“Hidden Incidents of Pet Food” merges AI, data visualization, and research to explore the commodified human-pet relationship under capitalism. This project examines the economic impact of pet affection, particularly through pet food, a key market commodity. It investigates pet food production’s “race to the bottom,” highlighting the use of unhealthy ingredients, toxic substitutes for profit, and cross-species poisoning from chemicals like Taurine, Melamine, and Pentobarbital. The series includes five segments. A web-based interactive visualization focuses on entangled relationships. Digital artwork analyzes 6,000 pet economy incidents, highlighting the impact of taurine deficiency in cats. A spatial-temporal visualization of melamine contamination across feed, pet food, and human food. An interactive dual-screen installation on the multi-species secondary poisoning caused by the euthanasia drug Pentobarbital. An incorporation of real-life archives documenting these events provides a comprehensive examination of pet food-related issues. The artwork aims to reveal obscured stories of the under-acknowledged realm of pet food-related issues and draw connections across the historical, current, and future landscape of pet food-related life issues.

Employing AI technology to reconstruct these incidents, the artwork bridges the gap between fact and fiction, employing AI as both a tool of revelation and a medium for artistic expression. Artist Statement (195 words): Ziwei Wu is a media artist and researcher born in 1996 in Shenzhen, China. She had an outstanding graduate bachelor’s degree from the China Academy of Art, School of Intermedia Art (SIMA), and a Master of Fine Art with distinction in Goldsmiths, the University of London in Computational Arts. She is a Ph.D. candidate in the Academy of Interdisciplinary Studies, majoring in Computational Media and Arts (CMA) at the Hong Kong University of Science and Technology. Her artworks and research primarily focus on biology, science, and their impact on society, utilizing various media. She engages in interdisciplinary studies of Artificial Life Art, exploring the intersection of art and research with biology as concepts, bio information as data, and biomaterial as the medium. She is a Lumen prize; Batsford prize winner and Longlist in Information is Beautiful Award. Her research was published in the SIGGRAPH Art Program, ISEA, and Artificial Life Journal in MIT Press. She has exhibited at international venues, including Ars Electronica in Linz, CYFEST in Russia, Norwegian BioArt Arena (NOBA), Watermans Gallery and Cello Factory in London, NeurIPS AI Art Gallery, Run Run Shaw Creative Media Centre in Hong Kong, and so on.

Software Visualization of taurine data (Video): Unity, Final Cut Pro, DCGAN AI Model, Maya, Visual Studio Code Visualization of melamine data (Video): Unity, Final Cut Pro, Photoshop, Visual Studio Code Visualization of pentobarbital data: Information screen (Web): Visual Studio Code Roaming screen (Software): Unity, 3DGAN AI Model, DreamGaussian AI Model, Visual Studio Code Visualization of interactive timeline (Web): Visual Studio Code Hardware Visualization of taurine data: Sony Projector, Maxhub Interactive Touch Screen Visualization of melamine data: Maxhub Interactive Touch Screen Visualization of pentobarbital data: Any-touch Interactive Touch Screen, Epson Short-Throw Projector Visualization of interactive timeline: Sony Projector, iPad

Credits:

Principal artist and researcher: Ziwei Wu

Cooperate: Danlu Fei, Xiaofu Jin, Burak Korkmaz, You Wen, Yifang Wang

Special thanks: Xinyu Ma, Guangda Zhu,

Supervisor: Prof. Kang Zhang

Acknowledgments: Ngaio Richards, Robert Jankowski, Marta Herrero Villar, Katie Wells, Xavier Ho, Jon McCormack

Data sources from organizations: World Health Organization, Food and Drug Administration, USGS National Wildlife Health Center, Veterinary Poisons Information Service, US Fish & Wildlife Department Services, Wildlife Incident Investigation Scheme, Veterinary Medicines Directorate, Institute for Game and Wildlife Research

Support received from：

Hong Kong University of Science and Technology, VisLab in HKUST, Computational Media and Arts (CMA) Lab in Hong Kong University of Science and Technology, SensiLab in Monash University