1. The Psychosocial Impacts of Generative AI Harms
- Author
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Vassel, Faye-Marie, Shieh, Evan, Sugimoto, Cassidy R., and Monroe-White, Thema
- Subjects
Computer Science - Computation and Language - Abstract
The rapid emergence of generative Language Models (LMs) has led to growing concern about the impacts that their unexamined adoption may have on the social well-being of diverse user groups. Meanwhile, LMs are increasingly being adopted in K-20 schools and one-on-one student settings with minimal investigation of potential harms associated with their deployment. Motivated in part by real-world/everyday use cases (e.g., an AI writing assistant) this paper explores the potential psychosocial harms of stories generated by five leading LMs in response to open-ended prompting. We extend findings of stereotyping harms analyzing a total of 150K 100-word stories related to student classroom interactions. Examining patterns in LM-generated character demographics and representational harms (i.e., erasure, subordination, and stereotyping) we highlight particularly egregious vignettes, illustrating the ways LM-generated outputs may influence the experiences of users with marginalized and minoritized identities, and emphasizing the need for a critical understanding of the psychosocial impacts of generative AI tools when deployed and utilized in diverse social contexts., Comment: Presented in Impact of GenAI on Social and Individual Well-being at AAAI 2024 Spring Symposium Series (2024)
- Published
- 2024