Similarly, in research, the trajectory points toward systems that can increasingly automate the research cycle. In some domains, that already looks like robotic laboratories that run continuously, automate large portions of experimentation and even select new tests based on prior results.
At first glance, this may sound like a welcome boost to productivity. But universities are not information factories; they are systems of practice. They rely on a pipeline of graduate students and early-career academics who learn to teach and research by participating in that same work. If autonomous agents absorb more of the “routine” responsibilities that historically served as on-ramps into academic life, the university may keep producing courses and publications while quietly thinning the opportunity structures that sustain expertise over time.
The same dynamic applies to undergraduates, albeit in a different register.
Yeah, it’s a really eloquent way of phrasing it.
It’s something I’ve been thinking about a lot lately, because I have a lot of friends who are doing PhDs at the moment. It’s interesting because especially at this stage, their actual research output isn’t the point. Like, ofc publishing your research is a key part of the process of getting a PhD, but that’s almost like an incidental byproduct of the process — the actual primary product is a person who is knowledgeable and experienced enough in the academic process that they can be trusted to be a part of the system.
(Tangentially, something I’ve been pondering lately is that I think Wikipedia works similarly, in that the encyclopedia itself isn’t the point, but rather the robust systems of editor organising and social infrastructure is the “real” product of value, and the encyclopedia is just a byproduct that exists downstream of the system of practice)