Nicholas Polson has authored 258 academic papers in 2026 (so far)(statmodeling.stat.columbia.edu) |
Nicholas Polson has authored 258 academic papers in 2026 (so far)(statmodeling.stat.columbia.edu) |
If one were inclined, they could shorten the title to "AI Synthesis Across Economics, Psychology, Biology, Philosophy, Game Theory, and Spiritual Tradition." Maybe that's an Easter egg.
AI submissions, soon AI reviewers, and shortly after only AI readers.
The guy's name is "nosloP" spelled backwards. Maybe spelled normally it's supposed to signify the opposite.
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It isn't even partially human written, it's just an LLM's output.
I mean it's everywhere now. I complained already at my workplace multiple times, we get huge Claude generated documents, which people then ask Claude to summarize. I don't mind some of it in principle but people are too lazy now to input all the details so you get a bunch of fantasies that were explicitly ruled out already. It's tiring.
How do i know? Because i doubt "Access&Identity will help us push forward the productivity of all collaborators" was what the team responsible for the prompt wanted to say.
For some weird reason in the last few years people forgot the differences and now any PDF is an "academic paper" [3]. (I'd be more annoyed, if the internal system of the university also forgot the difference. I'm afraid to ask.)
[1] Whatever "serious" means, that's a huge can of worms.
[2] They get an doi and a version number in case of a change.
[3] A few years ago they were call "whitepapers".
Source: https://statmodeling.stat.columbia.edu/2026/08/27/258/#comme...
You add up all the claimed activities and then realize it’s more hours than are in a day so someone’s lying.
I don’t see how this author can claim that these papers didn’t “…suddenly materialize from a magical “chatbot” in 2026” when it’s obvious that 1-2 people are not producing 258 papers that are tens of pages each in 9 months with any sort of academic rigor.
Perhaps this will help bring more scrutiny to the metric of publishing quantity not being as valuable as it has been treated.
Can’t imagine the utter garbage that Claude will produce when you give it a simple prompt and let it write thousand of pages.
Kind of makes me wonder about all that AGI talk if these models can’t even the work of a good PhD or postdoctoral student.
What a disgusting, tasteless joke.
(For instance, 58 pages, 80 pages ... I don't think of these as normal academic length if this is the main body content ...)
[1] https://docs.oracle.com/javase/specs/jls/se17/html/index.htm...
The Everest effect.
George Mallory: "The first question you will ask, and the one I have to answer is, 'What's the point of climbing Mount Everest?' And my answer should be, 'It's no use.' There is not the slightest prospect of any gain. Oh, maybe we can learn a little about the behavior of the human body at height, and medicine can change our observations for aviation purposes. But nothing else could come of it. We will not bring back a little gold or silver or gemstones or coal or iron. We will not find soil or earth that we can grow crops that produce food. There is no point. So if you can't understand that there's something in humans that responds to the challenges of this mountain and goes to meet those challenges, then the struggle that ensues is a struggle from life itself upwards, and you won't see why we're leaving. What we get from this adventure is just joy. We don't live to eat and make money. We eat and make money to enjoy life. That is the meaning of life and the purpose of living."
Why generate all of these papers? Because, for the first time, he can.
Doesn't have to be for the money or fame or potential for speaking engagements. It could simply be that he wants to test the limits of what's possible.
0. https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=170...
1. https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=228...
2. https://www.chicagobooth.edu/faculty/directory/p/nicholas-po...
it was right in front of you :)
Sin: A Slop Colon!
If the papers were of a uniformly high standard then I might not have a problem with it.
If they are hoping some of them are good and the review process will filter out the bad then it seems like they are not doing research, they are writing hypotheses and at pushing the work of testing them onto the reviewers.
I could also see that being done to make some sort of statement about the review process, but it's not clear if that is their goal.
He's wasting people's time, which is already the resource that many people lack any to spare. I'm not sure if he realises this part.
Oh also at least 40% generated peer-reviews are contributing to this statistic.
For condensed knowledge on highly specific topics (i.e. more specific than is economical in book form) I often know nothing better.
Most recently I did sort of a self-taught crash course in ground-penetrating radar and applications for an archeological endeavour I write software for, and a number of papers have been really invaluable.
Polson is just pushing the knob to 11 because it's louder.
We've been in the dark ages of science for so many decades...
He was supposed to present a topic he learned about at the conference. Instead, he gave a cheeky talk which introduced the very concept of written language to the audience, as if we had never heard of it. Starting from the history of writing on tablets and so on, and ending in practical advice like, "when words are written down, you don't have to remember what they were exactly; you can just read the words again." I loved the chutzpah and could barely hold myself from chortling out loudly at some of his slides.
There has always been bad writing, but historically it has been easy enough to filter the garbage out. Now we get garbage that looks so much like real thoughts that it's hard to tell. This is not a positive development. Separating the wheat from the chaff is extra work, and the overhead is a burden on humanity. I suspect that this is a burden that almost nobody actually wants, but we're getting it anyway.
Your intelligence and competencey are going to be 1:1 correlated to the quality and quantity of tokens a billionaire gives you access too (local, sure, they control the hardware markets as well).
Keep excercising your writing and reading muscles because it will definatley set you apart from the captive masses in the future.
I really don't like AI for document writing as a whole, especially within organizations. Code can be a form of communication, but for the most part it's an engineered thing that can be re-run, tested, verified and so on. But documents drive decision-making, and decision making is often one-time. Decisions should be studied and understood, and depriving authors of much of both is not having any good effects.
The fact that most teachers refuse to do in-person oral exams has always been due to laziness, incompetence, and the reality of the economics of dealing with classroom sizes where 30 is considered small.
If you only knew.
That is not realistic, but I suppose where things are heading is that you have some indicator of the strength of evidence -- see Fig. 13 in the following insightful take:
https://news.ycombinator.com/item?id=49407226
Though, "strength" should probably be "reliability" and "validity", and I suppose those indicators are more for picking signals from the noise; i.e., what is even worth clicking and reading. That would be increasingly valuable already today due to the volume (and, yes, slop and other related stuff).
And to expand on this, it's not realistic because science is not armchair philosophy. You have to go out and measure the world.
Sometimes, through force of will, a person can think deeply about a problem and come up with beautiful theories that explain our measurements. Many scientists had careers like this, probably most famously, Einstein. But it's worth noting that Einstein also got a lot wrong! [1]
Even if we somehow give an LLM the ability to go out and measure things, I seriously doubt that the role of humans in science is done. There's a big difference between "an explanation" and "a good explanation." Ask any physicist. There's a surprising amount of aesthetics involved. Good theories are consistent with the evidence, but it's more than that-- there's a great deal of "taste" involved. And there's a good reason for that. For any real problem, there are effectively an infinite number of alternative hypotheses. From a "theory of science" standpoint, this should cause scientists nightmares, but it doesn't. Because by the time you are a practicing scientist, you've developed a feel for what constitutes a satisfying explanation. If you spend time with scientists, especially in the "hallway track" at a conference, "taste" is a frequent topic of conversation!
[1] https://en.wikipedia.org/wiki/Einstein%27s_unsuccessful_inve...
People in the early days used to often whine that LLMs just regurgitate text snippets (unfounded of course), but I think the way we currently train and RLHF them actually seems to largely make them unable to reproduce the knowledge they have been trained on, since they seem to just always want to please the mean with their output. I'm oversimplifying the mechanisms, but you get my drift.
I work full time on "lab in the loop" AI, so I'm pretty familiar with the need for real-world experiments. I am not proposing a fully autonomous scientist that could read an arbitrary paper and emit whether it's universally true without some verification method.
Also, to your statement: " Because by the time you are a practicing scientist, you've developed a feel for what constitutes a satisfying explanation."
I'm a practicing scientist (well, ex-scientist) and it seems like most "satisfying explanations" end up being wrong or incomplete simply because they seem so satisfying.
What's the difference? How do you find real mistakes without a model? Either you have a trusted mathematical model (in which case you already have a complete explanation) or you have to compare it against the ultimate oracle: the world. Or are you proposing something like "let's use an LLM to convert this hand-wavy English paper into a formal proof and then check it for logical fallacies?" In which case, fine, that would be useful, but that's not exactly the same thing (and also not as important) as saying that a paper advances a bad explanation. Just that the explanation is flawed in some way.