Human-Centered AI for Older Adults

Objective To 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. Background AI 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. Method A 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. Results Findings 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. Conclusion This study offers a set of design recommendations that can support the development of AI tools attuned to older adults’ needs. Application This review identifies critical design gaps and offers actionable design recommendations. Findings can inform future participatory, interdisciplinary efforts in age-inclusive AI development.

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Publication Details

Journal
Human Factors The Journal of the Human Factors and Ergonomics Society
Published
2026-09-24
DOI
https://doi.org/10.1177/00187208261490714
Primary Topic
Technology Use by Older Adults
Type
article
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article

Human-Centered AI for Older Adults

Maryam Zahabi, Sarah Allahvirdi
Human Factors The Journal of the Human Factors and Ergonomics Society
Technology Use by Older Adults
article

Human-Centered AI for Older Adults

Maryam Zahabi, Sarah Allahvirdi
article en

Abstract

Objective To 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. Background AI 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. Method A 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. Results Findings 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. Conclusion This study offers a set of design recommendations that can support the development of AI tools attuned to older adults’ needs. Application This review identifies critical design gaps and offers actionable design recommendations. Findings can inform future participatory, interdisciplinary efforts in age-inclusive AI development.

Human Factors The Journal of the Human Factors and Ergonomics Society
Mitchell Institute (US)
Quality Education
Openalex Percentile: Top 4%
Technology Use by Older Adults
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Human-Centered AI for Older Adults — Maryam Zahabi, Sarah Allahvirdi · Human Factors The Journal of the Human Factors and Ergonomics Society (2026) | TGRS Research Map | TGRS