Speciesist Language and Nonhuman Animal Bias in English Masked Language Models
Various existing studies have analyzed what social biases are inherited by NLP models. These biases may directly or indirectly harm people, therefore previous studies have focused only on human attributes. If the social biases in NLP models can be indirectly harmful to humans involved, then the models can also indirectly harm nonhuman animals. However, no research on social biases in NLP regarding nonhumans exists. In this paper, we analyze biases to nonhuman animals, i.e. speciesist bias, inherent in English Masked Language Models. We analyze this bias using template-based and corpus-extracted sentences which contain speciesist (or non-speciesist) language, to show that these models tend to associate harmful words with nonhuman animals. Our code for reproducing the experiments will be made available on GitHub.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Speciesist Language and Nonhuman Animal Bias in English Masked Language Models
Various existing studies have analyzed what social biases are inherited by NLP models. These biases may directly or indirectly harm people, therefore previous studies have focused only on human attributes. However, until…
Speciesism in Natural Language Processing Research
Natural Language Processing (NLP) research on AI Safety and social bias in AI has focused on safety for humans and social bias against human minorities. However, some AI ethicists have argued that the moral significance …
SurveySpeciesist bias in AI -- How AI applications perpetuate discrimination and unfair outcomes against animals
Massive efforts are made to reduce biases in both data and algorithms in order to render AI applications fair. These efforts are propelled by various high-profile cases where biased algorithmic decision-making caused har…
Decision MakingFairnessRecommendation SystemsSpeciesism in AI: Evaluating Discrimination Against Animals in Large Language Models
As large language models (LLMs) become more widely deployed, it is crucial to examine their ethical tendencies. Building on research on fairness and discrimination in AI, we investigate whether LLMs exhibit speciesist bi…
Text GenerationWhat do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text
As machine learning systems become increasingly embedded in society, their impact on human and nonhuman life continues to escalate. Technical evaluations have addressed a variety of potential harms from large language mo…