An Open Book, On Whose Terms? Power Dynamics in Sensor-Derived, LLM-Generated Summaries Sharing Between Older Adults and Remote Families
Jiachen Li, Reina Szeyi Chan, Shihan Fu, Zijian Wang, Akshat Choube, Yingtian Shi, Rosemarie Santa Gonzalez, Thomas Ploetz 等 12 位作者
As older adults (OAs) increasingly favor aging in place, remote family members (RFMs) need meaningful awareness of their loved ones without intrusive monitoring. Large language models can provide rich interpretations of non-intrusive sensing data, yet recent work has largely emphasized technical accuracy over how families use or benefit from this information. We conducted formative interviews with 12 RFMs and 2 OAs, followed by a three-month deployment case study with one OA-RFM dyad. Our system provided daily AI-generated summaries of multimodal sensing data, which we iteratively refined with both parties using a research-through-design approach. Although the summaries integrated well into the dyad's daily routine, sustaining over 90% engagement, their lived experience revealed evolving tensions around agency, reassurance, privacy, trust, and communication, shaped by sensor limitations and existing communication misalignments. Our findings inform the design of future AI-mediated sharing systems that account for real-world sensing constraints and complex family care dynamics.
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