Why Should Kids Learn Math Without AI?

Cliff Sosin argues that children should learn foundational skills apart from models so they can direct a model. You cannot ask a model to treat a problem as a stochastic process unless you already know what a stochastic process is. A model could teach the term, but figuring it out that way adds a lot of friction. You do not have to work out the math, but you do have to know what it is.

Foundational skills build on one another, and children have to be able to do them without models. The point is not that later work will happen without models. If they cannot multiply, matrix multiplication is very hard to understand. They need not perform matrix multiplication especially well. They do need a high enough sense of what the model is doing so they can direct it. A bunch of time with kids should be spent separated from models, on basic skills judged important. Choosing which skills matter is a hard problem. The model can do the work, and the child still needs to know it in order to tell the model what to do.

An English teacher who rejects models because kids cheat on Shakespeare essays is not being ambitious enough. Give them work a hundred times harder and more ambitious, and have them use models to the fullest extent. They should bring the work product back. Make sure they did not just give a prompt to the model and submit the homework, and make sure they own it. Ask why the result looks the way it does and force them to justify it. Kids need to be good at using models, and they need to be taught that they can do anything.