Global Voices, Local Biases: Socio-Cultural Prejudices across Languages
Anjishnu Mukherjee, Chahat Raj, Ziwei Zhu, Antonios Anastasopoulos
Abstract
Human biases are ubiquitous but not uniform: disparities exist across linguistic, cultural, and societal borders. As large amounts of recent literature suggest, language models (LMs) trained on human data can reflect and often amplify the effects of these social biases. However, the vast majority of existing studies on bias are heavily skewed towards Western and European languages. In this work, we scale the Word Embedding Association Test (WEAT) to 24 languages, enabling broader studies and yielding interesting findings about LM bias. We additionally enhance this data with culturally relevant information for each language, capturing local contexts on a global scale. Further, to encompass more widely prevalent societal biases, we examine new bias dimensions across toxicity, ableism, and more. Moreover, we delve deeper into the Indian linguistic landscape, conducting a comprehensive regional bias analysis across six prevalent Indian languages. Finally, we highlight the significance of these social biases and the new dimensions through an extensive comparison of embedding methods, reinforcing the need to address them in pursuit of more equitable language models.- Anthology ID:
- 2023.emnlp-main.981
- Volume:
- Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 15828–15845
- Language:
- URL:
- https://aclanthology.org/2023.emnlp-main.981
- DOI:
- 10.18653/v1/2023.emnlp-main.981
- Cite (ACL):
- Anjishnu Mukherjee, Chahat Raj, Ziwei Zhu, and Antonios Anastasopoulos. 2023. Global Voices, Local Biases: Socio-Cultural Prejudices across Languages. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 15828–15845, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Global Voices, Local Biases: Socio-Cultural Prejudices across Languages (Mukherjee et al., EMNLP 2023)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.emnlp-main.981.pdf