The op-ed examines the relationship between human translators and AI machine-translation tools, framing them as complementary rather than competing. It argues AI contributes speed and lexical variety while human post-editors add context, cultural nuance, pragmatics, and audience awareness that machine systems still lack. Citing a comparative study of human versus AI post-editing of Chinese-to-English tourism texts that found broadly similar sentence-structure patterns between the two, it argues translator training must now include teaching students to evaluate and refine machine output rather than only produce translations from scratch.
