Researchers and policy-makers have started creating frameworks and guidelines for building machine-learning (ML) pipelines with a human-centered lens. Machine Learning pipelines stand for all the necessary steps to develop ML systems (e.g., developing a predictive keyboard). On the other hand, a child-centered focus in developing ML systems has been recently gaining interest as children are becoming users of these products. These efforts dominantly focus on children's interaction with ML-based systems. However, from our experience, ML pipelines are yet to be adapted using a child-centered lens. In this paper, we list the questions we ask ourselves in adapting human-centered ML pipelines to child-centered ones. We also summarize two case studies of building end-to-end ML pipelines for children's products.

翻译：研究人员和政策制定者已开始构建以人为中心的机器学习（ML）流水线的框架与指南。ML流水线涵盖了开发ML系统（例如开发预测性键盘）所需的所有必要步骤。另一方面，随着儿童成为这些产品的用户，以儿童为中心开发ML系统的方向近期日益受到关注。当前研究主要聚焦于儿童与基于ML的系统之间的交互。然而，根据我们的经验，ML流水线尚未通过以儿童为中心的视角进行适配。本文列举了我们在将人本化ML流水线改造为儿童中心化流水线过程中提出的问题，并总结了两项面向儿童产品的端到端ML流水线构建案例研究。