Allison Parish


Allison Parrish, programmer, poet, and educator at NYU’s Interactive Telecommunications Program, discusses her latest project on computer-generated poetry. Her book, “Articulations,” explores poetic similarity using a corpus from Project Gutenberg and the CMU Pronouncing Dictionary to model phonetic resemblances. Parrish’s work involves constructing poetry by linking lines that sound alike, creating a unique phonetic cohesion. She emphasizes that her approach to poetry involves using computational tools not just to mimic human creation but to extend artistic capabilities and explore new forms of expression. Parish critiques the notion of AI replacing human creativity, arguing instead for a view of AI as an enhancement that brings new dimensions to poetic exploration. She highlights the influence of randomness and procedural generation in art, referencing historical and contemporary examples to underline that art made with computational methods still reflects the artist’s intent and personality.

This presentation was part of the symposium ARTIFICIAL IMAGINATION which unites innovative artists engaged with emerging technologies. This focused on exploring and sharing their individual practices, experiences, and insights related to algorithms, artificial intelligence, and machine learning. It served as a platform for an enriching exchange of ideas between the artists and the audience, aiming to contribute a distinctive artistic viewpoint to the ongoing discussions about our evolving relationships with machine collaborators. Each session, including this one, highlighted how these technologies are being integrated and reflected in contemporary artistic processes, encouraging a broader understanding and appreciation of the creative potential of new digital tools.

Allison Parrish is a computer programmer, poet, and game designer whose teaching and practice address the unusual phenomena that blossom when language and computers meet. She is an Assistant Arts Professor at NYU’s Interactive Telecommunications Program.

According to Ars Technica, Allison’s work “delight[s] everyone.” She was named “Best Maker of Poetry Bots” by the Village Voice in 2016, and her zine of computer-generated poems called “Compasses” received an honorary mention in the 2021 Prix Ars Electronica. Allison is the co-creator of the board game Rewordable (Clarkson Potter, 2017) and author of several books, including @Everyword: The Book (Instar, 2015) and Articulations (Counterpath, 2018). Her poetry has recently appeared in BOMB Magazine and Strange Horizons.

Allison is originally from West Bountiful, Utah and currently lives in Brooklyn.

It’s all based around this idea of how we can specifically create poetry that tricks people into thinking that it was written by human beings in a typical way, like even redefining the difference between human and machine authorship, which I don’t actually think exists.

The purpose of art is to impart a sensation, and part sensation to an object is something seen rather than merely recognized.


Allison Parish

My most recent project that sort of illustrates the kind of work that I do is this book of poetry that was just released by counterparts just last month. It’s called Articulations, and I included the sample of the poem here. And this book started out as an exploration of the idea of similarity and poetry actually having been discussed, discuss this project and realize that there’s actually a lot of similarities between this project and hers.


I started out with the idea of similarity in poetry and how similarity, whether phonetic, syntactic or semantic, contributes to our sense of poetic ness and cohesion in a text. The poetry is constructed from a corpus of several million lines of poetry that I extracted from Project Gutenberg, which is a database of thousands of texts that are in the public domain.


I used a phonetic dictionary called the CMU Pronouncing Dictionary to create a computational model of phonetic similarity that predicted a vector or like a sequence of numbers, like a point in space for each line of poetry. Then the selectors have the property where two lines that sounded similar to each other are closer. The vectors are more similar if the lines of poetry sound similar to each other.


The composition itself is accomplished by doing a random walk through that space. Essentially, it starts with the randomly selected line of poetry and then finds a line of poetry that is most phonetically similar to that and then adds that to the output and then finds the line of poetry that’s similar to that and adds it to the output and so forth until it’s produced like, you know, a book of of poetry.

Poetry by Allison Parish

Allison Parish

It was the hour of prayers in the hour of parting, hour of parting hour of meeting, hour of parting. This with power avenging his towering wings, his power enhancing and his power, his power. Thus the blithe powers about the flowers chirp about the flowers A power of butterfly must be with the purple flower Might be the purple flowers for the petals of our purple flowers where the purple aster flowered Here is the purple aster of the purple aster there’s lives a purpose stern a sterner purpose fills turns up so pert and funny of motor trucks and vans, and after kissed a stone an ode after Easter an iron laughter stirred a wanderer turn a wanderer

return a wanderer Stay a wanderer near been a wanderer I wander away and then I wander away And thence we shall we wander away. And then we would wander away away. Oh, why? And for what are we waiting or why? And for what are we waiting? Why then? And for what are we waiting?

Finding inspiration through Ted Bergen

Allison Parish

I’ve been rereading the Ted Bergen’s book, The Sonnets, which is this really amazing book of poems composed with a cut up process similar to the one used by Burroughs and Brian Geist. And this is maybe my favorite book of poetry of all time. I should have included an excerpt of it here, but I’m the that book is from 1964.



Barragan was sort of working in the same era as Cage and the Fluxus and Fluxus and all of the stuff happening in that scene. And this is a quote from the introduction to the book. And Alice Notley wrote this introduction, and I’m just I’m just going to read this for Cage. The application of a method results in a work or a performance that’s serene and free or rather liberated, as Cage is a serious Zen Buddhist, and his work is permeated with Buddhist thought.



For Ted, it more results in one that’s deeply true an allegory method used with seriousness and respect puts one in touch with hidden powers and truths within oneself and becomes revelatory, hopefully in a way that might be relevant to anyone. Yeah. By giving oneself up to chance, an artist does not lose his or her originality. As Marcel Duchamp said, your chance is not the same as mine, just as your throw of the dice will rarely be the same as mine, and that was really interesting to me.



Next slide, please. And so I sort of I take it as axiomatic that correct procedures are a kind of computational procedure, even if Ted Berrigan wasn’t working with a computer, it’s still essentially a computational process to take a text and cut it up and randomly arrange its components or other techniques for rearranging a text. But that formulation that that it was enabling Ted Berrigan to do something that was more true, that really struck me.

Can computers help us write poetry?

Allison Parish

The question in my research is; can computers help us write poetry? That is true and true again, in that sense, not of like being the opposite of false being factual, but instead poetry that is that is firm and that’s fundamental. And that expresses something that that is true. And of course, most people don’t think of computer generated poetry in these terms. Right. Usually the idea of computer generated poetry is framed like this, where that that narrative of the labour, of artificial intelligence, where any any A.I. task is essentially just trying to take over the labour of a person. And the idea that human expression will be superseded by cold, robotic precision eventually, and we just have to go along with it. We’re helpless to resist. Right. And that relies on this idea of that you can formulate the composition of poetry as a task that boils down to just like a list of instructions which you can with research and be reproduced with perfect fidelity. And if you look at a lot of the like, a lot of the academic research is happening in artificial intelligence and computational creativity right now. It’s all based around this idea of how can we specifically create poetry that tricks people into thinking that it was written by by human beings in a typical way, like even redefining the difference between human and machine authorship, which I don’t actually think exists. And hopefully you’ll see that by the time I’m finished speaking. But that idea that the purpose of using artificial intelligence in art is to recreate with as much fidelity as possible things that are produced by humans without eight of those techniques, I think is like extremely boring. It’s the worst possible thing to do with this technology. Next slide means when I’m making poetry with a computer, I’m actually thinking about this line of argumentation that was, you know, it’s been articulated by many people in many different ways. But Viktor Shklovsky in 1916, in that wonderful old saw, which I can get to somehow in my notes, art is device, he says. The purpose of art is to impart a sensation, and part sensation to an object is something seen rather than merely recognized. The device of art is the device of estrangement of things and the device of facilitated form enhancing the difficulty and duration of perception. So the perceptual process in art is an end in itself and should be prolonged.

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