Visualizing the datasphere: Representations of old bodies and their data in promotional images of smart sensor technologies for aging at home

Abstract

Technologies for people aging at home are increasingly prevalent and include ambient monitoring devices that work together with wearables to remotely track and monitor older adults' biometric data and activities of daily living. There is, however, little research into the promotional and speculative images of technology-in-use. Our paper examines the ways in which the datafication of aging is offered up visually by technology companies to promote their products. Specifically, we ask: how are data visualized in promotional images of smart sensor technologies for aging at home? And in these visualizations, what happens to the aging body and relations of care? We include in our definition of smart sensor technologies both wearable and ambient monitoring devices, so long as they are used for the in-home passive monitoring of the inhabitant by a caregiver, excluding those devices targeted for institutional settings or those used for self-monitoring purposes. Our sample consists of 221 images collected between January and July of 2021 from the websites of 14 English-language companies that offer smart sensor technology for aging at home. Following a visual semiotic analysis, we present 3 themes on the visual representation of old bodies and their data: (1) Captured Data, (2) Spatialized Data, and (3) Networked Data. Each, we argue, contribute to a broader visualization of the “datasphere”. We conclude by highlighting the underlying assumptions of old bodies in the co-constitution of aging and technologies in which the fleshy and lived corporeality of bodies is more often lost, reduced to data points and automated care scenarios, and further disentangled from other bodies, contexts and things.

Addressing the Black Box of AI—A Model and Research Agenda on the Co-constitution of Aging and Artificial Intelligence

“…This truncated data imaginary risks devaluing or obscuring other kinds of knowledge or experience, rendering factors outside of the machine’s calculations as less relevant to the production of knowledge. Through datafied classification and categorization, the visibility of an older body is limited to the data produced by AI systems, which is then “aggregated and itemized into risk assessments and patterns of behavior” ( Ellison et al, 2022 ). Older adults get placed into categories with consequences for their lives—they can become “fallers,” “at risk,” “frail,” “aggressive,” in need of residential care or “untrustworthy” reporters ( Berridge & Grigorovich, 2022 ), while their subjective experiences of these categories become less relevant forms of knowledge.…”

“…Understanding older adults’ embodiments and agency in the context of AI includes further unpacking the ways in which the everyday lives of older people are becoming sites of datafication, monitoring, and surveillance ( Dalmer et al, 2022 ; Ellison et al, 2022 ). This might also include making visible how the embodiment of aging in everyday life is more-than-human, and how diverse materialities (including AI systems) are part of the constitution of aging in the lives of older adults.…”