Aging in Data

In datafied societies, algorithms and its capacities to analyze data are somewhat of a modern myth. On the one hand, they are depicted as omnipotent entities that govern our lives through the automated analysis of big data sets, on the other hand, as vulnerable and unstable systems that make wrong decisions or (re)produce bias through flawed data (Ziewitz, 2015). In gerontology and age studies, the interest in algorithms is fueled by enthusiasm about their transformative potential and hopes to increase care giver productivity and efficiency, as well as care safety and autonomy through automated decision making (Lenouvel et al. 2020; Rantz et al. 2015). Critical age studies literature has, however, also identified blind spots in the current discourse on ageing and algorithms and has, e.g., highlighted that the language and concepts used around algorithmic technologies often promise more than can be delivered by these technologies (Lenouvel et al. 2020), that a discourse on age-discrimination and age-bias in big data that feed algorithms is currently missing (Stypinska 2021; 2022) and that the perspectives of older adults on algorithmic decision-making and the collection of big data are only rarely discussed (Chu et al. 2022).

The project has two aims: First, it aims to explore the epistemological claims that accompany discussions around algorithms and big data in the field of age studies and gerontology. Second, it aims to re-image ageing with and through algorithms through participatory research with older adults. Drawing on an understanding of algorithms as "stories that help people deal with contradictions in social life that can never be fully resolved" (Mosco 2005), the project asks how the figure of the algorithm is employed in the current discourse in age studies and gerontology, how it has come to matter in this particular field of research, and how stories about algorithms can be imagined otherwise through creative storytelling and co-design with older adults. The project poses the following research questions:

• What characterizes the scientific engagement with algorithms in gerontology and age studies so far? Which epistemological claims accompany the current discourse on algorithms and big data in age studies and gerontology?
• What are current blind-spots in the current discourse on algorithms in gerontology and age studies?
• How can algorithmic ageing be imagined otherwise? How can an alternative imagination of algorithmic ageing be developed through participatory research with older adults?

To answer these questions, the project takes two methodological steps. First, it conducts a structured literature review in four international journals for gerontology and age studies, asking how the figure of the algorithm and big data has been discussed in gerontological literature so far. This literature review is an extension of Vera Gallistl's post-doc project that is currently conducted at the Karl Landsteiner University Krems, Austria. Through qualitative mapping and counter-mapping (Hepp et al. 2022), the project then identifies current blind-spots in the gerontological discourse on algorithms. In a second step, the project aims to develop alternative imaginaries of algorithmic ageing together with older adults. In two participatory workshops with older adults (65+ community-dwelling adults, living in Austria), the project presents and discusses the results of the conducted literature and, through co-design methods and creative story-telling, aims to develop an alternative imagination of ageing with and through algorithms together with older workshop participants.

Project management: Dr. Vera Gallistl (Karl Landsteiner University of Health Sciences, Krems), Dr. Unmil Karadkar (CIRAC)