Title: Designing for Algorithmic Autonomy: Lessons from Children and Families in a Datafied World

Abstract: In this talk, I will focus on the concept of algorithmic autonomy—how we can support users in understanding and gaining greater autonomy when interacting with algorithmic systems. I will illustrate this through a multi-year HCI project on children and online datafication. Children are a particularly important group to study because they are growing up in digital environments where algorithmic systems shape much of their everyday experiences, often in ways that are opaque and beyond their control. Datafication—the transformation of children’s activities, preferences, and interactions into data—raises pressing questions about privacy, agency, and how young people learn to navigate algorithmically mediated environments. This series of studies has engaged more than 500 children and their parents, demonstrating how a typical HCI research trajectory unfolds: from establishing ground truth, to conducting co-design, to developing systems, and ultimately to deployment. Together, these efforts highlight both the challenges and opportunities in designing for user autonomy in an era of pervasive algorithmic decision-making.

Bio: Ge “Tiffany” Wang is an Assistant Professor of Computer Science at the Siebel School of Computing and Data Science. Her research lies at the intersection of human-computer interaction (HCI), human-centered artificial intelligence (HAI), and usable security and privacy. As AI becomes increasingly embedded in everyday smart devices, these systems have shifted from passive tools to active agents that analyze personal data, infer characteristics, and make consequential decisions. Wang’s work explores how AI can be designed to be more autonomy-supportive, enabling individuals to better understand, challenge, and assert agency over the algorithmic decisions that shape their digital lives.