Actually the automobile and aviation sectors are under more strict regulation than Healthcare because the ECU software and aviation software running, when making a mistake, does not only influence one life but many. So whilst being added more and more in cars and planes, you will see AI faster in Healthcare than in cars or planes. I've been in a shared European subsidiary project recently (http://www.emc2-project.eu/) and these sectors were always laughing when I complained about FDA. I wouldn't want to work a single day in their sectors. They had to disable the second core on a dual core fpga because it was not allowed. Meanwhile, I was happily running my data science in a cloud network.
Regarding design, design is a peculiar thing potentially much more difficult to automate than a medical diagnosis because there is only emotion attached. For medical diagnosis for a lot of cases it is just comparing to others and spotting the differences in the images as early as possible. Before even a human eye can spot them. And not with one dimension but hundreds. Many algorithms do not give the actual diagnosis, they let the doctor know this scan deviates from the default in marked places so a doctor can assess quickly without searching.
> Regarding design, design is a peculiar thing potentially much more difficult to automate than a medical diagnosis because there is only emotion attached.
"Emotion" is not the reason companies still design airplanes and CPUs by hand.
True. Was for the cars. The other part holds for airplanes. By the way, I know of at least one case where a cpu algorithm steered the team on optimizing the resistance of a plane wing (or whatever needs to be optimized there, it was a conversation over beers). Example was that they never could have thought of that improvement themselves. Basically you had to be very stupid to try it as it couldn't work, until a spinoff (one of the millions of automated tries) actually did. CPUs I have no knowledge of.
Regarding design, design is a peculiar thing potentially much more difficult to automate than a medical diagnosis because there is only emotion attached. For medical diagnosis for a lot of cases it is just comparing to others and spotting the differences in the images as early as possible. Before even a human eye can spot them. And not with one dimension but hundreds. Many algorithms do not give the actual diagnosis, they let the doctor know this scan deviates from the default in marked places so a doctor can assess quickly without searching.