Learning to Ride Your Brain

The central argument is that AI literacy is not simply an extension of computer literacy. Conventional computers resemble separate power tools, while AI behaves more like a motorcycle: using it well depends on an ability to steer attention and thought. The brain itself is already a kind of bicycle, combining intelligence with the capacity to direct it, but not everyone learns to “ride” it. The essay distinguishes this cognitive balance from conventional “smarts,” which are often socially recognized through grades, erudition, and the ability to expose gaps in someone else’s knowledge. That performance can help establish authority and deference without requiring a strong commitment to truth or sound reasoning.

The author describes learning to manage attention in childhood as the real change behind being labeled smart: once attention could be directed steadily, the challenge shifted from figuring out how to think to choosing what to think about. This capacity is likened to learning to balance on a bike. Before the breakthrough, conscious corrections are effortful and unstable; afterward, regulation becomes integrated, freeing attention for steering and exploration. Conventional markers of intelligence are therefore unreliable proxies for this underlying ability. People who appear unremarkable in school may become impressive in environments better suited to them, while people certified as smart may lack the balance needed to use AI effectively.