Today, with modern search and computerized tools, one of the primary heuristics I use for determining which preprints to read is "do I know any of the authors". If I don't know you, your ideas are most likely not worth reading, even if they appear to be about a topic I'm interested in. There are so many papers published every year and so little time to read them properly, and the search tools that exist are not that good. If you don't have an established reputation, your best bet is submitting your work to a relevant journal or conference, where the peer reviewers will usually give you a fair chance.

Google Scholar is a good example of how bad the tools are. Its recommendations are apparently based on things like the papers you publish, the papers you cite, and the papers that cite your work, which sounds superficially reasonable. That worked well enough when I was doing my PhD within the boundaries of an established academic field. But when I started doing more interdisciplinary work, the recommendations quickly turned into garbage. A better recommendation system would understand that there is a field I work in, an upstream field I take ideas from, a downstream field I contribute to, and several fields further downstream that use the work I contributed to.

Would/could you apply this same argument to books?

I feel this is already true of books, the question is will a publisher put it out... books cost money to produce and by comparision to hosting are massive investments.

I wish more self-published books would find a way to hire a copyeditor.

gpt to the rescue?

Actually, yeah. I think it could make a difference. Usually there is some basic spell-check, grammar check stuff already going on, but the kinds of things that would be easily fixed/identified by LLMs could be:

- continuity checking - often moving sections of text around introduces temporal errors - style cleanup - quasi-duplicated text that came from multiple edits or start/stops being merged - fixing vague and unclear passages

But probably what they won't do well in a near terms is provide more critical feedback, such as when to throw away large sections of book, or remove subplots, or where to dive deeper on other topics. I'm sure they can generate general suggestions for this kind of thing though.

What people usually picture for books is things written for profit by the author. That's very different from academic papers.

If you're talking about monographs/etc then that's a different beast.