From ‘Barbies scissoring’ to ‘contorted emotion’: the artists using AI

You type in words – however nonsensical or disjointed – and the algorithm creates a unique image based on your search. This is Dall-E 2, a startlingly advanced, image-generating AI trained on 250 million images, named after the surrealist artist Salvador Dalí and Pixar’s Wall-E.

While use of Dall-E 2 is currently limited to a narrow pool of people, Dall-E mini (or Craiyon) is a free, unrelated version that is open to the public. Drawing on 15m images, Dall-E mini’s algorithm offers a smorgasbord of surreal images, complete with absurd compositions and blurred human forms.

Already, trends have emerged: nuclear explosions, dumpster fires, toilets and giant eyeballs abound. On a dedicated Reddit thread, people delight in the images generated by the free, low-resolution version, which range from amusing (Kim Jong-un lego) to dark (The Last Supper by Salvador Dali), hellish (synchronized swimming in lava) and deeply disturbing (Steve Jobs introducing a guillotine). Like other machine-learning networks, this AI model seems biased in its images of people – who appear, perhaps unsurprisingly, overwhelmingly white and mostly male. (A cursory search for “the Guardian journalist” procured nine wallet-sized images of light-skinned men in suits, 90% of whom wore dark-rimmed glasses.)

OpenAI, the company behind Dall-E 2, acknowledges, however vaguely, that image-generators may “reinforce or exacerbate societal biases”. The policy page says composite images may “contain stereotypes against minority groups”.

The company’s rules claim that the software prohibits the creation of “sexual or political content, or creating images of people without their consent”. But who decides what is political? Isn’t the very definition of “sexual” subjective?

Dall-E is not the first text-to-image AI model, but its sophistication, along with Dall-E mini’s popularity, have given new urgency to questions about the role of AI in artmaking. When Dall-E produces an image, who is the creator? Is it the person who typed in the text, the coders who trained the neural network, the photographers whose images appear in the network – all of the above?

We spoke to four artists working across textiles, photography, installation, video art, and oil painting about harnessing Dall-E’s trove of images – and asked them to provide us with an exclusive example of how they used the tool.

I’m at a break between shows and exploring Dall-E 2. I’ve been playing around with it, trying to break it or to see how far it goes or where the edge is. Some of this stuff you’re playing with online, it could feel like, “oh it’s so infinite” or sentient, but no, it’s not as infinite as my imagination.

I’d been familiar with OpenAI through two projects I worked on – Neural Swamp, on view at Philadelphia Museum of Art, and my first foray into AI with MythiccBeing. I’d like to be able to combine images, like if you had the ability to mate two images and add context, write different scenarios. It’s more surprising to put something not descriptive but more open-ended and let the Dall-E try to figure out what an adjective means. I’m interested in generated imagery in relationship to motion, which I’m sure is coming sooner rather than later. And [the machine learning system] GAN imagery is the average tool; Dall-E is the next step in that direction.

Mostly I’ve been typing in lines – almost poetry, like “writhing in contorted emotion”. I also typed in: “Whenever I do something illogical, inefficient, unproductive, or nonsensical I can just smile at my innate humanity.” I think that’s more interesting than trying to do like “Kanye West as a clown in the middle of Times Square”. I’m more interested in thinking about poetics. That’s what brought me to machine learning in the first place.

It’s cool, the novelty of it. Sometimes I think the images have a ghostliness or remind me, honestly, of drug trip imagery. They look subconscious, not fully rendered.