The paper ‘Gender Neutralization for an Inclusive Machine Translation: from Theoretical Foundations to Open Challenges‘, by Andrea Piergentili, Dennis Fucci, Beatrice Savoldi, Matteo Negri, and Luisa Bentivogli was accepted at the Gender Inclusive Translation Technologies workshop at EAMT 2023.
Gender inclusivity in language technologies has become a prominent research topic. In this study, we explore gender-neutral translation (GNT) as a form of gender inclusivity and a goal to be achieved by machine translation (MT) models, which have been found to perpetuate gender bias and discrimination. Specifically, we focus on translation from English into Italian, a language pair representative of salient gender-related linguistic transfer problems. To define GNT, we review a selection of relevant institutional guidelines for gender-inclusive language, discuss its scenarios of use, and examine the technical challenges of performing GNT in MT, concluding with a discussion of potential solutions to encourage advancements toward greater inclusivity in MT.