AI for translation and interpreting. A roadmap for users and policymakers

This Reflection Paper by the Special Interest Group on AI in Translation and Interpreting (hereafter T&I) of the European Language Council, comprising 25 scholars from 19 universities across 14 countries, calls for a more informed use of AI for T&I purposes. While acknowledging the potential of Generative AI and Large Language Models (LLMs), the authors point to several communicative, legal, and ethical concerns and risks and liabilities that occur when these concerns are not duly considered. The authors’ aim is to help policymakers and the wider public understand how LLMs ‘communicate’, what they are capable of, and where their limitations lie. They also seek to highlight communicative settings in which LLMs’ quality and reliability are insufficient, and in which the expertise of trained translators, interpreters, and T&I scholars is needed. A central claim is that LLMs offer powerful tools but not catch-all solutions. T&I are complex, human-centred communication activities that require much more than probabilistic prediction. In contexts where understanding, trustworthiness, and clarity are crucial, and especially where sensitive data and high-stakes settings are involved, professional expertise remains irreplaceable. Responsible AI use—anchored in human values, ethics, equity and the pursuit of quality in communication—is the only sustainable path forward.

Authors

Institutions

Publication Details

Journal
Interpreting and Society
Published
2026-03-28
DOI
https://doi.org/10.1177/27523810251409377
Primary Topic
Interpreting and Communication in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI for translation and interpreting. A roadmap for users and policymakers

Kris Peeters, Mehmet Şahin, Joke Daems, María Isabel Rivas Ginel et al.
Interpreting and Society
Interpreting and Communication in Healthcare
article

AI for translation and interpreting. A roadmap for users and policymakers

Kris Peeters, Mehmet Şahin, Joke Daems, María Isabel Rivas Ginel, Claudia Plieseis
article en

Abstract

This Reflection Paper by the Special Interest Group on AI in Translation and Interpreting (hereafter T&I) of the European Language Council, comprising 25 scholars from 19 universities across 14 countries, calls for a more informed use of AI for T&I purposes. While acknowledging the potential of Generative AI and Large Language Models (LLMs), the authors point to several communicative, legal, and ethical concerns and risks and liabilities that occur when these concerns are not duly considered. The authors’ aim is to help policymakers and the wider public understand how LLMs ‘communicate’, what they are capable of, and where their limitations lie. They also seek to highlight communicative settings in which LLMs’ quality and reliability are insufficient, and in which the expertise of trained translators, interpreters, and T&I scholars is needed. A central claim is that LLMs offer powerful tools but not catch-all solutions. T&I are complex, human-centred communication activities that require much more than probabilistic prediction. In contexts where understanding, trustworthiness, and clarity are crucial, and especially where sensitive data and high-stakes settings are involved, professional expertise remains irreplaceable. Responsible AI use—anchored in human values, ethics, equity and the pursuit of quality in communication—is the only sustainable path forward.

Interpreting and Society
University of Vienna (AT), University of Antwerp (BE), Ghent University Hospital (BE), Dublin City University (IE), Boğaziçi University (TR)
Quality Education
Openalex Percentile: Top 3%
Interpreting and Communication in Healthcare
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

AI for translation and interpreting. A roadmap for users and policymakers — Kris Peeters, Mehmet Şahin, et al. · Interpreting and Society (2026) | TGRS Research Map | TGRS