Published studies have suggested the bias of automated face-based gender
classification algorithms across gender-race groups. Specifically, unequal
accuracy rates were obtained for women and dark-skinned people. To mitigate the
bias of gender classifiers, the vision community has developed several
strategies. However, the efficacy of these mitigation strateg
这项研究分析了由三种流行的生成人工智能工具生成的图像 - Midjourney、Stable Diffusion 和 DALLE 2 - 代表各种职业，以调查 AI 生成器中潜在的偏见。我们的分析揭示了这些 AI 生成器中两个主要关注领域，包括（1）系统性的性别和种族偏见，以及（2）面部表情和外貌方面的微妙偏见。