Quo Vadis, Academia?

Tags: academia, research, musings

« Previous post: A Barbarian’s Guide to Full-Disk …

After the recent announcements by OpenAI et al., I am often asked whether there is still a future for researchers in academia. I think this is an important question—but I believe an equally important question is whether there is a future for academia (but we will get to the first question, I promise). Concerning the latter question, I believe that unless we finally gather our wits, academia in its current form is doomed; and I, for one, will not shed a single tear for it. We¹ have created a system that equates “productivity” with “number of papers” and/or “number of citations.” We never stopped and asked whether it is a good idea to use the same metrics that one uses to, say, run a burger joint² for something that is supposedly aiming to measure “insights.” Aye, there’s the rub: Counting things in the real world is much easier than counting insights—who could have possibly known?

And now, here we are: The revolution is here and the systems we built are creaking. Even before, peer review was nearing its breaking point. Even before, citation metrics were gamed. Even before, the focus was more on prestige than on long shots. But now we are here, well beyond the breaking point. With new AI systems turning (badly written) papers into a commodity, we finally have to think about reforms. It is now up to us to build something better and there are many ideas floating around that are worth considering, including moving away from citation-based metrics or assessing faculty candidates only based on a small number of their papers.

Let us get back to the question I promised to address, that is, “Is there a future for researchers?” This question requires some additional framing in that it assumes that there is a future for academia as an institution. In my usual Pollyannaish way of viewing the world, I emphatically believe this to be the case.³ However, we are currently living in a period of transformation; I already alluded to this in an earlier post on the time of monsters and the quote therein bears repeating:

The old world is dying, and the new world struggles to be born: now is the time of monsters.

This is a loose paraphrase of Antonio Gramsci, who was writing about the interregnum after World War I, which saw massive societal changes as the ruling order lost its authority. I am no Gramsci scholar, but our situation strikes me as similar: I do not yet see what kind of (scientific) society we are ultimately approaching. It is just clear to me that the old world is slowly fading away.

We now have powerful tools at our disposal and, wielded properly, they can result in a flourishing of the sciences and the humanities that is probably unparalleled in history.⁴ At the same time, we, that is, academia, are still fumbling and dropping the ball left and right. Instead of speaking with clarity and charting a course for the future, some prominent voices in the mathematics community are mourning their field. I understand the feeling—suddenly, the craft one spent decades honing appears to be automatable, so grief is a natural response. But I do not think that proclamations about the death of mathematics are a good way to move forward. Besides, having also been “raised” in the CS community, I know that BSD has been dying for more than 20 years now, so…

Papers are cheap now, so we should focus on the things that cannot be easily counted instead: Insights, research directions, exposition. With that in mind, the advice that I would give to young mathematicians or academics in general is as follows:

1. Do not make any hasty decisions about your future right now. No one can predict how things will be in a couple of years, which means that the best strategy is to remain flexible and open.

2. Even if AI becomes substantially better and more autonomous, research is vast and there will always be more things to discover and explore. Curiosity, creativity, and “taste” in research problems will remain important skills for human beings of all walks of life—someone still needs to ask the hard questions.

3. AI is much more powerful in the hands of an expert. But to become an expert, you must endure desirable difficulty. Short term, there are all kinds of quick ways out. Long term, you will pay if you rely on them too much.

4. Tomorrow belongs to those who prepare for it today. That is, if you continue to sharpen your skills, focusing on deep understanding as opposed to shallow explanations, you have an excellent chance at doing work that matters over the long run.

Finally, whether it is inside academia or outside of it: The future is determined by all of us. Do not underestimate your agency and do not shy away from calling out misuses of new technology. In that sense, you could even borrow a page from the Luddites: Contrary to popular belief, the Luddites did not oppose machines per se but rather how they were used against skilled workers—this is a worthwhile fight! Turning one’s back on a technology with so much potential, by contrast, is not. I, for one, would prefer that we find better ways to deal with it than flat out banning it altogether.

Good luck on your journey, until next time!