Sometimes, when I walk into an exhibition and see a huge wall of text right at the start, I immediately feel overwhelmed. The barrage of abstract, convoluted language can be intimidating and confusing. Take this kind of example: “Peter Rogiers is and remains one of those sculptors who, averse to all personal interests, remains stubbornly committed to his art, refusing to create any form of languid art. His new drawing can further be considered a thought-mold where worlds tilt, and imagination chases off grimy reality.” Not only does this type of writing confuse me, but it also feels oddly mechanical, almost robotic. It’s like we don’t actually know who Peter Rogiers is, what he’s trying to say, or even where he’s coming from—but we’re left feeling like maybe we should.
This sense of confusion seems shared by Alix Rule and David Levine in their 2012 essay International Art English (IAE), where they dissect this dense, jargon-heavy style of language that dominates the world of contemporary art. They analyzed press releases, especially those from e-flux, to highlight how this special type of language—formal, abstract, and often difficult to understand—has taken over. They called it International Art English, which has become a global dialect for galleries, museums, and art publications. With its passive structures and theoretical buzzwords, IAE has become the go-to method for talking about art, but it often feels detached from reality.
As AI makes its way into the creative world, including art criticism, it thrives in this environment where IAE is the norm. AI can easily produce critiques that sound fluent in this complex art-speak. It can mimic the phrases and tone of IAE almost perfectly. The problem, however, is that AI’s ability to replicate IAE exposes the limitations of this type of language. While AI can produce text that fits neatly into the art world’s expectations—using phrases like “interrogates the boundaries of” or “foregrounds materiality”—what it generates often sounds polished but hollow, lacking genuine insight or emotional depth.
IAE and AI art critiques both tend to obscure meaning rather than clarify it. Both use formal, academic language to create an intellectual distance between the artwork and the viewer. When AI replicates this, it compounds the issue. The critique sounds professional, but it’s often vague, filled with buzzwords like “problematize” or “subvert” that can leave the reader more confused than enlightened. The risk is that AI could amplify the problems of IAE, reproducing the same kind of writing without challenging its usefulness, and making art criticism feel more alienating and inaccessible.
By relying so heavily on IAE, AI struggles to break free from established patterns. It lacks the originality and personal insight that human critics bring to their work. Both IAE and AI critiques lean heavily on familiar conventions, but they rarely provide fresh perspectives. This can lead to a homogenized art world, where critiques sound the same and fail to resonate with broader audiences.
Ultimately, the rise of AI and the dominance of IAE offer a chance for the art world to rethink how it communicates. There’s a real opportunity here to make art criticism more inclusive, accessible, and engaging. We can move away from language that feels distant and inaccessible, and toward a way of discussing art that connects with people on a more emotional and personal level.
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Very interesting topic! I too have noticed how sometimes the language used in discussion of artworks is overly-complicated and hard to consume. This seems to be a longstanding tradition, possibly due to the historical association of art with elitism and intellectualism – if you want to speak or read about art you must be smart enough for that type of language (which is ridiculous). The truth is however that the jargon level of English used in those texts hardly comes natural to anyone and since their point is to educate and pass through some information its a pity that they fail to make it engaging. A very interesting point you make is that since AI leans trough already existing examples, it will further deepen the problem and the language may stay this way forever.