Supporting Holistic AI Ethics Literacy Education Through Critical Reflection : Three Recommendations for Fostering Children’s Ethical Growth

With childhood increasingly mediated by AI and marked by children’s heightened vulnerabilities, critical reflection emerges as a vital tool for both understanding and strengthening children’s ethical reasoning, steering them between uncritical adoption and blanket pessimism about AI. As such, we present outcomes of a study with 66 children (aged 10-11) wherein we trace what children attend to and how they perceive AI ethics. Aligned with UNESCO’s ethical principles for AI, we utilised 10 design fiction scenarios set in familiar contexts to prompt reflection. Mixed-methods data showed that children’s perceptions skewed towards caution; ethical concerns were also distributed unevenly across principles, indicating where AI ethics literacy may need targeted scaffolding. This work contributes to HCI by highlighting the complexity of children’s perceptions and showing how speculative, reflection-based methods can shift children’s ethical considerations about AI, with three recommendations for AI ethics literacy education that the HCI community should consider in future.

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Publication Details

Journal
Lancaster EPrints (Lancaster University)
Published
2026-01-15
Primary Topic
Ethics and Social Impacts of AI
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article
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article

Supporting Holistic AI Ethics Literacy Education Through Critical Reflection : Three Recommendations for Fostering Children’s Ethical Growth

Elisa Rubegni, Gail Collyer-Hoar, Ben Tomczyk
Lancaster EPrints (Lancaster University)
Ethics and Social Impacts of AI
article

Supporting Holistic AI Ethics Literacy Education Through Critical Reflection : Three Recommendations for Fostering Children’s Ethical Growth

Elisa Rubegni, Gail Collyer-Hoar, Ben Tomczyk
article en

Abstract

With childhood increasingly mediated by AI and marked by children’s heightened vulnerabilities, critical reflection emerges as a vital tool for both understanding and strengthening children’s ethical reasoning, steering them between uncritical adoption and blanket pessimism about AI. As such, we present outcomes of a study with 66 children (aged 10-11) wherein we trace what children attend to and how they perceive AI ethics. Aligned with UNESCO’s ethical principles for AI, we utilised 10 design fiction scenarios set in familiar contexts to prompt reflection. Mixed-methods data showed that children’s perceptions skewed towards caution; ethical concerns were also distributed unevenly across principles, indicating where AI ethics literacy may need targeted scaffolding. This work contributes to HCI by highlighting the complexity of children’s perceptions and showing how speculative, reflection-based methods can shift children’s ethical considerations about AI, with three recommendations for AI ethics literacy education that the HCI community should consider in future.

Lancaster EPrints (Lancaster University)
Quality Education
Openalex Percentile: Top 61%
Ethics and Social Impacts of AI
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