Artificial Intelligence Invades the Artworld, Part (5): Is the Use of AI Reference Material Deceptive or Inauthentic?

Image: Always Drowning

Julie Kirsch via DALLE-2

The use of artificial technology is presenting artists with new creative possibilities. As I explained in my last post, some artists now make art using AI art generators alone, whereas others incorporate AI-generated images into their artistic process, using the image as a sketch or reference photo to work from. The technology raises several philosophical questions, some of which I have already explored in earlier posts. In this post, I want to consider whether using AI in the art making process is a form of cheating or inauthenticity. In answering this question, I will compare the use of an AI art generator with the use of reference materials, including photographs and the work of other artists. Ultimately, I will show that even if the use of an AI generator is not a form of cheating, it may amount to a kind of misrepresentation of one’s abilities. Still, even this claim may lose force as AI becomes increasingly popular and our assumptions about creative work change. If we no longer assume that artists conceive of their work on their own, then they won’t mislead us by integrating AI into their artmaking process.

Let us begin with a thought experiment. Tabitha is an artist who lives and works in NYC. She is trying to finish a series of paintings for her first solo show that will take place three months from now. Money is tight and she is struggling to pay down her student loan from art school. She shares a small studio with two other artists in Brooklyn, Alice and Damien. Of the three artists, Alice is the star. She is in perpetual motion and her mind is always brimming with brilliant new ideas. One day, while taking a coffee break in the studio, Tabitha pages through one of Alice’s many sketchbooks. She comes across one drawing that is particularly striking—an expressive female figure that is swimming toward the bottom of a dark pool of water. The image resonates with Tabitha, and she decided to use it for her own purposes. Without wasting any time, Tabitha pulls out her phone and takes a quick photo of the drawing. She is confident that this soon-to-be painting will save her show and help her cover the studio rental fee. Alice has so many sketchbooks—so many ideas—that she will never suspect Tabitha of using one of her sketches. And, anyway, how could Alice ever prove that Tabitha did not come up with the image on her own?

Is there anything wrong with Tabitha’s use of Alice’s idea? We might find Tabitha’s use of Alice’s drawing problematic for several reasons. In the first place, most people would accuse Tabitha of stealing Alice’s idea; it is a fairly uncontroversial example of intellectual or artistic theft. And we may view this act of stealing as morally problematic because, among other things, Tabitha may benefit in various ways from Alice’s inventiveness. If Tabitha uses Alice’s idea and presents it to the public first, then she will receive the praise and accolades that should have been bestowed upon Alice. She is robbing Alice of this good. Even if praise and accolades are not forthcoming, we may nevertheless believe that artists own the ideas or artworks that they produce. If Tabitha wanted to use Alice’s idea in her own work, then she should have requested permission to do so. And Alice, for her part, is always at liberty to disallow this use of her creative work.

Now let us revise this thought experiment slightly and replace Alice with an AI art generator. Accordingly, let us suppose that Tabitha is again preparing for an art show while struggling to pay down her student loan for art school. This time, however, she finds her inspiration in an AI art generator, and not in the sketch book of Alice. She plugs a string of search terms into, say, DALLE-2 and is provided with the image that will serve as the skeleton of her painting. How does this case, the Tabitha-DALLE-2 case, differ from the Tabitha-Alice case just considered? Importantly, in this case, Tabitha is not using the idea of another artist who owns their own work. And so, we cannot accuse her of intellectual theft. Putting aside worries of scraping, or the often morally problematic way in which AI databases are formed, she does not appear to be harming another person. However, she is using the work of a machine, an AI, as the basis of her finished painting. It might seem, therefore, that her work is not entirely her own.

When we praise an artist for their work, we are often praising them for their inventiveness. Someone, a prospective art buyer, say, may admire Tabitha’s painting, not for its technical qualities, but for its apparent inventiveness—for the imagination that conceived of the piece. If Tabitha derived her idea from an AI, then an art buyer’s praise of her may seem misplaced. Her imagination did not conceive of the piece; rather, the AI did. Many of us take works of art to be valuable insofar as they express something special and unique about the artist. They grow out of the artist’s mind or imagination, as it were; they are products of the artist’s creative genius. An art buyer may be less impressed by a work of art if they discovered that it was conceived of by an AI. Relatedly, it might seem as though Tabitha is guilty of a kind of misrepresentation or inauthenticity by creating a work of art based upon an AI’s “idea.”

A defender of Tabitha might respond here by pointing out that not all works of art come from the imagination and we admire more in a work of art than just its imaginative quality. We admire plenty of representational painters who paint still lifes, landscapes, and portraits from life. When painting from life, a painter may exercise great skill in deciding what to paint and how to paint it, carefully controlling the light and composition. And after decisions about lighting and composition are made, and the painting process begins, they may exercise expertise in terms of accuracy, brushwork, texture, etc. It is also common for artists to paint the same subject matter from photographs. While it is arguably more difficult to paint from life (insofar as it involves translating something in three dimensions onto a two-dimensional surface), we nevertheless appreciate works of art created from photographs. Indeed, most of the time, the artist is not simply trying to copy what they see in the photograph, but to interpret it and create a more beautiful and interesting version of it in their work. There is still much for the artist to do. If all this is true, then using an AI-generated reference image may seem to be no different from using a run-of-the mill photographic reference image. (To be sure, concerns about cheating and inauthenticity arise if an artist is using another person’s photographs without their permission. Even though an artist may not simply copy a photograph in their painting, they must nevertheless request the owner’s permission to use the photograph.)

A defender of Tabitha (in the Tabitha-DALLE-2 case) may also point out that, although she did not conceive of the idea entirely on her own, she guided the process by way of the search terms she chose. When a person uses an AI-art-generator, they must have some idea of what they—in cooperation with the AI—would like to create. For some artists, using an AI generator is akin to sketching – a way of exploring different ways of handling an initial idea. And, of course, Tabitha also created the final piece—painted the final image—based upon the “sketch” that DALLE-2 provided her with. Even if her work is largely derivative, she must have a certain set of skills and abilities to do even this.

I pointed out in an earlier post that we admire different forms of art for different reasons. We should bear this in mind in this context as well. What we admire in representational art – a landscape, still life, or portrait—may be different from what we admire in a work of the imagination. Often what we admire in the work of imagination is the concept or idea—the inventiveness of the artist in dreaming up an image. To be sure, we may admire much else in the piece as well, including its believability and execution, but the concept or idea may be given greater weight. If a lover of Salvador Dali’s art discovered that not he, but an AI, conceived of The Persistence of Memory, they would likely think differently of it (and him), even if he is the one who translated the idea into paint. And if this fan of Dali discovered that many or most of his works were not conceived of by him, they would likely revise their overall assessment of him as an artist. They would probably also feel duped.

Now, an artist whose work appears to be the product of their own imagination does not explicitly say as much to the viewer. Instead, the viewer makes this inference on the basis of what they see—the apparent inventiveness in the image itself. What the viewer knows about the artworld, and the context surrounding the artist, also informs this assumption. We might, therefore, doubt that an artist is guilty of any kind of misrepresentation since they, other things being equal, make no claims about the art’s origin. They are simply in the business of making art. In this view, they would only be guilty of misrepresentation if they denied, when asked, that they had an AI collaborator, or if they claimed that they conceived of the work wholly on their own.

Still, as the world changes, and AI becomes more integrated into the artmaking process, it is possible that viewers of art will no longer make this assumption. Perhaps, at some future time, we will pause to consider whether a human artist conceived of a piece on their own or with the help of an AI collaborator. We will not immediately assume that the artist dreamt up their work independently in the private chamber of their imagination. Instead, we may be inclined to ask questions about the artist and their creative practice—about whether they used any technology, including AI, in the production of their work. But we cannot always expect honest and forthcoming answers. In many spheres, AI makes deception and trickery easier than ever. And like a teacher who fails to spot an essay created using AI in the classroom, consumers of art may be fooled by a crafty artist who conceals their sources and true art-making process.

Artificial Intelligence Invades the Artworld, Part (4): A New Creative Tool for Artists?

Image: A Place for Tomorrow

Julie Kirsch via DALLE-2

In my last post, I considered whether AI art generators, like DALLE-2, Midjourney, and Stable Diffusion, pose an existential threat to artists and other creative professionals. I argued that they do, and my treatment of new AI art-making technology was largely negative. But as is the case with most new forms of technology, its consequences are not all bad. In this post, I shift gears and look at positive ways in which artists are embracing this technology and incorporating it into their creative practice. Drawing from the extended mind theory in the philosophy of mind, I also explore the possibility that human beings may be merging with artificial intelligence and other forms of technology.

            As someone who already enjoys making pictures, I find DALLE-2, the art generator that I have experimented with, to be a lot of fun to use. It has an entertaining, game-like quality and involves an element of the unexpected. While you can influence the imagery that the generator produces by way of text prompts, you cannot control it in the way that you can an oil painting or graphite drawing. Sometimes you are disappointed by what it produces, but at other times you are delighted and inspired by its “inventiveness.” The challenge is to tame what is not completely under your control by mastering the language of text prompts. Through its use, which is now widespread, this technology has brought joy to countless people who would not otherwise be in the image-making business. It’s not difficult to appreciate the technology’s appeal. As Kevin Kelly explains, people are attracted to it simply because they like to look at pretty pictures: 

“Like flames in a campfire, the light patterns are mesmerizing. They never repeat themselves; they surprise, again and again. They depict scenes no one has witnessed before or can even imagine, and they are expertly composed. It’s a similar pleasure to exploring a video game world, or paging through an art book. There is a real beauty to their creativity, and we stare much in the way we might appreciate a great art show or museum. In fact, viewing a parade of generated images is very much like visiting a personal museum—but in this case, the walls are full of art we ask for (“Picture Limitless Creativity at Your Fingertips”).”

— Kevin Kelly

In this way, the technology has ushered in a kind of democratization of image-making. People who would be too intimidated, insecure, or just plain lazy to pick up a pencil or paintbrush can use DALLE-2 and other AI art generators to produce images that are unique and responsive to their feelings, experiences, and preference.

           Many professional artists have embraced developments in artificial intelligence in various forms as well. Artist Refik Anadol, for example, has integrated machine learning and data visualization methods into his technically and aesthetically impressive data paintings. His piece, Coral, is the product of over 100 million coral images of raw data. The artwork is the visualization of this data on a 40 by 40-inch screen—various forms of coral continuously ebb and flow into others (PBS). He created this piece, which was displayed at the World Economic Forum 2023, for the purpose of raising awareness about climate change. Unlike the casual DALLE-2 user, Anadol did not simply plug in a few descriptive text prompts into an art generator. Instead, he and the team of experts working in his studio (including computer and data scientists, engineers, researchers, and designers) collected the data themselves and translated it into the final piece using by programs that that they created and trained. Compiling the dataset alone was a years-long project (PBS/Refki Anadol). It is also worth noting Anadol and his team only use “ethically sourced” data that they themselves collect; that is, they do not “scrape” or steal images from other artists on the Internet when their compiling datasets (PBS). As Anadol sees it, his data paintings involve a collaboration between the human artist and the machine. In his view, the integration of AI into the artworld as a “beautiful movement” that brings art, science, and technology together; it is something that we should embrace since we are “getting closer to machines every single day.”

             Anadol is not alone in sourcing his own images for his projects. Artist Sougwen Chung, who is also interested in human-machine interactions, designed and built her own AI robots to serve as art-making collaborators. Her early robots, all “Dougs” for “Drawing Operations Unit, Generation (followed by a number)” (Kaufman), were all trained on about 20 years of her own drawings. A more recent Doug, Doug 4, is connected to her via brain-wave data. Chung’s robots do not simply copy her drawings but offer new interpretations of her style in response to the dataset that they have been fed. In collaborating on a new painting, the robot responds to Chung, and Chung to the robot. They often do this in front of a live audience as performance art, the finished works selling for more than $131,000 (Kaufman).

            Chung’s upbringing involved a synthesis of art and technology; her mother was a computer programmer and her father an opera singer. She played the violin and piano as a child and started coding and building websites in grade school (Kaufman). Chung is interested in exploring the interactions between smart technology and human beings. She does not subscribe to the various dystopian AI narratives that we often hear and is always looking for new ways to push her art and technology projects forward (Kaufman). She welcomes the technology and believes that interactions with AI devices, such as robots, provide us with new possibilities for creativity (TED).

            Like Anadol and Chung, some high-profile artists embrace artificial intelligence in a way that goes beyond the causal use of mainstream AI generators like DALLE-2. Indeed, they are researchers as much as they are artists; often working with teams of experts, their technological accomplishments are as impressive as their artistic ones. But less tech savvy artists are also finding ways to integrate the new technology into their practice. For some artists, AI art generators, like DALLE-2, play a role in brainstorming or working through an idea. If an artist is not sure how to approach a piece, they can play around with it in an AI art generator. If an artist is interested in painting, say, a train crossing over a foggy river, they can plug these words into DALLE-2 (as text prompts) and see what it produces. In this way, the generator provides artists with materials to work with – “ideas” to explore in the creative process. The images that it produces may play the role that sketches or reference photos traditionally do in refining an idea or preparing for a new piece.

            More dramatically, some theorists may take artists to be merging with the new AI technology that they have adopted, particularly if the artists in question consistently use a generator in their creative process. In the philosophy of mind, the extended mind thesis claims that the mind can extend beyond the skull to include external objects, such as smart phones and notepads, which play a regular role in our mental processing. In this view, associated with the work of Andy Clark and David Chalmers, a person’s iPhone becomes part of their mind when they offload memories, and thereby cognitive tasks, to it; in such cases, the iPhone plays a role in their mental processing that used to be played by the brain. While I do not take this view literally, I think that it provides us with a helpful way of thinking about the contribution that technology makes to our mental lives. Artists are “merging” with technology insofar as they are offloading imaginative tasks to AI art generators.

             To appreciate the force of this point, compare how an AI generated image is produced with how a traditional artist’s sketch is produced. An artist who is formulating an idea for a painting may create a series of preliminary sketches. In these sketches, the artist may play around with value, texture, composition, and so forth. But importantly, the artist is the creative agent who produces and conceives of these sketches; the artist dreams them up in their imagination. In comparison, when an artist uses an AI art generator, the AI art generator is the one that “makes the magic happen,” as I put it an earlier post, and produces the imagery in response to text prompts. In this way, the AI art generator is stepping in for the human imagination and producing an image, or series of images, in response to text prompts.

If we give this a positive spin, then we may view this technology as providing artists with new possibilities for creativity, as Chung might put it. We can integrate machines into our creative process by offloading some of the imaginative work to them. We may even expand our imaginative capacities by doing this, for the machine may prompt us to take our initial idea in a new and unexpected direction. After reviewing the images that an AI art generator produces, an artist may revise their preliminary drawing and then set about working on the final piece. In this scenario, what the AI art generator produces is not the finished work, but new reference material from which to work. And given how common it is for artists to work from reference materials, this use of AI is nothing new or alarming.

It is possible that, in the future, technology like this will take the form of a neural implant, in which case the extended mind thesis will become even more compelling. Our own carbon-based brains will begin to mingle more closely with silicon-based implants. Neural implants already do exist to assist human beings in various ways. Incredibly, in 2022, Ujwal Chaudhary et al. reported that they had trained a man with CLIS (completely locked-in syndrome) to communicate via a neural implant simply by thinking. Their study showed that it is possible for someone who is completely paralyzed to communicate by using “brain-based volitional communication” (1). This technology will undoubtedly improve and expand in the years to come.

In my next AI post, I take up the issue of cheating and authenticity in art. We have already seen that AI art generators are beginning to play a role in the creative process of many artists. The use of this technology raises questions about what constitutes cheating in the art making process. In grappling with this issue, I will compare the way that an artist might use an AI art generator with the ways in which they use other tools and resources, such as reference images and Photoshop.

Works Cited:  

Chaudhary, U., Vlachos, I., Zimmermann, J.B. et al. “Spelling Interface Using Intracortical Signals in a Completely Locked-in Patient Enabled via Auditory Neurofeedback training.” Nat Commun 13, 1236 (2022). https://doi.org/10.1038/s41467-022-28859-8

Chung, Sougwen. “Why I Draw with Robots.” TED. https://www.ted.com/talks/sougwen_chung_why_i_draw_with_robots?language=en. Accessed July 2, 2023.

Kaufman, Sarah L. “Artist Sougwen Chung Wanted Collaborators. So She Designed and Built Her Own AI Robots.” Washington Post. Nov. 5, 2020. https://www.washingtonpost.com/business/2020/11/05/ai-artificial-intelligence-art-sougwen-chung/. Accessed July 2, 2023.

Kelly, Kevin. “Picture Limitless Creativity at Your Fingertips.” Wired. https://www.wired.com/story/picture-limitless-creativity-ai-image-generators/. November 17, 2022. Accessed June 24, 2023.

“Use of Artificial Intelligence Generates Questions about the Future of Art,” PBS. https://www.pbs.org/newshour/show/use-of-artificial-intelligence-generates-questions-about-the-future-of-art. May 2, 2023. Accessed June 24, 2023.

Artificial Intelligence Invades the Artworld, Part 2: Who Is the Artist?

Image: Let the Children Play

Julie Kirsch via DALLE-2

Let us assume for the sake of argument that AI-generated imagery is art. If this is true, who is the artist? The AI generator or the person who uses the AI generator? Neither? Both? Let us explore this question by considering a thought experiment. Amy fashions herself an artist but often finds herself lacking in imagination and inventiveness. She has tried to cultivate her creative powers in various ways—even experimenting with marijuana and psilocybin—but finds herself sadly uninspired. In comparison with Amy, Amy’s younger brother, Felix, is wildly creative and imaginative. Although he creates artwork for fun, it is not his true passion. He is pursuing a career as a science researcher and has no interest in making his own artwork public. He also loves his sister dearly and would do almost anything to help her. Amy would like to submit a piece to an upcoming show and competition for emerging artists but is struggling to come up with something that is unique and technically impressive. She asks Felix if he might help her develop a piece for the show.

They meet over a series of days, Amy presenting Felix with a set of word prompts, and Felix translating these into imagery. Amy asks Felix to create something about “nostalgia,” “childhood,” and “friendship.” Felix created a pen sketch of two young friends walking away from each other with one of the friends, as an older person, looking upon the scene with a slightly melancholic expression. “That’s perfect… you just hit the nail on the head…. Now paint this in cool but muted watercolors and I will be all set. Thank you! You knew just how to put on to paper what I was struggling to say!” Amy submits the piece to a local art competition and wins first place. This helps her budding art career tremendously. She continues to pursue her dreams as an artist with Felix by her side, giving visual expression to her idea prompts.

How does Amy’s use of Felix resemble an artist’s use of an AI art generator? It might be argued that Amy’s use of Felix is different from an artist’s use of an AI art generator insofar as Felix is human and AI art generators are not. While this is undoubtedly the case, we might wonder what, if anything, hangs on Felix’s humanness. There might be moral, social, and even legal issues that surround Amy’s use of Felix, but in both cases the agent as artist is using the “intelligence,” or “creativity,” of something (or someone) external to her for the purpose of producing a work of art that is inspired by word prompts. My suspicion is that many of us would say that Felix, not Amy, created the work of art that she submitted to the art competition. And if, in the Amy-Felix case, we want to say that Felix is the artist who created the painting that he made, then why should we not also say that the AI art generator is the artist, or partial creator, of the art that it produces via its machine learning algorithms?

One problem with claiming that AI art generators are artists or creators is that AI generators are not even agents with mental states, goals, desires, and so forth. We generally reserve the term “artist” for agents. We can, of course, imagine a revised version of this case in which Felix is not a human brother but an intelligent robot with mental states. In this version of the case, we might be more prepared to say that that the AI is an artist. So, perhaps we should think of AI art generators in their current manifestation as quasi-artists or partial creators of the work that they generate. Alternatively, we might devise a new term to encapsulate the causal role that they play (qua non-agents) in the production of artwork through interactions with a user. Putting these issues aside, the Amy-Felix thought experiment shows that Amy’s role in creating a work of art is different from, and arguably more limited than, Van Gogh’s was, for example, in painting The Starry Night. Even if the AI art generator is not an agent or artist, it nevertheless contributes causally to a significant portion of the finished work.

If we make this move, then what should we say about photographers? Are photographers mere partial authors of the work that they create? And is the camera best understood as a quasi-artist? When we compare a Frida Kahlo self-portrait with, say, one of Cindy Sherman’s untitled film stills, I think that we do recognize an important difference between the two. In the case of photography, the camera, like the AI art generator, makes an important causal contribution to the finished work. Still, there is much left for the photographer to do. While the camera may be an astute observer, it is lacking in creativity and imagination, among other cognitive abilities. The photographer not only conceives of the piece, but also controls the lighting, composition, and so forth. The user of an AI art generator, it seems, does less of what the photographer does. After the user enters word prompts into the AI art generator, the AI art generator takes over –makes the magic happen—and produces its results, i.e., a set of images.

Of course, it is even more jarring for us to refer to a camera as a quasi-artist than it is for us to refer to an AI art generator as one. Perhaps as our tools become more human-like—more intelligent and creative—we are more inclined to think of them as agents, authors, artists, or creators. In comparison with AI art generators, cameras may seem “dumb” and unsophisticated. If, in the future, we have the ability to use intelligent robots to create art – robots whose imagery producing powers are accompanied by mental states like our own – then we might be more willing to grant them author, artist, or creator status.

None of this is to deny that users play an important role in creating the images produced by AI art generators. I thought that it would be wise, in writing this series of posts, to give the technology a try for myself. I began with Midjourney, which is attached to Discord, but could not tolerate the interface or figure out how to get started or even where to go from the Discord landing page. (This is perhaps because I am old, impatient, and not very tech savvy.) I found DALLE-2 to be comparatively straightforward and easy to use. However, having researched award-winning works of AI generated art for these blog posts, I was astonished to see how awful my own AI artworks were in comparison. I find Jason Allen’s Théâtre D'opéra Spatial to be truly beautiful and inspiring; it contains multiple figures, a highly detailed composition, and dramatic lighting. The images that I produced via DALLE-2 (which accompany these blog posts) were not off the same caliber. I found that the figures that DALLE-2 generated often had blurry and contorted faces. (See, for example, the faces of the children in the image accompanying this post.) And the images had a tacky and almost cartoonish quality about them. Digital artists who use DALLE-2 and other AI art generators, often edit and improve the images on Photoshop. As a non-digital artist myself, I did not have the ability to do this.

After playing around with DALLE-2 for even a few minutes, I realized that one could be better or worse at producing images by understanding which prompts to use. And so, to be a really great AI artist, one would nevertheless need to possess right set of skills and abilities.

One upshot of this discussion is that different forms of art require different skills and abilities. One could be an excellent oil painter but a terrible photographer; one could be an expert charcoal artist, but a mediocre AI artist. And thus, for many purposes, it may be wise to keep the categories of art separate. For example, it may not be fair, or in our in the best interests of the artworld, to allow AI artists to compete for prizes or recognition with photographers. While there may be a place for AI art in the world, it may not be in the same competitions and shows as photographers. This is nothing new. Many art competitions are limited to a single medium and have strict submission requirements. For example, a watercolor competition may refuse to accept or consider watercolor paintings that are “impure” insofar as they contain colored pencil or gouache.

It also follows from this discussion that, even if AI generated images are art, the artists who created them may not be especially talented, skilled, and praiseworthy. Again, this is nothing new. We might embrace Fountain as a work of art without thinking that it took much talent or skill to produce. After all, Duchamp didn’t construct the urinal himself; he simply flipped it over and signed it. Similarly, a person might hastily splash some colorful paint on a canvas and call it art. They may be right that it is art even if it is not great art – even if it took virtually no talent to produce.

To sum things up, AI art leaves a significant amount of the art making process in the hands of the AI art generator. If an artist simply uses an AI art generator, and does nothing more to alter the image, then the AI is responsible for making almost all the magic happen, as I put it. For this reason, it would be wise to keep AI art separate from not AI art for at least certain purposes. In my next post, I will consider whether the existence of AI art poses an existential threat to artists and creative professionals.