LA REPRESENTACIÓN DEL GÉNERO EN LA ERA DE LA INTELIGENCIA ARTIFICIAL: Hacia una traducción más inclusiva del Español al Italiano.

In the digital age, AI-generated machine translation has revolutionized the way we interact globally. In this context, gender representation has become a crucial issue at the intersection of language, culture, and technology. However, despite advances, many challenges remain, particularly regarding gender misrepresentation. This study explores how ChatGPT 3.5, when translating textual segments from Spanish to Italian —two typologically similar Romance languages— often perpetuates and, in some cases, exacerbates gender biases. Large Language Models (LLMs), such as neural network-based machine translation systems, typically rely on vast datasets to learn linguistic patterns. However, these datasets can reflect inherent societal gender biases, leading to biased translations. This phenomenon not only has linguistic implications but also cultural and social ones, as it perpetuates gender stereotypes that can influence the perception and understanding of gender roles across different cultures. Moreover, these errors can be particularly problematic in contexts where accuracy and neutrality are essential. Therefore, addressing these challenges is crucial to promote more inclusive and accurate gender representation. This requires a combination of technical and ethical approaches: on the one hand, AI developers must work on gender-sensitive algorithms and carefully select training data to reduce biases; on the other, it is important to foster critical awareness of gender representation in society and promote diversity and inclusion in the design and use of AI-based systems.