Informing Age-Appropriate AI: Examining Principles and Practices of AI for Children

Abstract

AI systems are becoming increasingly pervasive within children’s devices, apps, and services. However, it is not yet well-understood how risks and ethical considerations of AI relate to children. This paper makes three contributions to this area - first, it identifies ten areas of alignment between general AI frameworks and codes for age-appropriate design for children. Then, to understand how such principles relate to real application contexts, we conducted a landscape analysis of children’s AI systems, via a systematic literature review including 188 papers. This analysis revealed a wide assortment of applications, and that most systems’ designs addressed only a small subset of principles among those we identified. Finally, we synthesised our findings in a framework to inform a new “Code for Age-Appropriate AI”, which aims to provide timely input to emerging policies and standards, and inspire increased interactions between the AI and child-computer interaction communities.

Ge Wang

DPhil (Ph.D.) student

I’m a Dphil student in the Department of Computer Science at University of Oxford. My research investigates the algorithmic impact on families and children, and what that means for their long-term development. I’m keen to explore the potential for designing more age-appropriate AI for families, as well as building more ethical web and data architecture for them. My research takes a human-centric approach, and focuses on understanding users' needs in order to design technological prototypes that are of real impact on today’s society.