Gender Bias in Translation Automation
Marta García González · 2024
Machine translation (MT) has become an essential tool for overcoming language barriers and facilitating cross-cultural communication. However, it has also raised significant concerns, particularly regarding gender bias—the tendency of MT systems to produce translations that reinforce stereotypical gender roles and fail to accurately reflect individual differences in ability or behavior. Gender bias in MT is a complex, multifaceted issue, with far-reaching ethical and practical implications, as MT systems not only reflect existing societal inequalities but also contribute to amplifying them. This chapter explores the issue of gender bias in MT, discussing its implications, methods of identification, and various mitigation strategies. It aims to enhance our understanding of the challenges involved in developing ethical and inclusive MT systems, ultimately contributing to the promotion of gender equality and social progress through language technology, rather than the exacerbation of the issues hampering them.