Participatory Research as a Path to Community-Informed, Gender-Fair
  Machine Translation
Dagmar Gromann Manuel Lardelli Katta Spiel Sabrina Burtscher Lukas Daniel Klausner Arthur Mettinger Igor Miladinovic Sigrid Schefer-Wenzl Daniela Duh Katharina Bühn
Recent years have seen a strongly increased visibility of non-binary people
in public discourse. Accordingly, considerations of gender-fair language go
beyond a binary conception of male/female. However, language technology,
especially machine translation (MT), still suffers from binary gender bias.
Proposing a solution for gender-fair MT beyond the binary from a purely
technological perspective might fall short to accommodate different target user
groups and in the worst case might lead to misgendering. To address this
challenge, we propose a method and case study building on participatory action
research to include experiential experts, i.e., queer and non-binary people,
translators, and MT experts, in the MT design process. The case study focuses
on German, where central findings are the importance of context dependency to
avoid identity invalidation and a desire for customizable MT solutions.