This paper examines the implications of AI and machine translation on traditional lexicography, using three canonical scenarios for dictionary use: text reception, text production, and text translation as test cases. With the advent of high-capacity, AI-driven language models such as OpenAI’s GPT-3 and GPT-4, and the efficacy of machine translation, the utility of conventional dictionaries comes under question. Despite these advancements, the study finds that lexicography remains relevant, especially for less-documented languages where AI falls short, but human lexicographers excel in data-sparse environments. It argues for the importance of lexicography in promoting linguistic diversity and maintaining the integrity of lesser-known languages. Moreover, as AI technologies progress, they present opportunities for lexicographers to expand their methodology and embrace interdisciplinarity. The role of lexicographers is likely to shift towards guiding and refining increasingly automated tools, ensuring ethical linguistic data use, and counteracting AI biases.

本文研究了人工智能和机器翻译对传统词典编纂的影响，使用三种典型的词典使用场景：文本接收、文本生成和文本翻译作为测试用例。随着高容量、人工智能驱动的语言模型（例如 OpenAI 的 GPT-3 和 GPT-4）的出现，以及机器翻译的功效，传统词典的实用性受到质疑。尽管取得了这些进步，研究发现词典编纂仍然具有相关性，特别是对于人工智能不足的记录较少的语言，但人类词典编纂者在数据稀疏的环境中表现出色。它论证了词典编纂在促进语言多样性和维护鲜为人知语言的完整性方面的重要性。此外，随着人工智能技术的进步，它们为词典编纂者提供了扩展方法论和拥抱跨学科性的机会。词典编纂者的角色可能会转向指导和完善日益自动化的工具，确保道德语言数据的使用，并抵消人工智能的偏见。