The Role of Human Agency in AI-Assisted Classical Chinese Translation: A Case Study of the Pumenpin

This study examines the role of human agency in AI-assisted translation, focusing on how the selection of reference databases influences the translation of Classical Chinese Buddhist texts. Using Retrieval-Augmented Generation (RAG) with the Deepseek R1 model, the research evaluates how consciously selected knowledge sources impact translation accuracy and doctrinal interpretation. The study applies this methodology to the Pumenpin chapter of the Fahuajing, analyzing multiple translation iterations with varying reference materials. Evaluation is conducted against authoritative translations to assess accuracy, doctrinal nuance, and interpretive biases. The study demonstrates that AI does not replace human expertise but instead requires active engagement in selecting reference sources, which fundamentally shape translation outcomes. This research establishes a methodological framework for AI-assisted religious text translation, emphasizing the necessity of human oversight to maintain theological coherence while leveraging computational advancements. It highlights the evolving role of translators in curating AI inputs rather than merely post-editing outputs.