There were eras in which the work of Christian poets was respected and even lauded. But that was then and this is now. While we still value poetry in the form of songs, most of us pay scant attention to reading or writing poetry. There could be any number of explanations for this, though I am inclined to blame the decline of formal verse (i.e. defined forms of poetry) and the rise of free verse (i.e. neglecting rhyme and meter), much of which is enough to cause the best of us to give up on poetry altogether.
Tim Challies, Poetry of Redemption
I have been trying to will myself back into poetry. I used to consume a lot of poetry. Pretty sure I lost it in my tumultuous twenties. The quote above started my Sunday with lament and awareness that it wasn’t just me seeing poetry’s decline.
And then I read this morning that the rising AIs cannot write poetry. Or do basic arithmatic, which is unsurprisingly interlinked with poetry.
So I decided to try a nonce form and asked ChatGPT to produce a poem with a particular number of stanzas and a set number of stanzas per line. Over and over, it would write a few stanzas with the correct number of lines and then veer off towards the end and produce a much longer stanza. Like it lost count.
The danged robot couldn’t count.
AK Krajewska, Robot without rhyme or rhythm
Some very interesting points follow in the article— which you really should read.
Ted Chiang explained that when large language models (LLMs) are trained, they don’t actually assimilate the underlying principles. Instead, they produce the statistically likely next thing.
These LLMs does actually understand, as they cannot. Well, they can understand, but not truly. Because English doesn’t give us multiple words for understand. In Christian circles, we oft separate head and heart knowledge. These AIs have head knowledge but no heart.
More than that, formal verse is an exercise in applying principles you’ve understood. ChatGPT could produce a statistically likely definition of a sestina based on all the examples of sestina definitions it had come across in its training. To produce a sestina, it would have to have assimilated the principles.
[…]
There’s one more reason why LLMs can’t write formal verse, and this one is a little more obvious, though still, I think, worth mentioning. LLMs are trained exclusively on written text. They do not have the sound of words in their training, as far as I know.
[…]
Formal verse with meter and rhyme relies on the sound of the words. While you can guess what words are statistically likely to rhyme based on their spelling, it’s only saying them out loud that lets you know if you’ve succeeded.
Our language is far more complex than letters combined. Pronunciation is key to writing poetry. Manipulation of pronunciation too.
I wonder what other effects LLMs will have on literature. Might formal verse in English, which has fallen out of favor since the early 20th century, make a comeback as a prestige form, edging out free verse?
And there was the full circle to Tim Challies. Tim noted that the last hundred years have seen a dearth of poetry. But now it may be what separates us from the AI.
Finally, I wonder if, given that LLMs can produce polished but contentless prose corporate speak, will poetry make a comeback as the form for signaling sincerity? Could you imagine getting a notice of layoffs from your very humane VP in the form of sonnet? I’m not sure it would be a better world but it would be interesting.
