This model (“flipped classroom”) has been recommended by many for quite a long time (at least since internet video delivery for the purpose became practical, but ISTR the first suggestions actually predate even that) and the reasons just seem to keep growing.
High school: Watch ~1hr lecture every night for next day's class, in which we did worksheets and the teacher would work through problems, but we were generally expected to have learned the material (teacher would not re-teach it).
College: Last semester I had a Data Structures class with a similar structure, but with 2-3 lectures a week. Same idea, we worked on practice sheets in class and had far more time to ask questions instead of having the entire concept taught to us. I much preferred this because some concepts covered, I had a very solid understanding of, so not wasting time in class was great.
It... It sometimes works. It depends a LOT on the instructor.
Should also note: it only really works when all your lecturers share some information about workloads...
Why does so much learning and research take place if these are not primary purposes of schools?
We are absolutely nowhere near even close to beginning to know how to even start building such a thing. Chat bots, language models and image generators are fun tools that look amazing to people who don't understand how they work, but they're extremely rudimentary compared to real intelligence.
I'll make a counter-prediction. All the low hanging fruit in language model development have been picked. Like all technologies there's a steep part of the S-curve of development and that's where we are now, but you can't extrapolate that to infinity. We'll soon hit the top of the curve and it will level off, and the inherent limitations of these systems will become a severe obstacle to further major advances. They will become powerful, useful tools that may even be transformative in some activities, but they won't turn out to be a significant step towards general AI. An important step maybe, but not a tipping point.
Hiring AIs to do something is extremely expensive. You're basically setting a warehouse of GPUs on fire.
Anyway, if it was true total factor productivity would be exploding, but it's actually kinda underperforming. (And automation almost always causes increased employment.)
Other way round, right?
Humans (labor) are different from horses (capital) because 1. they actively participate in work, ie, they don't just literally do what you tell them 2. they actually signed up to work, whereas horses don't care. And 3. if you give them money, they'll also become your customers. Though, I don't know if that's a major factor for employers, even if there is that Henry Ford anecdote.
ATMs are a good example here because there are more bank tellers now than before ATMs were invented. (see Jevons' paradox)
There are some jobs where labor needs to care. Most tech jobs, for example. But there are lots of jobs, especially temp ones, that are about throwing as many bodies as you can afford at a problem, and don't ask questions or try to do it smarter. So 1 is actually a detriment in those kinds of jobs.
To point 3, Henry Ford aside, if businesses really wanted employees to be able to afford their goods, they'd stop offshoring jobs!
ATMs put bank tellers out of work. There do happen to be more bank tellers now than before because there are more bank customers needing more bank services, but my bank only needs X tellers at at time vs X+1 or 2 or 3, and they don't hire any for 24 hours services. It's a bit hard to see, because the number of tellers is higher now than before, but the question is how many more tellers would there be without said machines?