Weekly sessions | 5pm - 6:30pm | 10 May - 12 July 2024
This course has now ended. However, we are rerunning the course again, starting in October. To book please follow this link.
A ten-part course presented by The University of Surrey, Centre for Translation Studies.
Cut through the hype and counter the pessimism. Develop a fresh perspective on the use of AI in translation, and learn strategies to manage its impact on translation business models.
Following their recent AI webinars, The University of Surrey, Centre for Translation Studies is now offering this in-depth course, addressing the key themes that translators need to understand in order to make AI a powerful tool in their work.
It aims to provide answers to common questions about AI in translation, empower translators to find their own answers to questions, and enable you to use AI proficiently and effectively.
The course has five modules, each comprising two, ninety-minute sessions.
Module 1
5 & 12 June 2025 | 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.
Module 2
19 & 26 June 2025 | 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.
Module 3
3 & 10 July 2025 | 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.
Module 4
17 July 2025 | 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’.
Module 5
24 July 2025 | 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.
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 a translation task involving AI tools. This is designed to help you analyse the usefulness of AI translation tools and to reflect on how your view of AI in translation alters over the duration of the course. The assignment will be marked by the tutors and individual feedback provided.
By completing the course, you will be able to:
- Understand the main concepts related to AI, Large Language Models (LLMs) and Neural Machine Translation
- Recognise different applications and uses of AI tools in translation
- Identify processes that reduce the risk of using language AI
- Acknowledge the role that creativity plays in AI and translation
- Understand the impact of AI on translation business models
- Develop strategies to manage the impact of AI on translation business models, reducing risk and promoting value for clients
- Develop a fresh perspective on the use of AI in translation.
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