The Misgendering Machines

Citations Over TimeTop 1% of 2018 papers

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.

Related Papers

• → Challenging the Cisgender/Transgender Binary: Nonbinary People and the Transgender Label(2020)162 cited
• → Preferences for and barriers to gender affirming surgeries in transgender and non-binary individuals(2021)32 cited
• On Subject And Subject′ s Construction(2005)
• Susquehanna Chorale Spring Concert "Roots and Wings"(2017)
• → Non-Substantial Individuals In Aristotle’S Categories(2004)