I really don't mind text filtered through an LLM per se. But I prefer high signal-to-token so to speak. The way humans talk and write means that the seemingly extraneous text they add often provides an interesting insight into the thought patterns of the person, and therefore mistakes or even pointless monologues can be interesting.

This is not always true. Once there was an online reaction to short content that made people treat "long-form" content as desirable entirely due to its length. I rather like reading books and the New Yorker's fiction section when I still subscribed, but much of this "long-form" content was token-expansion of a formulaic nature which I did not enjoy. LLMs have mastered this kind of long-form token-expansion.

This is assuming people are using an LLM in good faith, obviously. One day, perhaps LLMs will learn to express what someone is saying in an elegant way that is enjoyable for people like me to read. But even then, I will have the difficulty of distinguishing whether this is a human speaking through an LLM in good faith or a human who has set up a machine that is set up to mimic a human.

The latter is undesirable to me because I have access to the best such machines at a remarkably low cost. Were I to desire a conversation with an LLM, it is trivial for me to find one. I'm not coming here for that[0].

A sufficiently insightful LLM which prompts my thinking in certain ways wouldn't be unwelcome to me, I suppose. I have a couple of my friends for whom I still go on Twitter to read what they say even after I have stopped using the site routinely. If I found out the posts were entirely an LLM I think I would still read them simply because I find the posts useful and with sufficiently high signal-to-token.

0: Certainly, if every place only spoke about things I was interested in and never in things I was not interested in, I wouldn't need separation of interest spaces at all. But the variation of interest vectors for different humans has made this impossible.