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Cited by 76Ethics and Social Impacts of AIChild Development and Digital TechnologyInnovative Human-Technology Interaction

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

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Wang, Ge, Zhao, Jun, Van Kleek, Max, Shadbolt, Nigel·2022·CHI Conference on Human Factors in Computing Systems
DOI 10.1145/3491102.3502057
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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.

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Authors
Wang, G., Zhao, J., Van Kleek, M., & Shadbolt, N.
Affiliations
  • University of Oxford (GB)
  • Department of Computer Science, University of Oxford, United Kingdom
ORCID
Venue
CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2022-04-29
Pages
1-29
DOI
10.1145/3491102.3502057
OpenAlex
W4225095645
Cited by
76
References
125
Citations by year
2026: 20 · 2025: 27 · 2024: 18 · 2023: 11
FWCI
13.91
Type
conference paper
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
CHI Conference on Human Factors in Computing Systems (publishedVersion)
Funders
Engineering and Physical Sciences Research Council (EP/J017728/2)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Education › Child Development and Digital Technology
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
design principles, AI risks, design codes, landscape analysis

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