CYCLDec 11, 2023

Disentangling Perceptions of Offensiveness: Cultural and Moral Correlates

arXiv:2312.06861v139 citationsh-index: 12FAccT
Originality Incremental advance
AI Analysis

This addresses the need for AI models to respect diverse cultural and moral values in offensive language detection, which is incremental by highlighting existing gaps in current approaches.

The study tackled the problem of subjective perceptions of offensiveness in AI language detection by conducting a large-scale cross-cultural analysis with 4309 participants from 21 countries, finding substantial differences driven by moral values like Care and Purity.

Perception of offensiveness is inherently subjective, shaped by the lived experiences and socio-cultural values of the perceivers. Recent years have seen substantial efforts to build AI-based tools that can detect offensive language at scale, as a means to moderate social media platforms, and to ensure safety of conversational AI technologies such as ChatGPT and Bard. However, existing approaches treat this task as a technical endeavor, built on top of data annotated for offensiveness by a global crowd workforce without any attention to the crowd workers' provenance or the values their perceptions reflect. We argue that cultural and psychological factors play a vital role in the cognitive processing of offensiveness, which is critical to consider in this context. We re-frame the task of determining offensiveness as essentially a matter of moral judgment -- deciding the boundaries of ethically wrong vs. right language within an implied set of socio-cultural norms. Through a large-scale cross-cultural study based on 4309 participants from 21 countries across 8 cultural regions, we demonstrate substantial cross-cultural differences in perceptions of offensiveness. More importantly, we find that individual moral values play a crucial role in shaping these variations: moral concerns about Care and Purity are significant mediating factors driving cross-cultural differences. These insights are of crucial importance as we build AI models for the pluralistic world, where the values they espouse should aim to respect and account for moral values in diverse geo-cultural contexts.

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