When I say "hardcoding" I don't actually mean hardcoding. I mean forcing the ML system to keep iterating on specific problems that it did poorly at, with human

When I say "hardcoding" I don't actually mean hardcoding. I mean forcing the ML system to keep iterating on specific problems that it did poorly at, with human supervision. e.g. the car did the wrong thing at the intersection of 9th and Elm? Give it 100 similar situations (at 9th and Elm), let it generate lots of possible behaviors, and then have humans tell it which are correct. Then whenever a car is at 9th and Elm, it uses that training as a priority. For a relatively small geofenced area that is a reasonable approach and should work well. Unfortunately it doesn't scale to the whole country/world.