Informing age-appropriate AI: Examining principles and practices of AI for children

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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.

Authors: Wang, G; Zhao, J; Van Kleek, M; Shadbolt, N

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Association for Computing Machinery
• Journal: Proceedings of the CHI Conference on Human Factors in Computing Systems
• Article number: 536
• Publication date: 2022-04-29
• Acceptance date: 2021-11-18
• Event title: CHI '22: CHI Conference on Human Factors in Computing Systems
• DOI: 10.1145/3491102.3502057
• ISBN: 978-1-4503-9157-3
• Language: English
• Keywords: FFR