Translating With Feeling: Centering Translator Perspectives within Translation Technologies - Chechelnitsky, Daniel; Gururaja, Sireesh; Olojo, Seyi; Deng, Wesley; Attanasio, Giuseppe; Zerva, Chrysoula; Sap, M. (arXiv, 2026)
Rapid development of Large Language Models (LLMs) and similar automated approaches for translation tasks is increasingly affecting the landscape of translation technologies. As concerns about the outsourcing of translator work to these automated translation tools grow, it becomes increasingly crucial to gather insights from the translation community directly. To this end, we conduct an interview study with 19 professional translators working across 11 languages and 11 domains to understand their perspectives, experiences, and concerns with using translation technologies in their work. We find that translators are cautious when incorporating new tools into their workflow, with several expressing concerns machine translation (MT) and LLMs are infringing on the necessary human aspects and verification steps of translation, worried that these tools have potential for harmful downstream effects due to compromising the human aspect of translation work. These findings demonstrate the need to develop translation technologies that directly serve translators'needs rather than replacing human translation. This can be done by focusing more on the assistive, rather than the automating aspects of these tools.