Exploring artificial intelligence-powered virtual assistants to understand their potential to support older adults’ search needs

作者：Emily Langston, Varitnan Hattakitjamroen, Mario Hernández, Hye Soo Lee, Hannah Ç. Mason, Willencia Louis-Charles, Neil Charness, Sara J. Czaja, Wendy A. Rogers, Joseph Sharit, Walter R. Boot · 发表于：Human Factors in Healthcare · 年份：2025 · DOI：10.1016/j.hfh.2025.100092 · 被引用次数：16 · 研究领域：Technology Use by Older Adults、AI in Service Interactions、Dementia and Cognitive Impairment Research

Objective We investigated the accuracy and amount of information provided by artificial intelligence (AI)-powered virtual assistants in response to queries relevant to aging adults in the domains of Medicare, long-term care insurance, and resource access. Background Older adults are faced with complex decisions and must gather and integrate information from diverse sources to help support these decisions (e.g., across various websites and online resources). Information-seeking, integration, and decision-making are cognitively demanding and can be impacted by age-related cognitive changes. Virtual assistants powered by AI have the potential to provide older adults with easy access to information and answers to their queries. However, it is unclear how accurate this information and these answers might be. Method Alexa, Google Assistant, Bard, and ChatGPT-4 were queried. Coders assessed the accuracy of these responses, and the amount of supplemental information provided as a measure of response complexity. Results Overall, Large Language Model (LLM)-based virtual assistants (Bard, ChatGPT-4) responded more accurately than non-LLM assistants (e.g., 6 % inaccurate responses for Bard vs. 60 % for Alexa) and provided substantially more supplemental information (79 % of responses with high supplemental information for Bard and 37 % for Chat-GPT, vs. 20 % or less for others). We note, however, that responses can vary over time. Conclusion Based on their ability to provide largely accu...