Calvino’s creative writing machine

In contrast to Kenneth Goldsmith, champion of machine-aided uncreative writing, Italo Calvino entertains the idea that machines could learn to write creatively:

I am thinking of a writing machine that would bring to the page all those things that we are accustomed to consider as the most jealously guarded attributes of our psychological life, of our daily experience, our unpredictable changes of mood and inner elations, despairs and moments of illumination. What are these if not so many linguistic “fields,” for which we might well succeed in establishing the vocabulary, grammar, syntax, and properties of permutation?

But one consequence is common in Goldsmith’s and Calvino’s visions: the death of the traditional author. Calvino again:

Literature as I knew it was a constant series of attempts to make one word stay put after another by following certain definite rules; or, more often, rules that were neither definite nor definable, but that might be extracted from a series of examples, or rules made up for the occasion—that is to say, derived from the rules followed by other writers. […] A writing machine that has been fed an instruction appropriate to the case could also devise an exact and unmistakable “personality” of an author, or else it could be adjusted in such a way as to evolve or change “personality” with each work it composes. Writers, as they have always been up to now, are already writing machines; or at least they are when things are going well.

Calvino is content with his thought experiment: he says that “it would not be worth the trouble of constructing such a complicated machine” as he describes. But one wonders whether artificial intelligence might progress to such a place. We are already trying to write under the influence of data. People decry that as forcing the writer into a well-traveled rut, but add a little AI and writing might become more adventurous:

…given that developments in cybernetics lean toward machines capable of learning, of changing their own programs, of developing their own sensibilities and their own needs, nothing prevents us from foreseeing a literature machine that at a certain point feels unsatisfied with its own traditionalism and starts to propose new ways of writing, turning its own codes completely upside down.

Calvino perhaps understates the difficultly in getting machines to ‘develop their own sensibilities’ (he was writing in 1967) but still—imagine what might be added to Goldsmith’s vision of fashioning new art from existing literary material if that material began to have even a rudimentary mind of its own, if it danced with us a little bit, like sculpting with living clay.

More on art machines

Kenneth Goldsmith thinks that when machines begin writing, we will be promoted to editors and curators. Peter Wayner thinks we’ll just be out of a job:

These debates about the bounds of fair use will always be important, but they obscure a very unfair dynamic that is squeezing artists — and turning the web into a battleground between humans and machines. The trouble is that in many cases today, there’s no human artist, writer, or editor creating what we see on the web. Some algorithm assembled the photos and it’s enjoying a nice little loophole. The machines sail on past the rules about copyright because the law lets those companies blame any infringement on the chaos of the internet. It’s a system that’s tilting the tables against any of the human artists who write, edit, or illustrate.

[…]

The automated machines have me and the photographers beat. Aggregators — whether listmakers, search engines, online curation boards, content farms, and other sites — can scrape them from the web and claim that posting these images is fair use. (BuzzFeed claims that what it does is “transformative,” allowing them to call their lists a new creation.)

We already know these companies make a profit on the ads. But what we don’t know is that the algorithms they use are acting less and less like a card catalog for the web and more and more like an author. In other words, the machine isn’t just a dumb hunk of silicon: It’s a living creator. It’s less like a dull machine and more like a fully functional, content-producing Terminator.

Looking at what these machine-authors are doing, you might call it remixing or your might call it plagiarism. I guess it depends on what is being fed into the machine and perhaps how close the human oversight is. But it would be a mistake to think that remixing or plagiarizing is all machines are good for. John Brownlee describes the role of computers in avant garde music composition:

A grad student pursuing his doctorate in composition at Harvard University, Oberholtzer applies the techniques of electronic music to compose works meant to be played by human orchestras. Instead of just stringing note after note, Oberholtzer uses a series of custom tools to translate a nebulous musical intention into a human-readable score. He does this by trying to define in words what the finished piece will sound like.

[…]

“When I want to capture some new music concept or idea, I’ll usually write a tool first, then think about it a lot and work it into a piece,” says Oberholtzer. “These tools are kind of like meta-instruments, and I can even write tools on top of tools, giving me a wider palette.”

For Oberholtzer, this seems like a perfectly natural way to write music. “All art is a kind of curatorship. You work through all these possibilities mentally, and then in the end, you try to reproduce the one you’ve decided upon. There’s no difference for me. My computer isn’t writing my music for me. It’s just handling the version control.”

Peter Wayner in the first quote above saw an Intellectual Property Terminator because Google et al were crawling and remixing the web without benefiting the original artist. But this composer demonstrates that involving machines with art isn’t always about an insidious corporate IP grab. Imagine what could be accomplished if the idea of machines collaborating in art were brought to a larger scale while still remaining un-corporate, with the direct oversight of artists?

It’s already happening. The documentary CLOUDS (not released yet, preview below) takes a look at artists who are using code to make art, and in some cases sharing code in order to create stuff they couldn’t create working in isolation.

Imagine that. Invent a cool new art tool? Put it on GitHub and watch your friends make it better.

As transformative as people talk about the internet being for artists/creatives, I feel like we’re at the beginning. Most of the energy has been poured into new distribution mechanisms for existing forms: ebooks with faux page-turn animations, videos and pictures that strive for a lean-back theater or museum experience. We have barely begun to scratch the surface of the unique opportunities enabled by computing and networks.

Word machines

I’ve been reading Uncreative Writing by writer and UbuWeb founder Kenneth Goldsmith, who thinks that writing is ripe for a revolution. He thinks of language not solely as semantic content but also as raw material — material that can be transformed by computers, or written from scratch by computers, sometimes even meant to be read only by other computers. In effect, writers get abstracted (promoted?) a level, from generating language to managing its creation and manipulation.

It has me wondering what this would mean for stories. Goldsmith’s narrative examples involve the appropriation of existing narrative material. What would it look like to not make up a story but to manage a machine generating a story?

The only example I’ve found is A Ship Adrift. Perfectly, the credits say that “a ship adrift is a thing “by” james bridle.” Bridle explains on his blog that he began by creating a system to read information from a weather station:

A Ship Adrift takes the data from that weather station and applies it to an imaginary airship piloted by a lost, mad AI autopilot. The ship is drifting because the pilot is mad or the pilot is mad because the ship is drifting; it doesn’t really matter.

If the wind whips eastwards across the roof of the Southbank centre at 5mph, then the Ship Adrift floats five miles to the East. […]

As the Ship drifts, it looks around itself. It doesn’t know where it is, but it is listening. It’s listening out for tweets and foursquare check-ins and posts on dating sites and geotagged Wikipedia articles and it is remembering them and it is trying to make something out of them. It is trying to understand.

The ship is lost, and I don’t know where it’s going. I don’t know what it’s going to learn, but I want to work with it to tell some stories. I want to build a system for cooperating with software and chance.

The result is, to my eye, gibberish. But it’s gibberish on a timeline, written by hundreds of people and amalgamated through a partnership of man and machine. And if you look at the text in the context of the wandering little dot representing the ship, it’s even a little poignant. Perhaps the beginning of something.

Further reading: Nietzsche Family Circus