Not only can AI write in the style of famous poets, but it can also improve on their work, according to this story.
Researchers at the University of Pittsburg asked ChatGPT-3.5 to create poems that would appear to have come from writers like Chaucer, Shakespeare, Dickinson, and Plath. Then, they shuffled the results with actual poems from those artists and asked non-expert readers – i.e. people who didn’t necessarily read poetry much – which ones were written by humans and which ones they liked.
The results weren’t dramatic, but a trend did emerge: They thought the AI poems had been written by people and they preferred them to the real thing. Here is the research abstract.
The deck was (and will always be) stacked against humans when it comes to competing with AI that can train on what artists say and do.
For starters, AI can understand a methodology, style, and tone better than any person by accessing more direct and related data and compiling processes that explicitly provide guidelines that artists only know implicitly and incompletely.
Shakespeare had no “Writing Shakespeare For Dummies” to follow. He couldn’t mimic himself as well as an AI could even if he tried.
This means also that the AI poems in the study didn’t cover new ground in terms of ideas, per se, but rather presented variations on those themes. It’s as if the Walt Whitman’s poetry was the draft for the AI to refine and present. Doing something better isn’t the same thing as doing something different.
Intentionality also played a part in the research, as we can debate what Allen Ginsberg or Dorothea Lasky wanted to communicate in their poems because, well, that’s because metaphors, analogies, nuances, and sometimes outright cognitive dissonance are legit tools of the trade.
Poems can “say” many things and/or say them in ways that aren’t easily grasped, which is probably why many of the test participants weren’t poetry readers.
The AI used in the research had no such complex relationship with its art or audience; in fact, it possessed a bias toward synthesizing and delivering ideas in ways that made them more understandable.
Think translator more than creator.
AI-generated content that appears to be “in the style of” other content is already a fact of life in news and the arts, copyright lawsuits notwithstanding. But this research shows that there’s truly no way to differentiate it from what’s real or, more importantly, that the line between real and unreal is either blurred or no longer exists.
Already, this content is appearing in Internet search and informing not only what people think but the models on which future LLMs train. The job market for poets has gone from utterly horrible to something worse.
The market for those historic poets is also going to change.
I’m just waiting for someone to find a previously unknown Shakespeare play that passes every conceivable litmus test and is accepted as real. New readers will find it easier to read than his other works and it will change how experts understand his evolution as a playwright. While we have and should always reinterpret history, when the basic facts of past events are fluid, we have little to, well, stand on.
While Shakespeare will still “say” things to us from across the ages, we’ll be listening to an AI.
