Walk into almost any home today and you are likely to find a child chatting happily with a machine. Not using it, exactly. Chatting with it. The glowing rectangle has become tutor, entertainer, confidant, and occasional philosopher. It answers instantly, never gets tired, and rarely insists on homework before recreation.
The usual response to this technological upheaval has been to teach children coding. A sensible idea, perhaps, but not the most important one. Before children learn how machines think, they should learn how they think.
The curious thing about the human brain is that it arrives without a user manual. Children study mathematics, geography, and grammar, yet often reach adulthood knowing remarkably little about the three-pound organ making every decision they will ever make.
This matters because modern technology has become extraordinarily skilled at exploiting the brain’s shortcuts. Algorithms compete for attention with the determination of casino operators. Explain neuroplasticity to a child, the unsettling fact that repeated thoughts and habits physically reshape the brain, and suddenly endless scrolling begins to look less like entertainment and more like training.
And training matters.
For more than forty years, the motto of School of Thinking has been simple: Daily Brain Training. The reason is straightforward. Performance follows training. If we wish to multiply brain performance by ten, we must multiply brain training by ten.
Curiously, the same principle now governs artificial intelligence.
The spectacular rise of AI did not occur because machines suddenly became magical. It occurred because researchers dramatically increased the amount of training. As Jack Clark, co-founder of Anthropic, has observed, “Every time we dump more compute into the training of AI they get better so that – allocating more compute to the training of them – has turned out to be the most important insight to what subsequently has happened“.
The lesson for children is profound. Both biological brains and artificial brains improve through training. The difference is that AI companies invest billions training their machines, while many young people spend hours scrolling each day, accidentally training themselves the wrong way.
Neuroscience teaches children that their attention is not merely being consumed, it is being programmed. Once they understand that, AI loses its mystical aura. It becomes what it really is: a trained system. And the child begins to see themselves the same way, not as a passive consumer of technology, but as a brain in training.
If we don’t train kids about their brain then others will do it for them. There is no guarantee it will be done in their best interests.
That is why neuroscience should be taught to kids in primary schools in Australia.
