Tootfinder

Bias Amplification in Stable Diffusion's Representation of Stigma Through Skin Tones and Their Homogeneity
Kyra Wilson, Sourojit Ghosh, Aylin Caliskan
https://arxiv.org/abs/2508.17465

Bias Amplification in Stable Diffusion's Representation of Stigma Through Skin Tones and Their Homogeneity
Text-to-image generators (T2Is) are liable to produce images that perpetuate social stereotypes, especially in regards to race or skin tone. We use a comprehensive set of 93 stigmatized identities to determine that three versions of Stable Diffusion (v1.5, v2.1, and XL) systematically associate stigmatized identities with certain skin tones in generated images. We find that SD XL produces skin tones that are 13.53% darker and 23.76% less red (both of which indicate higher likelihood of societal…

WeDesign: Generative AI-Facilitated Community Consultations for Urban Public Space Design
Rashid Mushkani, Hugo Berard, Shin Koseki
https://arxiv.org/abs/2508.19256 https://

WeDesign: Generative AI-Facilitated Community Consultations for Urban Public Space Design
Community consultations are integral to urban planning processes intended to incorporate diverse stakeholder perspectives. However, limited resources, visual and spoken language barriers, and uneven power dynamics frequently constrain inclusive decision-making. This paper examines how generative text-to-image methods, specifically Stable Diffusion XL integrated into a custom platform (WeDesign), may support equitable consultations. A half-day workshop in Montreal involved five focus groups, eac…

Evaluating and comparing gender bias across four text-to-image models
Zoya Hammad, Nii Longdon Sowah
https://arxiv.org/abs/2509.08004 https://arxiv.org/pdf…

Evaluating and comparing gender bias across four text-to-image models
As we increasingly use Artificial Intelligence (AI) in decision-making for industries like healthcare, finance, e-commerce, and even entertainment, it is crucial to also reflect on the ethical aspects of AI, for example the inclusivity and fairness of the information it provides. In this work, we aimed to evaluate different text-to-image AI models and compare the degree of gender bias they present. The evaluated models were Stable Diffusion XL (SDXL), Stable Diffusion Cascade (SC), DALL-E and E…