@Viss @da_667 @iagox86 @hrbrmstr Two thoughts from the academic side:
1) Higher ed is absolutely all in on AI. While I think there are some novel use cases, it comes down to two things. First, at least in most computing disciplines, the vast majority of research funding (which tenure-track faculty are required to get) is tied to AI usage at the moment. Second, we're largely being told - by industry - that it's going to be all AI, all the time in the future.
To quote Upton Sinclair, "It is difficult to get a man to understand something when his salary depends on him not understanding it." AI is, at the moment, deeply embedded into two of the biggest revenue streams for universities.
We desperately need external people - ideally people tied to revenue streams - talking to Deans and Chairs about the problems associated with AI. The filter bubble is real.
2) On the student side... the root problem here is that the tech industry has lost it's veneer of being an ideal (maybe even good) place to work. I broadly see less intrinsic motivation. I would cautiously say that working in tech now is perceived similarly to working in business/banking 15 years ago. Decreasing intrinsic motivation is very likely tied to students trying to find the quickest/easiest way through.