About Vibeke Bertelsen

Vibeke Bertelsen (Udart) transforms AI's generative errors into explorations of post-human identity. She embraces algorithmic anomalies—distorted limbs, multiplying faces, impossible anatomies—as formal elements that reveal how machines parse flesh into data. The name "Udart" derives from a Danish word meaning unpredictable evolution, capturing her method of working with, rather than against, technological glitches.

In her work individual bodies merge into new collective beings—faces overlap with faces, limbs multiply and intertwine, and single forms dissolve into crowds of morphing flesh, creating entities that transcend individual identity.

Udart's distinctive aesthetic emerged from her early experiences in Copenhagen's underground visual culture, where she began as a VJ for concerts and club nights. Today, she's part of the renowned Vertigo Artist Studio in Copenhagen, where she creates visual art for concerts and theater productions.

Whether transforming fingers and hands into dancing figures or creating kaleidoscopic videos of faces, she pursues unexpected visual outcomes. Instead of trying to fix AI's quirks like strange-looking hands, she leans into the glitches and makes it her signature style.

While engaging with AI art, Udart draws inspiration from both old and current developments in art. She feels a kinship with surrealists and dadaists who challenged established visual conventions, seeing their approach as a way to navigate the absurdity and chaos of today's political landscape. Her work channels this spirit of disruption, using AI to challenge fixed notions of what bodies mean in our algorithmically mediated world.

Through her work, Udart questions fundamental assumptions about permanence and identity. Her distorted, overlapping figures exist in perpetual states of becoming – neither fully formed nor completely dissolved. This aesthetic of bodily excess and multiplicity challenges viewers to reconsider the relationship between human flesh and digital algorithms, asking what remains of the self when reduced to data points and probabilities.