When Is an AI Image Truly Art?

AI generated images are now seeping into advertising, social media, entertainment, and more, thanks to models like Midjourney and DALL-E. But creating visual art with AI actually dates back decades.

Christiane Paul curates digital art at the Whitney Museum of American Art, in New York City. Last year, Paul curated an exhibit on British artist Harold Cohen and his computer program AARON, the first AI program for art creation. Unlike today’s statistical models, AARON was created in the 1970s as an expert system, emulating the decision-making of a human artist.

IEEE Spectrum spoke with Paul about Cohen’s iconic AI program, digital art curation, and the relationship between art and technology.

How do you curate digital art?

Christiane Paul: Curating digital art is not that different from any other art form. Whether painting or photography or print, we all look at the sophistication of a concept and how it is translated into a medium. So my curatorial choices are not driven by the technology. If you’re a curator of painting, the selection of a work for an exhibition would not be driven by a specific paint or technique for a brush stroke.

In 2001, Harold Cohen produced AARON KCAT as part of his experiments in producing figures with the AI model. Cohen taught the model how to handle overlapping objects in a composition, which he did by having the model fill in objects from the foreground to the background.Whitney Museum of American Art

That being said, of course, there have been shows about pointillism as a specific technique in painting. And, there could be an exhibition focused on AI technologies as an artistic medium. But the general criteria would still be the sophistication of concept and its implementation.

Do you collaborate with engineers as part of your work?

Paul: Yes, of course. Many artists also have a background in engineering, particularly when it comes to the older generation of digital artists. When there weren’t any digital art programs or schools, digital artists often would have a background in engineering or programming. So you work with developers and software engineers, and many artists are programmers or coders themselves—I would say most of the artists I’m working with. They sometimes have to outsource, just due to the amount of work, but most of them are also very deeply in the weeds.

What are the challenges of collecting and preserving digital art?

Paul: For art institutions or collectors, it is important to have standards and best practices for archiving and keeping track of the technologies, because computers and systems change at such a rapid pace. In the ’90s people started paying more attention to implementing conservation approaches, and there are several strategies. One of them is storage and hardware conservation. This is used for pieces that conceptually depend on hardware. And then there is migration, emulation, and re-creation.

There is no silver bullet. One has to look at the individual artwork to see which approach may be the best one. In the Harold Cohen exhibition, for example, we basically re-created one of the earlier pieces from scratch based on Cohen’s notebooks and printed out code that we found, and his son actually recoded that in Python. We reconstructed the original BASIC but then also recoded in Python.

What inspired the Cohen exhibit?

Paul: I had known Harold Cohen for quite some time. We worked together on an exhibition in 2007, and AARON is an iconic work. Everybody studying digital art knows this as one of the fundamental pieces.

We had brought some of his works into the collection of the Whitney Museum, so showcasing that was one point. But I also thought that it would be particularly interesting to revisit the first AI software for art making in the light of current text-to-image models. Their processes are radically different, and authorship and collaboration play out in a very different way.

AARON learned how to generate images of plants, as seen in AARON Gijon from 2007, using rules that Harold Cohen provided about their size and patterns governing their branching and leaf formation.Whitney Museum of American Art

Harold Cohen wrote AARON from scratch. He was completely in charge of building that software, which he evolved across five different languages over his lifetime, so the composition of an image was completely under his control. He moved from evocative forms, to a figurative phase, to a plant-based phase, and then returned to abstraction. Later in life, he taught the software color composition and he also built the drawing devices that would execute AARON’s work. He really considered AARON a collaborator, and AARON encapsulated Cohen’s sensibility and aesthetics.

Today’s AI software is essentially statistically based, and a lot of the authorship and agency happens in the corporate black box. The artist has no control over that, even if artists train and tweak their own models. Artists working with AI are very invested in manipulating the software and working with it, but there always is a component that is created by corporations that they do not have control over.

Can AI-generated images be art?

Paul: Not all visuals created by text-to-image models are art. It’s wonderful that people can use AI to generate images and play with it, but I wouldn’t call that end result art.

AI art uses artificial intelligence as a tool and medium in a conceptual and practical way, critically engaging with those technologies and questioning them, be that from an ethical or aesthetic perspective. Most of today’s AI artists are engaging with these technologies in a very deep way. They’re putting together their own training datasets. They train the models. They question the biases embedded in AI. So it’s quite a complicated and involved process, and it’s not simply a text prompt generating an image.

This article appears in the May 2025 issue as “5 Questions for Christiane Paul.”