Descriptions of women are longer than that of men: An analysis of gender portrayal prompts in Stable Diffusion
Yan Asadchy, Maximilian Schich

TL;DR
This study analyzes over 1.8 million prompts used in AI image generation to reveal gender stereotypes, showing women are described with longer, more body-focused terms, highlighting biases in prompt construction.
Contribution
It provides a large-scale statistical analysis of gendered language in prompts for Stable Diffusion, uncovering stereotypical portrayals and differences in description length between genders.
Findings
Women have longer descriptions than men in prompts.
Stereotypes such as 'strong' for men and 'beautiful' for women are prevalent.
Prompting practices reflect cultural stereotypes influencing AI-generated images.
Abstract
Generative AI for image creation emerges as a staple in the toolkit of digital artists, visual designers, and the general public. Social media users have many tools to shape their visual representation: image editing tools, filters, face masks, face swaps, avatars, and AI-generated images. The importance of the right profile image can not be understated: It is crucial for creating the right first impression, sustains trust, and enables communication. Conventionally correct representation of individuals, groups, and collectives may help foster inclusivity, understanding, and respect in society, ensuring that diverse perspectives are acknowledged and valued. While previous research revealed the biases in large image datasets such as ImageNet and inherited biases in the AI systems trained on it, within this work, we look at the prejudices and stereotypes as they emerge from textual prompts…
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Taxonomy
TopicsMedia, Gender, and Advertising · Media Influence and Health
