Roles of Artificial Intelligence (AI) in Climate Fiction Translation
Abstract
This study investigates the role of AI in translating climate fiction (Cli-Fi) literature, focusing on key challenges such as metaphorical language, cultural references, and specialized climate terminology. By analyzing the English narrative Woodland, the research examines how AI-assisted translation handles the nuanced linguistic and cultural features critical to disseminating Cli-Fi and raising awareness of climate change issues. This study employs an error analysis framework by the American Translator Association (ATA) error parameters to evaluate the accuracy and quality of AI-generated translations compared to human efforts. The results shows that there are 26 metaphors, 23 cultural words, and 10 climate terms found in the data, while the errors mostly found in the meaning transfer. The findings highlight both the potential and limitations of AI in literary translation, especially in terms of cultural specificity and metaphor interpretation. The findings offer practical insights for translators, AI developers, and climate communicators seeking to enhance AI’s effectiveness in cross-cultural and environmental literary dissemination. This research provides the view that AI can assist translators in translating and analyzing. The study also opens up opportunities for cross-disciplinary collaboration between linguists, translators, literary practitioners, and AI observers to create more in-depth solutions to understand climate change through a multidisciplinary approach.
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