Proactive and Ongoing Analysis and Management of Ethical Concerns in the Development, Evaluation, and Implementation of Smart Homes for Older Adults With Frailty

Abstract

Successful adoption and sustained use of smart home technology can support the aging in place of older adults with frailty. However, the expansion of this technology has been limited, particularly by a lack of ethical considerations surrounding its application. This can ultimately prevent older adults and members of their support ecosystems from benefiting from the technology. This paper has 2 aims in the effort to facilitate adoption and sustained use: to assert that proactive and ongoing analysis and management of ethical concerns are crucial to the successful development, evaluation, and implementation of smart homes for older adults with frailty and to present recommendations to create a framework, resources, and tools to manage ethical concerns with the collaboration of older adults; members of their support ecosystems; and the research, technical development, clinical, and industry communities. To support our assertion, we reviewed intersecting concepts from bioethics, specifically principlism and ethics of care, and from technology ethics that are salient to smart homes in the management of frailty in older adults. We focused on 6 conceptual domains that can lead to ethical tensions and of which proper analysis is essential: privacy and security, individual and relational autonomy, informed consent and supported decision-making, social inclusion and isolation, stigma and discrimination, and equity of access. To facilitate the proactive and ongoing analysis and management of ethical concerns, we recommended collaboration to develop a framework with 4 proposed elements: a set of conceptual domains as discussed in this paper, along with a tool consisting of reflective questions to guide ethical deliberation throughout the project phases; resources comprising strategies and guidance for the planning and reporting of ethical analysis throughout the project phases; training resources to support leadership, literacy, and competency in project teams for the analysis and management of ethical concerns; and training resources for older adults with frailty, their support ecosystems, and the public to support their awareness and participation in teams and ethical analysis processes. Older adults with frailty require nuanced consideration when incorporating technology into their care because of their complex health and social status and vulnerability. Smart homes may have a greater likelihood of accommodating users and their contexts with committed and comprehensive analysis, anticipation, and management of ethical concerns that reflect the unique circumstances of these users. Smart home technology may then achieve its desired individual, societal, and economic outcomes and serve as a solution to support health; well-being; and responsible, high-quality care.

AI-Assisted Decision-Making in Long-Term Care: Qualitative Study on Prerequisites for Responsible Innovation (Preprint)

“…The predominant viewpoint highlighted by care professionals is that specific data and associated AIbased insights ought only to be generated in accordance with established goals agreed upon by key stakeholders including the client (prerequisite 1). In different terms, the collection and utilization of specific data should be proactively and continuously balanced against potential harms such as privacy infringement, cognitive overload and over-problematization of old age (see also [52][53][54]). While our findings underline that only relevant data should be generated as input for AI-DSSs, they also suggest that whenever it has been decided to generate certain data and have it processed by AI-DSSs, it should be part of the routine to utilize the resulting insights (prerequisite 7).…”

AI-Assisted Decision-Making in Long-Term Care: Qualitative Study on Prerequisites for Responsible Innovation

“…The predominant perspective of care professionals was that specific data and associated AI-based insights should only be generated in accordance with established goals agreed upon by key stakeholders, including clients (Prerequisite 1). The collection and utilization of specific data should be proactively and continuously balanced against potential harms such as privacy infringement, cognitive overload, and the over-problematization of old age (see also [64][65][66]). Although our findings emphasize the importance of generating only relevant data as input for AI-DSSs, they also suggest that once it has been decided to generate certain data and have them processed by AI-DSSs, it should be routine practice to utilize the resulting insights (Prerequisite 7).…”