Using experiences from machine learning/artificial intelligence in pedagogics

It is interesting to see how now people working in machine learning (ML) are classifying learning strategies or learning methods. Engineering and math has the clear advantage of being very concrete. You could probably call it constructionistic. Those different learning strategies are  classified and advantages are also investigate in relation to different constraints.

Thus, I have a prediction that that is that the work now done in ML will be very useful for pedagogics. How can we use what we learned about optimal teaching in ML to teaching humans or animals? There must be a connection there.

About machine learning

It has recently, in so many places, been suggested that "AI" poses the single largest threat to humanity. To me, this claim is just uninformed and rediculus. Some arguments against:

1. It has been stated that we will not be able to predict the evolution of AI. And it will grow in intellegence exponentially and BAM out-smart and kill us all. But looking at history this kind of prediction has been made lots of times befor with different technical advancememts. To error. I see no reason to beleive this piece of tech will be any more disruptive in that sense.

2. AI is, also amongst highly educated people, vastly miss-understood. In its current incarnation, it is a set of tools to solve detailed technical problems. No where is there any will or intention. AI people still say (and so do I)they do not even understand will.

3. They keep saying we will have an escalation of ai evolving it self away from us slow biologically evolved beings. And finally erasing us. But if an ai is intelligent enough, and the above is a problem, why would it want to have it self superseded by a smarter ai? Won't that feel like for us and the level 1 ai?