This project investigates skin tone bias in text-to-image generation by analyzing the output of Stable Diffusion models when prompted with socially and occupationally descriptive text. Despite the growing popularity of generative models like Stable Diffusion, little has been done to evaluate how these models reproduce or amplify visual bias—especially related to skin tone, perceived race, and social class—based solely on textual prompts.
