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Jiayi Young
ProffesorJiayi Young is an Assistant Professor of Design at the University of California, Davis. Her interest lies within the discipline of experimental media as it applies to the intersection of art, design, science and technology. Using a dynamic combination of materials, methods, concepts and subjects, she creates experiences and environments that allow for the virtual to inform the actual and vise versa. As an artist and designer, her current research and creative work is focused in the emergent fields of data mapping and sensor-driven objects, interfaces, projections, and immersive environments. Using multidisciplinary approaches, her work examines contemporary society including the culture of consumption, the programming and exploitation of the feminine, cultural assimilation, and personal identity. Young is deeply invested in exploring the place of the “self”, as we attempt to balance technology with questions about the human condition.
Her work has been published and exhibited nationally and internationally, including the International Symposium of Electronic Art (ISEA); the Leonardo Electronic Almanac (LEA); Hall of Science, New York; the United Nation’s Fourth Conference on Women, Beijing, China; the Hermitage Museum, St. Petersburg, Russia; and Moltkerei Werkstatt, Cologne, Germany.
The project transforms data from the 2016 US presidential election into a large-scale immersive installation exploring how social media influences public opinion and a nation’s future. Using flickering lights, ticking sounds and fluid dripping from IV bags, it visualises Twitter activity between February and November 8, 2016, revealing how human users and automated bots interacted to spread political messages. The project collected around 10 GB of Twitter data daily and developed through two earlier prototypes, Twitter Rain and Fields of Gold, which tested the representation of tweet activity through water, light and sound. In collaboration with a big data analytics research group at UC Davis, the project further investigates influential accounts, patterns of information propagation and the distinction between human-generated and AI-generated tweets.
