Konferencens keynote-speaker er Barbara Heinisch
Barbara Heinisch is a researcher at the Institute for Applied Linguistics at Eurac Research in Italy, where she is conducting research on terminology work by means of large language models with a focus on language-variety specific terminology. She has been and lecturer at the Centre for Translation Studies at the University of Vienna, Austria, where she was teaching localisation, technical documentation, terminology and language technologies. Her research interests include specialised translation, terminology, accessibility, digital humanities and citizen science as well as their relation to technology. She has worked in different research and educational projects as well as applied research projects related to accessibility management, specialised translator or interpreter training, machine translation engine development, translation platforms, terminology and relation extraction as well as engaging members of the public in humanities research in the form of citizen science. Her recent focus is on the use of large language models in the field of specialised translation and terminology work.
Barbara Heinisch: "Terminology in the age of large language models: Triumphs, traps and turmoil"
The rise of Large Language Models (LLMs) has profoundly transformed the landscape of terminology and translation, creating a complex interplay between terminology as a resource for artificial intelligence (AI) and AI as a tool for terminologists. This keynote critically examines this dual relationship, navigating the promises and pitfalls that come with the integration of AI into terminology work.
On one side, terminology plays a crucial role in AI applications, underpinning the quality of outputs in systems such as neural machine translation and automated content generation. At the same time, LLMs are useful tools for terminologists, offering assistance in term extraction, multilingual terminology research and database creation.
Yet, this shift also brings forth ethical questions. The cost of training and deploying LLMs is significant (both in terms of environmental cost and socio-economic impact). Furthermore, LLMs exert a transformative influence on language and terminology themselves, challenging established notions of authorship, originality and the concept of a ‘genuine’ text in an era increasingly shaped by machine-generated texts. This evolution also prompts critical reflection on the preservation of linguistic diversity (not only across languages but also within them), raising concerns about the homogenizing tendencies of AI-driven language production.
Therefore, a critical reflection on the opportunities, risks and ethical concerns surrounding LLM-based terminology work is needed to shape the future of terminology management and specialized translation in a sustainable and responsible manner.
