Session 14 – Part 2: Yasmin B. Kafai & Luis Morales-Navarro (USA)

High School Youth Peer Auditing of Machine Learning-Powered Applications to Promote Computational Literacies

The Role of Data in Artificial Intelligence Literacy in school education

The increased prominence of artificial intelligence/machine learning in youth’s lives has called for inclusion in computational literacies. Our focus on algorithm auditing—a practice which involves repeated examination of an algorithm’s output to make more transparent inner workings and possible impact—addresses key dimensions of artificial intelligence/machine learning literacies: (a) building on informal personal practices that youth engage with everyday technologies, (b) connecting with already existing computational thinking practices, and (c) integrating critical evaluation for algorithmic justice. In this presentation, we share findings from a study that positioned youth (ages 14-15) as peer-auditors. We conducted a two-week workshop in which youth designed machine-learning powered applications and later audited each other’s projects. We analyzed pre/post clinical interviews in which they were presented with auditing tasks. Our analyses show that in post interviews all youth identified algorithmic biases and inferred dataset and model design issues. Youth also discussed algorithmic justice and machine learning model improvements. Furthermore, youth reflected that auditing provided them new perspectives on model functionality and ideas to improve their own models. We discuss potential applications of algorithm auditing in K-12 education.

Yasmin B. Kafai is Lori and Michael Milken President’s Distinguished Professor at the Graduate School of Education, University of Pennsylvania, with a courtesy appointment in Computer and Information Science. She is a learning designer and researcher of online tools, projects, and communities to promote coding, criticality, and creativity. With colleagues at MIT, she developed the widely popular programming language Scratch, now with over 100 million users, and researched computational participation in clubs, classrooms, and communities. She is currently researching the use of algorithm auditing with high school youth and teachers. As part of the nationwide Exploring Computer Science curriculum, she has investigated electronic textiles to introduce computing, engineering, and machine learning to high school students and teachers. She has written several books, among them “Connected Code: Why Children Need to Learn Programming,” “Connected Gaming: What Making Videogames Can Teach Us About Learning and Literacy,” and recently edited with Nathan Holbert and Matthew Berland “Designing Constructionist Futures: The Art, Theory, and Practice of Learning Designs” — all published by MIT Press. Kafai earned a doctorate in education from Harvard University while working at the MIT Media Lab. She is an elected Fellow of the American Educational Research Association and the International Society for the Learning Sciences.

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