Algorithmic methods are increasingly being used to identify and categorize human characteristics. A range of human identities, such as gender, race, and sexual orientation, are becoming interwoven with systems. This entry discusses the case of automatic gender recognition technologies that algorithmically assign binary gender categories. Based on previous work with trans participants in human–computer interaction (HCI), this entry examines the ways in which current gender recognition systems misrepresent complex gender identities and undermine safety. Future work can build on this foundation by conducting participatory design workshops with designers and potential users to develop improved methods for conceptualizing gender identity in algorithms.