Tom White

aka Dribnet

American

1971

Tom White, aka Dribnet, is a New Zealand–based artist and researcher whose practice explores how machines see and interpret the world. He treats AI as a creative partner, making its unfamiliar vision visible and revealing patterns of meaning that lie beyond human perception.

Image courtesy the artist.

Full Bio

Tom White, aka Dribnet, is a New Zealand–based artist and researcher. He studied computer graphics and visual design at the MIT Media Lab’s Aesthetics and Computation Group, completing his master’s degree in 1998. He is a lecturer at the Victoria University School of Design in Wellington, where he teaches creative coding, interaction design, and neural networks, and leads research in neural design. His early academic work at MIT included collaborations with peers in the Aesthetics and Computation Group, grounding his practice in technical and artistic research. He also publishes public projects on platforms such as Observable, reflecting his commitment to shared experimentation.

White’s artistic practice investigates what he calls the “Algorithmic Gaze,” using abstraction to explore how machines register and represent visual reality. His works often appear ambiguous to human viewers but are consistently recognized by neural networks, exposing the logics and biases of machine vision. His approach makes machine vision visible by staging situations where its modes of reading emerge, using misclassification, ambiguity, and constraint as material. In Perception Engines in 2017, he trained algorithms on thousands of images to produce abstract forms legible to AI but strange to us, suggesting the emergence of a distinct machine visual language. Synthetic Abstractions in 2018 extended this approach to automated moderation systems, generating images misread by Google SafeSearch and Amazon Rekognition and showing how fragile such filters can be. With Ants in 2021, he pushed further by designing a feedback loop where networks generated and then curated their own depictions of ant-ness, treating algorithms as active participants in the creative process. Other series, such as Portrait Manifold and Electric Fan, continue this line of inquiry, emphasizing how learning systems compress and reorganize categories into unexpected visual outcomes. Across all of these projects, White positions AI as a partner in the making of images, constructing a practice that probes the boundaries of human and machine vision.

White’s work has been recognized internationally, with exhibitions at Nature Morte in New Delhi, Honor Fraser Gallery in Los Angeles, Sapar Contemporary in New York, Unit London, Kate Vass Galerie in Zurich, and Le Cube in France, along with a permanent display at Oyfo Kunst & Technniek in the Netherlands. His projects have been presented at MoMA, Ars Electronica, SIGGRAPH, and the National Taiwan Museum of Fine Arts. He took part in Gradient Descent in 2018, the first major gallery exhibition of AI art in India, and in 2025 his series Synthetic Abstractions was reissued on Objkt as part of Pioneers, a program honoring foundational works of digital art.