Artificial intelligence (AI) is playing an increasingly important role when it comes to age(ing). But how exactly does it influence the lives of older people and how is this relationship viewed in research? As part of a study at the Competence Centre for Gerontology and Health Research at the Karl Landsteiner University of Health Sciences, it was worked out how the sociology of ageing has so far theoretically described the interaction between AI and age(ing)

On this basis, key concepts were developed in order to better understand this new relationship between "age and AI". The analysis is based on gerontological approaches and combines theoretical considerations with findings from a qualitative study. The study analysed how AI is developed, used and implemented in long-term care - and what concrete effects this has on ageing. The results show that AI must be understood not only as a technical, but rather as a socio-technical structure.

Specifically, the study pursued three objectives, explains study author Dr Vera Gallistl, BA MA, Assistant Professor at the Competence Centre for Gerontology and Health Research at Karl Landsteiner University of Health Sciences: "Firstly, we want to show that many current discussions about artificial intelligence in the field of ageing research overlook important aspects," explains Gallistl. AI is often seen purely as a support or solution for problems in old age - for example in care or to increase safety. However, this view falls short because it ignores the complex and multi-layered relationships between AI and ageing. Building on this, the study presents the so-called assemblage theory* - an approach that can help to better understand the many different connections between AI and ageing. "In contrast to a purely technical view, this approach asks: How do the relationships between AI and ageing arise? Who helps to shape them and what role do older people play?" As Gallistl goes on to explain, the team orientated itself on research fields that have long been concerned with the social significance of technology, such as science and technology research or surveillance studies. The aim is to use assemblage theory to draw a more realistic and differentiated picture of the interplay between AI and ageing - beyond simple promises of solutions. "Thirdly, we are examining how this approach works in practice. To do this, we refer to a qualitative study on the development and use of AI in elderly care."

Diversity, power and limits
In practice, there are many more different relationships between AI and older people than one would expect at first glance, explains the expert. It's not just about technology in the lab, but about real, complex situations in everyday life. "It is important not to see AI as a standardised and rigid 'concept'. It is brought into very different forms by people especially in the field of care. This means that AI is not a specific technology, but is only created through its use and design in everyday life," explains Gallistl. Another key question is the distribution of roles: who is seen as an expert in AI? Who is seen as a user - and who is not? Older people are often not perceived as active participants, but rather as passive "objects" of monitoring or care. "Boundaries are drawn: Who gets to decide? Who is taken seriously? These boundaries are not natural, but are set - usually based on certain interests. At the same time, such boundaries make certain abilities of older people invisible," says Vera Gallistl. Building on this, power relations are another key aspect that needs to be taken into account - the question of who has influence over how AI is used seems particularly important. "In many cases, older people are primarily used as a source of data, but are not perceived as co-creators. So it's also about whose voices are heard and whose are not."

Three central practices in relationships between AI and ageing
The current analysis ultimately identified three types of practices that are particularly influential in how AI structures and processes perceive, involve and influence older people: "Firstly, we are talking about data practices, which mean that ageing bodies are often reduced to measurable data. This data is of economic interest to companies that develop AI. However, the view of the human being as a whole is often lost from view. The second practice defined was innovation practices, which assume that the idea of "progress" is usually equated with technological progress. Little thought is given to whether innovation could also mean social change or new roles for older people. And as a third sub-category, black-boxing practices show that many processes surrounding AI remain hidden for example, what assumptions about older people are built into the technology or what economic interests are in the background. At the same time, older people are often not visible as actors, but merely as targets of monitoring and analysis," explains Dr Vera Gallistl. Her conclusion: "The widespread belief that AI automatically improves the lives of older people falls short of the mark. In reality, the relationship between ageing and AI is much more complex. It is worth taking a closer look at who is involved in these relationships, what interests play a role and what may be overlooked or deliberately ignored."

Source: https://www.kl.ac.at/en/news/how-artificial-intelligence-shaping-our-understanding-ageing