As you have implied in your example, humans cannot make observations about the present and reason about the near future. As a result, they must learn the consequences of any action by experiencing it.

So the situation is really much worse than you describe. Even if we invested in demonstrating the "soccer ball and child" scenario for all driving students, they wouldn't be able to apply the experience to tennis balls and dogs, or a child entering the road without any sort of ball. Teaching people to drive would require an exhaustive course in every conceivable scenario that might arise while driving. You can see why it's an intractable problem.

I've yet to meet a human that needs to observe enormous numbers of balls and children against a number of different backdrops before they grasp the concept that they're different from the background environments, never mind potentially linked to unsafe road use.

The conclusion that a neural network classifies stuff 'correctly forever' is also not one supported by the current state of computer vision.

By "taught this" do you mean kill a kid?

Run this scenario in a thousand variants in sims.

No. He means see a human avoid killing a kid.

It's not that hard for people to learn; see a ball, expect danger and take action.

The problem with people is distraction. The problem with code (AI-ish) is people.