Interactive Storytelling for Children: A Case-study of Design and Development Considerations for Ethical Conversational AI
Project Overview
The document explores the role of generative AI, particularly Conversational Artificial Intelligence (CAI), in education, with a focus on enhancing storytelling for children. It highlights the importance of ethical considerations in the design and implementation of CAI systems, addressing critical issues such as privacy, safety, and the developmental impacts on children's cognitive, social, and linguistic skills. A notable case study illustrates the creation of a meta-story chat tool aimed at increasing children's engagement with storytelling, while adhering to ethical design practices. The findings advocate for participatory design approaches that actively involve children and their parents in the development process, ensuring that the technologies meet their needs and promote positive educational outcomes. Through these insights, the document underscores the potential of generative AI to enrich educational experiences while prioritizing ethical standards and stakeholder involvement.
Key Applications
AI Fan Along - a meta-story chat tool for children
Context: Educational context aimed at children aged 9-14, focusing on storytelling and social development
Implementation: Developed through a pilot case-study involving research on technical and ethical aspects, with participatory design principles.
Outcomes: Aims to enhance children's social, literary, and empathetic understanding through immersive storytelling experiences.
Challenges: Ethical considerations regarding consent, privacy, and the potential for harmful interactions with CAI.
Implementation Barriers
Ethical Barrier
Concerns regarding privacy and safety for children using CAI, especially in terms of data collection and surveillance.
Proposed Solutions: Implementing transparent data practices, obtaining parental consent, and ensuring the system does not run as a background process.
Technical Barrier
Challenges in designing CAI that accurately understands and responds to the varied speech patterns of children, which differ from adults.
Proposed Solutions: Developing ASR systems tailored for children's speech and considering the physical and physiological differences in developing voices.
Project Team
ennifer Chubba
Researcher
Sondess Missaouib
Researcher
Shauna Concannonc
Researcher
Liam Maloneyb
Researcher
James Alfred Walker
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: ennifer Chubba, Sondess Missaouib, Shauna Concannonc, Liam Maloneyb, James Alfred Walker
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai