GROWTH: An Interdisciplinary Analysis of gender-based discrimination in Translation Technology

We present a novel and multidisciplinary approach to reflect on and address issues related to gender bias in Machine Translation (MT) systems. With MT systems, we refer to technology that can automatically translate from one language into another (e.g. Google Translate). Due to its ubiquitous presence in our societies, MT systems have been subject to heavy scrutiny, in particular, their current tendency to perpetuate (gender) biases. For example, the English sentence ‘my husband is a kindergarten teacher’ is translated by Google Translate as ‘mijn man is kleuterjuf [feminine]’ in Dutch (April 19, 2023). While there have been attempts to address some of these biases (e.g. Vanmassenhove et al. 2018; Stanovsky et al. 2019; Salvoldi et al. 2021; Tomalin et al. 2021), the issue(s) remain largely unsolved and the solutions proposed focus merely on the computational linguistic aspect but do not take into consideration the broader societal and cultural context nor the actual stakeholders. With this proposal, we present an original framework, which offers legal, ethical and linguistic insights leading to recommendations for the mitigation of the current MT systems’ gender biases.