Deep Learning seems good at approximating things or iterating on things in coordination with humans. Or if you are doing things that do not need an explanation

Deep Learning seems good at approximating things or iterating on things in coordination with humans. Or if you are doing things that do not need an explanation for how the magic box came to its results, and does not need guarantees of correctness, it is a great tool. Thus, it is perfect for human assistance tools, lossy compression, brainstorming, art, games, and so on. It is also great for things where the answers are verifiable, like protein folding or various other kinds of problems where all that matters is that you find the best-fitting solution and don't care how you arrived at it. But it seems particularly ill-suited for something like fully self-driving cars because in that case there would be no human feedback, and the decision-making process matters. If you cannot defend in court why the system performed the actions that it did, then it is a non-starter. Even if you personally are comfortable with the probability that nothing bad will happen, the regulators and courts likely won't be. And if you don't really know why it is making decisions, then it could start making bad ones at any time with almost unlimited severity. Which is why it is the wrong technology for any life-or-death matter.