如果我的玩具会说话：幼儿如何想象、设计和测试AI赋能的玩具

中文摘要 AI 辅助

为了探索儿童可能为其玩具设计AI聊天机器人的设计空间，我们开发了ToyTalk，一种将儿童定位为LLM赋能玩具设计者的技术探针。儿童从熟悉的玩具开始，通过无代码界面配置其AI赋能版本，然后与角色互动并对其进行测试。我们在美国东南部五所小学部署了ToyTalk，共有76名7-9岁的儿童参与。我们考察了儿童如何定义其玩具、探测其变成什么，以及当行为偏离预期时如何回应。儿童设计的玩具主要具有社交积极型人格、支持性角色和人际规则。在对话中，他们最常探测身份和知识，同时也测试能力、记忆和关系。当出现不匹配时，儿童通常通过纠正、坚持和重新测试来回应，而少数人会返回重新配置系统。我们讨论了儿童设计能动性、测试实践以及对面向儿童生成式AI一致性期望的启示。

英文摘要

To investigate the design space where children might design AI chatbots for their own toys, we developed ToyTalk, a technology probe that positions children as designers of LLM-enabled toys. Children begin with a familiar toy, configure its AI-enabled version through a no-code interface, and then interact with and test the character. We deployed ToyTalk with 76 children aged 7-9 across five elementary schools in the southeastern U.S. We examine how children define their toy, probe what it becomes, and respond when behavior diverges from expectations. Children predominantly designed toys with socially positive personalities, supportive roles, and interpersonal rules. In conversation, they most often probed identity and knowledge, while also testing capabilities, memory, and relationships. When mismatches arose, children typically responded through correction, persistence, and retesting, while few returned to reconfigure the system. We discuss implications for children's design agency, testing practices, and expectations of coherence in child-facing generative AI.

发表机构

• University of Pennsylvania（宾夕法尼亚大学）
• Graduate School of Education, University of Pennsylvania（宾夕法尼亚大学教育学院）
• University of Florida（佛罗里达大学）
• Department of Computer Science, North Carolina State University（北卡罗来纳州立大学计算机科学系）
• Department of Information Technology, Kennesaw State University（肯尼索州立大学信息技术系）
• Computer Science, North Carolina State University（北卡罗来纳州立大学计算机科学）

机构由 AI 辅助整理，请以论文原文为准。