  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.
