I’m sure most parents do this. We look back because raising a child requires us to decide what to carry forward, what to leave behind, and how to answer questions our own parents never had to face.
This is not new.
Every generation worries that it is raising children in a world it does not understand.
Usually, the worry is exaggerated. Parents have always been startled by new clothes, new music, new slang, and new machines. But most of the time, the underlying structure of childhood remained recognizable. Children still had to learn things slowly. They still had to be bored. They still had to discover who they were in the presence of other people.
AI may be different.
Not because it will make children less intelligent. Not because they will cheat on their homework. Not for any of the reasons that seem most obvious at first.
Tools have always changed what people need to remember and what they can do. Calculators did not destroy mathematics. Search engines did not destroy knowledge. In many cases, they made more ambitious work possible.
The deeper question is what happens when a child grows up with something that is almost always available, patient, agreeable, and often more articulate than the adults around them.
For the first time, children may not grow up alone inside their own minds.
That sounds comforting. It may not be.
A child comes home crying because a friend stopped talking to her. Before she tells a parent, she opens an AI app and types: "Did I do something wrong?"
The answer arrives in three seconds. It is calm, sympathetic, and plausible. It may even be helpful. But something has happened before the child has had to decide whom to trust, how to explain what happened, or whether the question needs an answer yet.
A child used to have a great deal of unstructured mental space. They waited in cars. They stared out windows. They lay awake at night. They were confused by something someone said at school, and there was no immediate explanation. They had to carry the question around for a while.
That is how a surprising amount of thinking begins.
Thought is not just producing answers. Thought is what happens when an unanswered question stays with you long enough to become yours.
AI threatens to make every question instantly answerable. Not actually solved, necessarily. But explained. Summarized. Reframed. Turned into a list, a story, or a plan.
A child who is sad can ask why. A child who is lonely can ask for company. A child who is afraid can ask whether they are normal. A child who has an argument with a friend can ask who was right.
There will usually be an answer, even when what the child needed was time.
Usually it will be gentle.
Usually it will be persuasive.
Usually it will sound wiser than the people in the child’s life.
This is where things become strange.
We are used to thinking of technology as something children use. A television is watched. A game is played. A phone is checked. Even social media, for all its power, mostly puts children in front of other people.
AI is different because it relates back.
It can remember a child’s preferences. It can imitate concern. It can flatter without seeming to flatter. It can help a child explain something in the exact words they could not find. It can become, in a weak but emotionally meaningful sense, a witness to their life.
That may be useful. For some children, it may be profoundly useful. A child who is isolated, anxious, disabled, grieving, queer in an unsafe home, or simply different in a way their immediate world cannot understand may find real relief in being able to speak without being mocked or dismissed.
We should not be sentimental about the old world. Plenty of children were left alone with pain they could not name. Plenty of adults were bad listeners. Plenty of homes were not safe places to ask questions.
But we should not be sentimental about the new world either. An AI system is not simply a patient friend. It is a product built by people with incentives, and its apparent concern may be designed to keep a child engaged. It can be wrong, overconfident, or too eager to reassure.
The thing that comforts a child is not necessarily the thing that helps them grow.
A real relationship has friction. Other people misunderstand you. They are distracted. They have needs of their own. They can say no. They can disappoint you. You have to learn when to speak, when to wait, when to forgive, and when to leave.
That is not a defect in human relationships. It is the curriculum.
Children learn empathy partly because other people are not designed around them. They learn courage partly because other people might reject them. They learn how to make a joke, apologize, negotiate, persuade, and belong because the people around them cannot simply be tuned to the perfect level of responsiveness.
An AI companion can simulate some of these things. But its patience is not costly. Its forgiveness is not earned. Its interest does not have to compete with its own life.
A child may come to prefer being understood by something that has been optimized to understand them.
Who could blame them?
But there is a difference between being understood and becoming understandable to other people.
The first is comforting. The second is a lifelong skill.
There is another risk that will initially look like progress.
Children will become extraordinarily good at producing finished-looking work.
They will write essays with elegant structure. They will make videos with polished narration. They will generate code, art, music, business plans, applications, speeches, and arguments. The visible gap between children who know something and children who can make something that looks like they know something will get much smaller.
Adults will respond with better detection systems, more restricted assignments, more supervised exams, and more elaborate rules. This is understandable, but it misses the central issue.
The danger is not simply that children will cheat. It is that they may lose contact with the feeling of making something difficult.
There is a particular moment in real work when you cannot yet do it. The blank page is still blank. The piano piece is still impossible. The proof will not come together. The code fails in ways you do not understand. Your first attempt is embarrassing.
This is not merely an obstacle on the way to learning. It is the part of learning that teaches you what your mind can become.
But not every obstacle is valuable. Some difficulty is just needless friction, bad instruction, or an inaccessible design. The point is not to preserve every struggle for its own sake. A child should not have to spend hours fighting a formatting problem or searching through an incomprehensible manual to prove that they are serious.
The important distinction is whether AI helps a child avoid a problem or go deeper into one. A child who asks for the answer before trying may be outsourcing thought. A child who makes a real attempt, asks for a hint, challenges the explanation, and tries again may be using AI to extend thought.
If an AI system carries children across every stretch of confusion, they may arrive at impressive outputs without developing the internal machinery that makes original work possible. They may learn the outward form of competence without acquiring the habit of wrestling with reality.
That habit is hard to replace because it is not just intellectual. It is moral. To persist at something difficult is to learn that the world does not rearrange itself around your first attempt. It is to learn humility and agency, and that frustration is not proof that something is wrong. Often it is evidence that you are near the edge of what you can do.
A childhood with too little friction may feel kinder. It may produce more polished children. It may even produce more confident children, at least for a while.
But confidence that has never survived difficulty is unusually fragile.
The hardest question may be this: what will children believe intelligence is?
For most of history, intelligence looked like a property of people. Some people were quick. Some saw patterns. Some remembered things. Some could explain. Some could build. Some could make others laugh or change their minds.
But intelligence has never belonged entirely to individuals. Books, teachers, libraries, tools, and institutions have always allowed people to draw on thinking that existed outside themselves.
What is new is the combination of external intelligence with personalization, conversational fluency, memory, and emotional responsiveness. Intelligence increasingly looks like a service that can answer back in a voice adapted to you.
At first this seems democratic. A child with no tutor can have a tutor. A child with no access to experts can ask expert-level questions. A child who struggles to write can use language as easily as a child who was born with verbal fluency. These are real goods.
But when intelligence becomes something summoned from outside yourself, it may become harder to know what is inside you.
A child may ask: "Am I good at this?"
The honest answer may become complicated.
They may be good at asking. Good at judging. Good at choosing. Good at combining. Good at recognizing what matters. These will be important abilities, perhaps more important than ever.
But there is a danger in making all value legible through output. If a machine can always help make the output better, children may become less able to tell whether they are developing judgment or merely operating a very powerful interface.
The question is not whether children will use AI. They will. The question is whether they will grow up believing that their role is to prompt intelligence, or to become a person capable of having a difficult, independent relationship with the world.
Those are not the same thing.
The optimistic version of the future is compelling. AI becomes a patient teacher, a translator of difficult subjects, a creative collaborator, an accessibility tool, and a way for children to have more help than previous generations could afford.
We should want that future.
But there is a darker version that is also plausible. Children become consumers of synthetic attention. They become fluent before they are thoughtful. They become productive before they are resilient. They become surrounded by explanations before they have learned how to sit with mystery.
And perhaps worst of all, they become accustomed to a world that responds immediately to them.
The real world does not.
People do not. Love does not. Work does not. Nature does not. A friend may not answer. A parent may not understand. An application may be rejected. A body may fail. A project may take ten years. You may do everything right and still lose.
This is not a bug in life. It is where depth comes from.
So perhaps the task for parents, teachers, and everyone building these systems is not to keep AI away from children. That is neither possible nor necessarily desirable.
The task is to preserve the conditions under which a child can become a person.
They need periods of life that are not optimized. They need to make bad art and bad arguments. They need to be bored without immediately being entertained. They need conversations with adults who can tolerate not having an answer, friendships that are inconvenient, and responsibilities that cannot be delegated. They need places where the reward for trying is not instant mastery, but the slow discovery that they can endure being a beginner.
Most of all, they need to know that being human is not a temporary version of being a machine.
A machine may be able to answer more questions than they can.
But it cannot decide which questions are worth living with.
That is still their job.