Creative AI Literacies for Families

Abstract: Many families engage daily with artificial intelligence (AI) applications, from conversations with a voice assistant to mobile navigation searches. Unfortunately, existing intelligent technologies in the home are prone to algorithmic bias and cyber-security attacks. To ensure the new generations of children growing up with AI can develop a critical understanding of AI technologies, we must explore parents' roles in helping their children develop AI literacies.

While AI technologies often perpetuate and exacerbate inequities in many contexts, they could also support family learning goals if properly contextualized for use by stakeholders. Our prior work has explored this idea in informing youth about how to train and program smart games in self-directed learning experiences and informing curriculum & technology designers' domain expertise with empirical evidence on family AI literacies practices. This proposed work investigates how to design novel programming and AI learning interfaces for families to develop literacies for creating and being creative with AI. This involves the development of CogniSynth, a family AI programming tool.

My dissertation demonstrates the following thesis:
family joint engagement in creative AI literacy activities enables children to: (1) discover the core concepts of AI technologies and the power they can bring, (2) foster critical reflection on uses of AI in the home and beyond, and (3) learn creative coding with AI as a way to enable self-expression.

Supervisory Committee

Chair: Amy J. Ko, Professor, iSchool, University of Washington
Graduate School Representative: Jon Froehlich, Associate Professor, Allen School, University of Washington
Member: Katie Davis, iSchool, University of Washington
Member: Ben Shapiro, Associate Professor, Allen School, University of Washington