So, in my grad program in ag, we had a Bay-area ML startup come in to give a seminar on how they were revolutionizing agriculture. The presented their findings on how to increase yields (which they claimed could only be understood from their algorithm).

The problem they were diving into was well understood, and has been researched to death for the last 100+ years. And they had the relationship backwards, not understanding their "input" to increase yields was actually a response to low yields. They were the opposite of helpful, but rather a waste of our time.

As with anything, it helps to know the current state of knowledge before you jump into contribute. An understanding of math doesn't get you there.

The difficulty with medicine lies in attempting to control the death count involved in gaining the experience. Some supervision required.

There are lots of not-fully-understood processes in the world that only work because we lucked into some way of doing them. If you come at these problems with a scientific mindset but with no real experience, you are going to have a bad time.

There is a lot more to medicine than just math and science. That is not a sound basis for criticizing the field. You'll have to do better than that.

>There is a lot more to medicine than just math and science

This is the problem.

That is not a problem. It's simply a fact that you'll have to accept.