The Misgendering Machines

Abstract

Automatic Gender Recognition (AGR) is a subfield of facial recognition that aims to algorithmically identify the gender of individuals from photographs or videos. In wider society the technology has proposed applications in physical access control, data analytics and advertising. Within academia, it is already used in the field of Human-Computer Interaction (HCI) to analyse social media usage. Given the long-running critiques of HCI for failing to consider and include transgender (trans) perspectives in research, and the potential implications of AGR for trans people if deployed, I sought to understand how AGR and HCI understand the term "gender", and how HCI describes and deploys gender recognition technology. Using a content analysis of papers from both fields, I show that AGR consistently operationalises gender in a trans-exclusive way, and consequently carries disproportionate risk for trans people subject to it. In addition, I use the dearth of discussion of this in HCI papers that apply AGR to discuss how HCI operationalises gender, and the implications that this has for the field's research. I conclude with recommendations for alternatives to AGR, and some ideas for how HCI can work towards a more effective and trans-inclusive treatment of gender.

One Voice Fits All?

“…As the research highlighted in this paper illustrates, decisions about whether a smart device reflects a gender through its voice and other characteristics has profound impacts on user interaction, and particular gender choices lead to stereotypes and other social implications [35]. Indeed, the voices of both social robots and voice assistants are often gendered as male or female by default [46], which reinforces a problematic notion that gender is a binary [33].…”

Female librarians and male computer programmers? Gender bias in occupational images on digital media platforms

“…As we will discuss in subsequent sections of this article, we acknowledge that our study is significantly limited because it takes a binary approach to gender, meaning we only discuss men and women in our analysis. However, we hope that our discussions of this limitation bring continued attention to wider problems with ways in which media, technical systems, and data collection instruments operate within frameworks that assume a gender binary and subsequently perpetuate inequities against nonbinary people (Keyes, 2018;Spiel, Keyes, & Barlas, 2019).…”

Human-Computer Insurrection

“…In the case of gender, there are several examples of this approach being done-in particular Alsheikh et al's work on intimacy in Arab contexts, and Alex Ahmed's work on trans-inclusive interaction design [4,9]. Nonetheless, we have (as other papers note) much progress to make [84,123].…”