The fields of art and writing have seen increased exposure to AI this year. With its impact comes fundamental questions about the value of individual creativity and productivity. Today, AI writing assistants can write content well enough to be considered a threat in higher education. In some fields of visual art, AI apps can generate imaginative and aesthetic-looking images—yet they’ve also received criticism for plagiarizing existing artists’ work. Recently, members of the Writers Guild of America are striking over unfair labor treatments, among which include the projected use of AI for scriptwriting in the movie and tv industry. The moral concerns of using AI in these cases may seem clear. Little attention, however, has been paid to the qualitative value underscored by AI’s usage.
Considering the ways in which creative ability is valued in the arts, the presence of AI points to an impasse. First is the amount of experience naturally assumed to be behind creative ability. Whatever form of art is in question, one generally expects creative work to reveal an appreciable amount of skill or insight in its making. That is, when an artwork is considered “good”, one typically expects to see, hear, or experience things that are well-crafted, well-composed, enacted, executed or imagined (using any definition one might choose).
If an artwork doesn’t convey these qualities, one would naturally assume the work to be insignificant or run-of-the-mill (again, using whatever definitions one chooses—one’s way of dealing with the mundane could, for example, be exceptional). Talent and uniqueness can also be important, but when it comes to measuring proficiency or consistency, again we are looking to levels of experience and abilities that enable one to produce such work. For those who can produce such work, likely we’d expect them to say that practice and experience are necessary for developing proficiency, and that this involves skills, experience, and practice that typically take years to master.
Then on the other side of the creativity coin are influences that restrain one’s ability to produce art. Vying for visibility in places like social media, for example, users are pressured to share consistent content regularly. Other real-world pressures exist, too, like deadlines. Just as one expects a good student to turn in quality work by its due date, a good artist is expected to deliver quality work on time to its showing. Such realities can be at odds with one’s capacity for producing creative work because generating it at a consistent level requires a calculated performance, while creativity often waits for inspiration, motivation, ability, or purpose.
Other limiting factors can come into play as well, like the investment of time and cost. Which is say, in addition to the necessary investment of time and money to develop skills or experience, there is the cost of actually paying for the work to be made. Since art is a specialized commodity, patronizing art (even if commercial or graphic) can sometimes be prohibitive for those without serious, well-funded interests.
Due to these cumulative limitations, it’s easy to see how AI becomes an appealing tool. When the muse or purpose for creative work doesn’t arrive on time, one could turn to AI to get ideas. When ability itself is lacking, or when costs become too prohibitive, one can cheaply use AI to generate quickly something that looks like art.
Some may not see anything wrong with this picture, and perhaps there isn’t really anything wrong with it at all. By default, when one’s work is introduced to the world’s stage, it becomes measured against some of the most widely-accepted ideas about art. If one’s goal were to simply make the most widely-appealing piece of art, one could take a look at it and just try to replicate it. If they did, they wouldn’t be doing things much differently than how AI functions: by imitating and replicating ideas based on widely-established conventions and using other people’s work as a model.
AI operates on platforms like ChatGPT by mining LLMs (Large Language Models), which utilize various data systems (mostly the internet) to detect desired patterns and make predictions. With image platforms like DALL-E, the process is similar, except that its language equivalents are visual, using what we might call “large image models” instead. In either case, AI scours the internet for models to compile into a singular, albeit, we might say, crude “platonic model” prompted by the text input of the user.
Rather than platonic idealism, though, what some have suggested is that AI’s reliance on LLMs instead strives for the “platonic ideal of the bullshitter.” This “bullshitter” is someone who doesn’t “…care whether something is true or false. They care only about rhetorical power — if a listener or reader is persuaded”. Linguist Emily M. Bender refers to these bullshitters as “Stochastic Parrots”, those who “… haphazardly stitch together sequences of linguistic forms … according to probabilistic information about how they combine, but without any reference to meaning.” Although Bender is speaking about linguistics, the observation seems apt for describing to the results produced by AI with art.
Rhetorical parroting naturally suggests disingenuousness or inauthenticity. Like a parrot, AI is trained to seek words and images, and sometimes it appears to utter the right thing at the right times, but it does so without truly understanding its own context of meaning and without making any form of value assessment.
These clues would seem to point to AI’s incapability of forming definitive or comprehensive nexuses from which creativity can be authored and/or experienced. Rather than creating conscious or authentic creative initiatives, what AI offers instead are approximations of established modes of creativity and it tries to pass them off as the real thing. But is this what we would expect from art, to be unconsciously imitative of other art? If it’s a question of uncovering original sources of creativity, or of an art produced within a nexus of potential conscious meaning, then probably not.
But then again, if we agree that art should involve a fair amount of cognizance and artistic intent in its making (i.e., not just be imitative), we are still left with the problem of measuring authenticity not just on quantitative, but on qualitative grounds. Since humans are equally capable of such artistic mimesis, the task becomes more difficult to solve (and why should only AI fall suspect, particularly if it is modeled on the work of human beings?). It might help to look at the differences between the production of meaning value made by both humans and AI.
For humans, it could be said that meaning-value is generated by individuals and groups involved with particular circles of discourse. The meaning value of art is culturally determined and relies on a cycle of creation, feedback, and consensus. First, there is the artist, who is influenced or driven by certain ideas or impulse and, creates the work. Then an audience offers forms of feedback which is reflected in how it is received. Ultimately, a consensus is formed based on the interaction between the artist’s intent and audience’s reception.
With AI, however, meaning-value is formed downstream from any such cultural determination. Like much online content, its meaning value is determined through an analysis of data, posterior or even outside of how it is received. AI’s valuation, in other words, is based on historical statistics rather than organic discourse. And what exactly is behind it? Behind the AI’s behavior lies its algorithm. Algorithms offer not only a set of instructions used for performing calculations but use predictive modeling to perform tasks such as creating experiences for users. According to some studies, such modeling limits judgment, creates biases, and can lead to stifling stages of cultural homogeneity. In many ways, digital culture itself has become synonymous with forms of addiction, manipulation, and crisis of individual self-identity. Algorithms, as many know, are not only for AI but many forms of digital technology today.
This offers a few keys about how digital technology becomes suspect in delivering inauthentic content. But if it were truly the case that all art touched by digital technology automatically produced inauthentic work, what might be said of every visual reproduction of a well-known painting whose image still moves us, even though we are looking at a copy of it? What about digitally-generated music or film—especially since we spend a great deal of time experiencing art through these media? Here, the questions start to become even more complicated, prompting us to ask further questions about whether the presence—or authenticity—of such works is diminished by their relationship to technology or another factor.
Walter Benjamin of course discussed such issues in his Art in the Age of Mechanical Reproduction in 1935, where he raised problems of objects, craft, and their loss of authenticity during a moment when the technology behind photography and film was becoming ubiquitous in mass culture. For Benjamin, authentic art is cultish in nature, meaning for him that its essence lies in the direct apprehension of its presence free of intermediaries that could interfere with it. Such interferences could include the mechanical apparatus used to replicate the image, the effects of this technology, or even the social phenomena surrounding it.
According to Benjamin, technological phenomena and perspective shifts secularize the object’s presence, resulting in the fragmentation of the object’s aura. This loss of the object’s aura spells doom for its authenticity, instead reducing it to what today Benjamin might say was trivial hype.
Yet it has been almost 100 years since Benjamin wrote this work, and the experience of craft, as well as media, has changed. Digital, as well as mechanical reproduction, are now well established in our age, and definitions of craft are no longer limited to practices like chiseling stone, carving wood, or applying paint with a brush. Today, definitions of craft can include the organizing, composing, and imagining of several things through many forms of media.
With the coming of the information age, creative roles like director, curator, or designer have taken precedence as valid disciplines. Whether overseeing or being directly involved with the hands-on execution of the work, forms of craft have emerged that surpass the technical limitations of the media itself. It might even be said that many such “behind the scenes” forms of craft have long existed in the arts—like how a musician crafts their song, how an author crafts their book, a playwright their theater, or a choreographer their dance. These “hands-off” ways of crafting lay behind the making of their art. So why should it be different for any form of art produced where premeditated planning and creation are involved, whether it be mediated through any such material, medium, or form of technology?
Considering now that authentic dimensions of craft can in fact remain present despite, or even via, the influence of technology, it could be said that the aura of art is also capable of surviving the influence of digital reproduction as well as any medium. Where the aura of a work does truly appear to dissolve is when it doesn’t participate in a nexus involving an original source of inspiration behind its creativity.
But how does one define inspiration as being original? Is it connected to the uniqueness of thought art’s making, its visual appearance, or related to something more concrete like a tradition or an established way of doing things? Likely all. When Benjamin touches on the idea, he appears preoccupied with the rejection of media effects that were still new to his time. At one particular moment in Art in the Age of Mechanical Reproduction, however, his point is made clear. Describing what happens when the public’s eye is substituted by the camera, he explains how the theater actor’s aura becomes vanquished:
The aura which, on the stage, emanates from Macbeth, cannot be separated for the spectators from that of the actor. However, the singularity of the shot in the studio is that the camera is substituted for the public. Consequently, the aura that envelops the actor vanishes, and with it the aura of the figure he portrays.
But then later, he says it is the distance associated with the experience that preserves the aura:
The definition of the aura as a “unique phenomenon of a distance however close it may be” represents nothing but the formulation of the cult value of the work of art in categories of space and time perception. Distance is the opposite of closeness. The essentially distant object is the unapproachable one. Unapproachability is indeed a major quality of the cult image. True to its nature, it remains “distant, however close it may be.”
In other words, rather than the indirectness or intervention of the “artificial lens” being the cause of the loss of aura, as one might assume (i.e. the problem of a mediated experience vs. a live, in-person experience), the issue is actually a matter of distance and closeness. It’s the lens being too up close, or familiar, that is the problem. Conversely, it is the “unapproachable nature” of a work that preserves the aura. We must ask then, what qualifies as an art’s “unapproachable nature”? To answer this, we’ll have to turn away from ideas of physical closeness and distance, since the distance Benjamin is referring to is associated with acts of reverence. Here, distance and separation are a matter of establishing a sublime impression through the object’s idea, form, or function. It is in the impression of venerability, in other words, where one finds art’s aura.
While looking for evidence of imitation or sources of original inspiration behind the creation art today, the problem of art’s venerability appears easily solved: imitative art can’t possess the same aura as something that is original. But then, how does one tie originality to venerability? How can one even identify or define originality? Isn’t everything made in the world influenced by something or someone else?
Influences can come from a variety of places and appreciated for the sake of ingenuity alone. With originality, however, it is generally measured within a particular observed context that could simply be called tradition. A very basic way of defining tradition is to look for an established way of doing things—a mode of activity that is generated, picked up and participated in by others. A tradition (similar to the use of genre) becomes established when it begins to exert and maintain a certain gravity and becomes a mode of cultural activity. What this means for art is that our understanding is in part socially based—from which stems our knowledge of common modes of expression, interpretations, and lexical forms—yet also through contextualizing the creative impetus, or the individual inspiration, working from within or behind the work in is own environment.
Herein also lies how a definitive nexus is formed: through cooperation between originality and tradition. Instead of through linear or historic data, as models via the internet or algorithms are generated, this is represented by relationships between the single and the many—the particular and the whole, the individual and the social, or of difference and unity. In this arena, the intent of one side informs the other, like a two-way street with two levels of interpreting communication occurring, wherein as one advances, the other yields, and vice versa.
As communications theorist Arthur B. Bochner states:
“[there are] at least two communicators; intentionally orienting toward each other; as both subject and object; whose actions embody each other’s perspectives both toward self and toward other.”
Originality can thus be thought of as acts of attempted recognition made between a singular performer or group and a collective audience sending feedback to one other. Contrary to what some might say, the making and reception of art are not unidirectional, i.e. going from just artist to audience. Artist and audience both exist and act in an environment where there is constant back-and-forth production of meaning, reception, and feedback. The artist differs from the audience only in that they initiate the creative act. The audience differs from the artist only in that they are on the receptive end. Yet, the artist is always responding to the audience’s experience during the act of creating, and the audience is always empathizing with the individual creator’s experience through reflecting on their own creative potential.
Needless to say, with AI, this dynamic doesn’t occur. What it produces is akin to dumping artworks into a blender and throwing them on the wall to see if anything sticks. Since imitative work like this doesn’t adhere to any original source of inspiration behind its creativity and isn’t involved in the discourse of meaning value, it is thus distant from any activity formed within a particular nexus. AI’s inspiration is neither internally derived nor does it participate in the occupation inherent in any art form’s tradition. Since, creatively speaking, AI amounts to approximating form and faking inspiration, it is akin to the degrading quality of a photocopy, having been duplicated and generated further from its origin.
If AI, or any form of art, becomes principally imitative and can only approximate preexisting images that hold a certain amount of recognizable venerability, how successful can they actually be in producing such venerability themselves? What does this do to our understanding and assessment of the qualitative value of art?