Can AI Write Authentic Poetry?

From The MIT Press Reader:

“Time — a few centuries here or there — means very little in the world of poems.” There is something reassuring about Mary Oliver’s words. Especially in an era of rapid change, there is comfort to be had in those things that move slowly. But oceans rise and mountains fall; nothing stays the same. Not even the way poetry is made.

The disappearance of the author in 20th-century literary criticism can perhaps be traced back to the surrealist movement and its game of “exquisite corpse.” The surrealists believed that a poem can emerge not only from the unconscious mind of an individual, but from the collective mind of many individuals working in consort — even, or perhaps especially, if each individual has minimal knowledge of what the others are doing. Soon the idea of making art from recycled objects emerged. In the realm of literature, this approach took the form of found poetry.

To create a found poem, one or more people collect bits of text encountered anywhere at all, and with a little editing stitch the pieces together to form a collagelike poem. Examining this generative activity, it may be difficult to identify who if anyone is the “poet” who writes the found poem (or for that matter, to be confident that “writing” is an apt name for the process). Still, even if no one’s consciousness guided the initial creation of the constituent phrases, one or more humans will have exercised their sensitivity and discrimination in selecting the bits to include, and the way these pieces are ordered and linked to form a new whole. The author (or authors) at a minimum must do the work of a careful reader. Can the human be pushed still further into the background, or even out of the picture?

The most radical technological advance of the 20th century might seem to have nothing at all to do with the writing of poetry. If we make a list of the great leaps that led to modern civilization — control of fire, agriculture, the wheel, electricity, and perhaps a few more — the most recent addition is a machine that uses electrons to do computation. The first functioning digital computers were constructed midcentury by Alan Turing and a few others. Over the next not-quite-a-century-yet, computers became enormously faster and more powerful, began to process information in parallel rather than just sequentially, and were linked together into a vast worldwide network known as the internet. Along the way, these devices enabled the creation of artificial versions of a trait previously found only in biological life forms, most notably humans — intelligence.


In a certain sense, poetry may serve as a kind of canary in the coal mine — an early indicator of the extent to which AI promises to challenge humans as artistic creators.

Artificial intelligence (AI) is in the process of changing the world and its societies in ways no one can fully predict. On the hazier side of the present horizon, there may come a tipping point at which AI surpasses the general intelligence of humans. (In various specific domains, notably mathematical calculation, the intersection point was passed decades ago.) Many people anticipate this technological moment, dubbed the Singularity, as a kind of Second Coming — though whether of a savior or of Yeats’s rough beast is less clear. Perhaps by constructing an artificial human, computer scientists will finally realize Mary Shelley’s vision.

Of all the actual and potential consequences of AI, surely the least significant is that AI programs are beginning to write poetry. But that effort happens to be the AI application most relevant to our theme. And in a certain sense, poetry may serve as a kind of canary in the coal mine — an early indicator of the extent to which AI promises (threatens?) to challenge humans as artistic creators. If AI can be a poet, what other previously human-only roles will it slip into?

So, what is the current state of AI and computer-generated poetry? This is a less central question than might be supposed. Especially in this time of rapid AI advances, the current state of the artificial poetic arts is merely a transitory benchmark. We need to set aside the old stereotype that computer programs simply follow fixed rules and do what humans have programmed them to do, and so lack any capacity for creativity. Computer programs can now learn from enormous sets of data using methods called deep learning. What the programs learn, and how they will behave after learning, is very difficult (perhaps impossible) to predict in advance. The question has arisen (semiseriously) whether computer programs ought to be listed as coauthors of scientific papers reporting discoveries to which they contributed. There is no doubt that some forms of creativity are within the reach, and indeed the grasp, of computer programs.

But what about poetry? To evaluate computer-generated poetry, let’s pause to remind ourselves what makes a text work as a poem. A successful poem combines compelling content (what Coleridge called “good sense”) with aesthetically pleasing wordplay (metaphor and other varieties of symbolism), coupled with the various types of sound similarities and constraints of form.

In broad strokes, an automated approach to constructing poems can operate using a generate-then-select method. First, lots of candidate texts are produced, out of which some (a very few, or just one) are then selected as winners worth keeping. Roughly, computer programs can be very prolific in generating, but (to date) have proved less capable at selecting. At the risk of caricature, the computer poet can be likened to the proverbial monkey at the typewriter, pounding out reams of garbage within which the occasional Shakespearean sonnet might be found — with the key difference that the computer operates far more rapidly than any monkey (or human) could. To be fair, the program’s search can be made much less random than the monkey’s typing. Current computer poetry programs usually bring in one or more humans to help in selecting poetic gems embedded in vast quantities of computer-generated ore. An important question, of course, is whether an authentic creator requires some ability to evaluate their own creations. Perhaps, as Oscar Wilde argued, there is a sense in which an artist must act as their own critic — or not be a true artist at all.

One use of computers is simply to provide a platform for human generation and selection. The internet makes it easy for large groups of people to collaborate on projects. The kind of collective poetry writing encouraged by the surrealists has evolved into crowdsourcing websites that allow anyone to edit an emerging collective poem. Each contributor gets to play a bit part as author/editor. No doubt some people enjoy participating in the creation of poems by crowdsourcing. It’s less clear whether Sylvia Plath would have associated this activity with “the most ingrown and intense of the creative arts.”

Link to the rest at The MIT Press Reader

PG Postscript – Trigger Warning – Poetry Snob Below

PG harbors substantial doubts that more than 0.1% of all computer engineers know anything about decent poetry. Hint: It’s way more than meter and rhyme.

Because I could not stop for Death, The Waste Land, and The Road Not Taken are much, much more than anything a typical computer engineer (at least in PG’s experience) or an AI is likely to create. And, yes, PG has known and worked with a lot of computer engineers, including some brilliant ones, and appreciates what a talented computer engineer is capable of creating in her/his world.

However, brilliance as a computer engineer does not necessarily transfer to brilliance in understanding poetry and how to create good poetry.