From Canon to Code: Rethinking the Translation Policy of the BDK Buddhist Canon Project in the Age of AI
In recent years, AI technologies have increasingly been applied to the translation of sacred texts, a field often regarded as one of the last bastions of human translation. Drawing on González Núñez’s framework of translation policy, this paper examines the translation management, practice, and beliefs of the BDK Buddhist Canon Project, one of the most ambitious modern efforts to translate the Chinese Buddhist canon into English. The findings demonstrate that BDK has developed a scholar-led, dissemination-oriented model that seeks to balance translation accuracy with reader accessibility. Compared with AI translation, this model retains clear strengths in interpretive depth, philological accuracy, and ethical accountability. At the same time, AI translation continues to intensify some of its own limitations, including the absence of a clear AI-use policy, insufficient collaboration, and a minimalist annotation policy that may obscure interpretive complexity. The paper suggests that BDK could move toward a human–AI collaborative model in which machines support drafting and technical organization, while the interpretive and editorial authority remains with human experts.