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The impact of AI on social behavior and cultural cognition is becoming more significant. The development of AI is no longer just a technological issue; it profoundly affects cultural aspects.

Regional cultural training to counter AI bias involves combating prejudice through archiving. It aims to address historical and representational biases by reestablishing data from different cultural contexts. Aim to train AI systems to understand and adapt to a broader range of human experiences. The goal is to create and maintain rich, region-specific databases and establish a novel open-source community to address gaps and biases in mainstream AI datasets.

Taking the common Taiwanese food, “pig’s blood cake,” as an example, the project collects various data related to pig’s blood cake, including its appearance, production process, ingredient sources, regional variations, and cultural significance in different communities. This data can enable AI to more accurately identify and understand the uniqueness of pig’s blood cake as a specific cultural food. Ultimately, this project aims to enhance AI’s sensitivity and accuracy regarding Taiwan’s distinctive cultural elements.

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Production Crew List

Creator: Dimension Plus

Project Host: Escher Tsai

Producer: Szu-Ya Wang

Technical Coordinator: Tzu-Chen Lee Technical Support: Seth Hon / Reviles Huang

Interface Design: Seth Hon

Production Team: Monique Chiang / Jessie Huang / Ping-yi Chen / Zun-Yu Tan

Installation Production: Hozen Studio 

Organizer: Taiwan Creative Content Agency / Ars Electronica Center

Co-organizer: Quanta Research Institute

Special Thanks: Keith Lam / Tyng-Ruey Chuang / Tim Wei 