[artyom]

And I welcome the change. In my long experience in academia, I've only found two types of practitioners:

1% are the absolutely brilliant minds that academia was originally created for. People that, without a doubt, leave their mark in the vast corpus of human knowledge. I consider myself fortunate for meeting and learning from them, and I thank the academia ecosystem for that.

But the remaining 99% are the maximalists, as described in the article. More papers/students/grants, then repeat. Worse enough, they're absolutely useless outside of academia, as they never did anything at all outside that bubble.

An embarrassing lot of CS professors would stumble around your average production codebase.

I think AI is just the final nail in the coffin for the latter bunch, as they have been dogs eating their own tail for decades already.

[ViscountPenguin]

I think it's very field dependant. In maths and biology I've seen very few professors that could reasonably be described as maximialists here; computer science really seems to be the outlier. My impression is that impactful CS professors tend to be more strongly associated with either maths, or the field that their cs research is being used in.

Arts faculty on the other hand seem to basically just be a popularity competition.

[artyom]

Matches my experience. Hard science may not have that many maximalists. Applied science and technology (electrical, electronics, computer science, even mechanical), I've found plenty.

What got me out of academia (yup, I was a professor) was:

Do you have vast field experience and want to get into the classroom to teach how it's really done? Tough luck, you should've spent your time writing papers.

No matter how much you know or how good you are, everything is about feeding the maximalist machine, if you're an outlier, worse people with better "scores", more papers and never leaving faculty will forever beat you until they retire.

I took a good look at the publishing process. Absolutely everything about it was back-channeling to carefully select the topic, scope and reviewers of a paper to get it through the process. Goodhart's Law at its finest.

Advice given to me: "aim for a lower rank and be happy with teaching the whole thing while the old professor takes a nap in the corner".

AI or not AI, anything destroying that self-perpetuating bureaucracy is welcome.

[root_axis]

> An embarrassing lot of CS professors would stumble around your average production codebase.

As would be expected. The value of computer science has very little overlap with navigating a typical production code base.

[artyom]

Well, as would be expected of the 1% of brilliant-mind CS professors.

As for the remaining 99%, maybe they should stop pretending they know (and giving advice) about navigating a typical production code base.