A new dataset and surprisal-based metric estimate that roughly 20% of naturally occurring generic sentences are weak generalisations and that generics are more context-sensitive than explicit quantifiers.
Towards Countering Essentialism through Social Bias Reasoning
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abstract
Essentialist beliefs (i.e., believing that members of the same group are fundamentally alike) play a central role in social stereotypes and can lead to harm when left unchallenged. In our work, we conduct exploratory studies into the task of countering essentialist beliefs (e.g., ``liberals are stupid''). Drawing on prior work from psychology and NLP, we construct five types of counterstatements and conduct human studies on the effectiveness of these different strategies. Our studies also investigate the role in choosing a counterstatement of the level of explicitness with which an essentialist belief is conveyed. We find that statements that broaden the scope of a stereotype (e.g., to other groups, as in ``conservatives can also be stupid'') are the most popular countering strategy. We conclude with a discussion of challenges and open questions for future work in this area (e.g., improving factuality, studying community-specific variation) and we emphasize the importance of work at the intersection of NLP and psychology.
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cs.CL 1years
2024 1verdicts
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Generics are puzzling. Can language models find the missing piece?
A new dataset and surprisal-based metric estimate that roughly 20% of naturally occurring generic sentences are weak generalisations and that generics are more context-sensitive than explicit quantifiers.