S3 #44 How should machines translate sensitive language? Brain-to-brain with Sabrina Frohn.

Sabrina’s linkedin: https://www.linkedin.com/in/sabrina-frohn/

Papers:

not THE implicit bias paper but one explaining implicit and explicit bias:

“Social Justice in Our Minds, Homes, and Society: The Nature, Causes, and Consequences of Implicit Bias” by Laurie A. Rudman, 10.1023/B:SORE.0000027406.32604.f6

about the implicit association test I mentioned: https://www.projectimplicit.net/nosek/iat/default.html (I was not able to find the study I participated in, but I assume it is similar to this, perhaps was even based on this.)

bias in machine translations:

„Gender Bias in Machine Translation Systems“ Stefanie Ullmann et al., isbn: 978-3-030-88615-8

“What about em? How Commercial Machine Translation Fails to Handle (Neo-)Pronouns, Lauscher et al., 10.48550/arXiv.2305.16051

comparing LLM and MT

“Benchmarking Machine Translation with Cultural Awareness” by Binwei Yao, 10.48550/arXiv.2305.14328

„Evaluating Gender Bias in Machine Translation“, Stanovski et al., 10.18653/v1/P19-1164

machtsprache: