Yeah I've been thinking about that a lot within the context of self-driving cars. What if we could take the rare but significant examples of model confusion, and then... explain to the model what it did wrong just as we would to a human. If it could then incorporate that information into future weights, that would be game changer in a LOT of fields where it's been hard to bridge the gap.