Imagining Ageing in AI-Based Technologies for Long-Term Care – What Technology for Whom?

The present is shaped by demographic change and an ageing population, leading to what has been termed the care crisis. Meanwhile, an increasingly wide array of AI-based technologies for long-term care (LTC) settings is being developed. These trends are framed and interlinked discursively in a particular manner: ageing is a problem and technology the solution. Drawing on empirical findings from three multi-perspective case studies of AI-based technologies for LTC settings, this contribution seeks to both elicit and trouble the images of aging and technology that characterize this narrative. The intent of this endeavor is twofold: firstly, we aim to critically explore the implications of these images for the development and deployment of these systems and the resulting consequences for LTC residents. Secondly, we aspire to unveil mechanisms of exclusion, which leave LTC residents as mere bystanders to changes that may fundamentally impact their lives.

Our empirical inquiry spans AI-based fall detection and prevention, social robots and automated emotion and pain recognition. Specific negative images of ageing such as frailty, loneliness, pain and incompetence influenced these technologies from initial conception to large-scale deployment: they were inscribed into the technologies and predisposed who could participate to what extent. Conversely, positive images of technology based on an assumption of functionality were employed to legitimize the use of these systems, serving as means to provide safety, security, sociality or happiness for older adults, although they often fell short of what they had promised to achieve. When technologies that fail to serve their official beneficiaries – the LTC residents – are deployed nonetheless, this raises the question of who these technologies really serve and how, especially when chosen over auspicious non-technological alternatives.