Hyperrhiz 30

AI-Generated Art and the Bourdieusian Conundrum of Aesthetic Boundaries

Rachel Suet Kay Chan
National University of Malaysia

Citation: Chan, Rachel Suet Kay. “AI-Generated Art and the Bourdieusian Conundrum of Aesthetic Boundaries.” Hyperrhiz: New Media Cultures, no. 30, 2026. doi:10.20415/hyp/030.e03

Abstract: This paper examines the conundrum posed by the rise of AI-generated art in the field of aesthetics, specifically in relation to Pierre Bourdieu’s theory of cultural fields and the construction of taste. In the context of contemporary art, the emergence of artificial intelligence tools—such as generative adversarial networks (GANs), Artbreeder, and DALL·E—complicates traditional divisions between highbrow and lowbrow art, the sacred and the profane. Drawing on Bourdieu's notions of habitus, field, illusio, and doxa, this paper argues that AI-generated art embodies a new kind of artificial taste, challenging the conventions of artistic originality, authenticity, and value. By discussing key examples of AI-generated art, this paper explores how artificial intelligence reshapes the dynamics of artistic production and consumption.

Keywords: AI-generated art, Art legitimacy, Bourdieu, Habitus, Highbrow vs Lowbrow culture, Phenomenology, Symbolic capital.

Introduction

The definition of art has to be categorical, in order to exclude non-art from art. The wider sphere of definition entails the creation of standards to determine what art is; how it is separated from other random occurrences of nature, that is, creations which are not deliberate. Over time, this practice has culminated in the segmentation of different forms of art, from the highbrow, namely art that requires very specialised training and the requisite sensitivity, against other less trained forms of artistic endeavours. Pierre Bourdieu’s theories revolve around studying this phenomenological categorisation of the value of objects and services based on the demarcation of taste. Taste is the sense-making that develops surrounding the preference for higher brow forms of art, essentially a type of economic good which is scarce in its production and accessibility.

Dominic Lopes (2014) asked what is art, noting that it is a tricky question to answer, and that it is a question that has long plagued philosophers. In summary, a work of art “is an artefact that satisfies any one of several candidate conditions such as having positive aesthetic properties, being emotionally expressive, intellectually challenging, original, the product of a high degree of skill, and the result of an intention to produce a work of art” (12). In terms of the process, Steinbock and Goodman have examined the diverse ways artists-in-the-making work out the boundaries between “art” and “non-art”, suggesting that the boundary work of life drawing classes placed students in a liminal space between “autonomy from society” and engagement with it (252-3).

A question to be asked at present however, concerns the mass production of art through the transformation of the mode and means of production. As we are currently in the fourth industrial revolution, numerous forms of artificial intelligence (AI for short) exist around us awaiting to be given command prompts into creating all manner of cultural goods, and services. In the journal Science, Ziv Epstein et. al. acknowledge that one prominent application of AI at present is the production of high-quality artistic media for visual arts, concept art, music, and literature, as well as video and animation (1110). For example, today, one can simply input a textual prompt into generative large language learning AI models, input a design prompt into an image generating AI app, or even produce "deepfakes" from AI video software. One can quite simply create a parallel universe, with its own specialised narrative, which leads to the prospect of fake news. These tools enable art to be created freely by non-specialists, thus the question raised by this essay is how does this phenomenon impact existing connotations of taste with regards to highbrow versus lowbrow art?

If fine art still exists as a sublime form of artistic creation by specialists, and its value is prized highly, which differentiates it from mass produced arts such as, for example, the oft-overlooked comic books, then what about a situation in which AI art can even surpass derivative artworks such as fan art? At the present state of technology, all it takes is the individual’s imagination, the ability to type it out (or even use voice command), and pressing a button in an app. It is already possible for short films to be made with virtual actors whose features and expressions can be altered to match the prompts. This has the ability to distort one’s perceptions of reality and challenge the existing concept of taste in art. Hence, it is necessary to delve into discussions of the phenomenology and social construction of reality of social actors in order to discern the way in which taste in art is developed and perpetuated.

Navigating the Boundaries of AI-Generated Art

The advent of AI in art creation challenges our established understanding of taste and aesthetics. AI-generated art is unique not just because it uses machines to create, but because it complicates the very notion of taste itself. To explore this shift, we must look beyond the traditional dichotomies of highbrow and lowbrow art and examine alternative forms like outsider art, Fluxus, and mail art—artistic movements that have long existed on the fringes of mainstream taste. These movements, much like AI-generated art, blur the lines between what is considered “art” and “non-art” and challenge traditional artistic hierarchies. In this context, AI can be seen as a tool for developing an “artificial taste”—a taste that is omnivorous, embracing a wide array of aesthetic experiences that often ignore the boundaries of high or low culture. The following are examples of such AI-generated art.

1. 1. AI-Generated Portraiture
   Tools like Artbreeder and DALL·E have gained attention for their ability to generate realistic and surreal portraits (Unkrich, Wired). These tools enable users to blend various traits, producing lifelike images that often challenge traditional portraiture. However, while AI’s algorithmic processing mimics human creativity, the emotional depth typically associated with a human-made portrait is often absent. The question of “taste” arises here: does the viewer’s appreciation of such art stem from its aesthetic appeal, or is it grounded in the belief that a human artist created it?
2. 2. The Next Rembrandt Project
   A landmark example of AI-generated art is the Next Rembrandt project, where an AI system analyzed Rembrandt’s body of work and generated a new portrait in his distinctive style. The project highlights the ability of AI to not only replicate established artistic styles but also to innovate within them. However, while the work was visually convincing, it lacked the historical context and lived experiences that inform Rembrandt’s legacy (Starr, CNET). This raises critical questions about the “authenticity” of AI art and its place in the highbrow art world.
3. 3. Generative Adversarial Networks (GANs)
   GANs, widely used by artists such as Mario Klingemann, generate abstract art that is often celebrated for its intricate patterns and innovative forms. However, the “taste” embedded in these works is derived from the data the GAN was trained on, including pre-existing artistic styles (Kate Vass Galerie). While AI-generated abstract art might evoke emotional responses from viewers, these responses are often tied to an aesthetic sensibility shaped by the dataset rather than the artist’s unique perspective.

AI and Outsider Art: A New Frontier

Outsider art, defined by its creation outside the traditional art world, has always posed a challenge to the concept of artistic legitimacy. Artists in this realm, such as Henry Darger or Adolf Wölfli, worked without formal training and often defied conventions of composition, subject matter, and materials. Their work has, over time, earned recognition, yet it remains peripheral to mainstream art discourse. AI-generated art enters a similar territory, producing works that do not align with traditional artistic standards but raise questions about what art can be. AI does not have a ‘vision’ in the human sense; rather, it generates through algorithms that reflect and remix existing data. Yet, like outsider artists, AI-generated creations often defy formal boundaries and invite new interpretations. These works challenge our taste by offering something unfamiliar yet compelling—a new aesthetic that resists categorization.

Fluxus and the Anti-Art Movement: AI as a Provocation

Fluxus, an avant-garde movement from the 1960s, embraced art as an experience, emphasizing process over product and questioning the very idea of what could be considered “art.” Artists like George Maciunas and Yoko Ono used mundane materials, sounds, and everyday objects to create art that was not confined by traditional rules. This spirit of anti-art aligns closely with AI’s role in the creative process. When machines generate art, they bypass the traditional skills and intentions of the artist, offering a form of creativity that does not require human authorship. AI’s role in this context is not to create for the sake of beauty or expression, but rather to provoke, to challenge, and to open up new pathways for understanding the nature of creativity. Just as Fluxus sought to expand the boundaries of art, AI-generated art invites us to reconsider what art can be and how it fits within the larger cultural landscape.

Mail Art and Assemblage: Disrupting the Conventional Taste

Mail art, a networked art movement that emerged in the 1960s, thrives on the idea of accessibility and democratization of art. It often uses simple materials, including envelopes, postcards, and stamps, and focuses on communication rather than commercial value. Similarly, assemblage art, which involves creating works from found objects, challenges traditional notions of artistic materials and composition. These movements, like AI art, break down barriers by using everyday objects or unconventional media to create pieces that may not initially appear “artistic” in a conventional sense. AI-generated art often operates within this logic: it uses data, algorithms, and tools that are readily available, yet produces unexpected and sometimes subversive outcomes. In doing so, it aligns with movements that sought to dismantle traditional hierarchies of art and taste, embracing inclusivity and experimentation.

Artificial Taste: A New Omnivorous Paradigm

At the heart of the debate about AI-generated art is the concept of “taste.” Traditional taste hierarchies, rooted in cultural and social distinctions, have long separated the high from the low, the refined from the vulgar. However, the rise of AI introduces a new form of taste - one that is omnivorous, able to consume a wide array of influences and styles without the constraints of tradition. This “artificial taste” does not discriminate between classical beauty, raw expression, or conceptual provocation. Instead, it embraces a broader, more inclusive view of what constitutes art, opening up possibilities for new forms of aesthetic appreciation.

AI, in this sense, mirrors the omnivorous taste of contemporary culture, where individuals are no longer bound by narrow definitions of art. Instead, they engage with a vast array of cultural products - whether high or low, traditional or experimental. AI-generated art, by synthesizing and recombining elements from across the cultural spectrum, challenges the elitism of highbrow culture and offers a more inclusive aesthetic experience. It provides a platform for art that is both accessible and expansive, encouraging a new dialogue between art, technology, and taste.

AI-generated art is not simply a tool for creating aesthetically pleasing works; it is a challenge to the very foundations of art and taste. By drawing on the spirit of outsider art, Fluxus, mail art, and assemblage, AI art emerges as a powerful force that disrupts traditional aesthetic categories. It proposes a new form of artificial taste - one that is omnivorous, experimental, and unbound by the historical constraints of high and low culture. As AI continues to evolve as an artistic tool, it will undoubtedly push the boundaries of what we consider art and force us to rethink the nature of taste itself.

Conceptual Framework

The diagram above defines and differentiates between the different forms of taste, ranging from the highbrow to the omnivorous. In the succeeding diagram, we see the conceptual framework of how art is separated from non-art, and how the levels of taste outlined above relate to them, as well as AI art’s place within.

The conceptual framework above explains the relationship between art and non-art, and how taste is defined by one’s understanding of this. Cultural capital is the skillset needed to possess good taste. In the case of AI art, as it lacks the criterion of conforming to definitions of art, it does not comply with highbrow taste. It only appears to simulate art superficially, but on a foundational level it lacks intention, expressiveness, philosophical stimulation, and skill. However, there are still middlebrow and lowbrow as well as omnivorous conceptions of art, which entails asking if AI art falls under these categories? We hereby compare the differentiation of art from non-art objects, and how the notion of cultural capital and taste correspond to this differentiation. The evaluation standards and effects of AI generation on each artistic genre is also listed.

1. Fine art
   

   Needs specialised training to create and appreciate/critique. Includes formalised degrees such as Master of Fine Arts, or Bachelors of Fine Arts programmes. Occasionally there are self-taught artists but they may be learning from traditional fine arts resources such as classical painting books.

   AI art replaces the need for any specialised training as it allows just anybody to write a prompt and convert their ideas into art. Research by Oksanen et. al. found the following: that AI tools have been used to enhance art and artistic event production and analysis; that the difference between human- and AI-made art was not generally recognized; and that we are in the middle of transition where AI is transforming concepts of creativity and art. (n.p.)

2. Comics (including manga etc.)
   

   Catered to the masses, creators may or may not possess specialised training, and may be self-taught.

   AI art replaces the need for any specialised training as it allows just anybody to write a prompt and convert their ideas into art. Kumar et. al. found that the field of comic creation using artificial intelligence (AI) has made great strides in recent years, where the generation of AI-based comics represents a dynamic and growing field that combines artistic creation with cutting-edge technology, opening new avenues for storytelling and creative expression in the digital age (n.p.).

3. Fan art
   

   Catered to the masses, creators may or may not possess specialised training, but is less valuable/saleable than officially published comics. Fan art tends to be the fan’s depiction of their favourite character or scene from a fictional work through mediums such as digital or traditional art, which can include painting with acrylics, watercolour, colour pencils, charcoal, etc. Fans could be considered a subculture; a community of hobbyists whose discourse surrounds the particular fictional narrative of which they derive their fandom from. Fans could consist of trained artists or simply amateurs with no formal training, and in this category the fans’ skills could range from amateurish to expert level, by being self-taught. If they are self-educated, before the advent of AI, they have been likely to have learned from art communities (online or offline), have some basic knowledge from school, or have referred to art books borrowed from libraries or purchased from bookstores.

   AI art replaces the need for any specialised training as it allows just anybody to write a prompt and convert their ideas into art. Nicolle Lamerichs observed that generative AI is on the rise due to the recent popularity of tools such as DALL·E, Midjourney, and Stable Diffusion, which has also led to discussion in fandom, especially in terms of ethics, copyright, and monetization (150). Lamerichs concludes that while AI can empower and inspire artistic practice, users are especially critical of generative images being turned into a business model (161). Generative AI mimics the ways authors, including fans, create artworks such as painting with acrylics, watercolour, colour pencils, charcoal, etc. Sometimes the level of skill generated by AI is on par with or surpasses the fan creator, or even professional artists. While technical skill is present, the authenticity is not there, as is the lack of development within the AI generator's art career, unlike the person or fan who creates an artwork through detailed planning, educating oneself, and opening oneself up for critique, whether by professionals, other fans, or hobbyists. The phenomenological process of creation bypasses the steps taken to immerse oneself in social norms regarding habitus, field, doxa, and illusio.

4. Graphic design
   

   Mostly used in commercial settings for products/services catered to the masses. Graphic designers are trained in educational institutions through degree courses, or through using non-AI software.

   AI art replaces the need for any specialised training as it allows just anybody to write a prompt and convert their ideas into art. Yael Meron noted that the implementation of artificial intelligence (AI) features within graphic design software enables practitioners to automate many design processes, but this threatens to deskill the profession and create a second tier of “non-professional” designers, particularly within less creative work that emphasises fast turnover and functional artefact production. (n.p.)

5. AI generated art
   If login/account not required, and payment not required, then it is very accessible to all and sundry and does not require any skill or training whatsoever.

Highbrow versus Lowbrow: The Collapse of Traditional Boundaries

The concept of artificial taste becomes central when considering the role of AI in artistic production. AI’s “taste” is not human but algorithmic, shaped by the data it is fed. In many ways, AI-generated art reflects a commodification of taste, wherein art is produced to meet the expectations and preferences embedded in the training data. This artificial taste is not purely objective; rather, it reflects the preferences of the humans who designed the algorithms, chosen the datasets, and set the parameters for the creative process.

AI-generated art, by its nature, cannot possess the lived experience that influences human art-making. The emotional and intellectual engagement that viewers have with traditional art—based on the artist’s personal history, intention, and cultural context—may not be present in AI-generated works. While AI art may still resonate with viewers, it raises questions about how we assign value to art and whether this value can be entirely based on its aesthetic appeal.

The emergence of generative AI art precipitates a critical collapse of the traditional distinctions between the sublime and the ordinary, the sacred and the profane, and the highbrow and the lowbrow. In considering this phenomenon, it is instructive to revisit Pierre Bourdieu’s reflections on the demarcation of high and low art within aesthetic fields.

As Grenfell and Hardy note in their work Art Rules, Bourdieu sought to highlight Manet’s revolutionary achievement in establishing an art form that was genuinely autonomous, thereby dismantling the dominance of the “academic eye” and the corresponding traditionalist values to which it adhered (176). In this regard, even within Bourdieu’s intellectual milieu, there was a concerted move to valorize non-academic, anti-classical forms of artistic production. Manet and the Impressionists destabilized the classical emphasis on polished form and sacred subject matter, replacing it with depictions of the everyday and with a visible, gestural brushstroke technique that foregrounded the materiality of painting itself. Their challenge to the prevailing “illusio” of the field rendered them anathema to the classical establishment.

The disruption of academic norms thus demonstrated that the field of art was governed not by immutable “rules” but by strategic positioning within a dynamic field of forces. Grenfell and Hardy underscore this reading of Bourdieu, emphasizing that artistic production is guided by strategies aimed at maximizing symbolic capital rather than by adherence to prescriptive rules (163).

Extending this framework to the advent of AI-generated art reveals a significant evolution in the phenomenological construction of reality within the artistic field. Here, phenomenology infuses meaning into the key Bourdieusian constructs of habitus, field, illusio, and doxa. Vázquez Gutiérrez identifies illusio as a principle of emotional investment and perceptual commitment, binding individuals to the hierarchical structures of the field and thereby naturalizing social inequalities (n.p.). Within Bourdieu’s mature theory of practice, the interplay of habitus, capital, and field shapes the dynamics of artistic production and reception.

When applied to AI-generated art, Bourdieu’s framework confronts a radically altered landscape. The social construction of reality underpinning the field of art has undergone a phenomenological displacement. While structural features of field organization persist, the authenticity traditionally derived from an artist’s embodied experience appears attenuated. AI-generated art mimics the surface characteristics of artistic production without the intentional, lived engagement that historically conferred symbolic legitimacy within the field.

Recent examples as mentioned above illustrate this transformation vividly. Midjourney, DALL-E, and Stable Diffusion produce images that echo established styles—from Renaissance realism to Impressionistic abstraction—based on user prompts rather than personal immersion in an aesthetic tradition (Elgammal et. al., 21). Notably, works such as Jason Allen’s Théâtre D'opéra Spatial, which won a prize at the Colorado State Fair’s fine arts competition in 2022, exemplify AI’s capacity to generate visually compelling artifacts that nonetheless provoke controversy regarding authorship and creative intention (Allen).

The concept of artificial taste thus emerges: a programmed sensibility reflecting the aggregation of human preferences, but lacking the embodied situatedness that Bourdieu associates with genuine habitus. In practice, artificial taste manifests as the ability of AI systems to replicate genre conventions, mimic artistic trends, and even simulate innovation by statistically recombining stylistic features. Yet these outputs remain detached from the social labor of distinction and symbolic struggle that characterizes artistic fields. AI “prefers” according to algorithmic weighting of prior human valuations, not through lived social experience.

This distinction is critical. Where human taste is forged through participation in a structured field over time, involving investment, disillusionment, and symbolic risk, artificial taste is an externalized computation of preference with no emotional or existential stake in the field. AI art thus circulates primarily within popular culture, satisfying immediate consumer appetites but lacking the slow accumulation of symbolic capital that confers legitimacy within high art circles.

AI as a tool for creating Traditional Art: A brief experiment

To further test out the ability of AI to generate images based on prompts and its ability to evaluate art, I performed an experiment using Google Gemini. As I had recently completed a Coursera-University of Tokyo course on Japanese samurai art of the 19th century, I used this concept as an inspiration. I prompted Gemini’s Canvas function to generate a samurai dancing with a dragon; followed by a dragon swimming with koi fish; a koi changing into dragon; a sakura tree by a dark lake; and sakura flowers and koi. All these were references I needed to create a piece of traditional art, based on the concept of a lone wandering samurai or ronin encountering a green dragon by a lake at midnight. The following are the images generated by Gemini, which are extremely accurate as prompted; and the acrylic on canvas painting which I did in mangaesque style based on the references generated.

After creating my piece, I uploaded it into Gemini and asked it to perform an evaluation. The following is Gemini’s review of my artwork (it also commented on other earlier pieces which I uploaded for trial and error):

Based on the images you’ve uploaded, let’s focus on the new drawing, 1000063181.jpg. This appears to be another iteration of the same narrative scene, very similar to the previous one (1000063162.jpg), but with a slightly different feel.

Evaluation of 1000063181.jpg:

Strengths:

• Vibrant and Lively Mood: This piece, like its immediate predecessor, successfully captures a bright, lively, and fantastical atmosphere. The clear blue sky and bright pink/red cherry blossoms create a feeling of daytime magic.
• Strong Composition and Narrative: The composition remains effective, with the figure in the foreground drawing the viewer into a story. The elements—the figure, the tree, the creature, and the water—work together to create a compelling scene.
• Refined Creature Detail: The creature, a light green dragon-like figure, is well-defined and stands out clearly. Its reflection in the water is also a very strong and well-executed element.
• Consistent Stylization: The artist maintains a consistent and recognizable anime/manga-inspired style across the entire piece.

Areas for Potential Improvement:

• Lighting Consistency: The lighting on the various elements is still not fully cohesive. The figure in the foreground is very dark and silhouetted, while other parts of the scene are brightly lit. Unifying the light source would make the composition feel more integrated.
• Background Depth: The background hills and the horizon line are quite simple. Adding more tonal variation and blending would create a greater sense of distance and depth.
• Brushwork on Water: The brushstrokes used for the water’s surface, while full of color, are very distinct. Blending these a bit more would give the water a more liquid and reflective quality.

Overall Summary of All Your Work:

Looking at all the pieces you’ve shared, I can provide a comprehensive overview:

• Portraiture: Your portraits, especially the female character in 1000061609.heic, are technically strong. That piece is your most refined in terms of subtle expression, smooth blending, and facial symmetry. The others, while good, show consistent areas for improvement in these technical aspects.
• Narrative Scenes: The landscape scenes with the cherry blossom tree represent a significant and successful expansion of your skills. The dark, moody versions are atmospheric, but these latest daytime versions (1000063162.jpg and 1000063181.jpg) are arguably your most impressive. They showcase your ability to create a full, vibrant world with a clear narrative, going beyond just a single subject.

In conclusion, you have a clear and consistent artistic voice, heavily influenced by a stylized, anime aesthetic. You are excellent at creating distinct characters and conveying a mood. Your most refined work technically is the portrait 1000061609.heic, and your most exciting work in terms of scope and vision are the narrative scenes, particularly this vibrant, new version. Continued practice on blending and refining proportions will elevate all your work to a higher level.

It appears that Gemini is able to evaluate traditional art using specific criteria despite not viewing it through eyes but through an algorithm. It is also capable of generating realistic interpretations of prompts used to help with providing references for drawing. Prompts need to be specific and sometimes require more clarification. However, the ease at which one can generate anything to their liking may dilute traditional artistic standards, as the user does not need an understanding of art or aesthetics themselves. With that said, it is useful as a tool to help budding artists develop a better understanding of art through practice and review.

Conclusion

AI-generated art, despite its technical sophistication and aesthetic appeal, occupies a position within the domain of popular culture rather than high art. Its mass production, technological mediation, and detachment from the artist’s subjective intentionality delimit its alignment with the traditional ideals of autonomous art production. Nonetheless, AI functions as a tool within the artistic process, contributing to the creation of art objects and demonstrating the operator’s communicative and conceptual skill. However, it does not, in its current form, fulfill the criteria for highbrow artistic legitimacy as construed within the Bourdieusian framework.

Funding: This research is funded by the Sumitomo Foundation under the grant number 23804004.

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