ABOUT
A++ focuses on the identity and bodily sensation of GenZ and Millennial generations. We discuss the "see / be seen" relationship described in the post-internet era clothing history, and create works focusing on semiotic interpretation and materiality.
Makoto Amano
Technical Lead
Pursuing UI/UX design using geometrical and algorithmic methods and practicing Human Augmentation in the arts domain at M.A. program in Department of Media Creation in IAMAS, Japan.
Hanako Hirata
Design Lead
Studies fashion design and theory research in Keio university, Japan. Her work focuses on fashioned-body in the post-internet age, through a scope of both biomaterial research and CG expression.
Ryosuke Nakajima
Engineering
With a degree of M.A. x-Design program in Media and Governance in Keio University, Japan, Ryosuke speculates and practices on the subject of ontological turn in Artificial Intelligence while co-creating with AI.
Yuka Sai
Design / Movie
Currently spending her senior year at Keio university, Japan. Through her mixed-media pieces, Yuka seeks an alternative context of fashion.
With the advent of an AI-based surveillance society, we humans are digitizing all everyday behavior. They are identified as race, gender, age, and human, and their information is exploited for efficiency. For this reason, we propose "21st century camouflage clothing" that is not labeled "human" from the eyes of AI. Thinking about camouflage in modern times, we made camouflage clothing as a jacket that sampled the history of military.
SECOND EPOCH
FIRST EPOCH
With the development of AI technology using deep learning, a surveillance society using AI has arrived. Excessive surveillance and privacy threatened by humans living today. Therefore, we take advantage of the weakness of AI's image recognition and propose "21st century camouflage clothing" to protect privacy from the eyes of AI. It learned specific patterns so that the percentage of people identified as "persons" by the image recognition model was reduced, and created camouflage clothing as tops based on the generated images.