![]() This first sounded like a description of Patreon, but what's he talking about is something like a people-run Patreon that has all the bells and whistles of recommendation algorithms, reviews, etc., not just a simple way to give money directly to individuals. It's time for the latter to move on to where they are deeply appreciated, fairly paid, and really belong: among their true fans. In today's new world of slick, practically cost-free LLMs, even the pittance of royalties will no longer be on offer to most creators. That's unlike today, where many writers are little more than hired labourers churning out work for the larger publishing houses to exploit. But for that to happen publishers must accept that they serve creators. There's a place for publishers (and literary magazines) in this world, helping writers connect with their readers, and turning writing that fans support into publications offered in a variety of formats, both digital and physical. They understand that LLMs may be able to produce at an ever-cheaper cost, but that humans can't. They are happy to support the future work of traditional creators by paying a decent price for material. True fans don't care if LLMs can churn out pale imitations of their favourite creators for almost zero cost. True fans are not interested in the flood of AI-generated material: they want authenticity from the writers they know and whose works they love. The true fans approach has been discussed here many times in other contexts, and once more reveals itself as resilient in the face of change brought about by rapidly-advancing digital technologies. The real solution is to move to an entirely different business model, which is based on the unique connection between human creators and their fans. If anything, it will only cause LLMs to become better and to produce material even faster in an attempt to fool or simply overwhelm the vetting AIs. That will lead to an expensive arms race between competing AI software, with unsatisfactory results for publishers and creators. That is, to employ automated vetting systems to weed out the obvious rubbish. One obvious approach is to try to use AI against AI. ![]() The fact that much of it is poorly written makes things worse, because it becomes harder to find the good stuff ![]() The key point is that large language models (LLMs) are able to generate huge quantities of material. Exactly how is spelled out in this great post by Suw Charman-Anderson on her Word Count blog. More specifically, these systems, which can create quickly and cheaply written material on any topic and in any style, are likely to threaten the publishing industry in profound ways. Walled Culture has written several times about the major impact that generative AI will have on the copyright landscape. ![]()
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