Child-Centred AI Design: Definition, Operation, and Considerations-Reference-Cited by-同舟云学术

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

Published:2023-04-19 Issue: Volume: Page:
ISSN:
Container-title:Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
language:
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Author:

Wang Ge¹^ORCID,Sun Kaiwen²^ORCID,Atabey Ayça³^ORCID,Pothong Kruakae⁴^ORCID,Lin Grace C.⁵^ORCID,Zhao Jun¹^ORCID,Yip Jason⁶^ORCID

Affiliation:

1. Department of Computer Science, University of Oxford, United Kingdom

2. School of Information, University of Michigan, United States

3. School of Law, University of Edinburgh, United Kingdom

4. Media and Communications, LSE, United Kingdom and 5Rights Foundation, United Kingdom

5. Scheller Teacher Education Program | The Education Arcade, Massachusetts Institute of Technology, United States

6. Information School, University of Washington, United States

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3544549.3573821

Reference31 articles.

1. 2019. Generation AI: Establishing Global Standards for Children and AI. http://www3.weforum.org/docs/WEF_Generation_AI_%20May_2019_Workshop_Report.pdf 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 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 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. Context-Sensitive Affect Recognition for a Robotic Game Companion

5. Algorithmic Decision Making and the Cost of Fairness