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Announcements

Call for Papers: Special Issue for 2025

2024-07-05

Human-centeredness in Translation: Advancing Translation Studies in a Human-Centered AI Era

Editor:           Miguel A. Jiménez-Crespo, Professor, Rutgers University

Email:            jimenez.miguel@rutgers.edu

The centrality of human agents is paramount to the discipline of translation studies, (e.g. Chan 2018; Kenny 2020; Massey, Hurtas Barros and Katan 2023).  With the emergence of AI applications, such as generative Large Language Models (LLMs), there have been renewed calls to direct more efforts towards the centrality of human agents in the translation ecosystem, focusing on “the added value of human translation” (Massey and Ehrensberger-Dow 2017: 308). In this context, this special issue focuses on the introduction of the human-centered AI (HCAI) paradigm in translation studies (e.g. O’Brien 2023; Jimenez-Crespo 2023), where machines are used to “enhance human capacities and improve human experiences rather than replacing them through automation" (Rogers 2022: 1). AI applications in translation should thus be centered on “amplifying, augmenting, and enhancing human performance”, while at the same time supporting “human self-efficacy, encourage creativity, clarify responsibility, and facilitate social participation” (Schneiderman 2020: 2, 2022: 120). In this paradigm, developers and key players in the industry, the profession and TS should work towards uniting the strengths of humans and machines, keeping translators firmly in control (Jiménez-Crespo 2024). This call for papers welcomes contributions that focus on the centrality of the human translator (professional and non-professional alike) in AI-driven translation practices. This thematic issue welcomes papers that deal broadly with any of the different subareas in the recent map of the HCAI research landscape by Capel and Brereton (2023):

  1. Human teaming with AI. Humans teaming with AI technologies (including LLMs and NMT) for translation, post editing, automatic post editing (APE), terminology management or project management issues. Humans in the translation loop, automated tools to support human translation processes.
  2. Human-centered approaches to design and evaluation of AI. Interaction with AI, user-centered design methods, artificial intelligence user experience (AIX), translators as subjects of AI, contestable AI.
  3. Ethical AI. Human perceptions on AI, bias and fairness in NMT and LLMs, autonomy and agency in the human-AI tandem, machine ethics, values embedded in AI, roles, responsibilities and capabilities of AI.
  4. Explainable and interpretable AI. Critical literacy approaches to AI and MT, training translators to critically use AI.

Other relevant topics may also be covered, such as the design of AI options for optimal compatibility with human-centered models, and comparison between human- and AI-centered approaches.

Authors that work within any area within TS are welcome to contribute to this special issue (cognitive TS, AVT, CBTS, Translation Technologies, Sociology of TS, etc.). Submissions should follow the InContext style guidelines that can be found at https://incontextjournal.org/index.php/incontext/about/submissions. The template for submissions can be found at https://docs.google.com/document/d/1mni9bzsAkKHEC7T3KiHS7kcpgUYBtSd_/edit.

Interested researchers are kindly invited to first send an extended English abstract (300-350 words) of their work via email to the special issue editor (jimenez.miguel@rutgers.edu), as well as the journal editor-in-chief Cheong Ho-Jeong (angelhjchg@gmail.com). The submission of full papers should be made through the journal’s submission platform at https://incontextjournal.org/index.php/incontext/submission/wizard, followed by an email notification to the special issue editor (jimenez.miguel@rutgers.edu) and the editorial team (journal.incontext@gmail.com).

 

Important dates

English abstract deadline: Sept 15th, 2024. Submission via email (300-350 words).

Full paper deadline: Nov 15th, 2024. Submission through InContext platform.

Notification of acceptance to authors: Jan 15th, 2025

Final publication-ready submission: March 1st, 2025

Special issue publication: May 2025

 

References

Capel, Tara. And Margot Brereton (2023). “What is human-centered about human-centered AI? A map of the research landscape”. In: Proceedings of the 2023 CHI conference on human factors in computing systems, pp. 1–23.

Chan, Sin-Wai (2018). The human factor in machine translation. Routledge Studies in Translation Technology. New York-London: Routledge.

ELIS (2024). “European Language Industry Survey 2024. Trends, Expectations and Concerns of the European Language Industry”. https://elis-survey.org/wp-content/uploads/2024/03/ELIS-2024-Report.pdf.

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.

Jiménez-Crespo, Miguel A. (2023). “Augmentation and translation crowdsourcing: are collaborative translators minds really ‘augmented’?”. Translation, Cognition and Behavior.  https://doi.org/10.1075/tcb.00079.jim.

Jiménez-Crespo, Miguel A. (2024). “Professional Translators’ Attitudes Towards Control and Autonomy in the Human-Centered AI Era: Presenting a Survey Study”. NETTT Conference Proceedings, 2024. Varna, Bulgaria.

Kenny, Dorothy (2020). Human Issues in Translation Technology. New York-London: Routledge.

Massey, Garry, Huertas-Barros, Elsa and David Katan, D. (Eds.) (2023). The Human Translator in the 2020s. London and New York: Routledge.

O’Brien, Sharon (2023). “Human-Centered augmented translation: against antagonistic dualisms.” Perspectives 32(3): 391–406. https://doi.org/10.1080/0907676X.2023.224742321.

Rivas Ginel, María Isabel et al. (2024). “Exploring Translators’ Perceptions of AI”. ELC Survey. https://doi.org/10.13140/RG.2.2.23582.75842.

Sadiku, Mathew and Sarhan Musa (2021). A Primer on Multiple Intelligences, Cham, Switzerland: Springer.

Shneiderman, Ben (2020). “Human-centered artificial intelligence: Three fresh ideas”. AIS Transactions on Human-Computer Interaction 12(3): 109–124. https://doi.org/10.17705/1thci.00131.

Shneiderman, Ben. (2022). Human-centered AI. Oxford: Oxford University Press.