An evaluation of 240 English-to-Greek translations shows Google Translate and DeepL exhibit persistent male bias, while a prompted GPT-4o can generate gender-inclusive alternatives for ambiguous sentences.
Gender Bias in Machine Translation and The Era of Large Language Models
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abstract
This chapter examines the role of Machine Translation in perpetuating gender bias, highlighting the challenges posed by cross-linguistic settings and statistical dependencies. A comprehensive overview of relevant existing work related to gender bias in both conventional Neural Machine Translation approaches and Generative Pretrained Transformer models employed as Machine Translation systems is provided. Through an experiment using ChatGPT (based on GPT-3.5) in an English-Italian translation context, we further assess ChatGPT's current capacity to address gender bias. The findings emphasize the ongoing need for advancements in mitigating bias in Machine Translation systems and underscore the importance of fostering fairness and inclusivity in language technologies.
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Gender Bias in English-to-Greek Machine Translation
An evaluation of 240 English-to-Greek translations shows Google Translate and DeepL exhibit persistent male bias, while a prompted GPT-4o can generate gender-inclusive alternatives for ambiguous sentences.