X-Tutorial: Evaluating Gender Bias in German Machine Translation (Lehrforschungsprojekt)

Evaluating Gender Bias in German Machine Translation

A project-course (as part of the X-Tutorials) at the Institute of Software Engineering and Theoretical Computer Science, Technische Universität Berlin

Description:

Every day, millions rely on machine translation (MT) models to overcome language barriers, but can we trust them to be fair, or do they perpetuate harmful stereotypes? The goal of this project is to refine an evaluation method for assessing gender bias, specifically underrepresentation and stereotyping, in German MT. Central to this is a dataset that we will expand and improve, e.g. by integrating gender-neutral language plus better cultural and linguistic accuracy. Furthermore, we revise the automatic evaluation process of MT systems. We will then test popular MT models such as DeepL, and LLMs like ChatGPT for potential biases. Mid-Bachelor or Master students in computer science, linguistics, or social sciences with an interest in MT, gender studies, and fair technology are invited to join this project. Basic Python skills are a plus, but a willingness to learn is the most important thing. Let’s contribute to the development of fairer, more inclusive translation technologies together!

Project leader: Michelle Kappl (Contact: michelle.kappl@tu-berlin.de)

Language of the Group: English

Dates: Tuesday 12:00-16:00, weekly (or by arrangement), first session Tuesday, April 22, 2025

Room of the Group: MAR 0.007, Marchstraße 23 , 10587 Berlin

Further information:

·      Information on participation in an X-Tutorial

·      Module description X-Tutorials