Un any de ChatGPT: perspectives dels traductors i grau d'adopció
Resum
Des del llançament de ChatGPT al final de 2022, els acadèmics han provar d’investigar-ne el potencial per a la traducció i analizar-ne les possibles aplicacions, reptes i perills. Aquest article explora l’actitud prudent dels traductors envers ChatGPT i el grau limitat amb què l’han incorporat al seu flux de treball, principalmente per obtenir inspiració o per resumir textos.
Paraules clau
enquesta, corpus, perspectives, adopció, IA generativa, traducció automàticaReferències
Briva-Iglesias, Vicent (2024). Fostering human-centered, augmented machine translation: Analysing interactive post-editing. Doctoral Dissertation, Dublin City University. https://doras.dcu.ie/30182/ [Accessed: 20241126].
Briva-Iglesias; Vicent et al. (2024). Large Language Models" Ad Referendum": How Good Are They at Machine Translation in the Legal Domain?. ArXiv preprint arXiv:2402.07681 https://doi.org/10.48550/arXiv.2402.07681 [Accessed: 20241126].
Cadwell, Patrick; O’Brien, Sharon; Teixeira, Carlos S. (2018). Resistance and accommodation: factors for the (non-) adoption of machine translation among professional translators. Perspectives, 26(3), 301-321. https://doi.org/10.1080/0907676X.2017.1337210 [Accessed: 20241126].
Chen, Tzeng-Ji. (2023). ChatGPT and other artificial intelligence applications speed up scientific writing. Journal of the Chinese Medical Association, 86(4), 351-353. https://doi.org/10.1097/jcma.0000000000000900 [Accessed: 20241126].
Chesterman, Andrew. (2009). The name and nature of translator studies” Hermes Journal of Language and Communication Studies, 42, 14–20. https://doi.org/10.7146/hjlcb.v22i42.96844 [Accessed: 20241126].
Creswell, John. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Thousand Oaks, CA: Sage Publication, Inc.
Dam, Helle V. (2013). The translator approach in translation studies: Reflections based on a study of translators’ weblogs. In M. Eronen & M. Rodi-Risberg (Eds.), Point of view as challenge: vakki Publications 2 (pp. 16–35). https://vakki.net/publications/2013/VAKKI2013_Dam.pdf [Accessed: 20241126].
Delellis, Nicole S.; Yimin Chen; Sarah E. Cornwell; Dominique Kelly; Alex Mayhew; Sodiq Onaolapo, and Victoria L. Rubin. (2023). ChatGPT Media Coverage Metrics; Initial Examination Proceedings of the Association for Information Science and Technology 60 (1): 935–37. https://doi.org/10.1002/PRA2.903 [Accessed: 20241126].
Dell'Acqua, Fabrizio; McFowland, Edward; Mollick, Ethan; Lifshitz-Assaf, Hila; Kellogg, Katherine; Rajendran, Saran; Krayer, Lisa; Candelon, François; Lakhani, Karim. (2023). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality. Harvard Business School Working Paper, No. 24-013. http://dx.doi.org/10.2139/ssrn.4573321 [Accessed: 20241126].
ELIS Research. (2023). European Language Industry Survey 2023. Brussels: European Union of Associations of Translation Companies. http://elis-survey.org/wp-content/uploads/2023/03/ELIS-2023-report.pdf [Accessed: 20241126].
ELIS Research. (2024). European Language Industry Survey 2024. Brussels: European Union of Associations of Translation Companies. https://elis-survey.org/wp-content/uploads/2024/03/ELIS-2024-Report.pdf [Accessed: 20241126].
Farrell, Michael. (2023). Do translators use machine translation and if so, how? Results of a survey among professional translators. In J. Moorkens & V. Sosoni (Eds.) Proceedings of Translating and the Computer 44, pp. 49-60. https://dialnet.unirioja.es/servlet/articulo?codigo=9748727 [Accessed: 20241126].
Flanagan, Marian. (2016). Cause for concern? Attitudes towards translation crowdsourcing in professional translators’ blogs. The Journal of Specialised Translation, 25, pp. 149–173. https://www.jostrans.org/issue25/art_flanagan.pdf [Accessed: 20241126].
GALA (2024). AI and Automation Barometer Report 2024. GALA, Globalization and Localization Association. https://www.gala-global.org/knowledge-center/professional-development/articles/ai-automation-barometer-report [Accessed: 20241126].
Glikson, Ella; Woolley, Anita Williams. (2020). Human Trust in Artificial Intelligence: Review of Empirical Research. Academy of Management Annals 14 (2), pp. 627–660. https://doi.org/10.5465/annals.2018.0057. [Accessed: 20241126].
Guerberof-Arenas, Ana; Toral, Antonio. (2020). The impact of post-editing and machine translation on creativity and reading experience. Translation Spaces, 9(2), pp. 255-282. https://arxiv.org/abs/2101.06125 [Accessed: 20241126].
Guerberof-Arenas, Ana; Toral, Antonio. (2022). Creativity in Translation: Machine Translation as a Constraint for Literary Texts. Translation Spaces 11 (2), pp. 184–212. https://doi.org/10.1075/TS.21025.GUE. [Accessed: 20241126].
Jiao, Wenxiang; Wang, Wenxuan; Huang, Jen-Tse; Wang, Xing; Tu, Zhaopeng. (2023). Is ChatGPT a good translator? A preliminary study. http://dx.doi.org/10.48550/arXiv.2301.08745 [Accessed: 20241126].
Jiménez-Crespo, Miguel Ángel. (2023): Augmentation and translation crowdsourcing: are collaborative translators minds really “augmented”?. Translation, Cognition and Behavior. https://doi.org/10.1075/tcb.00079.jim [Accessed: 20241126].
Jiménez-Crespo, Miguel Ángel. (2024). Localization in Translation. New York-London: Routledge.
Jiménez-Crespo, Miguel Ángel. (in press). Exploring professional translators’ attitudes towards control and autonomy in the Human-Centered AI era: quantitative results from a survey study. Revista Tradumàtica. Tecnologies de la Traducció, 22.
Kirov, Vassil; Malamin, Bagryan. (2022). Are Translators Afraid of Artificial Intelligence? Societies, 12(2), 70. https://doi.org/10.3390/soc12020070 [Accessed: 20241126].
Läubli, Samuel; Orrego-Carmona, David (2017). When Google Translate is better than some human colleagues, those people are no longer colleagues. Proceedings of the 39th Conference Translating and the Computer, pp. 59–69. https://www.zora.uzh.ch/id/eprint/147260/ [Accessed: 20241126].
Lockey, Steven; Gillespie, Nicole; Holm, Daniel; Someh, Ida Asadi (2021). A review of trust in artificial intelligence: Challenges, vulnerabilities and future directions. Proceedings of the Annual Hawaii International Conference on System Sciences, 2020-Janua, pp. 5463–5472. https://doi.org/10.24251/hicss.2021.664 [Accessed: 20241126].
Long, Duri; Magerko, Brian (2020). What Is AI Literacy? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, pp. 1–16. CHI ’20. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727 [Accessed: 20241126].
McDonough Dolmaya, Julie (2007). How do language professionals organize themselves? An overview of translation networks. Meta, 52(4), pp. 793–815. https://doi.org/10.7202/017697ar [Accessed: 20241126].
McDonough Dolmaya, Julie (2011). A window into the profession. The Translator, 17(1), pp. 77–104. https://doi.org/10.1080/13556509.2011.10799480 [Accessed: 20241126].
Merali, Ali (2024). Scaling Laws for Economic Productivity: Experimental Evidence in LLM-Assisted Translation. https://arxiv.org/abs/2409.02391 [Accessed: 20241126].
Metz, Cade (2023). OpenAI Plans to Up the Ante in Tech’s A.I. Race. New York Times. https://www.nytimes.com/2023/03/14/technology/openai-gpt4-chatgpt.html [Accessed: 20241126].
O’Brien, Sharon (2023). Human-Centered augmented translation: against antagonistic dualisms. Perspectives 32(3), pp. 391–406. https://doi.org/10.1080/0907676X.2023.224742321. [Accessed: 20241126].
Peng, Keqin; Ding, Liang; Zhong, Qihuang; Shen, Li; Liu, Xuebo; Zhang, Min; Tao, Dacheng (2023). Towards making the most of chatGPT for machine translation. https://arxiv.org/abs/2303.13780 [Accessed: 20241126].
Ray, Partha Pratim (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems. https://doi.org/10.1016/j.iotcps.2023.04.003 [Accessed: 20241126].
Rivas Ginel, María Isabel; Sader Feghali, Lina; Accogli, Francesca (2024). Exploring Translators’ Perceptions of AI. ELC Survey. http://dx.doi.org/10.13140/RG.2.2.23582.75842 [Accessed: 20241126].
Sánchez-Gijón, Pilar; Palenzuela-Badiola, Leire (2023). Analysis and evaluation of ChatGPT-Induced HCI shifts in the digitalised translation process. Proceedings of the International Conference on Human-Informed Translation and Interpreting Technology, pp. 227-267. https://acl-bg.org/proceedings/2023/HiT-IT%202023/pdf/2023.hitit2023-1.21.pdf [Accessed: 20241126].
The Authors Guild. (2023). Survey reveals 90 percent of writers believe authors should be compensated for the use of their books in training generative AI. The Authors Guild. https://authorsguild.org/news/aisurvey-90-percent-of-writers-believe-authors-should-be-compensated-for-ai-training-use/ [Accessed: 20241126].
Vieira, Lucas Nunes (2018). Automation anxiety and translators. Translation Studies, 13(1), pp. 1–21. https://doi.org/10.1080/14781700.2018.1543613 [Accessed: 20241126].
Vuorio, Valtteri; Zachary Horne. 2023. A Lurking Bias: Representativeness of Users across Social Media and Its Implications for Sampling Bias in Cognitive Science. Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45): 45. https://doi.org/10.31234/osf.io/n5d9j [Accessed: 20241126].
Zaretskaya, Anna; Pastor, Gloria Corpas; Seghiri, Miriam. (2017). User perspective on translation tools: Findings of a user survey. Trends in E-tools and Resources for Translators and Interpreters, 37-56. http://dx.doi.org/10.1163/9789004351790_004 [Accessed: 20241126].
Zydroń, Andrzej (2017). The Localization industry Word Count Standard: GMX-V. Slaying the Word Count Dragon. In proceedings of Translating and the Computer 39, pp. 114-118. https://www.asling.org/tc39/ [Accessed: 20241126].
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Drets d'autor (c) 2024 María Isabel Rivas Ginel, Joss Moorkens
Aquesta obra està sota una llicència internacional Creative Commons Reconeixement 4.0.
