extended-abstract

Child-Centred AI Design: Definition, Operation, and Considerations

Authors:

Kruakae Pothong,

Jason YipAuthors Info & Claims

CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Article No.: 338, Pages 1 - 6

https://doi.org/10.1145/3544549.3573821

Published: 19 April 2023 Publication History

Abstract

AI systems and related algorithms are starting to play a variety of roles in the digital ecosystems of children - being embedded in the connected toys, smart home IoT technologies, apps, and services they interact with on a daily basis. Going forward, AI systems will, in all likelihood, become even more pervasive in children’s applications simply due to their sheer usefulness in creating compelling, adaptive, and personal user experiences. Yet, understanding the ways that AI-driven systems used by children operate, and how AI could be designed to better anticipate and respond to children’s diverse requirements is still a new and emerging area of investigation. Our goals of this workshop are to (1) extend the current critically constructive dialogue around the meaning of child-centred AI design and (2) explore ways to operationalise such child-centred AI design in practice, and finally (3) further expand and foster a community for those who are interested in designing and developing child-centred AI systems.

References

[1]

2019. Generation AI: Establishing Global Standards for Children and AI. http://www3.weforum.org/docs/WEF_Generation_AI_%20May_2019_Workshop_Report.pdf

[2]

2020. Age appropriate design code. https://ico.org.uk/media/for-organisations/guide-to-data-protection/key-data-protection-themes/age-appropriate-design-a-code-of-practice-for-online-services-2-1.pdf

[3]

2020. The state of AI in 2020. https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/global-survey-the-state-of-ai-in-2020

[4]

Ginevra Castellano, Iolanda Leite, André Pereira, Carlos Martinho, Ana Paiva, and Peter W. Mcowan. 2014. Context-Sensitive Affect Recognition for a Robotic Game Companion. ACM Trans. Interact. Intell. Syst. 4, 2, Article 10 (June 2014), 25 pages. https://doi.org/10.1145/2622615

Digital Library

[5]

Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, and Aziz Huq. 2017. Algorithmic decision making and the cost of fairness. In Proceedings of the 23rd acm sigkdd international conference on knowledge discovery and data mining. 797–806.

Digital Library

[6]

Thomas Dylan, Gavin Wood, Abigail C. Durrant, John Vines, Pablo E. Torres, Philip I. N. Ulrich, Mutlu Cukurova, Amanda Carr, Sena Çerçi, and Shaun Lawson. 2020. Designing IoT Resources to Support Outdoor Play for Children. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3313831.3376302

Digital Library

[7]

Anirudh Ekambaranathan, Jun Zhao, and Max Van Kleek. 2021. “Money Makes the World Go around”: Identifying Barriers to Better Privacy in Children’s Apps From Developers’ Perspectives. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 46, 15 pages. https://doi.org/10.1145/3411764.3445599

Digital Library

[8]

Ahmed Fadhil and Adolfo Villafiorita. 2017. An Adaptive Learning with Gamification and Conversational UIs: The Rise of CiboPoliBot. In Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (Bratislava, Slovakia) (UMAP ’17). Association for Computing Machinery, New York, NY, USA, 408–412. https://doi.org/10.1145/3099023.3099112

Digital Library

[9]

Mohamed Heni Frikha, Tarek Zlitni, and Nadia Bouassida. 2020. Towards a Recommendation System for Children’s Animated Movies Based on Chromatic Features. In Proceedings of the 2nd International Conference on Digital Tools (Virtual Event, Tunisia) (DTUC ’20). Association for Computing Machinery, New York, NY, USA, Article 22, 6 pages. https://doi.org/10.1145/3423603.3424058

Digital Library

[10]

Radhika Garg, Hua Cui, Spencer Seligson, Bo Zhang, Martin Porcheron, Leigh Clark, Benjamin R. Cowan, and Erin Beneteau. 2022. The Last Decade of HCI Research on Children and Voice-Based Conversational Agents. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, Article 149, 19 pages. https://doi.org/10.1145/3491102.3502016

Digital Library

[11]

Ben Hutchinson and Margaret Mitchell. 2019. 50 Years of Test (Un)Fairness: Lessons for Machine Learning. In Proceedings of the Conference on Fairness, Accountability, and Transparency (Atlanta, GA, USA) (FAT* ’19). Association for Computing Machinery, New York, NY, USA, 49–58. https://doi.org/10.1145/3287560.3287600

Digital Library

[12]

Kanae Kochigami, Jun Jiang, Yuriko Kakehashi, Chiwun Au, Yohei Kakiuchi, Kei Okada, and Masayuki Inaba. 2015. Walking together hand in hand: Design and evaluation of autonomous robot system that a robot recognizes moving direction with a child’s assistance of pulling its hand. In 2015 IEEE/SICE International Symposium on System Integration (SII). 738–743. https://doi.org/10.1109/SII.2015.7405071

[13]

N. Kumaresamoorthy and M.F.M. Firdhous. 2018. An APPROACH OF Filtering The Content Of Posts In Social Media. In 2018 3rd International Conference on Information Technology Research (ICITR). 1–6. https://doi.org/10.1109/ICITR.2018.8736152

[14]

Christine P Lee, Bengisu Cagiltay, and Bilge Mutlu. 2022. The Unboxing Experience: Exploration and Design of Initial Interactions Between Children and Social Robots. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, Article 151, 14 pages. https://doi.org/10.1145/3491102.3501955

Digital Library

[15]

Kung Jin Lee, Wendy Roldan, Tian Qi Zhu, Harkiran Kaur Saluja, Sungmin Na, Britnie Chin, Yilin Zeng, Jin Ha Lee, and Jason Yip. 2021. The Show Must Go On: A Conceptual Model of Conducting Synchronous Participatory Design With Children Online. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 345, 16 pages. https://doi.org/10.1145/3411764.3445715

Digital Library

[16]

Oussama Metatla, Sandra Bardot, Clare Cullen, Marcos Serrano, and Christophe Jouffrais. 2020. Robots for Inclusive Play: Co-Designing an Educational Game With Visually Impaired and Sighted Children. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376270

Digital Library

[17]

Rebecca Nicholson, Tom Bartindale, Ahmed Kharrufa, David Kirk, and Caroline Walker-Gleaves. 2022. Participatory Design Goes to School: Co-Teaching as a Form of Co-Design for Educational Technology. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, Article 150, 17 pages. https://doi.org/10.1145/3491102.3517667

Digital Library

[18]

Netta Ofer, Idan David, Hadas Erel, and Oren Zuckerman. 2019. Coding for Outdoor Play: A Coding Platform for Children to Invent and Enhance Outdoor Play Experiences. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300394

Digital Library

[19]

Aditi Ramachandran, Chien-Ming Huang, and Brian Scassellati. 2017. Give Me a Break! Personalized Timing Strategies to Promote Learning in Robot-Child Tutoring. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction (Vienna, Austria) (HRI ’17). Association for Computing Machinery, New York, NY, USA, 146–155. https://doi.org/10.1145/2909824.3020209

Digital Library

[20]

William Sandoval. 2014. Conjecture mapping: An approach to systematic educational design research. Journal of the learning sciences 23, 1 (2014), 18–36.

[21]

Yolande Strengers, Jenny Kennedy, Paula Arcari, Larissa Nicholls, and Melissa Gregg. 2019. Protection, productivity and pleasure in the smart home: emerging expectations and gendered insights from Australian early adopters. In Proceedings of the 2019 CHI conference on human factors in computing systems. 1–13.

Digital Library

[22]

Kaiwen Sun, Carlo Sugatan, Tanisha Afnan, Hayley Simon, Susan A. Gelman, Jenny Radesky, and Florian Schaub. 2021. “They See You’re a Girl If You Pick a Pink Robot with a Skirt”: A Qualitative Study of How Children Conceptualize Data Processing and Digital Privacy Risks. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 687, 34 pages. https://doi.org/10.1145/3411764.3445333

Digital Library

[23]

Kaiwen Sun, Yixin Zou, Jenny Radesky, Christopher Brooks, and Florian Schaub. 2021. Child Safety in the Smart Home: Parents’ Perceptions, Needs, and Mitigation Strategies. Proceedings of the ACM on Human-Computer Interaction 5, CSCW2(2021), 1–41.

[24]

Rashid Tahir, Faizan Ahmed, Hammas Saeed, Shiza Ali, Fareed Zaffar, and Christo Wilson. 2019. Bringing the Kid back into YouTube Kids: Detecting Inappropriate Content on Video Streaming Platforms. In 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). 464–469. https://doi.org/10.1145/3341161.3342913

Digital Library

[25]

UNICEF. 2020. Policy guidance on AI for children. (2020).

[26]

Ge Wang, Jun Zhao, Max Van Kleek, and Nigel Shadbolt. 2021. Protection or Punishment? Relating the Design Space of Parental Control Apps and Perceptions about Them to Support Parenting for Online Safety. Proc. ACM Hum.-Comput. Interact. 5, CSCW2, Article 343 (oct 2021), 26 pages. https://doi.org/10.1145/3476084

Digital Library

[27]

Ge Wang, Jun Zhao, Max Van Kleek, and Nigel Shadbolt. 2022. Informing Age-Appropriate AI: Examining Principles and Practices of AI for Children. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, 1–29. https://doi.org/10.1145/3491102.3502057

Digital Library

[28]

Julia Woodward, Feben Alemu, Natalia E. López Adames, Lisa Anthony, Jason C. Yip, and Jaime Ruiz. 2022. “It Would Be Cool to Get Stampeded by Dinosaurs”: Analyzing Children’s Conceptual Model of AR Headsets Through Co-Design. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, Article 152, 13 pages. https://doi.org/10.1145/3491102.3501979

Digital Library

[29]

Zheng Zhang, Ying Xu, Yanhao Wang, Bingsheng Yao, Daniel Ritchie, Tongshuang Wu, Mo Yu, Dakuo Wang, and Toby Jia-Jun Li. 2022. StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, Article 218, 21 pages. https://doi.org/10.1145/3491102.3517479

Digital Library

[30]

Jun Zhao, Ge Wang, Carys Dally, Petr Slovak, Julian Edbrooke-Childs, Max Van Kleek, and Nigel Shadbolt. 2019. ‘I Make up a Silly Name’: Understanding Children’s Perception of Privacy Risks Online. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3290605.3300336

Digital Library

[31]

John Zimmerman and Jodi Forlizzi. 2014. Research through design in HCI. In Ways of Knowing in HCI. Springer, 167–189.

Cited By

Wang CSher SChung C(2024)From Viral Content to Real-Life Cuisine and Beyond: Examining Teenagers' Interactions with TikTok Food Videos and the Influence on their Food PracticesProceedings of the ACM on Human-Computer Interaction10.1145/36869288:CSCW2(1-30)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686928
Honauer MFrauenberger C(2024)Exploring Child-AI EntanglementsProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3661155(1029-1031)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3661155
Han AZhou XCai ZHan SKo RCorrigan SPeppler K(2024)Teachers, Parents, and Students' perspectives on Integrating Generative AI into Elementary Literacy EducationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642438(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642438
Show More Cited By

Index Terms

Child-Centred AI Design: Definition, Operation, and Considerations
1. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

The Second Workshop on Child-Centered AI Design (CCAI)
CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

AI-powered solutions are increasingly woven into the fabric of children’s digital worlds. They’re found in interactive toys, home automation systems, everyday apps, and various online services that young users engage with. As we look ahead, it’s almost ...
Child-Centered AI for Empowering Creative and Inclusive Learning Experiences
IDC '24: Proceedings of the 23rd Annual ACM Interaction Design and Children Conference

In an era where Artificial Intelligence (AI) permeates our lives, its impact on children raises critical considerations. This workshop aims to delve into the multifaceted realm of Human-Centered AI (HCAI) for children, exploring the transformative role ...
Parent-Child Interaction in Children’s Learning How to Use a New Application
Intelligent Tutoring Systems
Abstract
This study investigated how parents support their children when they are learning how to use a new application in a situation where the parents do not have any practical knowledge of it and how parental support influences the children’s learning. ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

April 2023

3914 pages

ISBN:9781450394222

DOI:10.1145/3544549

Editors:
Albrecht Schmidt
LMU Munich, Germany
,
Kaisa Väänänen
Tampere University, Finland
,
Tesh Goyal
Google Research, USA
,
Per Ola Kristensson
University of Cambridge, UK
,
Anicia Peters
University of Namibia, Namibia

Copyright © 2023 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 April 2023

Check for updates

Author Tags

Qualifiers

Extended-abstract
Research
Refereed limited

Conference

CHI '23

Sponsor:

SIGCHI

CHI '23: CHI Conference on Human Factors in Computing Systems

April 23 - 28, 2023

Hamburg, Germany

Acceptance Rates

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

Upcoming Conference

CHI '25

Sponsor:
sigchi

CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
576
Total Downloads

Downloads (Last 12 months)388
Downloads (Last 6 weeks)66

Reflects downloads up to 18 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Wang CSher SChung C(2024)From Viral Content to Real-Life Cuisine and Beyond: Examining Teenagers' Interactions with TikTok Food Videos and the Influence on their Food PracticesProceedings of the ACM on Human-Computer Interaction10.1145/36869288:CSCW2(1-30)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686928
Honauer MFrauenberger C(2024)Exploring Child-AI EntanglementsProceedings of the 23rd Annual ACM Interaction Design and Children Conference10.1145/3628516.3661155(1029-1031)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3628516.3661155
Han AZhou XCai ZHan SKo RCorrigan SPeppler K(2024)Teachers, Parents, and Students' perspectives on Integrating Generative AI into Elementary Literacy EducationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642438(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642438
Wang GZhao JJohnston SZhang ZVan Kleek MShadbolt N(2024)CHAITok: A Proof-of-Concept System Supporting Children's Sense of Data Autonomy on Social MediaProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642294(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642294

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Full Text

View this article in Full Text.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View full text|Download PDF

View Table of Contents