That said, most of machine learning is not just engineering. If anything, there is little engineering done at all.
but do not forget the apparent point in the original poster's is the lacking approach below the implementations of above said techniques.
The techniques you listed in a substantial way expanded our knowledge ("oh, we can do this ... and solve more problems") while raising little more questions.
The said implementations on topic give results but raise many more unanswered questions.
(This post is unfortunately an "immature" reply - just a provisional tentative point. The matter of "ML algorithms ∩ science" requires more time and concentration and consultation of the texts of the Great Ones.)
That's right. I think the approach that is lacking is best explained in the submission guidelines for the Journal of AI Research:
>> Papers describing systems should clearly describe the contributions or the principles underlying the system. Papers describing theoretical results should also discuss their practical utility. In general, it should be clear how the work advances the current state of understanding and why the advance matters. Papers should report on what was learned in doing the work, rather than merely on what was done.
https://www.jair.org/index.php/jair/about/submissions
Doing stuff is not science, even if it's doing stuff that's never been done before. In science, we experiment to understand why stuff can be done, and how, not just that it can be done. And of course it matters what is being done, so for example experimenting to find the best combination of spices for a dish is not an instance of science.
Now change cabinet to particle accelerator that a giant team of other theorists and engineers designed. Am I not doing science by participating in building it? So experimental scientists arent scientists?
You might argue, though, that Computer Science is not "real" science.
The algorithms behind the Facebook feed and your favorite AI/ML product is the science. The code that powers the feed and chatgpt is the engineering.
Wikipedia is not wrong IMHO, but then I studied computer science 20 years ago so maybe I’m out of touch
I talk to my friends who sent projects into space and friends who design deep sea drilling rigs. The engineering process is very similar.