"Computers, like children, are more often taught by rote. They’re given thousands of rules and bits of data to memorize..."

"... If X happens, do Y; avoid big rocks — then sent out to test them by trial and error."

 This is slow, painstaking work, but it’s easier to predict and refine than machine learning. The trick, as in any educational system, is to combine the two in proper measure. Too much rote learning can make for a plodding machine. Too much experiential learning can make for blind spots and caprice. The roughest roads in the Grand Challenge were often the easiest to navigate, because they had clear paths and well-defined shoulders. It was on the open, sandy trails that the cars tended to go crazy. “Put too much intelligence into a car and it becomes creative,” Sebastian Thrun told me.

From a New Yorker article about self-driving cars.  I'm interested in the analogy to the education of humans especially with respect to the fear of creativity arising from too much intelligence but also the downside of too much experiential learning: blind spots and caprice.