Exploring a Makeup Support System for Transgender Passing based on Automatic Gender Recognition

要旨

How to handle gender with machine learning is a controversial topic. A growing critical body of research brought attention to the numerous issues transgender communities face with the adoption of current automatic gender recognition (AGR) systems. In contrast, we explore how such technologies could potentially be appropriated to support transgender practices and needs, especially in non-Western contexts like Japan. We designed a virtual makeup probe to assist transgender individuals with passing, that is to be perceived as the gender they identify as. To understand how such an application might support expressing transgender individuals gender identity or not, we interviewed 15 of them in Tokyo and found that in the right context and under strict conditions, AGR based systems could assist transgender passing.

著者
Toby Chong
The University of Tokyo, Hongo, Japan
Nolwenn Maudet
Université de Strasbourg, Strasbourg, France
Katsuki Harima
Harima Mental Clinic, Tokyo, Japan
Takeo Igarashi
The University of Tokyo, Tokyo, Japan
DOI

10.1145/3411764.3445364

論文URL

https://doi.org/10.1145/3411764.3445364

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Various People

[A] Paper Room 13, 2021-05-11 17:00:00~2021-05-11 19:00:00 / [B] Paper Room 13, 2021-05-12 01:00:00~2021-05-12 03:00:00 / [C] Paper Room 13, 2021-05-12 09:00:00~2021-05-12 11:00:00
Paper Room 13
13 件の発表
2021-05-11 17:00:00
2021-05-11 19:00:00
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