“What do we lose if LLMs kill the journal system? Nothing but some heavy ass chains, and a few weak heuristics for assessing CVs quickly that were never worth the outrageous amounts of time and labour the journal system wasted anyway.”
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That’s Jonathan Weisberg (Toronto), who knows a little bit more than the average philosopher about the journal system, having co-founded Ergo.
With AI and “a little human guidance,” he says,
you can crank out the kind of papers that make up 95% of what we publish in a few hours. Soon (already?), human guidance may not even be necessary. Do I find this depressing? Just the opposite. Sure, I built my career on this skill, honed it for decades, and now a computer can do it in a hundredth of the time... But this was always a goofy way of making a living…
[I]t’s always been a drag dealing with bafflingly slow journals, maddeningly lazy referees, and typesetters so incompetent it must be a bit. The publication process puts years of frustrated waiting, and dozens of hours of wasted labour, between when I’m actually done understanding an idea, and the point where my dean finally gives me a pat on the head and a sticker that says “good job!”.
Many see the AI onslaught as a net negative for academia, but Weisberg sees it as an opportunity:
just tell the dean, “sorry, LLMs.” They’ll find some other way to count our beans, I have no doubt. But while they work on figuring that out, we have an opportunity to radically revise the whole bean economy.
If the journals crash and burn, you can still read, think, and write about philosophy. You can still share your writing with other philosophers, build on what they’ve done, hope they’ll do the same in turn, etc. None of this requires publishers, typesetters, or even traditional peer review.
There are better things to do with one’s time than “agonizing over how to revise your manuscript so the referees at the fourth journal you send it to won’t be able to miss the reply to their objection buried somewhere in the middle of page 23.”
So what should replace the current system?
Note that it’s not just that the deans (etc.) who would need a new way to “count our beans.” Being able to assess skills and achievements is important in any academic discipline for a variety of reasons (hiring, promotions, grants, collaborations, attention), and it’s generally good to have more than one heuristic for doing that. (We don’t want to rely solely on, say, inherited institutional prestige.)
On x.com, Wes Pegden, a mathematician at Carnegie Mellon, suggests that “deep talks” could be part of “a new system for how we identify ‘awesomeness’ in math” (h/t Henry Shevlin). What is a deep talk?
This is an extended format talk given on a paper (regardless of authorship) accompanied by the claim that the presenter is prepared to reconstruct any desired detail of paper’s proof on the spot, unaided. For example, currently there is a document that contains the solution to the Navier-Stokes problem. No person currently could give a “Deep Talk” on this paper. But certainly, I expect it is within human capability to do so. Someone can be the first! So impressive!
A mathematician would have a repertoire of Deep Talks they currently offer; departments could invite speakers offering talks of new results of interest (sometimes for longer “Deep Talks”, with the detail-probing component, sometimes normal seminar talks). What this system offers is a way to measure technical excellence—impressiveness—in our field. (The present discussion is not about the value to society about having mathematics as an academic field, which I strongly believe in but which is a separate topic).
Pegden adds, “Having such a measure is vital to having a thriving academic discipline. In particular, we need to have a way of measuring excellence in a way roughly aligned with what we recognize as mathematical capabilities.” If we replaced “mathematical” with “philosophical” in that statement (with a suitably pluralistic understanding of what counts as “philosophical capabilities”), I think most philosophers would endorse it. But I’m not sure that they’d agree that “deep talks” would do the trick. What would?
At the moment, to my knowledge, AIs are not yet producing excellent philosophical work, at least not in the form of articles or books. (And it may turn out that articles and books are not the best formats for showcasing the philosophical capabilities of AI. I suspect that complex, customizable dynamic inference mapping will be among their distinctive excellences, and the best format for that may be a tool or application, not an article or book.) Still, many people believe AIs eventually will produce excellent philosophical work. If they do, what then should be the currency of achievement in human philosophy?
Yeah but you could just get fed what to say in a Deep Talk in a wireless mic or displayed on smart glasses where the source is just an LLM feeding this to you. The deep talk would need to occur in a Faraday Cage.