@inproceedings{jimenez-crespo-rodriguez-2025-ai,
    title = "Is it {AI} or {PE} that worry translation professionals: results from a Human-Centered {AI} survey",
    author = "Jim{\'e}nez-Crespo, Miguel A.  and
      Rodr{\'i}guez, Stephanie A.",
    editor = "Bouillon, Pierrette  and
      Gerlach, Johanna  and
      Girletti, Sabrina  and
      Volkart, Lise  and
      Rubino, Raphael  and
      Sennrich, Rico  and
      Farinha, Ana C.  and
      Gaido, Marco  and
      Daems, Joke  and
      Kenny, Dorothy  and
      Moniz, Helena  and
      Szoc, Sara",
    booktitle = "Proceedings of Machine Translation Summit XX: Volume 1",
    month = jun,
    year = "2025",
    address = "Geneva, Switzerland",
    publisher = "European Association for Machine Translation",
    url = "https://preview.aclanthology.org/mtsummit-25-ingestion/2025.mtsummit-1.32/",
    pages = "407--419",
    ISBN = "978-2-9701897-0-1",
    abstract = "Translation technologies have historically been developed without substantial input from professionals (e.g. O{'}Brien 2012). Conversely, the emerging human-centered AI (HCAI) paradigm emphasizes the importance of including end-users in the ``process of conceiving, designing, testing, deploying, and iterating'' technologies (Vallor 2024: 17). Therefore, early research engagement on the attitudes, needs and opinions of professionals on AI implementation is essential because incorporating them at later stages ``results in issues and missed opportunities, which may be expensive to recover from due to the cost, time, resources, and energy spent'' (Winslow and Garibay 2004: 123). To this end, this article presents a qualitative analysis of professional translators' attitudes towards AI in the future, centered around the role of MT and post-editing (PE). The discussion draws on data collected from open ended questions included in a larger survey on control and autonomy from a HCAI perspective, which were thematically coded and qualitatively examined. The thematic analysis indicates that predominant concerns regarding the future of the AI-driven translation industry still revolves around longstanding issues in PE and MT literature, such as PE, translation quality, communicating and educating LSP, clients, users, and the broader public, maintaining human control over the final product or creativity. This is explained to some extent to the relatively small rates of integration of AI technologies into translation workflows to date (e.g. ELIA 2024; Rivas Ginel et al 2024; GALA 2024; Jimenez-Crespo 2024), or the fact the professional report using AI primarily for tasks related to translation, but not necessarily to PE the output of LLMs or NMT (Rivas Ginel and Moorkens 2025)."
}