AI systems and their associated algorithms are increasingly integrating into the digital ecosystems that children encounter. These systems can be found in connected toys, smart home IoT technologies, and the everyday apps and services children use. Given their capability to craft captivating, adaptable, and personalized user experiences, it’s expected that AI’s role in children’s applications will only grow.
Yet, with this great potential come significant challenges. AI and the data processing it necessitates introduce a variety of risks. Some of these, such as concerns related to children’s privacy, safety, development, and future opportunities, are particularly acute. The recent discourse on age-appropriate design has spotlighted the importance of truly understanding and addressing children’s needs in design. It brings to the forefront the question: What does “child-centered” truly mean when we design for children’s AI interactions?
To pave the way for a genuinely child-centered AI, we must think beyond basic design attributes, like using child-friendly voices or restricting age-specific content. Instead, the design should prioritize the human factors of child-centered AI, ensuring that children’s best interests are central, and they’re treated with respect, fairness, and support for their autonomy.
This Special Issue is committed to showcasing high-impact, original research that delves into the current state of child-centered AI. We aim to further the insightful dialogue around designing child-focused AI and discovering ways to bring these ideas to fruition. We welcome submissions that touch on a range of topics, including, but not limited to:
Design principles and guidelines for child-centered AI
Case studies and user research
Empirical studies on child-centered AI
Innovative interaction methodologies for child-centered AI
Evaluation metrics and methods
Child-machine interface models, frameworks, and reference points
While this Special Issue prioritize original submissions, we are open to significantly revised versions of papers presented at recent conferences or workshops, provided they contain at least 50% new material. Every submission will undergo rigorous peer review to meet the high standards of the IJHCS journal. Should you wish to discuss potential contributions, feel free to contact the Special Issue editors at firstname.lastname@example.org.
Jun Zhao, PhDUniversity of Oxford, Oxford, United Kingdom
Grace C Lin, PhDMassachusetts Institute of Technology, Cambridge, United States of America
Zhen Bai, PhDUniversity of Rochester, Rochester, United States of America
Jason C Yip, PhDUniversity of Washington, Seattle, United States of America