Does AI Reflect Human Behaviour? Exploring the Presence of Gender Bias in AI Translation Tools

Marco Smacchia (), Stefano Za () and Alvaro Arenas ()
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Marco Smacchia: University “G. D’Annunzio” of Chieti-Pescara
Stefano Za: University “G. D’Annunzio” of Chieti-Pescara
Alvaro Arenas: IE Business School

A chapter in Digital (Eco) Systems and Societal Challenges, 2024, pp 355-373 from Springer

Abstract: Abstract Natural language processing tools are becoming more and more important in our daily life, enabling us to perform many tasks in a timely and efficient manner. However, as the utilisation of these tools growth, so does the risk of unexpected consequences due to the presence of bias. This study investigates the presence of gender bias within the most popular neural machine translation and large language model tools. We defined a set of Italian sentences concerning ten specific jobs, where the gender of the subjects is not explicitly mentioned. Employing those AI tools, we translated the sentences from Italian to English, requiring the gender to be explicitly mentioned. Afterwards, we developed a survey to obtain human translations for the same sentences, allowing us to compare the differences between the responses generated by the tools and those from individuals. Results show a high presence of gender bias especially for the jobs associated with a male gender and demonstrate a consistency between the outcome obtained by the tools and the results of the survey. These findings serve as a starting point for exploring the origins of gender bias within natural language processing tools and how they reflect gender distributions in our society and human behaviour regarding job occupations.

Keywords: Natural language processing; Neural machine translation; Large language models; Gender bias; Artificial intelligence bias (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/978-3-031-75586-6_19

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