Gender Recognition or Gender Reductionism?

TLDR

Automatic Gender Recognition (AGR) uses computational methods to identify gender from images, video, or audio and is increasingly applied in security, marketing, and social robotics, yet little is known about stakeholders’ perceptions, especially among vulnerable communities. The study interviewed 13 transgender individuals, including three transgender technology designers, to explore their perceptions and attitudes toward AGR. The authors developed recommendations for accommodating gender diversity in digital systems based on the interviews. Transgender participants expressed overwhelmingly negative attitudes toward AGR, questioning its accuracy and raising privacy and harm concerns about misgendering.

Abstract

Automatic Gender Recognition (AGR) refers to various computational methods that aim to identify an individual's gender by extracting and analyzing features from images, video, and/or audio. Applications of AGR are increasingly being explored in domains such as security, marketing, and social robotics. However, little is known about stakeholders' perceptions and attitudes towards AGR and how this technology might disproportionately affect vulnerable communities. To begin to address these gaps, we interviewed 13 transgender individuals, including three transgender technology designers, about their perceptions and attitudes towards AGR. We found that transgender individuals have overwhelmingly negative attitudes towards AGR and fundamentally question whether it can accurately recognize such a subjective aspect of their identity. They raised concerns about privacy and potential harms that can result from being incorrectly gendered, or misgendered, by technology. We present a series of recommendations on how to accommodate gender diversity when designing new digital systems.