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Meta-Cultural Competence: Climbing the Right Hill of Cultural Awareness

Saha, Sougata
Pandey, Saurabh Kumar
Choudhury, Monojit
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Department
Natural Language Processing
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Type
Conference proceeding
Date
2025
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Language
English
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Abstract
Numerous recent studies have shown that Large Language Models (LLMs) are biased towards a Western and Anglo-centric worldview, which compromises their usefulness in non-Western cultural settings. However, culture is a complex, multifaceted topic, and its awareness, representation, and modeling in LLMs and LLM-based applications can be defined and measured in numerous ways. In this position paper, we ask what does it mean for an LLM to possess cultural awareness, and through a thought experiment, which is an extension of the Octopus test proposed by Bender and Koller (2020), we argue that it is not cultural awareness or knowledge, rather meta-cultural competence, which is required of an LLM and LLM-based AI system that will make it useful across various, including completely unseen, cultures. We lay out the principles of meta-cultural competence AI systems, and discuss ways to measure and model those.
Citation
S. Saha, S. K. Pandey, and M. Choudhury, “Meta-Cultural Competence: Climbing the Right Hill of Cultural Awareness,” vol. 1, pp. 8025–8042, Jun. 2025, doi: 10.18653/V1/2025.NAACL-LONG.408
Source
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Conference
2025 Conference of the North American Chapter of the Association for Computational Linguistics-NAACL
Keywords
Cultural Awareness, Meta-Cultural Competence, Large Language Models (LLMs), Cultural Bias, Cross-Cultural Evaluation, Multicultural NLP, Cultural Representation, Equitable AI Systems
Subjects
Source
2025 Conference of the North American Chapter of the Association for Computational Linguistics-NAACL
Publisher
Association for Computational Linguistics
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