Call for Papers

The rapid advancement of artificial intelligence (AI) is transforming the theoretical foundations of translation and interpreting studies, the workflows of the language industry and the training of future language professionals. From machine translation and speech technologies to adaptive learning systems and multimodal communication tools, AI is being integrated into professional and educational practices at an accelerating rate. Due to this rapid development, the following key question emerges: How can we ensure that new AI-based technologies remain human-centered and grounded in legal and ethical principles, while also aligning with the needs and values of the people these technologies are meant to serve?

To date, the automation of translation and interpreting has been primarily progress- and profit-oriented. However, numerous critical voices have begun to advocate for a transition toward a human-centered approach. Such an approach would ensure that new technologies are developed with legal and ethical integrity (Bowker 2020; Defrancq 2024; Forcada 2023; Horváth 2022; Lacruz Mantecón 2023; Nousias 2023; Walter 2026) and that the needs of language industry professionals are considered (Jiménez-Crespo 2020, 2025a, 2025b; Jiménez-Crespo & Rodríguez 2025). Furthermore, a human-centered approach to language technologies would also guarantee that consumers have access to accurately translated texts that are of adequate quality––especially in (high-)risk areas such as medicine, law, occupational safety and civil protection (Pym 2025).

Due to the rapid advancement of AI-based translation and interpreting technologies, risk management has emerged as a key concept to address the potential consequences of a frequent overreliance on technologies with insufficient or no human control (Bowker 2024; Nitzke et al. 2019; Pym 2025). In response to various risks associated with AI-translated language, which range from linguistic impoverishment to dangers to life and limb, the importance of developing new skills to handle emerging AI-based technologies in translation and interpreting has been highlighted. To varying degrees, AI literacy is considered important for both professionals in the language industry (Corpas Pastor & Defrancq 2023; Hackenbuchner & Krüger 2022; Krüger 2023, 2024) and lay users (Bowker 2024). Nevertheless, while the perils associated with AI-based language technologies should not be underestimated, the very same tools that sometimes endanger humans may on other occasions also benefit those who have often been marginalized in interlingual and intermedial communication. Indeed, the potential of AI-based technologies has increasingly been explored in an emerging research field at the intersection of translation and disability studies (Agnetta 2026; Maaß 2020).

Foregrounding the needs of people in and outside the language industry, this international conference invites scholars and practitioners of translation and interpreting to contribute to a critical and constructive dialogue on the best ways to use the progressive automation of translation and interpreting to change outputs, workflows, as well as translator and interpreter training and translation-oriented language learning. We particularly welcome proposals that explore how AI can support, augment and empower human expertise, rather than replace it, as well as proposals that address the limitations of AI-related technologies.

We invite you to submit abstracts of 250 to 300 words (excluding references) for 20-minute presentations followed by discussion. Abstracts should outline the key research question, theoretical framework, methodology and achieved or expected results.

Abstracts must be submitted to katharina.walter@uibk.ac.at and marco.agnetta@uibk.ac.at. Proposals should include the author’s name, academic affiliation, contact information and a short biographical note (approx. 100 words).

The conference fee is €60 (full-time employees) or €40 (pre-doc/part-time employees).

Agnetta, Marco. 2026. “Between Empowerment and Dependency: Digital and AI-Supported Tools for Media Accessibility.” In: Applying Artificial Intelligence in Translation: Possibilities, Processes and Phenomena, edited by Katharina Walter and Marco Agnetta. Routledge, 163–181. https://doi.org/10.4324/9781003539698-14.

Bowker, Lynne. 2020. “Translation Technology and Ethics.” In: The Routledge Handbook of Translation and Ethics, edited by Kaisa Koskinen and Nike K. Pokorn. Routledge, 262–278. https://doi.org/10.4324/9781003127970-20.

Bowker, Lynne. 2024. “Risks for Lay Users in Machine Translation and Machine Translation Literacy.” In: The Social Impact of Automating Translation: An Ethics of Care Perspective on Machine Translation, edited by Esther Monzó-Nebot and Vicenta Tasa-Fuster. Routledge, 60–76. https://doi.org/10.4324/9781003465522-4.

Corpas Pastor, Gloria, and Bart Defrancq. 2023. Interpreting Technologies – Current and Future Trends. John Benjamins. https://doi.org/10.1075/ivitra.37.

Defrancq, Bart. 2024. “Conference Interpreting in AI Settings: New Skills and Ethical Challenges.” In: Handbook of the Language Industry: Contexts, Resources and Profiles, edited by Gary Massey, Maureen Ehrensberger and Erik Angelone. De Gruyter, 473–487. https://doi.org/10.1515/9783110716047-021.

Forcada, Mikel L. 2023. “Licensing and Usage Rights of Language Data in Machine Translation.” In: Towards Responsible Machine Translation. Machine Translation: Technologies and Applications, vol. 4, edited by Helena Moniz and Carla Parra Escartín. Springer, 49–69. https://doi.org/10.1007/978-3-031-14689-3_4.

Hackenbuchner, Janiça, and Ralph Krüger. 2023. “DataLitMT—Teaching Data Literacy in the Context of Machine Translation Literacy.” In: Proceedings of the 24th Annual Conference of the European Association for Machine Translation. Finland, Tampere. European Association for Machine Translation, 285–293. https://events.tuni.fi/eamt23/proceedings/.

Horváth, Ildikó. 2022. “AI in Interpreting: Ethical Considerations.” Across Languages and Cultures 23 (1): 1–13. https://doi.org/10.1556/084.2022.00108.

Jiménez-Crespo, Miguel A. 2020. “The ‘Technological Turn’ in Translation Studies: Are We There Yet? A Transversal Cross-Disciplinary Approach.” Translation Spaces 9 (2): 314–341. https://doi.org/10.1075/ts.19012.jim.

Jiménez-Crespo, Miguel A. 2025a. “Human-Centered AI and the Future of Translation Technologies: What Professionals Think About Control and Autonomy in the AI Era.” Information 16 (5): 387. https://doi.org/10.3390/info16050387.

Jiménez-Crespo, Miguel A. 2025b. “If Students Translate Like a Robot … or How Research on Human-Centered AI and Intelligence Augmentation Can Help Realign Translation Education.” The Interpreter and Translator Trainer 19 (3–4): 277–295. https://doi.org/10.1080/1750399X.2025.2542022.

Jiménez-Crespo, Miguel A., and Stephanie A Rodriguez. 2025. “Is It AI or PE that Worry Professionals: Results from a Human-Centered AI Survey.” In: Proceedings of Machine Translation Summit XX, vol. 1. Geneva, Switzerland. European Association for Machine Translation, 407–419. https://www.researchgate.net/publication/394533268_Is_it_AI_MT_or_PE_that_worry_professionals-_results_from_a_Human-Centered_AI_survey.

Krüger, Ralph. 2023. “Artificial Intelligence Literacy for the Language Industry—With Particular Emphasis on Recent Large Language Models such as GPT-4.” Lebende Sprachen 68 (2): 283–330. https://doi.org/10.1515/les-2023-0024.

Krüger, Ralph. 2024. “Outline of an Artificial Intelligence Literacy Framework for Translation, Interpreting and Specialised Communication.” Lublin Studies in Modern Languages and Literature 48 (3): 11–23. https://doi.org/10.17951/lsmll.2024.48.3.11-23.

Lacruz Mantecón, Miguel. 2023. “Authorship and Rights Ownership in the Machine Translation Era.” In: Towards Responsible Machine Translation. Machine Translation: Technologies and Applications, vol. 4, edited by Helena Moniz and Carla Parra Escartín. Springer: 71–92. https://doi.org/10.1007/978-3-031-14689-3_5.

Maaß. Christiane. 2020. Easy Language – Plain Language – Easy Language Plus: Balancing Comprehensibility and Acceptability. Frank & Timme GmbH.

Nousias, Alexandros. 2023. “The Ethics of Machine Translation.” In: Machine Translation: Technologies and Applications, vol. 4, edited by Helena Moniz and Carla Parra Escartín. Springer: 29–48. https://doi.org/10.1007/978-3-031-14689-3_3.

Pym, Anthony. 2025. Risk Management in Translation. Cambridge University Press.

Walter, Katharina. 2026. “Translation Copyright in the Age of Generative Artificial Intelligence: Addressing Legal and Ethical Challenges.” In: Transl-AI-tion 2.0: Embracing the AI Revolution, edited by Rashid Yahiaoui. Peter Lang. Forthcoming.

1. Human-Centered AI in Translation and Interpreting

• Collaborative human–AI translation and interpreting
• AI-supported decision-making, quality-assurance and revision processes
• Cognitive perspectives on interacting with automated translation systems, as well as AI-enhanced CAT and CAI tools
• Ethical, legal, social and professional implications of automation

2. AI-Related Transformations in Interpreting

• Real-time speech technologies and their integration into interpreting
• Smart booths, CAI tools and AI-supported notetaking
• AI in public service interpreting
• Sign language interpreting with AI-based tools and avatars

3. AI in Specialized Translation

• Human agency and automation in domain-specific translation
• AI models and translation management
• Workflows combining CAT tools, neural machine translation and large language models
• Text-generative large language models for preparation, translation, revision and follow-up stage of translation workflows

4. Automation in Literary Translation

• Automation as enhancement or obstacle to creativity
• Quality in (semi-)automated literary translation
• De-/Increasing (linguistic) diversity in literature through automated translation
• AI-related changes in the global literary market

5. Automation in Audiovisual Translation (AVT) and Accessibility

• Machine translation, automatic speech/image recognition and synthetic voices in AVT
• Quality, creativity and accessibility in AI-mediated AVT
• Multimodal and multilingual content creation
• AI models for easy and plain language

6. Translator and Interpreter Training and Translation-Oriented Language Learning

• AI-driven learning environments for current and future translators and interpreters
• Adaptive platforms for terminology and competence development
• Future roles and competencies of translators and interpreters
• Pedagogical strategies for training translators and interpreters to work with AI
• Data literacy and critical AI awareness in translation and interpreting education

7. Linguistic Aspects of Automation in Multilingual Contexts

• Theoretical and descriptive challenges of multilingual automation
• Evaluation and quality assessment across languages
• Large language models for language-specific adaptation and linguistic analysis
• Ethical and sociolinguistic implications of automation in multilingual environments
• Terminology and glossary management with large language models

8. Methodological and Theoretical Perspectives

• Human-centered design principles applied to translation technologies
• Interdisciplinary approaches connecting translation studies, human-computer interaction, linguistics and AI
• Empirical research on user experience and human–machine interaction
• AI-based applications for creating research designs.