As older adults increasingly prefer to age in place, their adult children often assume the role of informal caregivers. This dynamic creates a distinct tension between the adult child's need for awareness and the older adult's fundamental right to privacy. Traditional monitoring technologies, such as raw video feeds, often compromise the older adult's autonomy. To address this challenge, this study explores the use of generative Artificial Intelligence (GenAI) to create abstract, privacy-preserving ``visual summaries'' of daily activities. We design a 10-day Experience Sampling Method (ESM) study with dyads consisting of older adults and their adult children. Through daily smartphone prompts, participants report their current context and evaluate pre-generated AI sketches, indicating their willingness to share or receive these images. Follow-up interviews will further investigate participants' boundary-setting behaviours. This research aims to quantify the privacy mismatch between generations and provide actionable design guidelines for applying visual abstraction in AI-mediated caregiving tools, ultimately supporting inter-generational connection while protecting user dignity.

翻译：随着老年人越来越倾向于居家养老，他们的成年子女常承担起非正式照护者的角色。这一动态在成年子女的知晓需求与老年人的基本隐私权之间形成了显著张力。传统的监控技术（如原始视频流）往往会损害老年人的自主权。为应对这一挑战，本研究探索利用生成式人工智能（GenAI）创建抽象的、保护隐私的日常活动“视觉摘要”。我们设计了一项为期10天的体验抽样法（ESM）研究，以老年人与成年子女组成的二元组为对象。通过每日智能手机提示，参与者报告其当前情境并评估预生成的AI草图，表明其分享或接收这些图像的意愿。后续访谈将进一步探究参与者的边界设定行为。本研究旨在量化代际间的隐私错配，并为在AI介导的照护工具中应用视觉抽象提供可操作的设计指南，最终在保护用户尊严的同时支持代际连接。