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arXiv · 2509.24999

Color, Gender, and Bias: Examining the Role of Stereotyped Colors in Visualization-Driven Pay Decisions

Florent Cabric·Margret Vilborg Bjarnadottir·Petra Isenberg
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Abstract

We investigate the impact of stereotyped gender-color associations in a visualization-driven decision-making task. In the context of gender data visualization, the well-known "pink for girls and blue for boys" color assignment is associated with stereotypes that could bias readers and decision-makers. Understanding the effects of using stereotyped colors in visualizations for decision-making can help designers better choose colors in stereotype-prone contexts. We therefore explore the potential impact of stereotyped colors on compensation decision-making through two crowdsourced experiments. In these experiments, we evaluate how the association of color with gender (stereotyped vs non-stereotyped) affects the user's allocation decisions in the context of salary adjustments. Our results indicate that explicit expression of the color-gender associations, in the form of a legend on the data visualization, leads to in-group favoritism. However, in the absence of a legend, this in-group favoritism disappears, and a small effect of non-stereotyped colors is observed. A free copy of this paper with all supplemental materials is available at https://osf.io/d4q3v/?view_only=22b636d6f7bb4a7991d9576933b3aaad

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Florent Cabric, Margret Vilborg Bjarnadottir, Petra Isenberg. 2025-09-29. Color, Gender, and Bias: Examining the Role of Stereotyped Colors in Visualization-Driven Pay Decisions. https://arxiv.org/abs/2509.24999

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