{"title":"Human-Centered AI for Older Adults.","authors":"Sarah Allahvirdi, Maryam Zahabi","doi":"10.1177/00187208261490714","DOIUrl":null,"url":null,"abstract":"<p><p>ObjectiveTo identify the needs of older adults when interacting with artificial intelligence (AI) technologies, and to propose design recommendations that can inform the development of future AI systems.BackgroundAI technologies are increasingly integrated into healthcare, education, and social applications for older adults. However, many AI systems fail to account for age-related cognitive, perceptual, and emotional changes, resulting in usability barriers, low trust, and limited adoption.MethodA systematic review of 93 studies categorized by application area identified challenges and user needs through thematic analysis, leading to proposed design recommendations. Two AI-powered platforms were then benchmarked against these design recommendations to assess their suitability for older adults.ResultsFindings highlighted older adults' concerns related to usability, personalization, privacy, and explainability of these technologies. Older adults preferred systems that respect human autonomy, adapt to user context and emotions, and offer clear, trustworthy explanations. A set of actionable design recommendations was proposed to improve AI-powered technologies for older adults. Analysis of two selected AI platforms suggested that these systems only partially aligned with the proposed recommendations.ConclusionThis study offers a set of design recommendations that can support the development of AI tools attuned to older adults' needs.ApplicationThis review identifies critical design gaps and offers actionable design recommendations. Findings can inform future participatory, interdisciplinary efforts in age-inclusive AI development.</p>","PeriodicalId":56333,"journal":{"name":"Human Factors","volume":" ","pages":"187208261490714"},"PeriodicalIF":3.6000,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Factors","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1177/00187208261490714","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
ObjectiveTo identify the needs of older adults when interacting with artificial intelligence (AI) technologies, and to propose design recommendations that can inform the development of future AI systems.BackgroundAI technologies are increasingly integrated into healthcare, education, and social applications for older adults. However, many AI systems fail to account for age-related cognitive, perceptual, and emotional changes, resulting in usability barriers, low trust, and limited adoption.MethodA systematic review of 93 studies categorized by application area identified challenges and user needs through thematic analysis, leading to proposed design recommendations. Two AI-powered platforms were then benchmarked against these design recommendations to assess their suitability for older adults.ResultsFindings highlighted older adults' concerns related to usability, personalization, privacy, and explainability of these technologies. Older adults preferred systems that respect human autonomy, adapt to user context and emotions, and offer clear, trustworthy explanations. A set of actionable design recommendations was proposed to improve AI-powered technologies for older adults. Analysis of two selected AI platforms suggested that these systems only partially aligned with the proposed recommendations.ConclusionThis study offers a set of design recommendations that can support the development of AI tools attuned to older adults' needs.ApplicationThis review identifies critical design gaps and offers actionable design recommendations. Findings can inform future participatory, interdisciplinary efforts in age-inclusive AI development.
期刊介绍:
Human Factors: The Journal of the Human Factors and Ergonomics Society publishes peer-reviewed scientific studies in human factors/ergonomics that present theoretical and practical advances concerning the relationship between people and technologies, tools, environments, and systems. Papers published in Human Factors leverage fundamental knowledge of human capabilities and limitations – and the basic understanding of cognitive, physical, behavioral, physiological, social, developmental, affective, and motivational aspects of human performance – to yield design principles; enhance training, selection, and communication; and ultimately improve human-system interfaces and sociotechnical systems that lead to safer and more effective outcomes.