Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Stakeholders' Perceived Benefits and Concerns Regarding Artificial Intelligence in the Care of Older Adults
0
Zitationen
9
Autoren
2025
Jahr
Abstract
BACKGROUND: Artificial Intelligence (AI) applications in healthcare have significant potential to address the unmet needs of older adults. To successfully adopt and implement AI in the care of older adults, it is critical to understand stakeholders' perspectives. We sought to explore the perceived benefits and concerns among stakeholders about AI applications in caring for older adults. METHODS: We conducted individual semi-structured interviews with five groups of stakeholders: older adults and caregivers, clinicians, health system and health insurance plan leaders (payers), investors, and technology developers. Interviews asked about the perceived role of AI in the care of older adults, the perceived benefits and concerns regarding AI, and suggestions for mitigating the concerns. Interviews were audio recorded and transcribed verbatim. We used thematic content analysis to code the transcripts. RESULTS: Overall, 49 participants completed interviews: older adults/caregivers (n = 15), clinicians (n = 15), payers (n = 8), investors (n = 5), and technology developers (n = 6). We identified three themes. (1). Stakeholders reported multiple benefits of AI and identified several roles for its use in the care of older adults. (2). Stakeholders expressed concerns about AI, including worsening social isolation, high cost, propagating ageism, goal misalignment, and scams/misuse of AI; views on privacy concerns were mixed. (3). Stakeholders suggested potential solutions, such as setting appropriate guardrails, to mitigate concerns about AI. CONCLUSIONS: Given the complexity and significant unmet needs among older adults, AI's potential benefits and harms are both heightened in this population. Appropriate guardrails are needed to leverage the benefits of AI while mitigating potential harms. Our findings have implications for technology developers to design innovations that align with the stakeholders' perceived roles for AI, for regulatory bodies to incorporate stakeholders' concerns when developing AI regulations, and for health systems and end-users of technology to critically evaluate a product regarding its affordability and impact on social isolation and ageism.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.774 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.685 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.244 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.898 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.