The Design of a Critical Machine Learning Program for Young Learners

Abstract

Machine Learning (ML) is integrated into many of the technologies we use daily.However, biased training datasets have shown to be harmful for marginalized populations.As future consumers and producers of technologies, children should have the technical and social expertise to engage with such issues in ML.In this study, we describe a series of activities designed for elementary and middle-school aged children to learn concepts of machine learning (ML), bias, and the sociopolitical implications of ML.Grounded in critical constructionism principles, we describe how children engage in reflective discussions, tinker with existing ML tools, and build an ML-based robot for social good.