Replying to @⁨beep@piefed.world⁩

The #1 thing I can think of is plagiarism.

AI stories are quite literally unoriginal works generated from original mediums and it’s harmful to all authors worldwide.

AI-giarism is still plagiarism.

…uchicago.edu/…/plagiarism-copyright-and-ai

www.theatlantic.com/technology/2026/08/…/688167/

www.sciencedirect.com/…/S1096751625000806

lawreview.uchicago.eduPlagiarism, Copyright, and AI | The University of Chicago Law ReviewCritics of generative AI often describe it as a “plagiarism machine.” They may be right, though not in the sense they mean. With rare exceptions, generative AI doesn’t just copy someone else’s creative expression, producing outputs that infringe copyright. But it does get its ideas from somewhere. And it’s quite bad at identifying the source of those ideas. That means that students (and professors, and lawyers, and journalists) who use AI to produce their work generally aren’t engaged in copyright infringement. But they are often passing someone else’s work off as their own, whether or not they know it. While plagiarism is a problem in academic work generally, AI makes it much worse because authors who use AI may be unknowingly taking the ideas and words of someone else. Disclosing that the authors used AI isn’t a sufficient solution to the problem because the people whose ideas are being used don’t get credit for those ideas. Whether or not a declaration that “AI came up with my ideas

Replying to @⁨beep@piefed.world⁩

Considering you immediately down voted my comment, I think it’s fair to ask: is that a genuinely curious question?

edit: fuck it, I’ve been thinking about this anyway, may as well write it down. A few points:

Firstly, a few decades ago a similar claim about junk food would have been very hard to find evidence for, because research on it’s detrimental effects didn’t gain much momentum until after it was obvious there was a problem. AI will certainly have a similar lag, so it’s unlikely that we’ll have hard evidence of it’s effects (especially in the wild) for years or decades.

That said, I have a few hypotheses for impacts on readers/reading:

  • “quality” in this study is probably fairly highly correlated to “average” - text that reads simply and clearly, because it tries to be as close to cultural norms as possible is much easier to read. That removes barriers to reading, which to some degree makes it more fun to read. But it also makes it less challenging to read. Counterpose this with creative literature that often has a really strong author’s voice that can be a bit challenging initially, but beautiful it you persevere with it. I’m thinking like Ursula Le Guin, or Haruki Murakami.
    • in the longer term, reading a lot of AI writing is likely to lead to a strengthening of the bias towards simple, generic language. In turn this could lead a reduced demand for really creative writing. By analogy, we’ve already seen something similar happen with hollywood films over the last couple of decades - more focus on generic (e.g. Marvel) and rehashed stories.
    • AI use is already leading to more generic, less explorative science - see Hao, Q., Xu, F., Li, Y., & Evans, J. (2026). Artificial intelligence tools expand scientists’ impact but contract science’s focus. Nature, 1–7. doi.org/10.1038/s41586-025-09922-y
  • Because LLM-produced writing inherently produces less diverse content (because it is an averager, with noise, see the Hao reference above), then it’s less likely to produce ideas that challenge the mind, and require the reader to engage critically.
    • LLMs usage is already associated with reduced critical thinking capacity: Gerlich, M. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15(1), Article 1. doi.org/10.3390/soc15010006
  • LLM’s well-known tendency towards “hallucinations” is all fun and games when it’s overt, but more insidiously, more subtle hallucinations happen constantly too, and go undetected. This can end up producing ideas/memes that are subltly wrong and potentially damaging, but get accepted by the reader because the sound pretty close to the truth (especially when you’re lulled into a false sense of security by a voice that sounds VERY MUCH like it knows what it’s talking about).
  • Guardrails are garabage and easily bypassable and have already lead to deaths. While reading doesn’t have the rabbithole effect of using an LLM as a chatbot, it’s still capable of producing horrendous ideas and framing them as positive.
  • I suspect that reading less diverse content also results in a degraded capacity for imagination in general, so it could lead to less good art in the world.
    • Imagination is also necessary for solving major socio-environmental issues, and even for things like planning to prevent terrorism, so this could have broader ramifications in the long run. See Weick, K. E. (2005). Organizing and Failures of Imagination. International Public Management Journal, 8(3), 425–438. doi.org/10.1080/10967490500439883

I feel like a had more points, but that’ll do for now.

Plus obviously all the other GenAI complains - environmental destruction, copyright theft, EEE power grabs, associations with fascism in general

Replying to @⁨beep@piefed.world⁩

It literally addresses that in the linked article.

Speculating on why this might be, Dr Weisberg added: “AI writing tends to be clearer, more direct and easier to process. By contrast, human-written stories, are often more subtle and complex. For example, the AI versions of our stories usually stated their themes explicitly, rather than allowing readers to infer meaning from the characters’ words and actions.

“We hear a lot about the crisis in literacy, shrinking attention spans and the influence of platforms such as TikTok. But I don’t think we can say that our findings in this study can be entirely explained by contemporary media consumption. It’s more that these technologies amplify existing tendencies, rather than creating them.