Interpreting and AI

An eight-week course presented by the Centre for Translation Studies at the University of Surrey.

To complement its master’s programmes in translation and interpreting, and building on its open webinars and online lectures, the Centre for Translation Studies is now offering this in-depth course for the interpreters’ community, addressing the increasing presence of AI in their work.

The course examines how interpreters can benefit from AI across all stages of the workflow — from preparation to real-time support. Participants will gain a clear understanding of key AI concepts relevant to interpreting, including Large Language Models (LLMs), Automatic Speech Recognition (ASR), and Computer-Assisted Interpreting (CAI) tools.

Drawing on current research, the course highlights where AI offers real opportunities and where caution is required. It supports interpreters in developing informed, independent strategies for engaging with AI effectively in their practice.

The academic experience of the instructors guarantees an independent, non-commercial perspective on all matters related to AI. Rather than promoting specific platforms, the course fosters critical thinking, professional reflection, and hands-on experimentation with AI in the context of interpreting.

Centre for Translation Studies The University of Surrey

The Centre of Translation Studies of the University of Surrey (CTS) is dedicated to cutting-edge research, scholarship and teaching in translation, interpreting and other forms of inter- and intra-lingual communication. Since our formation in 1982, we have contributed to the theoretical advancement of translation and interpreting studies, whilst achieving real-world applicability by studying translation and interpreting as socio-technological practices, highlighting their economic and social value and their role as an enabling force for a globally connected world.
In this course, CTS is represented by:

• Professor Constantin Orasan, Professor of Language and Translation Technologies
• Professor Sabine Braun, Professor of Translation Studies
• Dr Diana Singureanu, Postdoctoral Research Fellow in Interpreting Studies

The course has five modules, each comprising of either one to two 90-minute sessions. Each session will be followed by an optional 30-minute Q&A.
At the end of each session there will be a short quiz to help you assess your understanding, plus suggested reading materials, to complement the session and deepen your knowledge.
There will also be a post-course assignment based on an interpreting-related task involving AI tools. This is designed to help you analyse the usefulness of AI tools in interpreting contexts and to reflect on how your view of using AI in interpreting has altered over the duration of the course. The assignment will be marked by the tutors and individual feedback will be provided.

By completing the course, you will be able to:

• Understand key concepts in language AI and how they apply to interpreting
• Recognise different applications and uses of AI tools in interpreting
• Evaluate the functions, potential and limitations of different AI tools in interpreter preparation and real-time use during interpreting assignments
• Understand the impact of AI on interpreting and related real-time multilingual communication workflows
• Assess the risks and ethical implications of using AI tools in interpreting, and identify processes that reduce the risk of using language AI
• Confidently discuss the role of AI in interpreting with clients and stakeholders, reducing risk and promoting value for clients, and preserving professional standards in interpreting
• Develop a fresh perspective on the use of AI in interpreting contexts, enabling you to adapt to future developments with insight and autonomy

05 & 12 February 2026 | 5pm - 6:30pm
Introduction to AI and how interpreters can benefit from it

• Introduction to the main concepts in AI: GenAI, LLMs, NLP, ASR
• Explanation of what LLMs are and how they work
• Discussion on how LLMs may assist interpreters with reference information and language support
• What ASR is and how it works
• Demonstration and homework on how to customise an ASR engine to improve its accuracy

19 & 26 February 2026 | 5pm - 6:30pm
AI-assisted interpreting

• AI support for interpreters during an interpreting assignment
• Computer-Assisted Interpreting (CAI) tools: overview of available options, functions and real-world applications
• What is needed to use these tools effectively
• Research insights: key findings from CAI research relating to interpreting quality, cognitive load and user experience

05 & 12 March 2026 | 5pm - 6:30pm
Preparing interpreting assignments with AI

• Introduction to prompt engineering and different types of prompts
• Discussion of how prompting can be used by interpreters for assignment preparation
• Demonstration of using LLMs for extracting terms and building bilingual glossaries
• Retrieval Augmented Generation (RAG)
• Test of how NotebookLM can be used to help with assignment preparation

19 March 2026 | 5pm - 6:30pm
AI-enabled real-time multilingual workflows

• Discussion of the homework given in the previous week
• Introduction to various AI-based workflows: speech to text/speech to speech
• What interpreters should know about ‘machine interpreting’

26 March 2026 | 5pm - 6:30pm
Risks associated with the use of AI in interpreting

• Professional risks of AI use in the context of interpreting
• Beyond liability: ethical and legal considerations, including maintaining privacy and confidentiality
• Data privacy, bias, quality assurance, and the impact of AI on professional roles and standards