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

Authors:

Nigel ShadboltAuthors Info & Claims

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Article No.: 536, Pages 1 - 29

https://doi.org/10.1145/3491102.3502057

Published: 29 April 2022 Publication History

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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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Index Terms

Informing Age-Appropriate AI: Examining Principles and Practices of AI for Children
1. General and reference
  1. Document types
    1. Surveys and overviews
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. HCI theory, concepts and models

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Kruis JPera MNapel ZLandoni MMurgia EHuibers TFeskens R(2024)Toward Personalised Learning Experiences: Beyond Prompt EngineeringProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3659367(644-649)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3659367
Liu DZhou HAn P(2024)"When He Feels Cold, He Goes to the Seahorse"—Blending Generative AI into Multimaterial Storymaking for Family Expressive Arts TherapyProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642852(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642852
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