The Google Maps smudging point is an interesting one and definitely worth considering, but the incentives at play are very different. While I'm sure they want to be seen as making an effort, Google isn't rewarded in any way for achieving high accuracy in their smudging. It just has to be "good enough" to the point that they aren't getting in trouble for deliberately neglecting it. For this reason, I'd imagine the resources they devote to it are quite limited. It's not having billions poured into it like self-driving AI is--while I have no inside knowledge, I'd guess the budget is orders of magnitude less.
> I'd imagine the resources they devote to it are quite limited
That's a problem inherent to AI or neural networks. We cannot spend our way out of these problems; they are underlying to the technology itself. Nobody knows what "doesn't work" when a neural network does something unexpected. AI is not a technology we have invented, it's a technology we've copied from nature. Nobody knows anything about what really goes on, this is why we're not getting anywhere.
Google could spend their entire budget on that smudge-bot, and it still wouldn't get any better using AI; they would have to go back to regular image analysis to make any improvements at this point. Google has trained it to be so good at finding faces; it started smudging faces on billboards/ads/shop-windows, but when these are flagged as errors, then it starts showing regular faces in shop windows un-smudged. The problem is that we have no idea of what's going on, so all we can do is to add new layers to the neural network, or give it more training data, neither of which gives an accurate result typically, making it impossible to use for self driving cars etc.
