Critical Machine Learning (CML) is about recognizing, questioning, and taking action against inequities in machine learning data practices and understanding the ideological, historical and political dimensions of data production and usage. Both machine learning and artificial intelligence applications are heavily reliant on data and are often used to make automated recommendations and decisions in real world situations that can be harmful for people, especially those from non-dominant populations and those living in poverty. In this program, youth are asked to design an algorithm, train their own machine, and critique and express solutions to harmful consequences of socio-technical systems.

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