The Curatorial Turn
How AI Art Redefines Artistic Practice Through Taste
For a few months my friends complained that their older relatives were sending them obvious AI slop that was unbearably cringe. After enjoying this content ironically for a bit the narrative quality improved enough that the same young people that laughed at boomers falling for AI are now falling for it themselves. There is a category of AI content now that is just sincerely enjoyable.
This video made me feel things I can hardly describe.
This progress has definitely annoyed a lot of people who deny that there is even a category of thing called “AI art”. A certain framing captivates many who want to believe that art is about “engaging with the artist” or requires “authenticity”. A contradictory framing champions advancing AI capability as democratizing creativity and liberating art from technique. Both sides miss the point because they're still thinking about art through the lens of Romantic individualism, the 19th-century notion that art is primarily about personal expression flowing from artist to audience.
But what if that entire framework is wrong? What if the real crisis isn't about authenticity but about the collapse of something much deeper, the communities of practice that have sustained artistic knowledge for millennia?
To understand what's genuinely at stake with AI art, we need to step back from our modern assumptions and recover a more sophisticated understanding of how art actually works in human communities.
From Art as Skill to Art as Expression
Consider how art functioned for most of history. In medieval guilds, artists were skilled craftspeople embedded in communities of technical knowledge. The master sculptor didn't primarily "express himself" but served as a conduit for collective wisdom about stone, light, and sacred proportion.
This model of artist as craftsman understood artistic creation through techne, skilled practice directed toward excellent work. The artist's energeia (being-at-work) flowed outward into the completed work, which then served the community's needs while transmitting technical knowledge to future practitioners.
In "The Archeology of the Work of Art," Giorgio Agamben identifies a shift in our understanding of art beginning with late scholastic theology. These theologians introduced the notion that creation resides in the creator's mind as an idea, God creates according to His mental model, so the artist creates according to theirs. This "disastrous transposition of theological vocabulary onto artistic activity" fundamentally altered art's nature.
The Romantic revolution completed this transformation, making art primarily about the artist's inner life rather than communal service. The work's value came to rest not in technical excellence or community function but in its capacity to express the artist's unique subjectivity. This created what Agamben calls the "artistic machine", a Borromean knot trying to reconcile artist, work, and operation into a coherent whole.
The rise in contemporary art of art-as-performance and of visually uninteresting objects that are only understood with a backstory of artist and process, rather than being an aesthetic degradation to be pilloried, are a cry from within the artistic world to reclaim something beyond machinic production. We're witnessing a return to art as liturgy, where the artist's energeia resides not in external objects but in the performance of aesthetic practice itself.
Three Modes of Artistic Communication
Understanding this liturgical turn requires recognizing that art has always operated through multiple channels simultaneously. By recovering these originary distinctions, we can see more clearly what AI actually threatens, and what it might preserve.
First, the technical mode: Artist-to-artist transmission of embodied knowledge. How to mix colors, how light behaves on different surfaces, how materials resist and respond to manipulation. This is vocational knowledge passed between practitioners who share the discipline of making. The artwork exists as a call or an awakening of vocation within the artistically inclined viewer.
Second, the curatorial mode: Artist-to-community transmission of aesthetic experience. The artist serves as a conduit, opening worlds of meaning and beauty for broader audiences. The artwork exists as the by-product of an artist's engagement with the world through his craft, which communicates something directly to the lay audience. The meaning is not necessarily controlled by the artist, nor is it guaranteed in an audience.
Third, the communal mode: Audience-to-audience formation of interpretive communities. People gather around shared aesthetic experiences, creating collective meaning through dialogue, disagreement, and mutual discovery. The true dialogue of art is not between artist and viewer, but viewers and other viewers who form grammar and community around what they love.
Heidegger captured this in "The Origin of the Work of Art," arguing that genuine artworks don't express the artist's subjectivity but rather "set up" worlds where communities can dwell together. The Greek temple doesn't communicate the architect's inner life, it creates sacred space where a people can encounter the divine.
This triadic structure helps explain why debates about AI art often feel like people arguing past each other. A Van Gogh painting functions differently for a painter studying brushwork than for a lay viewer forming emotional connection than for an art historian analyzing cultural context. The painter sees method, the viewer experiences meaning, the scholar traces influence, all valid but distinct modes of engagement.
What's remarkable is how stable this structure has remained across historical periods. Medieval guilds, Renaissance workshops, 19th-century academies, contemporary MFA programs, all organize around the same basic pattern of technical transmission, community service, and collective interpretation. The content changes (oil techniques vs. digital tools, religious vs. secular themes, aristocratic vs. democratic audiences) but the structural relationships persist.
This persistence suggests something deeper than cultural convention. As Agamben argues, drawing on Aristotle's analysis of human activity, these three modes correspond to fundamental aspects of how humans relate to skilled practice: the transmission of techne between practitioners, the service of communal needs through excellent work, and the formation of shared worlds through aesthetic encounter.
Where AI Art Succeeds and Fails
With this framework in mind, we can assess AI art more precisely. Rather than asking whether it's "real art," we can ask which of these three channels it preserves and which it disrupts.
Communities are forming around AI-generated images with the same patterns of collective interpretation we see around traditional art. Reddit communities, Discord servers, social media discussions—all exhibit the familiar dynamics of aesthetic appreciation, shared vocabulary development, and communal meaning-making.
The curatorial function also remains intact, though transformed. The human "AI artist" serves as a conduit between algorithmic possibility and community need. They curate outputs, refine prompts, select and context pieces. Most importantly, they exercise taste, the capacity to recognize aesthetic quality and cultural relevance.
This curatorial dimension is actually more sophisticated than critics acknowledge. Knowing how to create something that will resonate with an audience requires a deep understanding of aesthetic value and tradition.
The genuine crisis lies in the third channel: technical dialogue between practitioners. Traditional artistic formation involves embodiment, understanding that lives in the hands, eyes, and body rather than in explicit concepts. How paint behaves on canvas, how light changes throughout the day, how color relationships create spatial depth, this knowledge is transmitted through years of material dialogue.
AI art bypasses this entire formation process. The algorithm handles the technical translation from concept to image, leaving the human operator with linguistic rather than material engagement. No struggle with recalcitrant paint, no discovery of unexpected color relationships, no development of hand-eye coordination.
This threatens to break the chain of technical transmission that has sustained artistic practice for millennia. Without communities of practice built around shared struggle with materials, we lose not just techniques but ways of seeing, thinking, and being that constitute the artist's form of life.
Yet this sense of crisis might be overstated. Technology has disrupted artistic practice before without destroying it entirely. Walter Benjamin's "The Work of Art in the Age of Mechanical Reproduction" identified a similar crisis in the 1930s. Photography and film were eliminating art's "aura", its unique presence tied to original context and ritual function. Benjamin worried this would reduce art to mere commodity spectacle.
Yet photography didn't destroy artistic practice. Photographers developed their own forms of embodied knowledge around light, timing, and composition. Decades later digital artists mastered new tools requiring genuine technical sophistication. Each new medium initially appeared to threaten artistic authenticity, then established its own legitimate forms of practice.
The Possibility of Curatorial Formation
The pattern suggests a way forward. Instead of defending traditional practice against AI disruption, we might ask how to cultivate the contemplative communities that could transform AI from threat into genuine artistic medium.
What appears as simple "prompt engineering" could constitute a new form of artistic techne requiring years to master. But this isn't about optimizing outputs, it's about developing the contemplative capacity to see through algorithmic mediation. Just as traditional painters learn to see color relationships by working with pigment over time, practitioners could learn to perceive aesthetic possibility space through sustained dialogue with generative systems. Seeing with and through the algorithm.
Rather than relating to it as an external system that produces images, practitioners might develop such fluency that the AI becomes transparent, a means of aesthetic exploration rather than an object of technical manipulation. How would an artist shaped deeply by communication with AI and developing a grammar around a specific model’s latent space perceive the world as a whole differently? What aesthetic possibilities does that constant dialogue create?
The answer might lie in recovering what we've lost in our current cultural moment. Consider how we experience art today compared to how it functioned historically. Works once made for churches and state buildings and public squares are now cordoned off into specific locations for appreciating aesthetic, reducing the broader world to purely functional. The problem is that a lot of these art museums suck. Curators who should have an intuition for what’s beautiful and what experience a certain arrangement can produce often just lay things out without rhyme or reason. The sensibility to be fluent in the language of curation often comes not from deep study as much as deep practice.
When I look at the Wallace Collection in London or the Morgan Library in New York, it was the specific lives of Sir Richard Wallce and JP Morgan that informed what they found beautiful rather than abstract study. If AI artists are to develop legitimate curatorial capabilities their aesthetic fluency can only emerge through practice, something not conceptually studied but lived and acted.
Photography offers instructive precedent. Early critics dismissed it as mechanical reproduction lacking artistic soul. Yet photographers developed genuinely new forms of aesthetic vision, learning to see light, composition, and temporality in ways impossible before the camera's invention. The technology didn't diminish human aesthetic capacity but redirected it toward new forms of seeing. Digital art followed a similar trajectory.
In both cases, the crucial factor wasn't the technology itself but the contemplative communities that formed around sustained practice. Photographers developed darkroom cultures of mutual learning. Digital artists created communities around shared tool exploration. The technology enabled new aesthetic possibilities, but only through disciplined collective inquiry.
The possibility for AI art lies in developing similar contemplative communities, groups of practitioners committed to understanding how algorithmic generation might extend rather than replace human aesthetic capacity. This requires moving beyond the current paradigm of AI-as-tool toward AI-as-medium, developing fluency that makes the technology transparent to aesthetic inquiry.
When AI becomes truly ready-to-hand for aesthetic practice, practitioners stop thinking about prompt optimization and start thinking through algorithmic possibility toward aesthetic goals that transcend any particular technical implementation. They develop intuitive understanding of how creative intention translates through generative systems, learning to work with rather than against algorithmic tendencies.
Why This Matters Beyond Art
The real reason I've been thinking about AI art isn't purely concern for artists or aesthetic theory, it's that AI forces us to examine assumptions we've carried unconsciously for decades. When a machine can generate images and videos that move us aesthetically, we suddenly have to articulate what we thought we already knew about creativity, skill, and human value.
This is happening across domains. AI writing challenges our assumptions about authorship and intelligence. AI programming questions what we mean by problem-solving and expertise. Each capability that machines acquire forces us to dig deeper into what we actually value about human activity in that domain.
For art specifically, AI has revealed how much of our aesthetic discourse was really about maintaining cultural gatekeeping rather than understanding beauty itself. The people most threatened by AI art often can't articulate why it's inferior beyond appeals to "authenticity" that would have made no sense to medieval craftsmen or Renaissance masters. Meanwhile, the people most excited by AI art often reduce human creativity to mere technical problem-solving that machines can optimize away.
Both responses miss what's actually happening: we're being forced to rediscover what art does that matters beyond producing aesthetic objects. The triadic structure I've outlined: technical transmission, curatorial service, community formation; only became visible to me because AI presented a definitional challenge. The machine forced the question: what exactly are we trying to preserve?
This is why I'm ultimately optimistic about AI's cultural impact. Not because it will democratize creativity or eliminate artistic labor, but because it will force us to think more clearly about what we value and why. The communities that emerge around thoughtful AI art practice might develop more sophisticated understanding of aesthetic formation than we've had in generations.
We are, as Heidegger reminded us, the beings concerned with our own being. That capacity for self-reflection and conscious value-formation might be our most distinctly human characteristic. AI doesn't threaten this, it occasions it. Every domain AI enters becomes an opportunity to examine what we've been taking for granted and to choose more deliberately what we want to preserve and cultivate.
The question isn't whether AI will change art, it already has. The question is whether we'll use this disruption as an opportunity for deeper understanding or simply react defensively to protect existing institutions. The former path leads to communities of practice that could sustain and develop aesthetic intelligence in ways we can barely imagine. The latter leads to museums full of dead objects that no one knows how to see anymore.