ie Zukunft des Übersetzerberufs im Zeitalter der künstlichen Intelligenz. Ergebnisse einer Umfrage unter polnischen Übersetzern, Übersetzungstrainers und Studierenden der Übersetzung

Marek Łukasik

Abstract


Der Beitrag enthält das Abstract ausschließlich in englischer Sprache.


Schlagworte


Künstliche Intelligenz; neuronale maschinelle Übersetzung; professionelle Übersetzung; Übersetzungsstudien

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Literaturhinweise


Bar-Hillel, Y. (1951). The present state of research on mechanical translation. American Documentation, 2(4), 229–237.

Beßler, P. (2021). Post-editing and the evolution of translators. https://www.rws.com/blog/what-is-post-editing/

Castelvecchi, D. (2016). Deep learning boosts Google Translate tool. Nature. https://doi.org/10.1038/nature.2016.20696

CEATL (2024). Statement on Artificial Intelligence. The European Council of Literary Translators’ Associations. https://www.ceatl.eu/tools-of-the-trade/statement-on-artificial-intelligence

ELIS 2023 (2023). European Language Industry Survey 2023. Trends, expectations and concerns of the European language industry. ELIS Research.

ELIS 2024 (2024). European Language Industry Survey 2024. Trends, expectations and concerns of the European language industry. ELIS Research.

EMT 2022 (2022). European Master’s In Translation Competence Framework. European Commission.

Farrell, M. (2023). Do translators use machine translation and if so, how? Results of a survey held among professional translators. Translating and the Computer 44: proceedings. International Society for Advancement in Language Technology, 24–25 November 2022; pp. 49–60

Gordon, S. F. (2024). Artificial Intelligence and Language Translation in Scientific Publishing. Science Editor, 47(1), 8–9. https://doi.org/10.36591/SE-4701-05

Grucza, F. (1981). Zagadnienia translatoryki. In F. Grucza (Ed.), Glottodydaktyka a translatoryka (pp. 9–29). Wydawnictwa Uniwersytetu Warszawskiego.

Hutchins, W. J., & Somers, H. L. (1992). An Introduction to Machine Translation. Academic Press.

Krüger, R., & Hackenbuchner, J. (2024). A competence matrix for machine translation-oriented data literacy teaching. Target: International Journal of Translation Studies, 36(2), 245–275. https://

doi.org/10.1075/target.22127.kru

Koivisto, M. & Grassini, S. (2023). Best humans still outperform artificial intelligence in a creative divergent thinking task. Nature (Scientific Reports), 13 (13601). https://www.nature.com/articles/s41598-023-40858-3

Łukasik, M. (2023). Corpus linguistics and generative AI tools in term extraction: a case of Kashubian – a low-resource language. Applied Linguistics Papers, 27(4), 34–45. https://doi.org/10.32612/uw.25449354.2023.4.pp.34-45

Moorkens, J. (2022). The translator, an endangered species? The UNESCO Courier. https://courier.unesco.org/en/articles/translator-endangered-species

Moorkens, J., Castilho, S., Gaspari, F. Toral, A., & Popović, M. (2024). Proposal for a Triple Bottom Line for Translation Automation and Sustainability: An Editorial Position Paper. The Journal of Specialised Translation, 41, 2–25. https://doi.org/10.26034/cm.jostrans.2024.4706

Nexla (2024). Prompt Tuning vs. Fine-Tuning – Differences, Best Practices and Use Cases. https://nexla.com/ai-infrastructure/prompt-tuning-vs-fine-tuning/

Patil, S., & Davies, P. (2014). Use of Google Translate in medical communication: evaluation of naccuracy. British Medical Journal, 349:g7392. https://doi.org/10.1136/bmj.g7392

Poibeau, T. (2017). Machine Translation. MIT Press.

Pym, A. (2024, April 19–20). On the end of translation studies as we know it [Conference presentation abstract]. XII International Scientific Conference Major Problems of Translation Studies and Translator/Interpreter Training, Kharkiv, Ukraine. https://hcommons.org/deposits/item/hc:64499/

Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3,121–154.

Russel, S. J., & Norvig, P. (2010). Artificial Intelligence. A Modern Approach. Prentice Hall.

SoA 2024 (2024). SoA survey reveals a third of translators and quarter of illustrators losing work to AI. https://www2.societyofauthors.org/2024/04/11/soa-survey-reveals-a-third-of-translatorsand-quarter-of-illustrators-losing-work-to-ai/

SFT 2024 = Société française des traducteurs (2024). Statement on Artificial Intelligence by the Steering Committee of the Société française des traducteurs. https://www.sft.fr/docs/2024113848_statement-on-ai-sft-2024-version-en.pdf

Weaver, W. (1949). Translation. https://web.archive.org/web/20120114183631/http://www.mtarchive.info/Weaver-1949.pdf

Wu, Y., Schuster, M. Ch. Zhifeng, Q. V. Le, Norouzi, M., Macherey, W. … Dean, J. (2016). Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. [Preprint]. https://arxiv.org/pdf/1609.08144




DOI: http://dx.doi.org/10.17951/lsmll.2024.48.3.25-39
Date of publication: 2024-10-07 11:52:24
Date of submission: 2024-05-22 00:42:05


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