Performing the care crisis through the datafication of elderly welfare care

ABSTRACT

Demographic changes associated with contemporary society are often framed as a ‘care crisis’ where the aging population is portrayed as threatening the financial security and the future of younger generations. To rationally intervene in these issues, welfare states – particularly in Nordic countries – increasingly rely on digital technology as a ‘remedy’ and ‘promise’ of more effective and efficient public governance operating through technopolitical care practices and logics. Technological solutions such as AI, algorithms, apps and robotics are incorporated into elderly care and aligned with care work where the digitization of processes accompanies an intensification of datafication of elderly welfare care. This analysis is aimed at identifying and discussing how the welfare state is transformed through a practice of classification and its logic of standardization, a practice of taskification grounded on time-paced service logic, and a practice of categorization relying on a logic of prioritization. These three practices and logics embody tensions emerging where caring intersects with data sourcing, that is, where the datafication of elderly welfare care lies. Feminist posthumanism allows approaching them by resisting both techno-utopian and techno-dystopian claims about the datafication of elderly welfare care.

KEYWORDS:

• care crisis
• datafication
• feminist posthumanism
• matter of care
• old people
• welfare technology

Datafication as a matter of care

By mobilizing a feminist posthumanist perspective, I frame datafication as a matter of care (Puig de la Bellacasa, 2017) to highlight the ethically and politically charged issues that such a phenomenon embodies. I scrutinize datafication as the creation of ‘digital data out of human life’ (Mejias & Couldry, 2019, p. 2) and as part of the transformation of the welfare state in Nordic countries. The rationale for the datafication of caring practices targeting old people positions aging within the discourse of the ‘care crisis’ (Hansen et al., 2022) and identifies welfare technology¹ as its remedy, offered by Age-Tech, that is, ‘services purchased by older people; services purchased on behalf of older people; services traded between older and younger people; and services delivered to future older people’ (Woods, 2019, n.d.; italics in original).

To treat the datafication of elderly welfare care (i.e., home care and residential care homes) as a matter of care, that is, as a web of social and political interests with strong affective and ethical connotations (Puig de la Bellacasa, 2011; 2017), I find feminist posthumanism to be particularly relevant. It allows for situating and navigating problems and possibilities related to datafication while resisting apocalyptic thinking, as well as self-pity, techno-utopian and techno-dystopian claims (Lupton, 2021). The feminist posthumanist paradigm (Braidotti, 2013; 2019; 2020) enables us to appreciate datafication as a political development rather than as a technological one (Kaun & Dencik, 2020), specifically as embodying technopolitics (Kurban et al., 2017).

Techno-politics, a mode of politics based on techno-scientific knowledge that informs decision-making activities, functions as an organising principle in care practices. (…) Technologies are incorporated into all work, care work included. Solutions such as AI, algorithms, apps and robotics are rendered with care and aligned with care work practices and processes. (Kovalainen, 2022, p. 67)

To see technopolitics in the datafication of elderly welfare care, it is relevant to identify the onto-epistemological foundations of the ‘care crisis’ by drawing from critical gerontology (e.g., Katz, 1992; 2022) and socio-gerontechnology (e.g., Peine et al., 2021), as well as science and technology studies (e.g., Moreira, 2017). Critical scholars in these fields have emphasized that the connection between the ‘crisis of care’ and demographic change is far from neutral. ‘By naming something, we create its existence. Without thinking and language, the care crisis would not be visible as a political problem’ (Dahl, 2022, p. 20). At the same time, the care crisis is not only a discursive matter, but material in its unfolding and, as I will elaborate on later, it is performed or performatively enacted (Barad, 2007)² through specific practices and their logics.

There is a crucial economic aspect mobilized in the popular and professional construction of the care crisis in relation to the growing aging population portrayed as ‘‘greedy geezers’ who are stealing our children’s future’ (Estes, 2001, p. 131). Stephen Katz talks of ‘alarmist demography’ (1992) echoes Ann Robertson’s ‘apocalyptic demography’ (1997), which evolves into what Kathleen M. Woodward refers to as a culture of ‘statistical panic’ (2009). The care crisis due to the ‘demographic storm’ (Grande, 2018) is constructed as a statistically and demographically unquestionable objective truth, which is manufactured and portrayed as rationales for proposed cuts to health and care (direct) costs. Digital care technologies are meant to reduce expenses and costs of care, although the connection between such technologies and cost structures is not straightforward. Indirect costs (for example, those associated with training of health and welfare personnel and modifications to workflows and information flows) are often underestimated. Technology as a remedy is a ‘view from above, from nowhere’ (Haraway, 1988, p. 589) overlooking that the cost of technology – for example, online and data-driven care decisionmaking systems – varies by needs and that technology lowers care costs only in cases and countries where infrastructure functions well and technologies are supported by in-person care (Kovalainen, 2022). It is crucial to dig into imaginary legitimization of the datafication of elderly welfare care before looking at the practices and logics it enables.

Data’s promises

‘Datafication’ contains the word ‘data’ derived from the Latin dato meaning given in the sense of ‘fact.’ Despite suggesting facticity, however, data always come from a subjective selection executed from a situated position such that ‘data are never simply just data; how data are conceived and used varies between those who capture, analyse and draw conclusions from them’ (Kitchin, 2014, p. 5). Ulises A. Mejias and Nick Couldry specify that ‘datafication combines two processes: the transformation of human life into data through processes of quantification, and the generation of different kinds of values from data’ (2019, p. 3; italics mine).

When age is quantified and reduced to what results from such an operation, it is essentialized, seen as an objective chart of the flow of time between birth and death (chronological age) (Voléry & Julien, 2020) and changes occurring in age-related capabilities (functional age) (Katz & Marshall, 2004). The vibrancy of old bodies – their ‘affective forces, multisensory responses, and relational connections that open or close humans’ capacities for flourishing’ (Lupton et al., 2022, p. 363) – tends to be erased in the public discourse about aging. Reductionist ageist stereotypes of passivity and frailty become dominant and support the care crisis discourse, Age-Tech interventions, and – in relation to datafication – produce the old population through data practices. Old people are frequently chosen as ideal subjects for digitizing and datafying their bodily functions, health status, and movements in the interest of improving their mobility, protecting their health and helping them age in place (Joyce et al., 2017), preserving independence, autonomy and making successful aging possible in accordance with the ethical imperative for aging bodies (Cozza et al., 2022).

On the one hand, the datafication of elderly welfare care embodies a technopolitical principle organizing old people’s lives for their own (supposed) benefit through bodily measurements and quantified profiles. According to Dalmer and colleagues (2022, pp. 81-82), both measurement and quantification are integral to the medicalization of aging.

where monitoring and recording heart rate, blood pressure, cholesterol levels, memory test results, muscle tone, and weight have been key features of health assessments of old age. (…) [Thus] older bodies are increasingly reduced to numerical outputs of activity/inactivity embedded within trackable divisions between fit/frail, independent/dependent and risk-averse/risk-prone.

The datafication promises and makes possible technological personalization of numbers generated by self-tracking and self-monitoring that, in turn, are claimed to allow personalized solutions to medical challenges such as a healthier lifestyle, quick assessment of needs or diagnoses, proper monitoring, assistive devices, speedy updates and helpful peer support among other services (Van Dijck et al., 2018). This personalization ‘becomes resources by which older adults are expected to use data to manage lifestyle behavioral modifications and interventions’ (Dalmer et al., 2022, p. 83). In this imaginary, performing technical self-care corresponds to the enactment of responsible aging citizenship and the actualization of ethical imperatives of active and successful aging and independent living. Old people should feel empowered as contributing, through collecting and sharing personal data, ‘to the greater common good’ (Van Dijck et al., 2018, p. 100; italics in original) such as addressing challenges that ultimately cause the care crisis.

However, it is worth noting that the datafication of old people’s lives is instrumental to the technopolitical caring apparatus (Cozza et al., 2021). Government, as well as the medical industry and Age-Tech, emphasize its potential ‘to prevent and mitigate physical and financial burdens of ‘lifestyle diseases’ such as obesity, diabetes, and cardiovascular disease – conditions that derive from daily behaviors of overeating, underexercising, and smoking – by shifting their management away from hospitals and doctors and into the hands of empowered patients’ (Ruckenstein & Dow Schüll, 2017, p. 262; italics mine). With regard to datafication promises, Hoeyer (2023) argues that data serve the ambition of governing at a distance, resolving uncertainty with data and giving answers about effect (yes/no) and efficiency (low/high). Pushing the argument further, Zuboff (2019) considers datafication to be a form of ‘surveillance capitalism’ in that everyday activities are converted into data flows. People can be monitored continually and at a distance, offering healthcare and welfare professionals (and technology designers) the ability to expand their gaze and obtain remote access to previously inaccessible domains of individual lives. Van Dijck proposes the term ‘dataveillance’ – monitoring citizens based on their online data – which differs from surveillance in that ‘whereas surveillance presumes monitoring for specific purposes, dataveillance entails the continuous tracking of (meta) data for unstated present purposes’ (2014, p. 205). Concepts such as surveillance and dataveillance contribute to unraveling datafication’s ideological underpinnings (dataism) (Harari, 2017).

By critically acknowledging the above scholarly articulations of datafication, I use a feminist posthumanist perspective to engage with an ethos of care, resist the pitfalls of critique (Latour, 2004) and embrace an ethico-political commitment that affects the way I contribute to producing knowledge about datafication in relation to elderly welfare care. A feminist posthumanist perspective urges researchers to understand that there is a very fine line between old people using personal datafication for convenience and better welfare care and those responding with resentment, frustration or annoyance. Similarly, there is no clear distinction between professional caregivers applauding welfare technologies and those denouncing their drawbacks. Below I explore some transformations resulting from datafication of elderly welfare services by singling out three major changes affecting old people (as recipients of welfare care) and welfare practitioners (as professionals performing such care).

Transformations of elderly welfare care

Three interrelated practices (how caring is accomplished) and related logics³ (rationale orienting the practice) can be traced to the technopolitics of datafication of elderly welfare care.

The first corresponds to a practice of classification. One of the beliefs in the representation of the care crisis problem refers to the possibility of identifying the needs of particular groups (e.g., old people) using chronological (usually 65+) and functional age (capabilities) as measures to determine the eligibility for welfare care. This practice has, as a corollary, the idea that these needs can be objectively measured, quantified, and aggregated at a macro level by collecting personal data, indicating what is supposedly needed (or not needed) at a certain age in situations that can be generalized and indexed to a standard (logic of standardization). Chronological age is embedded in administrative practices that increasingly use datafication as a process to develop standards to assess needs and human functionality and deliver effective and efficient services according to evidence-based management aimed at developing standardized solutions in order to eventually allow cost savings (Cozza et al., 2019; Treas, 2009). The consequence of this technopolitical simplification – pursued through a practice of classification grounded on a logic of standardization – mutes individual differences and the affective, material vibrancy of an aging body, which is fragmented into convenient ‘boxes’ that can be easily managed.⁴ The datafication of an old body enacted by technologies such as digital monitoring technologies, wearable or implantable devices can open capacities for better knowledge of the body and its aging process, more effective needs assessment and diagnosis of diseases, prevention, welfare assistance and medical treatment. The living person is reduced to ‘clean’ digitized data and the body is made disposable to certain (but not other) services (Cozza et al., 2021).

The second is a practice of taskification of welfare care work. We might say that while the effects of the practice of classification are more directly impactful on old people, the immediate effects of the practice of taskification are most prominent on professional caregivers. Put differently, in the first case ‘data sourcing’ (Hoeyer, 2023) (and the consequential classification) depends on measurements acted upon an old body (although it might seem that individuals are active because they are sometimes performing such measurements themselves and generating data via the digital technologies they use). In the second case, data are made about tasks performed (on an old body) by professional caregivers. Klaus Hoeyer (2023, p. 4; italics mine) suggests using ‘data sourcing’ instead of the most common ‘data mining,’ highlighting that ‘data are not dug out of the ground – they are made.’ However, classification and taskification are two sides of the same coin, namely the digitally accelerated datafication of welfare elderly care, and it is sometimes difficult to draw a line between the direct consequences of datafication on old people and on professional caregivers. To be effective and efficient, care is sliced into clear tasks that can be targeted for bids and delivered, monitored and priced accordingly (time-paced service logic). The practitioner’s body becomes a central working tool that executes work according to specific instructions and timetables planned by higher-level managers. This practice of taskification that follows a time-paced service logic tends to stress innovation, flexibility and worker self-governance as values, rather than valuing primarily specialized education for care work, embodied expertise and experience – which are unlikely to be replaceable (Hoppania et al., 2022). What is not accounted for in this rational framework is that care can hardly be reduced to a service product in that care is always about bodily, corporeal relationships between a caregiver and a care receiver. Precisely, ‘caring about’ – which involves the recognition that care is necessary (Tronto, 2009) – cannot be quantified, while controlled and care needs are not static, but differ from day to day and from person to person (Rostgaard, 2012).

The practice of categorization of (chronological) age and ageing (in relation to functional age), and of (taskified) care and caring, is the third practice I single out in the same evidence-based rational framework. The alluring idea is that good management limits the need for economic investments in public care provision. This is possible by controlling old people with regard to specific issues related to their health and wellbeing and ignoring those who fall out of categories corresponding to the targeted aging population and intended levels of coverage services. At the same time, staff members face increasing demand to document in various ways (through case files, case records, digitized decision documents, checklists, nonconformance reports, etc.) (Olaison, 2010) the care they give to the care recipient so that data are available to control if what they do corresponds to the primary goal (logic of prioritization). Such a logic differs from the one embodied in the practice of classification in that prioritization is associated with hierarchization while standardization equates to generalization. To put it simply, while categorization leads to ordering old people and their needs based on an assigned priority, classification turns them into manageable standardized ‘boxes’ to eliminate the (embodied) complexity. Categorization allows prioritization because by defining the ‘categorical belonging’ of old people and turning them into manageable data (i.e., evidence-based management), public authorities can ‘predict individual risks or needs, and thus the level of assistance granted by state’ (Andreassen et al., 2021, p. 212). The consequence of this technopolitical agenda setting – pursued through a practice of categorization relying on a logic of prioritization – is that some needs remain inevitably unmet as less important, with implications for the quality of life of old people bypassed by the policy of recalibrating welfare care. Municipalities are increasingly focused on what I would call ‘superlative’ or ‘exceptional’ categories such as ‘the frailest of the frail’ (Rostgaard, 2012, p. 248) and ‘older people with multiple care needs’ (Rostgaard et al., 2022, p. 208). With categorization aiming at transforming old people into clients of welfare services and situating them within the organization’s frameworks, some needs are defined as more important than others. For example, medical and physical categories are ‘treated as superior to social needs in justifying decisions about home help’ (Olaison, 2010, p. 513). This has consequences for how images of old people are constructed and pathologized. This technopolitical imagining reverberates in policymaking and, eventually, in welfare care practices treating old people as a burdensome behemoth threatening national economic security.

Conclusion

The worldwide aging population is often described by an alarmist crisis discourse that portrays demographic change as compromising welfare care systems. I maintain that this is a performative discourse that constructs the same phenomenon (the care crisis) it refers to. Datafication – here analyzed in relation to elderly welfare care – is largely seen as beneficial to many actors (old people, professional caregivers, industry and governments), but if there is techno-enthusiasm on one side, techno-criticism is on the other. I do not indulge in such an oppositional epistemology, but rather propose to use a feminist posthumanist perspective to unpack datafication, highlight the interconnections between human and non-human actors that contribute to data-making and turn it into a matter of care embodying promises and troubles. By embracing this ethos of care, I identify three practices (classification, taskification, and categorization) and their corresponding logics (standardization, time-paced service, and prioritization) through which the care crisis is performed. Overall, these are performative enactments that contribute to the datafication of elderly welfare care by turning aging bodies and caring practices into objective, controllable and manageable data. Further elaboration of these practices and logics would advance the study of the ongoing transformation of Nordic welfare care.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This article was written with support from the Digitized Management – What can we learn from England and Sweden program funded by FORTE (grant no: 2016-07210).Forskningsrådet om Hälsa, Arbetsliv och Välfärd

Notes on contributors

Michela Cozza

Michela Cozza is an Associate Professor at the Department of Organization and Management at Mälardalen University in Sweden. She is a qualitative researcher, sociologist, and a scholar in science and technology studies. She is interested in the relationship between technology, age, aging and later life. email: [email protected].

Notes

1 In the Nordic context, ‘[w]elfare technology is all technology which in one way or another improves the lives of those who need it.’ (Nordic Welfare Centre, n.d.). The term ‘welfare’ makes explicit the uniqueness of Nordic countries where the state, especially municipalities, are highly involved. The word ‘technology’ stresses the eagerness of Nordic countries to use digitization to streamline public administration and the provision of welfare. Welfare technology is performed through practices enabling different actors to perform future aging (examples of such practices, along with an extensive problematization of them, are provided in Cozza et al., 2019).

2 I use a specifically posthumanist notion of performativity that, according to Karen Barad ‘incorporates important material and discursive, social and scientific, human and nonhuman, and natural and cultural factors’ (2003, p. 808).

3 I agree with Annemarie Mol, who adopted the word ‘logic’ when talking about care by acknowledging that ‘[t]here is a risk in using a word like ‘logic’ when talking of practices. It might seem to suggest that those practices are so coherent that everything within them is firmly defined by everything else’ (2008, p. 9). This is not the case, least of all when adopting a feminist posthumanist approach as I do here. Care is a process without clear boundaries. This analysis aims at foregrounding the tensions between this processual view and the transformations elderly welfare care goes through by identifying three practices and their logics.

4 My articulation of the concept of classification associated with a logic of standardization, is indebted to Geoffrey C. Bowker and Susan Leigh Star’s work on classification and its consequences. They define a ‘classification system’ as ‘a set of boxes (metaphorical or literal) into which things can be put to do some kind of work – bureaucratic or knowledge production’ (1999, p. 10). They also point out that ‘[c]lassifications and standards are closely related, but not identical’ (p. 13).