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Experts Unite, Kids Delight: Co-Designing an Inclusive AI Literacy Educational Tool for Children

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Forthcoming

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Experts Unite, Kids Delight: Co-Designing an Inclusive AI Literacy Educational Tool for Children. / Collyer-Hoar, Gail; Castellani, Aurora; Guluzade, Lala et al.
Interaction Design and Children (IDC) 2025. ACM, 2025.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Collyer-Hoar, G, Castellani, A, Guluzade, L, Tomczyk, B, Bilal, H & Rubegni, E 2025, Experts Unite, Kids Delight: Co-Designing an Inclusive AI Literacy Educational Tool for Children. in Interaction Design and Children (IDC) 2025. ACM.

APA

Collyer-Hoar, G., Castellani, A., Guluzade, L., Tomczyk, B., Bilal, H., & Rubegni, E. (in press). Experts Unite, Kids Delight: Co-Designing an Inclusive AI Literacy Educational Tool for Children. In Interaction Design and Children (IDC) 2025 ACM.

Vancouver

Collyer-Hoar G, Castellani A, Guluzade L, Tomczyk B, Bilal H, Rubegni E. Experts Unite, Kids Delight: Co-Designing an Inclusive AI Literacy Educational Tool for Children. In Interaction Design and Children (IDC) 2025. ACM. 2025

Author

Collyer-Hoar, Gail ; Castellani, Aurora ; Guluzade, Lala et al. / Experts Unite, Kids Delight : Co-Designing an Inclusive AI Literacy Educational Tool for Children. Interaction Design and Children (IDC) 2025. ACM, 2025.

Bibtex

@inproceedings{abdeb81623ef4183aabffe62901bccfa,
title = "Experts Unite, Kids Delight: Co-Designing an Inclusive AI Literacy Educational Tool for Children",
abstract = "The increasing adoption of generative AI raises concerns regarding its potential to reinforce gender stereotypes, especially in content aimed at children. AI-generated images that reflect traditional gender roles can inadvertently influence children{\textquoteright}s perceptions, embedding unconscious biases. Through co-design sessions with domain experts, we developed a child-friendly generative AI web application designed with dual purpose: (1) analysing children{\textquoteright}s choices to determine potential underlying bias and whether children{\textquoteright}s own gender identity influences these choices, and (2) investigating if specific non-aesthetic traits prompt the AI to produce characters with stereotypical presentations.",
author = "Gail Collyer-Hoar and Aurora Castellani and Lala Guluzade and Ben Tomczyk and Hania Bilal and Elisa Rubegni",
year = "2025",
month = apr,
day = "16",
language = "English",
booktitle = "Interaction Design and Children (IDC) 2025",
publisher = "ACM",

}

RIS

TY - GEN

T1 - Experts Unite, Kids Delight

T2 - Co-Designing an Inclusive AI Literacy Educational Tool for Children

AU - Collyer-Hoar, Gail

AU - Castellani, Aurora

AU - Guluzade, Lala

AU - Tomczyk, Ben

AU - Bilal, Hania

AU - Rubegni, Elisa

PY - 2025/4/16

Y1 - 2025/4/16

N2 - The increasing adoption of generative AI raises concerns regarding its potential to reinforce gender stereotypes, especially in content aimed at children. AI-generated images that reflect traditional gender roles can inadvertently influence children’s perceptions, embedding unconscious biases. Through co-design sessions with domain experts, we developed a child-friendly generative AI web application designed with dual purpose: (1) analysing children’s choices to determine potential underlying bias and whether children’s own gender identity influences these choices, and (2) investigating if specific non-aesthetic traits prompt the AI to produce characters with stereotypical presentations.

AB - The increasing adoption of generative AI raises concerns regarding its potential to reinforce gender stereotypes, especially in content aimed at children. AI-generated images that reflect traditional gender roles can inadvertently influence children’s perceptions, embedding unconscious biases. Through co-design sessions with domain experts, we developed a child-friendly generative AI web application designed with dual purpose: (1) analysing children’s choices to determine potential underlying bias and whether children’s own gender identity influences these choices, and (2) investigating if specific non-aesthetic traits prompt the AI to produce characters with stereotypical presentations.

M3 - Conference contribution/Paper

BT - Interaction Design and Children (IDC) 2025

PB - ACM

ER -