It seems there is a lot of this kind of AI risk. I'm trying to find the right label for it. Something that was a common good, that worked at a human scale, is now made unviable because automation has pushed it beyond what it can handle and still be useful.
several authors including the creator of arxiv, Paul Ginsparg, foretell a future in which we "increasingly rely on status markers such as author
pedigree and institutional affiliation as signals of quality, ironically
counteracting the democratizing effects of LLMs on scientific production."
I think this is a very plausible outcome of a flood of preprints. Because there's only so much time in a day and are we going to spend it on papers by less established people who we do not trust? It's a pity. If the science is good what does it matter who produced it.
Some government should fund a preprint server where the submissions are screened by open weight models. Ultimately AI prescreening is far more scalable than human prescreening.
Thus biasing submissions' language and content towards those most palatable to those open-weight models, creating further incentives to generate articles wholesale with them, and incentives against publishing null findings
Alternatively perhaps robust AI powered review pipelines eventually come into being. At that point the system as a whole would resemble a semi-supervised GAN setup optimizing for scientific paper quality. It might end up producing good results. (An absolute nightmare for the year or two leading up to that though.)
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<a href="https://arxiv.org/abs/2601.13187" rel="nofollow">https://arxiv.org/abs/2601.13187
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