Designing Conversational AI for Aging: A Systematic Review of Older Adults' Perceptions and Needs
Yuanhui Huang, Quan Zhou, Anne Marie Piper
Abstract
Recent advances in conversational AI and the ubiquity of related devices and applications—from robots to smart speakers to chatbots—has led to extensive research on designing and studying conversational systems with older adults. Despite a growing literature on this topic, many studies examine small groups of older adults and specific devices, neglecting a holistic understanding of how diverse groups of older adults perceive conversational interaction more broadly. We present a systematic review that synthesizes older adults’ perceptions of the challenges and opportunities for interacting with these systems. We highlight their vision for future AI-based conversational systems, emphasizing a desire for more human-like interactions, personalization, and greater control over their information. We discuss the implications for future research and design of conversational AI systems for older adults.
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