Large language models (LLMs) have demonstrated remarkable capabilities across a broad
spectrum of tasks. They have attracted significant attention and been deployed in numerous …

Generative AI systems across modalities, ranging from text, image, audio, and video, have
broad social impacts, but there exists no official standard for means of evaluating those …

Deep neural networks often learn unintended bias during training, which might have harmful
effects when deployed in realworld settings. This work surveys 214 papers related to …

Recent research has revealed undesirable biases in NLP data and models. However, these
efforts focus on social disparities in West, and are not directly portable to other geo-cultural …

With rapid development and deployment of generative language models in global settings,
there is an urgent need to also scale our measurements of harm, not just in the number and …

Rapid advancements of large language models (LLMs) have enabled the processing,
understanding, and generation of human-like text, with increasing integration into systems …

Warning: This paper contains content that may be offensive or upsetting. Language
technologies that perpetuate stereotypes actively cement social hierarchies. This study …

Abstract As Large Language Models and Natural Language Processing (NLP) technology
rapidly develops and spreads into daily life, it becomes crucial to anticipate how its use …

Abstract Objectives Immigrants to Canada tend to have a lower incidence of diagnosed
depression than nonimmigrants. One theory suggests that this “healthy immigrant effect …

Abstract As Large Language Models and Natural Language Processing (NLP) technology
rapidly develop and spread into daily life, it becomes crucial to anticipate how their use …