Major AI conference flooded with peer reviews written by AI

Hi Max! Thank you for updating my mental model of AI detectors.

I was with total certainty under the impression that detecting AI-written text to be an impossible-to-solve problem. I think that's because it's just so deceptively intuitive to believe that "for every detector, there'll just be a better LLM and it'll never stop."

I had recently published a macOS app called Pudding to help humans prove they wrote a text mainly under the assumption that this problem can't be solved with measurable certainty and traditional methods.

Now I'm of course a bit sad that the problem (and hence my solution) can be solved much more directly. But, hey, I fell in love with the problem, so I'm super impressed with what y'all are accomplishing at and with Pangram!

Formally? Sure. In the current zeitgeist it’s more than enough to start pointing fingers around, etc.

Everything has always been "shit"...

Things might be shit in interesting and scary new ways, but there is no such thing as "the good ole days". Our mind wants to believe that things could go back to "how they used to be", "when it was better" but it's a fantasy.

It's an inability to face the cognitive dissonance and accept things as they are -- which is different than what we wanted! Boo hoo.

We all do this constantly everyday, some more than others :)

That said, humans are quite good at getting by even when things are shit. We've been doing it for untold eons.

Perhaps the only thing more impressive is how good we are at complaining about it all! Heh.

> spending time to carefully and deeply review a paper because they care and they feel on principal that’s the right thing to do

Generally agree, although several parts of that issue.

One of the first was covered by a paper back in 2023 that speaks to the issue about maximum extraction mode. [1] Fairness, honesty, and loyalty are usually rewarded with exploitation. If you spend time to carefully and deeply review the paper, then that ironically marks you as someone that can be exploited. You're implicitly marked as someone who will make personal sacrifices for the academic community and allow even more awful behavior to be piled on top of you. Unless they're caught with something especially egregious, the people that don't, get promoted, spend less time on reviews, and get further rewards.

[1] https://www.sciencedirect.com/science/article/abs/pii/S00221...

The academic community has talked about this a bunch for years. Editors / reviewers that don't paid, or get minimal payment, and sacrifice large amounts of their personal time effectively volunteering, while authors pay $1000's for each paper submitted, and then journals charge $10,000's for each subscription. It's been talked about for decades, and yet in all that time, very little has actually occurred to change the situation.

Another part on top of the "deeply reviewing papers" is that the sheer volume has massively increased (which has been an issue in a bunch of industries, sci-fi compilation Clarkesworld broke for quite a while in 2023 for similar reasons [2]). In the land of "type a sentence, and get a free academic paper" the extremely prolific are pouring out a paper a month, sometimes greater amounts. In areas like clinical medicine, hyper-prolific publishing has hit 70+ papers a year rates. [3] ~1.5 papers a week. Every few days somebody cranks out yet another paper that needs to be reviewed. In the article linked, one author had 140 articles to a single journal alone. Almost 3 times a week, all year long, you've got a paper claiming research worthy of publishing you need to review.

[2] https://neil-clarke.com/how-ai-submissions-have-changed-our-...

[3] https://www.sciencedirect.com/science/article/pii/S175115772...

One that I have less direct, citeable proof for, yet am rather suspicious of, is that theft has also dramatically increased with a huge surge in invasive monitoring and snooping. If my TV changes what I'm watching, and what's recommended, because I typed a text message to somebody, it seems likely that a lot of academia is also dealing with massive intellectual theft issues. This then heavily prioritizes pouring out material as quickly as possible, with as little effort as possible, to get the equivalent of first post and maximal posts, before it can be scraped, exfiltrated, and published by somebody else.

Finally, a lot of the reward and incentive has become metric chasing. Publish or Perish [4] and the Replication Crisis [5] are relatively well known ideas. Citation is a proxy of the impact of a paper, tenure and advancement is heavily related to quantity of publications and citations, and researchers would prefer to be cited more. And weirdly, if it does not work, and it's junk work, in a theme with the above, then it has been suggested nonreplicable publications are cited more than replicable ones [6]. In the linked paper, the view is that when "interesting" findings are published, they get more views, more media, more citations, and lower review standards get applied. And afterward there's very little social punishment for proving the results are false and not replicable (or reward for those illustrating lack of reproducability). Notably, the paper actually got a counterpoint stating that in psychology at least, lack of replication eventually predicts citation decline [7] (cited by 10), while the original actually got its authors ~250 citations, and a bunch of media mentions.

[4] https://en.wikipedia.org/wiki/Publish_or_perish

[5] https://en.wikipedia.org/wiki/Replication_crisis

[6] https://www.science.org/doi/10.1126/sciadv.abd1705

[7] https://www.pnas.org/doi/10.1073/pnas.2304862120