Feb. 5, 2024, 3:46 p.m. | Nouar AlDahoul Talal Rahwan Yasir Zaki

cs.CV updates on arXiv.org arxiv.org

Text-to-image generative AI models such as Stable Diffusion are used daily by millions worldwide. However, many have raised concerns regarding how these models amplify racial and gender stereotypes. To study this phenomenon, we develop a classifier to predict the race, gender, and age group of any given face image, and show that it achieves state-of-the-art performance. Using this classifier, we quantify biases in Stable Diffusion across six races, two genders, five age groups, 32 professions, and eight attributes. We then …

age ai models amplify classifier concerns cs.ai cs.cv daily diffusion face free gender generated generative generative ai models image race show stable diffusion stereotypes study text text-to-image

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