Logo des Repositoriums
 
Textdokument

Measuring Gender Bias in German Language Generation

Lade...
Vorschaubild

Volltext URI

Dokumententyp

Zusatzinformation

Datum

2022

Zeitschriftentitel

ISSN der Zeitschrift

Bandtitel

Verlag

Gesellschaft für Informatik, Bonn

Zusammenfassung

Most existing methods to measure social bias in natural language generation are specified for English language models. In this work, we developed a German regard classifier based on a newly crowd-sourced dataset. Our model meets the test set accuracy of the original English version. With the classifier, we measured binary gender bias in two large language models. The results indicate a positive bias toward female subjects for a German version of GPT-2 and similar tendencies for GPT-3. Yet, upon qualitative analysis, we found that positive regard partly corresponds to sexist stereotypes. Our findings suggest that the regard classifier should not be used as a single measure but, instead, combined with more qualitative analyses.

Beschreibung

Kraft,Angelie; Zorn,Hans-Peter; Fecht,Pascal; Simon,Judith; Biemann,Chris; Usbeck,Ricardo (2022): Measuring Gender Bias in German Language Generation. INFORMATIK 2022. DOI: 10.18420/inf2022_108. Gesellschaft für Informatik, Bonn. PISSN: 1617-5468. ISBN: 978-3-88579-720-3. pp. 1257-1274. Trustworthy AI in Science and Society. Hamburg. 26.-30. September 2022

Zitierform

Tags