Why ought machine learning be boring to anyone but specialists? Does this imply that specialists ought to be born, rather than become specialists out of interest?
There are lots of things that I think are comparable to machine learning in the sense that they combine applied math and heavy computation and are very practically important, like simulating chemical reactions, solving operations research problems, or computational fluid dynamics. You cannot talk about these things at cocktail parties, though, because people will slowly shuffle away from you -- whereas you can talk about deep learning, which is odd.
Basically, I think if somebody wants to work in machine learning then they should be encouraged, and I think it's great that barriers to entry are lower than most fields, but the average person should not feel like they need to care about it, and if they do it might be because they have an inaccurate narrative.
>You cannot talk about these things at cocktail parties, though, because people will slowly shuffle away from you -- whereas you can talk about deep learning, which is odd.
It's really not odd at all. The average person has some familiarity with ML/AI, so you don't have to expend the energy to introduce them to the topic in a way that is understandable and also engaging to them. They already have a baseline, and are likely already aware of some interesting use cases. By contrast, they might not even know what "operations research" is, so you have to be both willing and able to expend the energy to explain the field in a way that is comprehensible and interesting. I'm sure it's possible, but the cross-section of people with the knowledge, the interest, and the social graces to do it is probably small.
To me it seems that a large swath of the science community dislikes buzzwordification and pop science more than they like proliferation of knowledge, based on how negative responses seem to be to things like normie interest in AI here. I would be fascinated to read any peer reviewed studies on the negative impacts of pop science on long term scientific advancement, so that I could understand this bias (and debunk my own bias that more interest in science is better in the long term).
I interpreted this to mean something like 'how phones / car engines / etc work' is not of interest to most of their users as long as they get the job done. If they get 'interesting' it can means that something isn't working right. Where 'interesting' = 'suddenly noticeable'.
Basically, I think if somebody wants to work in machine learning then they should be encouraged, and I think it's great that barriers to entry are lower than most fields, but the average person should not feel like they need to care about it, and if they do it might be because they have an inaccurate narrative.