Learning to Deconstruct AI/ML Systems: Scaffolds to Support Learners in Critically Evaluating AI/ML Systems
This symposium presents scaffolds that help learners critically deconstruct and evaluate AI/ML systems rather than treat them as black boxes. It draws on participatory design and case studies to foster equitable, contextually relevant practices for examining how such systems work and affect users.