Breaking or Repairing Long-Term Care for Older People?

摘要

From robots to chatbots, AI technologies in care (nursing) homes have gained policymakers’ attention amid critical issues like staffing shortages. Concurrently, the long-term care sector has become a prime target for technologists due to its global market potential given the growing ageing population. Drawing conceptually on ideas of breakdown and repair, we explore socio-technical discourses of AI-based care for later life. We combine Bruno Latour’s concept of delegation and Madeleine Akrich’s notion of user representations to frame how these discourses can support breaking or repairing long-term care. Through this theoretical lens, we analysed 33 AI companies targeting the sector. Visual, textual, and semiotic analysis of their websites identified overarching discourses on ageing carefication, public inefficiencies, AI solutionism, and care datafication. Older people were depicted as passive data sources and staff as inefficient, positioning AI as the solution to all caregiving challenges. We consider implications for caregiving’s futures and reimagining AI-human care.