发表机构
University of Illinois Urbana-Champaign; University of Washington（伊利诺伊大学厄巴纳-香槟分校; 华盛顿大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
系统回顾100项实证HCI研究，利用YAIR与MIT分类法绘制青年AI风险及应对措施图谱，发现多数措施仅被提议而未经实施或评估，并提出加强青年AI安全的具体研究方向。
AI 中文摘要
尽管人机交互（HCI）领域日益关注面向青年的人工智能安全，但现有文献缺乏对已识别风险、应对措施及其在实际中是否有效的全面概述。我们系统性地回顾了100项涉及儿童与青年在学校、家庭、照护环境及公共服务中与人工智能互动或接触的实证HCI研究。利用YAIR风险分类法和MIT缓解措施分类法，我们绘制了已识别风险、每项风险是否由应对措施解决，以及该风险的每项应对措施是否已实施甚至评估的图谱。风险-应对措施映射显示，大多数风险仅匹配到提议/构思的应对措施；少数应对措施已实施，评估的则更少；现有评估往往衡量技术性能而非免受伤害的保护。我们识别了覆盖缺失之处及保障措施未经检验之处，并为HCI研究提出了加强青年人工智能安全的具体方向。
英文摘要
While HCI increasingly examines AI-safety for youth, the literature lacks a comprehensive view of what risks have been identified, how they are addressed, and whether proposed protections work in-practice. We systematically reviewed 100 empirical HCI studies involving children and youth interacting with or exposed to AI across schools, homes, care settings, and public services. Using the YAIR taxonomy for risks and the MIT Mitigation Taxonomy for countermeasures, we map which risks have been identified, whether each risk is addressed by countermeasure(s), and whether each countermeasure for that risk is implemented and even evaluated. The risk-countermeasure mapping shows that most risks are matched only with proposed/ideated countermeasures; few countermeasures have been implemented, and fewer still evaluated; and existing evaluations often measure technical performance rather than protection from harm. We identify where coverage is absent, where safeguards remain untested, and propose concrete directions for HCI research to strengthen youth AI-safety.
