The Psychosocial Impacts of Generative AI Harms

• URL: http://arxiv.org/abs/2405.01740v1
• Date: Thu, 2 May 2024 21:21:06 GMT
• Title: The Psychosocial Impacts of Generative AI Harms
• Authors: Faye-Marie Vassel, Evan Shieh, Cassidy R. Sugimoto, Thema Monroe-White,
• Abstract summary: generative Language Models (LMs) are increasingly being adopted in K-20 schools and one-on-one student settings. This paper explores the potential psychosocial harms of stories generated by five leading LMs in response to open-ended prompting.
• Score: 0.33748750222488655
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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