Combining artificial intelligence and care? Insights into AI technologies for long-term care
Artificial intelligence (AI) is often presented as a solution to challenges in long-term care, but it raises both ethical and practical problems. A book contribution by experts from the Competence Centre for Gerontology and Health Research at Karl Landsteiner University (KL Krems) takes a critical look at the interplay between ageing and AI and shows how AI applications are used in care. Based on interviews with residents, carers and developers, three systems are examined: a fall sensor, the social robot Pepper and the robotic seal Paro.
The results point to three central approaches: the need to involve older people in the development and use of AI, the consideration of human and technical weaknesses in equal measure and the promotion of meaningful interactions between humans and AI.
Older adults in care settings actively engage with AI technologies in their environment and want to be involved as users of these developments. This insight is described in a recent book contribution, explains Katrin Lehner, BA, MA, corresponding author and research associate at the Competence Centre for Gerontology and Health Research at KL Krems: "Building on the previous project ALGOCARE ("Algorithmic Governance of Care"), we take a critical look at the interaction between old age and artificial intelligence (AI). To this end, three different AI applications in everyday care were analysed."
The use of fall sensors makes it clear that older residents of care and support centres are not passive users or merely "monitored subjects". Rather, they actively interact with the technology - an aspect that is often overlooked in care practice and technology development. For example, they adapt their daily routines or consciously engage with the technology in order to better understand it. The example of the Pepper robot in turn shows that its use is strongly characterised by the entertainment aspect, the author explains: "However, this technology is often based on assumptions about the needs, skills and preferences of older people, rather than on their actual participation. The service is therefore not designed by the residents, but for them. Although some felt entertained, there was no recognisable added value for the care staff, in particular no reduction in workload, as care and support were still required when using the AI." The robot Paro - a seal-shaped social robot - is a successful example of how AI and care can be successfully combined ("bridging"). "Paro could be better integrated into everyday routines, for example as part of biographical work, by stimulating residents' memories and stories. It also showed that it works well when older adults are explained how the technology works. This allows knowledge about AI and digital skills to be strengthened in a targeted manner," says Katrin Lehner.
Three key aspects for development and practice
Firstly, according to the conclusions from the research, the involvement of older adults and carers in the development and implementation of AI is essential. "Care is a highly complex system, while developers often have little contact with age and care. As a result, there is a risk that negative or incomplete images of old age are inscribed in technologies and stereotypical ideas of passive, uninterested old people are further reinforced," explains the expert.
The second aspect relates to the need to consider human and technological vulnerability together ("bridging human and technological vulnerability"). While AI is often seen as supportive and adaptable and older adults are perceived as passive and in need of protection, in practice it is clear that technologies also require care. Maintenance, care and hygiene measures - so-called invisible AI care practices - are necessary for AI to function at all in real care contexts.
Thirdly, it is about fostering meaningful connections, according to Lehner: "Older people should not be seen as distant from technology or disinterested, but as active players in development and implementation processes. It is crucial to take into account the diversity of ageing experiences, as ageing is a heterogeneous process. Equally important are mutual learning processes between residents, carers and developers. Participatory approaches play a key role in narrowing the gap between technology and care and enabling more inclusive and ethically responsible practice."
Link to the book incl. information: https://link-springer-com.uaccess.univie.ac.at/book/10.1007/978-3-032-11938-4
Link to the ALGOCARE "Algorithmic governance of care" project: https://www.wwtf.at/funding/programmes/ict/ICT20-055/
