Related papers: Biased Tales: Cultural and Topic Bias in Generating Children's Stories

Biased Tales: Cultural and Topic Bias in Generating Children's Stories

URL: http://arxiv.org/abs/2509.07908v1
Date: Tue, 09 Sep 2025 16:51:16 GMT
Title: Biased Tales: Cultural and Topic Bias in Generating Children's Stories
Authors: Donya Rooein, Vilém Zouhar, Debora Nozza, Dirk Hovy,
Abstract summary: Biased Tales is a dataset designed to analyze how biases influence protagonists' attributes and story elements.<n>Our analysis uncovers striking disparities. When the protagonist is described as a girl (as compared to a boy), appearance-related attributes increase by 55.26%.<n> Stories featuring non-Western children disproportionately emphasize cultural heritage, tradition, and family themes far more than those for Western children.
Score: 40.7784118893226
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: Stories play a pivotal role in human communication, shaping beliefs and morals, particularly in children. As parents increasingly rely on large language models (LLMs) to craft bedtime stories, the presence of cultural and gender stereotypes in these narratives raises significant concerns. To address this issue, we present Biased Tales, a comprehensive dataset designed to analyze how biases influence protagonists' attributes and story elements in LLM-generated stories. Our analysis uncovers striking disparities. When the protagonist is described as a girl (as compared to a boy), appearance-related attributes increase by 55.26%. Stories featuring non-Western children disproportionately emphasize cultural heritage, tradition, and family themes far more than those for Western children. Our findings highlight the role of sociocultural bias in making creative AI use more equitable and diverse.

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