Despite the growing concerns surrounding algorithmic biases in generative AI (artificial intelligence), there is a noticeable lack of research on how to facilitate children and young people’s awareness and understanding of them. This study aimed to address this gap by conducting hands-on workshops with fourth- and seventh-grade students in Finland, and by focusing on students’ ( N = 209) evolving explanations of the potential causes of algorithmic biases within text-to-image generative models. Statistically significant progress in children’s data-driven explanations was observed on a written reasoning test, which was administered prior to and after the intervention, as well as in their responses to the worksheets they filled out during a lesson that focused on algorithmic biases. The article concludes with a discussion on the development and facilitation of children’s understanding of algorithmic biases.

中文翻译：

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增强儿童对文本到图像生成人工智能中算法偏差的理解


尽管人们越来越担心生成人工智能（人工智能）中的算法偏差，但如何促进儿童和年轻人对它们的认识和理解却明显缺乏研究。本研究旨在通过与芬兰四年级和七年级学生举办实践研讨会来解决这一差距，并重点关注学生 (N = 209) 对文本到图像中算法偏差的潜在原因的不断发展的解释生成模型。在干预前后进行的书面推理测试中，以及他们在关注算法偏差的课程中对填写的工作表的反应中，观察到儿童在数据驱动解释方面取得了统计学上的显着进步。本文最后讨论了儿童对算法偏差的理解的发展和促进。