Equity in age tech for ageing well in technology-driven places

• Verfasst von: Rubeis, Giovanni [VerfasserIn]
• Verfasst von: Fang, Mei Lan [VerfasserIn]
• Verfasst von: Sixsmith, Andrew [VerfasserIn]
• Titel: Equity in age tech for ageing well in technology-driven places
• Titelzusatz: the role of social determinants in designing AI-based assistive technologies
• Verf.angabe: Giovanni Rubeis, Mei Lang Fang, Andrew Sixsmith
• E-Jahr: 2022
• Jahr: 27 October 2022
• Umfang: 15 S.
• Fussnoten: Gesehen am 14.11.2022
• Titel Quelle: Enthalten in: Science and engineering ethics
• Ort Quelle: Dordrecht : Springer Netherlands, 1995
• Jahr Quelle: 2022
• Band/Heft Quelle: 28(2022), 6, Artikel-ID 49, Seite 1-15
• ISSN Quelle: 1471-5546
• DOI: doi:10.1007/s11948-022-00397-y
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Errata: Rubeis, Giovanni, 1981 - : Correction: Equity in agetech for ageing well in technology-driven places
• Sach-SW: Artificial Intelligence
• Sach-SW: Healthy Aging
• Sach-SW: Self-Help Devices
• Sach-SW: Social Determinants of Health
• Sach-SW: Technology
• K10plus-PPN: 1822361494

Abstract

AgeTech involves the use of emerging technologies to support the health, well-being and independent living of older adults. In this paper we focus on how AgeTech based on artificial intelligence (AI) may better support older adults to remain in their own living environment for longer, provide social connectedness, support wellbeing and mental health, and enable social participation. In order to assess and better understand the positive as well as negative outcomes of AI-based AgeTech, a critical analysis of ethical design, digital equity, and policy pathways is required. A crucial question is how AI-based AgeTech may drive practical, equitable, and inclusive multilevel solutions to support healthy, active ageing.In our paper, we aim to show that a focus on equity is key for AI-based AgeTech if it is to realize its full potential. We propose that equity should not just be an extra benefit or minimum requirement, but the explicit aim of designing AI-based health tech. This means that social determinants that affect the use of or access to these technologies have to be addressed. We will explore how complexity management as a crucial element of AI-based AgeTech may potentially create and exacerbate social inequities by marginalising or ignoring social determinants. We identify bias, standardization, and access as main ethical issues in this context and subsequently, make recommendations as to how inequities that stem form AI-based AgeTech can be addressed.